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{"i18n":{"language":"en_US"},"userPageInfo":{"id":"3560270530016088","uuid":"3560270530016088","gmtCreate":1597176508251,"gmtModify":1597176508251,"name":"DKTED","pinyin":"dkted","introduction":"","introductionEn":null,"signature":"","avatar":"https://static.laohu8.com/default-avatar.jpg","hat":null,"hatId":null,"hatName":null,"vip":1,"status":2,"fanSize":0,"headSize":21,"tweetSize":3,"questionSize":0,"limitLevel":999,"accountStatus":2,"level":{"id":0,"name":"","nameTw":"","represent":"","factor":"","iconColor":"","bgColor":""},"themeCounts":0,"badgeCounts":0,"badges":[],"moderator":false,"superModerator":false,"manageSymbols":null,"badgeLevel":null,"boolIsFan":false,"boolIsHead":false,"favoriteSize":3,"symbols":null,"coverImage":null,"realNameVerified":"success","userBadges":[{"badgeId":"1026c425416b44e0aac28c11a0848493-4","templateUuid":"1026c425416b44e0aac28c11a0848493","name":"Tiger Star","description":"Join the tiger community for 2000 days","bigImgUrl":"https://static.tigerbbs.com/dddf24b906c7011de2617d4fb3f76987","smallImgUrl":"https://static.tigerbbs.com/53d58ad32c97254c6f74db8b97e6ec49","grayImgUrl":"https://static.tigerbbs.com/6304700d92ad91c7a33e2e92ec32ecc1","redirectLinkEnabled":0,"redirectLinkType":null,"redirectLink":null,"redirectLinkValidityFrom":null,"redirectLinkValidityTo":null,"hasAllocated":1,"isWearing":0,"stamp":null,"stampPosition":0,"hasStamp":0,"allocationCount":1,"allocatedDate":"2026.04.23","exceedPercentage":null,"individualDisplayEnabled":0,"backgroundColor":null,"fontColor":null,"individualDisplaySort":0,"categoryType":1001,"isScarce":0,"effectEnabled":0,"plateImgUrl":null,"plateColors":null,"validityTo":null,"validityToTimestamp":null,"wearingSort":0}],"userBadgeCount":1,"currentWearingBadge":null,"individualDisplayBadges":null,"crmLevel":1,"crmLevelSwitch":0,"location":null,"starInvestorFollowerNum":0,"starInvestorFlag":false,"starInvestorOrderShareNum":0,"subscribeStarInvestorNum":0,"ror":null,"winRationPercentage":null,"showRor":false,"investmentPhilosophy":null,"starInvestorSubscribeFlag":false},"baikeInfo":{},"tab":"post","tweets":[],"hots":[{"id":668848793,"gmtCreate":1664550487514,"gmtModify":1676537476194,"author":{"id":"3560270530016088","authorId":"3560270530016088","name":"DKTED","avatar":"https://static.laohu8.com/default-avatar.jpg","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3560270530016088","idStr":"3560270530016088"},"themes":[],"title":"","htmlText":"1","listText":"1","text":"1","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/668848793","repostId":"1110631384","repostType":4,"repost":{"id":"1110631384","kind":"news","pubTimestamp":1664464935,"share":"https://ttm.financial/m/news/1110631384?lang=en_US&edition=fundamental","pubTime":"2022-09-29 23:22","market":"uk","language":"zh","title":"The UK bond market is experiencing epic volatility; why is pensions the biggest \"powder keg\"?","url":"https://stock-news.laohu8.com/highlight/detail?id=1110631384","media":"华尔街见闻","summary":"若养老基金大规模撤出英国国债，英国债市或面临灭顶之灾。","content":"<p><html><head></head><body>Author: Bu Shuqing</p><p>As previously mentioned by Wall Street Insights, one of the most important reasons the Bank of England intervened in the bond market on Wednesday was that UK pension funds were facing large-scale additional margin requirements. Media reports, citing sources familiar with the matter, revealed that investment banks and fund managers have warned the Bank of England in recent days that additional margin requirements could trigger a collapse in the UK bond market.</p><p>Pension funds are able to wreak havoc on the UK bond market because they hedge their debt with high leverage through debt-driven investment strategies. As yields on Phnom Penh bonds (Treasury Bond issued by the UK government) continue to soar, pension funds holding trillions of pounds in assets may sell off Phnom Penh bonds on a large scale in order to pay huge margins.</p><p>LDI + High Leverage Hedging</p><p>Liability-driven investing (LDI) was the first major landmine planted by pension funds for the UK bond market.</p><p>For a long time, most pension funds in the UK have used liability-driven investing to hedge liabilities (future payments to pension clients), a strategy that allows pension funds to match their liabilities with the assets of the scheme.</p><p>This can be explained in a simple model:</p><p>If a pension fund needs to pay a client £1 million in pensions in 2046, then the fund can purchase gilt bonds maturing that year. If it buys high-quality, higher-yielding corporate bonds, the fund can use additional funds to invest in the stock market, real estate, or other growth assets in addition to purchasing bonds. Furthermore,<b>Pension funds can use interest rate swaps or inflation swaps to match long-term liabilities.</b>This means that pension funds only need to invest initial margin to trade, and the direction of Treasury Bond yield changes determines whether the fund pays or receives margin. Specifically, when Treasury Bond yields rise, pension funds need to pay margin to counterparties, and vice versa, they win the counterparties' margin. Therefore, pension funds that hedge through interest rate swaps face a certain level of leverage.</p><p>How much leverage is this?</p><p>According to a 2019 survey conducted by the UK's pensions regulator, among the top 600 pension funds in the UK (with total assets of approximately £700 billion),<b>62% of pension funds leverage their investments through interest rate swaps, which account for 43% of all leveraged investments. The maximum leverage allowed is 1 to 7 times!</b></p><p>Once yields rise, pension funds will face additional margin requirements and be forced to provide more collateral.</p><p>In fact, as early as July, media reports indicated that UK pension funds were facing additional margin requirements. Over the past year, UK Treasury Bond yields have continued to rise, with the UK 30-year Treasury Bond yield surging from 1.12% in October last year to 3.93% in July this year.</p><p><img src=\"https://static.tigerbbs.com/a7bfd9ed4efd73df53dfa7fe47cb6c4f\" tg-width=\"991\" tg-height=\"609\" referrerpolicy=\"no-referrer\" width=\"100%\" height=\"auto\"/></p><p>If pension funds withdraw on a large scale, the UK bond market could face annihilation.</p><p>The massive amount of capital is the second landmine planted by pension funds for the UK bond market.</p><p>Despite the extremely high risks, the LDI strategy helped UK pension funds expand rapidly during days of declining Phnom Penh bond yields. Data from the Investment Association shows that in the 10 years to 2020, UK pension funds held UK assets through LDI strategies tripled to £1.5 trillion.</p><p>What does this number correspond to?</p><p>Excluding the Treasury Bond held by the Bank of England,<b>Pension funds hold 40% of the UK's institutional asset management market, two-thirds of the UK's GDP, and the size of the entire Phnom Penh bond market.</b></p><p>It is currently unclear exactly how much of British Treasury Bond the pension fund holds, but analysts believe it is enormous.<b>If pension funds withdraw from the UK Treasury Bond on a large scale, the UK bond market could face annihilation.</b></p><p>Trigger: Britain's most radical tax cut plan in half a century</p><p>Last Friday, Britain announced its most aggressive tax cut plan in half a century, which sparked a sell-off in the Phnom Penh bond market, sending the yield on the 30-year Treasury Bond surging 120 basis points in just a few days.</p><p>Treasury Bond yields soared, and pension funds faced rising margin calls.</p><p>Ben Gold, head of investment at pension consultancy XPS, estimates that UK pension funds have received at least £1 billion in additional margin notices since the UK government announced its tax cut plans. He stated that approximately two-thirds of the 400 pension plans his company advises on have been affected.</p><p>To pay the huge deposit,<b>UK pension funds may have to sell large amounts of gilt bonds and other liquid assets, further putting pressure on the UK bond market and pushing up Treasury Bond yields, which will cause margin requirements to snowball.</b></p><p>In response, Kerrin Rosenberg, Chief Investment Officer of Cardano Investments, stated:</p><p><b>If the Bank of England does not intervene today, gilt bond yields could rise from 4.5% this morning to 7-8%, in which case approximately 90% of UK pension funds would run out of collateral and be wiped out!</b>As Wall Street Insights previously analyzed, in order to prevent a large-scale exodus of pension funds from the UK Treasury Bond from dealing a fatal blow to the bond market, the Bank of England reversed its long-standing \"no intervention\" strategy and announced unlimited purchases of UK Treasury Bond.</p><p>The Bank of England issued a statement on Wednesday saying it would temporarily purchase long-term UK Treasury Bond \"at any necessary scale\" to restore order in the UK bond market. Subsequently, the Bank of England stated that it would purchase traditional British Treasury Bond with a remaining maturity of more than 20 years in the secondary market.</p><p>As a result, the UK Treasury Bond surged, and the yield on the UK 30-year Treasury Bond fell by 100 basis points at one point.</p><p></body></html></p>","source":"live_wallstreetcn","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>The UK bond market is experiencing epic volatility; why is pensions the biggest \"powder keg\"?</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 12.5px; color: #7E829C; margin: 0;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nThe UK bond market is experiencing epic volatility; why is pensions the biggest \"powder keg\"?\n</h2>\n<h4 class=\"meta\">\n<p class=\"head\">\n<strong class=\"h-name small\">华尔街见闻</strong><span class=\"h-time small\">2022-09-29 23:22</span>\n</p>\n</h4>\n</header>\n<article>\n<p><html><head></head><body>Author: Bu Shuqing</p><p>As previously mentioned by Wall Street Insights, one of the most important reasons the Bank of England intervened in the bond market on Wednesday was that UK pension funds were facing large-scale additional margin requirements. Media reports, citing sources familiar with the matter, revealed that investment banks and fund managers have warned the Bank of England in recent days that additional margin requirements could trigger a collapse in the UK bond market.</p><p>Pension funds are able to wreak havoc on the UK bond market because they hedge their debt with high leverage through debt-driven investment strategies. As yields on Phnom Penh bonds (Treasury Bond issued by the UK government) continue to soar, pension funds holding trillions of pounds in assets may sell off Phnom Penh bonds on a large scale in order to pay huge margins.</p><p>LDI + High Leverage Hedging</p><p>Liability-driven investing (LDI) was the first major landmine planted by pension funds for the UK bond market.</p><p>For a long time, most pension funds in the UK have used liability-driven investing to hedge liabilities (future payments to pension clients), a strategy that allows pension funds to match their liabilities with the assets of the scheme.</p><p>This can be explained in a simple model:</p><p>If a pension fund needs to pay a client £1 million in pensions in 2046, then the fund can purchase gilt bonds maturing that year. If it buys high-quality, higher-yielding corporate bonds, the fund can use additional funds to invest in the stock market, real estate, or other growth assets in addition to purchasing bonds. Furthermore,<b>Pension funds can use interest rate swaps or inflation swaps to match long-term liabilities.</b>This means that pension funds only need to invest initial margin to trade, and the direction of Treasury Bond yield changes determines whether the fund pays or receives margin. Specifically, when Treasury Bond yields rise, pension funds need to pay margin to counterparties, and vice versa, they win the counterparties' margin. Therefore, pension funds that hedge through interest rate swaps face a certain level of leverage.</p><p>How much leverage is this?</p><p>According to a 2019 survey conducted by the UK's pensions regulator, among the top 600 pension funds in the UK (with total assets of approximately £700 billion),<b>62% of pension funds leverage their investments through interest rate swaps, which account for 43% of all leveraged investments. The maximum leverage allowed is 1 to 7 times!</b></p><p>Once yields rise, pension funds will face additional margin requirements and be forced to provide more collateral.</p><p>In fact, as early as July, media reports indicated that UK pension funds were facing additional margin requirements. Over the past year, UK Treasury Bond yields have continued to rise, with the UK 30-year Treasury Bond yield surging from 1.12% in October last year to 3.93% in July this year.</p><p><img src=\"https://static.tigerbbs.com/a7bfd9ed4efd73df53dfa7fe47cb6c4f\" tg-width=\"991\" tg-height=\"609\" referrerpolicy=\"no-referrer\" width=\"100%\" height=\"auto\"/></p><p>If pension funds withdraw on a large scale, the UK bond market could face annihilation.</p><p>The massive amount of capital is the second landmine planted by pension funds for the UK bond market.</p><p>Despite the extremely high risks, the LDI strategy helped UK pension funds expand rapidly during days of declining Phnom Penh bond yields. Data from the Investment Association shows that in the 10 years to 2020, UK pension funds held UK assets through LDI strategies tripled to £1.5 trillion.</p><p>What does this number correspond to?</p><p>Excluding the Treasury Bond held by the Bank of England,<b>Pension funds hold 40% of the UK's institutional asset management market, two-thirds of the UK's GDP, and the size of the entire Phnom Penh bond market.</b></p><p>It is currently unclear exactly how much of British Treasury Bond the pension fund holds, but analysts believe it is enormous.<b>If pension funds withdraw from the UK Treasury Bond on a large scale, the UK bond market could face annihilation.</b></p><p>Trigger: Britain's most radical tax cut plan in half a century</p><p>Last Friday, Britain announced its most aggressive tax cut plan in half a century, which sparked a sell-off in the Phnom Penh bond market, sending the yield on the 30-year Treasury Bond surging 120 basis points in just a few days.</p><p>Treasury Bond yields soared, and pension funds faced rising margin calls.</p><p>Ben Gold, head of investment at pension consultancy XPS, estimates that UK pension funds have received at least £1 billion in additional margin notices since the UK government announced its tax cut plans. He stated that approximately two-thirds of the 400 pension plans his company advises on have been affected.</p><p>To pay the huge deposit,<b>UK pension funds may have to sell large amounts of gilt bonds and other liquid assets, further putting pressure on the UK bond market and pushing up Treasury Bond yields, which will cause margin requirements to snowball.</b></p><p>In response, Kerrin Rosenberg, Chief Investment Officer of Cardano Investments, stated:</p><p><b>If the Bank of England does not intervene today, gilt bond yields could rise from 4.5% this morning to 7-8%, in which case approximately 90% of UK pension funds would run out of collateral and be wiped out!</b>As Wall Street Insights previously analyzed, in order to prevent a large-scale exodus of pension funds from the UK Treasury Bond from dealing a fatal blow to the bond market, the Bank of England reversed its long-standing \"no intervention\" strategy and announced unlimited purchases of UK Treasury Bond.</p><p>The Bank of England issued a statement on Wednesday saying it would temporarily purchase long-term UK Treasury Bond \"at any necessary scale\" to restore order in the UK bond market. Subsequently, the Bank of England stated that it would purchase traditional British Treasury Bond with a remaining maturity of more than 20 years in the secondary market.</p><p>As a result, the UK Treasury Bond surged, and the yield on the UK 30-year Treasury Bond fell by 100 basis points at one point.</p><p></body></html></p>\n<div class=\"bt-text\">\n\n\n<p> source：<a href=\"https://wallstreetcn.com/articles/3671538\">华尔街见闻</a></p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/741a7a9152b273ef524b8d371b44958e","relate_stocks":{"EWU":"英国ETF-iShares MSCI"},"source_url":"https://wallstreetcn.com/articles/3671538","is_english":false,"share_image_url":"https://static.laohu8.com/cc96873d3d23ee6ac10685520df9c100","article_id":"1110631384","content_text":"作者：卜淑情据华尔街见闻此前提及，英国央行周三出手干预债市最重要的一个原因在于英国养老基金面临大规模追加保证金的要求。媒体援引知情人士透露，投资银行和基金经理最近几天警告英国央行，追加保证金的要求可能引发英国债市崩盘。养老基金之所以能对英国债市产生摧枯拉朽的破坏力，是因为它通过负债驱动型投资策略对其债务进行了高杠杆对冲，在金边债券（英国政府发行的国债）收益率持续飙升的情况下，为支付巨额保证金，持有万亿英镑资产的养老基金可能会大规模抛售金边债券。LDI+高杠杆对冲负债驱动型投资（LDI）是养老基金为英国债市埋下的第一颗大雷。长期以来，英国多数养老基金一直采用负债驱动型投资来对冲负债（未来支付给养老金客户的款项），通过该策略，养老基金可以将其负债与计划的资产相匹配。这可以通过一个简单的模型中说明：如果养老基金需要在2046年向客户支付100万英镑的养老金，那么基金可以购买于该年到期的金边债券。如果买到优质的收益率更高的企业债券，基金可以在购买债券之余使用额外的资金投资股市、房地产或其他成长型资产。更进一步，养老基金可以使用利率掉期或通胀掉期来匹配长期负债。这就意味着，养老基金只需要投入初始保证金进行交易，而国债收益率变动方向决定该基金是缴纳还是收获保证金。具体来看，在国债收益率上行时，养老基金需要向交易对手缴纳保证金，相反则赢得交易对手的保证金。因此，通过利率掉期进行对冲的养老基金面临一定的杠杆。这个杠杆有多大？根据英国养老金监管机构2019年进行的调查，在英国前600家养老基金（总资产约为7000亿英镑）中，有62%的养老金通过利率掉期进行杠杆投资，利率掉期投资规模占所有杠杆投资的43%，允许的最大杠杆水平为1倍至7倍！一旦收益率上行，养老基金将面临追加保证金的要求，被迫提供更多抵押品。实际上，早在7月就有媒体报道，英国养老基金面临追加保证金通知。在过去一年中，英国国债收益率持续上升，其中英国30年期国债收益率从去年10月的1.12%飙升至今年七月的3.93%。若养老基金大规模撤出，英国债市或面临灭顶之灾庞大的资金规模是养老基金为英国债市埋下的第二颗雷。虽然风险极高，LDI策略在金边债券收益率下降的日子里仍帮助英国养老基金迅速扩张。投资协会（Investment Association）的数据显示，在截至2020年的10年中，英国养老基金通过LDI策略持有的英国资产增加了两倍，达到1.5万亿英镑。这一数字相当于什么概念？除去英格兰银行持有的国债后，养老基金持有的资产占英国机构资产管理市场的40%，占英国GDP的三分之二以及整个金边债券市场的规模。目前尚不清楚养老基金到底持有多大规模的英国国债，但分析认为这一规模十分巨大，如果养老基金大规模撤出英国国债，英国债市或面临灭顶之灾。导火索：英国半世纪以来最激进的减税计划上周五，英国宣布了半个世纪以来最激进的减税计划，该计划在英国金边债券市场掀起了抛售浪潮，英国30年期国债收益率在短短几天内飙升了120个基点。国债收益率飙升，养老基金面临的追加保证金水涨船高。养老金咨询公司XPS投资主管Ben Gold估计，自英国政府公布减税计划以来，英国养老基金已收到至少10亿英镑的追加保证金通知。他表示，在其公司提供咨询服务的400个养老金计划中，大约有三分之二受到了影响。为支付巨额保证金，英国养老基金可能不得不抛售大量金边债券和其他流动资产，进一步使英国债市承压，推高国债收益率，这将导致需缴纳的保证金像滚雪球一样越来越大。对此，卡尔达诺投资公司首席投资官Kerrin Rosenberg表示：如果英国央行今天没有干预，金边债券收益率可能会从早上的4.5%上升到7-8%，在这种情况下，大约90%的英国养老基金将用完抵押品，他们会被消灭！正如华尔街见闻此前分析，为防止养老基金大规模出逃英国国债给债市带来致命打击，英国央行扭转了长期以来的“不干预”策略，并宣布无限量购买英国国债。英国央行周三发布声明称，将“以任何必要的规模”临时购买英国长期国债，以恢复英国债券市场秩序。随后，英国央行表示将在二级市场购买剩余期限超过20年的传统英国国债。受此影响，英国国债暴涨，英国30年期国债收益率一度下行100个基点。","news_type":1,"symbols_score_info":{"EWU":0.9}},"isVote":1,"tweetType":1,"viewCount":1922,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":668841219,"gmtCreate":1664549891736,"gmtModify":1676537476026,"author":{"id":"3560270530016088","authorId":"3560270530016088","name":"DKTED","avatar":"https://static.laohu8.com/default-avatar.jpg","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3560270530016088","idStr":"3560270530016088"},"themes":[],"title":"","htmlText":"1","listText":"1","text":"1","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/668841219","repostId":"1146232184","repostType":4,"repost":{"id":"1146232184","kind":"news","pubTimestamp":1664542806,"share":"https://ttm.financial/m/news/1146232184?lang=en_US&edition=fundamental","pubTime":"2022-09-30 21:00","market":"uk","language":"zh","title":"Firsthand experience of the UK crisis: The entire pension market was almost destroyed!","url":"https://stock-news.laohu8.com/highlight/detail?id=1146232184","media":"三思期权","summary":"巨亏本身不是那么可怕，最可怕的是短期连续的巨亏。","content":"<p><html><head></head><body>Having personally experienced this week's storm, this short essay commemorates it in the form of a notebook. This week has been incredibly exhausting. Besides being mentally exhausted, I also feel a little regretful that I didn't have any foresight about such a big event, which is why I missed this black swan trade.</p><p>How do you describe what happened this week? I feel like it's closest to March 2020. UK interest rates and the pound market completely collapsed, the entire UK pension market nearly collapsed, and the LDI industry within pensions collapsed overnight. If the entire pension market collapses, it won't be March anymore; it will be 2008. Fortunately, the central bank intervened to rescue the market.</p><p>I've been so exhausted these past two days that I don't want to write too much. For basic knowledge about what's happening in the market, you can check out this article by Degg_GlobalMacroFin. In this article, I will focus on my front-line experiences.</p><p><img src=\"https://static.tigerbbs.com/3631a2312876324acb9456bbd80c4a2d\" tg-width=\"587\" tg-height=\"114\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>Remember these two men, who almost single-handedly destroyed the huge pension market. Of course, the leverage in the LDI industry cannot be blamed on them. However, introducing unrestrained tax cuts without experience was the trigger that almost caused the sudden demise of the pension market.</p><p></li></ul><img src=\"https://static.tigerbbs.com/70f8e2c3c00e5ca5bb643a16e7534a83\" tg-width=\"658\" tg-height=\"407\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>The simplest explanation is that the idiotic tax cuts caused interest rates to skyrocket. The sharp rise in Interest rates has led to huge short-term losses on Interest rates (Interest rate swaps) used by many pension funds in LDI funds to hedge against Interest rate and inflation risks. Huge losses themselves aren't so terrible; what's most terrifying is the short-term, continuous huge losses that cause the margin to run out quickly.</p><p></li></ul><ul><li>From the end of August to the end of September, the 30-year interest rate in the UK surged 230 basis points. How much impact will this surge have on these LDI funds that hold interest rate swaps? We can make a rough estimate.</p><p></li></ul><img src=\"https://static.tigerbbs.com/3dd447ad5d4d8ebe9b9acb9cc8d502b1\" tg-width=\"683\" tg-height=\"419\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>A pension fund with a scale of 1 billion yuan holds approximately two million yuan in DV01 (profit or loss resulting from a one-basis-point interest rate change) from interest rate swaps in its LDI fund. This means that over the past two months, due to a 230-basis-point change in the 30-year interest rate, the loss resulting from the interest rate swap is 230 * 2m = 460m. In other words, the losses resulting from the interest rate swap over the past two months amount to nearly half of the pension fund's assets!</p><p></li></ul><ul><li>This loss is not a real loss. Because these interest rate swaps are used to hedge against the liabilities of pension funds, if the interest rate swaps result in losses, the value of the liabilities will also decrease. Theoretically, this is a long-short hedging transaction that will not result in any losses.</p><p></li></ul><ul><li>However, however, in the previous example, after losing 400 million in such a short period of time, those LDI funds first sold their most liquid UK Treasury Bond to raise funds to cover the margin.</p><p></li></ul><ul><li>Those who know a little about over-the-counter trading might ask, why don't these funds use these UK Treasury Bond as margin? Because many over-the-counter transactions can directly use Treasury Bond as margin. This brings us to another topic: the interest rate swap market has undergone a major transformation in the past 10 years. Most interest rate swaps have moved from simple over-the-counter transactions to centrally cleared over-the-counter transactions. The clearing house is LCH, and currently only cash can be used as security.</p><p></li></ul><ul><li>Okay, here comes the key point: this is the most important step in the death spiral. The UK Treasury Bond rate and the UK interest rate swap rate are actually quite similar. Because the interest rate swap resulted in losses, the fund manager had to sell Treasury Bond to cover margin. The massive sell-off of Treasury Bond led to rising interest rates in Treasury Bond, while rising interest rates in Treasury Bond led to higher interest rates on interest rate swaps. These rising interest rates led fund managers to sell more Treasury Bond to replenish margin.</p><p></li></ul><ul><li>Financial markets are neither afraid of rising nor falling; when prices are low, people will naturally buy, but the market is most afraid of this death spiral.</p><p></li></ul><ul><li>How big is this pension market? According to PPF estimates, pension assets totaled approximately £1.5 trillion at the end of August. In other words, the rough estimate of the margin requirements caused by the losses in the LDI strategy of the entire pension fund over the past two months is 690 billion yuan. My friend's LDI desk paid 1.2 billion yuan in back deposits in one day last Friday! Yes, a desk costs 1.2 billion a day!</p><p></li></ul><ul><li>During the sell-off, Treasury Bond sold out, leaving only other assets to be sold. First and foremost, there are stocks with high liquidity. This caused stocks to fall as well, and indiscriminately. Because there are requirements for the speed at which pension funds can be replenished during this process (usually T+0), they can only be sold blindly.</p><p></li></ul><ul><li>Stocks will fall if they fall; if they get cheap, people will naturally buy them. However, another crucial point in the whole process is that these pension funds have significantly increased their allocation to illiquid assets, such as real estate and private equity funds, over the past 10 years. These are not things you can redeem just because you want to. This creates a huge problem: liquidity mismatch!</p><p></li></ul><ul><li>If you can't sell it, sorry, if you can't pay the margin, those interest rate swap positions will be exploded. Investment banking desks must sell these interest rate swap positions in the market. This has led to the interest rate on interest rate swaps continuing to rise! This will further drag down other well-liquid pension funds.</p><p></li></ul><ul><li>At that time, the entire interest rate swap market had been paralyzed, and most market makers had already left the market. Previously, the spread between buying and selling one-year UK interest rate swaps was only 0.1-0.2 bps, but by then it had risen to 9-10 bps!</p><p></li></ul><ul><li>After the death spiral, the only thing that can be done is to wait for the Bank of England to bail out the market. Fortunately, the central bank took decisive action, implementing quantitative easing (QE) to curb the rising momentum of interest rates in Treasury Bond. The death spiral was broken. It brought many pension funds and LDI funds back from the brink of death.</p><p></li></ul><ul><li>But not everyone saw the dawn. Several large UK asset management companies' LDI funds exploded. Just look at their stock prices... I won't reveal their names, just be polite.</p><p></li></ul><img src=\"https://static.tigerbbs.com/e4b774b4e7003f42a53ee0d06289797a\" tg-width=\"1080\" tg-height=\"793\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>The worst were those pensions that collapsed on the eve of dawn, and the holders who lived off them.</p><p></li></ul><ul><li>If the market rescue had been delayed by another two days, the entire pension industry would have collapsed.</p><p></li></ul><ul><li>With this major upheaval in the LDI industry, even surviving funds will find it difficult to continue to survive, and the biggest flaw in the industry's business model has been exposed. Without leverage, the industry would not survive. It can only be said that this industry is likely to disappear in the near future.</p><p></li></ul><ul><li>Breaking the death spiral, the British Treasury Bond rose by 40% in one day in 50 years! Who says Treasury Bond is rising slowly?</p><p></li></ul><img src=\"https://static.tigerbbs.com/499bde85b23a6e2bf8d80bc692321a91\" tg-width=\"1080\" tg-height=\"516\" referrerpolicy=\"no-referrer\"/></p><p></body></html></p>","source":"lsy1607924588218","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Firsthand experience of the UK crisis: The entire pension market was almost destroyed!</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 12.5px; color: #7E829C; margin: 0;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nFirsthand experience of the UK crisis: The entire pension market was almost destroyed!\n</h2>\n<h4 class=\"meta\">\n<p class=\"head\">\n<strong class=\"h-name small\">三思期权</strong><span class=\"h-time small\">2022-09-30 21:00</span>\n</p>\n</h4>\n</header>\n<article>\n<p><html><head></head><body>Having personally experienced this week's storm, this short essay commemorates it in the form of a notebook. This week has been incredibly exhausting. Besides being mentally exhausted, I also feel a little regretful that I didn't have any foresight about such a big event, which is why I missed this black swan trade.</p><p>How do you describe what happened this week? I feel like it's closest to March 2020. UK interest rates and the pound market completely collapsed, the entire UK pension market nearly collapsed, and the LDI industry within pensions collapsed overnight. If the entire pension market collapses, it won't be March anymore; it will be 2008. Fortunately, the central bank intervened to rescue the market.</p><p>I've been so exhausted these past two days that I don't want to write too much. For basic knowledge about what's happening in the market, you can check out this article by Degg_GlobalMacroFin. In this article, I will focus on my front-line experiences.</p><p><img src=\"https://static.tigerbbs.com/3631a2312876324acb9456bbd80c4a2d\" tg-width=\"587\" tg-height=\"114\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>Remember these two men, who almost single-handedly destroyed the huge pension market. Of course, the leverage in the LDI industry cannot be blamed on them. However, introducing unrestrained tax cuts without experience was the trigger that almost caused the sudden demise of the pension market.</p><p></li></ul><img src=\"https://static.tigerbbs.com/70f8e2c3c00e5ca5bb643a16e7534a83\" tg-width=\"658\" tg-height=\"407\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>The simplest explanation is that the idiotic tax cuts caused interest rates to skyrocket. The sharp rise in Interest rates has led to huge short-term losses on Interest rates (Interest rate swaps) used by many pension funds in LDI funds to hedge against Interest rate and inflation risks. Huge losses themselves aren't so terrible; what's most terrifying is the short-term, continuous huge losses that cause the margin to run out quickly.</p><p></li></ul><ul><li>From the end of August to the end of September, the 30-year interest rate in the UK surged 230 basis points. How much impact will this surge have on these LDI funds that hold interest rate swaps? We can make a rough estimate.</p><p></li></ul><img src=\"https://static.tigerbbs.com/3dd447ad5d4d8ebe9b9acb9cc8d502b1\" tg-width=\"683\" tg-height=\"419\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>A pension fund with a scale of 1 billion yuan holds approximately two million yuan in DV01 (profit or loss resulting from a one-basis-point interest rate change) from interest rate swaps in its LDI fund. This means that over the past two months, due to a 230-basis-point change in the 30-year interest rate, the loss resulting from the interest rate swap is 230 * 2m = 460m. In other words, the losses resulting from the interest rate swap over the past two months amount to nearly half of the pension fund's assets!</p><p></li></ul><ul><li>This loss is not a real loss. Because these interest rate swaps are used to hedge against the liabilities of pension funds, if the interest rate swaps result in losses, the value of the liabilities will also decrease. Theoretically, this is a long-short hedging transaction that will not result in any losses.</p><p></li></ul><ul><li>However, however, in the previous example, after losing 400 million in such a short period of time, those LDI funds first sold their most liquid UK Treasury Bond to raise funds to cover the margin.</p><p></li></ul><ul><li>Those who know a little about over-the-counter trading might ask, why don't these funds use these UK Treasury Bond as margin? Because many over-the-counter transactions can directly use Treasury Bond as margin. This brings us to another topic: the interest rate swap market has undergone a major transformation in the past 10 years. Most interest rate swaps have moved from simple over-the-counter transactions to centrally cleared over-the-counter transactions. The clearing house is LCH, and currently only cash can be used as security.</p><p></li></ul><ul><li>Okay, here comes the key point: this is the most important step in the death spiral. The UK Treasury Bond rate and the UK interest rate swap rate are actually quite similar. Because the interest rate swap resulted in losses, the fund manager had to sell Treasury Bond to cover margin. The massive sell-off of Treasury Bond led to rising interest rates in Treasury Bond, while rising interest rates in Treasury Bond led to higher interest rates on interest rate swaps. These rising interest rates led fund managers to sell more Treasury Bond to replenish margin.</p><p></li></ul><ul><li>Financial markets are neither afraid of rising nor falling; when prices are low, people will naturally buy, but the market is most afraid of this death spiral.</p><p></li></ul><ul><li>How big is this pension market? According to PPF estimates, pension assets totaled approximately £1.5 trillion at the end of August. In other words, the rough estimate of the margin requirements caused by the losses in the LDI strategy of the entire pension fund over the past two months is 690 billion yuan. My friend's LDI desk paid 1.2 billion yuan in back deposits in one day last Friday! Yes, a desk costs 1.2 billion a day!</p><p></li></ul><ul><li>During the sell-off, Treasury Bond sold out, leaving only other assets to be sold. First and foremost, there are stocks with high liquidity. This caused stocks to fall as well, and indiscriminately. Because there are requirements for the speed at which pension funds can be replenished during this process (usually T+0), they can only be sold blindly.</p><p></li></ul><ul><li>Stocks will fall if they fall; if they get cheap, people will naturally buy them. However, another crucial point in the whole process is that these pension funds have significantly increased their allocation to illiquid assets, such as real estate and private equity funds, over the past 10 years. These are not things you can redeem just because you want to. This creates a huge problem: liquidity mismatch!</p><p></li></ul><ul><li>If you can't sell it, sorry, if you can't pay the margin, those interest rate swap positions will be exploded. Investment banking desks must sell these interest rate swap positions in the market. This has led to the interest rate on interest rate swaps continuing to rise! This will further drag down other well-liquid pension funds.</p><p></li></ul><ul><li>At that time, the entire interest rate swap market had been paralyzed, and most market makers had already left the market. Previously, the spread between buying and selling one-year UK interest rate swaps was only 0.1-0.2 bps, but by then it had risen to 9-10 bps!</p><p></li></ul><ul><li>After the death spiral, the only thing that can be done is to wait for the Bank of England to bail out the market. Fortunately, the central bank took decisive action, implementing quantitative easing (QE) to curb the rising momentum of interest rates in Treasury Bond. The death spiral was broken. It brought many pension funds and LDI funds back from the brink of death.</p><p></li></ul><ul><li>But not everyone saw the dawn. Several large UK asset management companies' LDI funds exploded. Just look at their stock prices... I won't reveal their names, just be polite.</p><p></li></ul><img src=\"https://static.tigerbbs.com/e4b774b4e7003f42a53ee0d06289797a\" tg-width=\"1080\" tg-height=\"793\" referrerpolicy=\"no-referrer\"/></p><p><ul><li>The worst were those pensions that collapsed on the eve of dawn, and the holders who lived off them.</p><p></li></ul><ul><li>If the market rescue had been delayed by another two days, the entire pension industry would have collapsed.</p><p></li></ul><ul><li>With this major upheaval in the LDI industry, even surviving funds will find it difficult to continue to survive, and the biggest flaw in the industry's business model has been exposed. Without leverage, the industry would not survive. It can only be said that this industry is likely to disappear in the near future.</p><p></li></ul><ul><li>Breaking the death spiral, the British Treasury Bond rose by 40% in one day in 50 years! Who says Treasury Bond is rising slowly?</p><p></li></ul><img src=\"https://static.tigerbbs.com/499bde85b23a6e2bf8d80bc692321a91\" tg-width=\"1080\" tg-height=\"516\" referrerpolicy=\"no-referrer\"/></p><p></body></html></p>\n<div class=\"bt-text\">\n\n\n<p> source：<a href=\"https://mp.weixin.qq.com/s/kMwPDK6F78YABLQIBpUexA\">三思期权</a></p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/d28e326edc19611f4a02f9a0ebb66bf9","relate_stocks":{"EWU":"英国ETF-iShares MSCI"},"source_url":"https://mp.weixin.qq.com/s/kMwPDK6F78YABLQIBpUexA","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1146232184","content_text":"亲历了这周的风暴，这篇小短文就以手记的形式纪念一下。这周实在累的不行了，心累之余还有点遗憾，这么大的事件，竟然没有先知先觉，也就错过了这次的黑天鹅交易。怎么比喻这周发生的事情呢？我感觉最接近2020年三月。英国利率以及英镑市场完全垮掉，英国整个养老金市场差点扑街，而养老金里的LDI行业一夜之间就垮了。要是整个养老金市场垮了，就不是3月份了，那就是08年。好在央行出来救市了。。。这两天实在太心累，不想码太多字。市场上大概发生了什么，基础知识可以看看Degg_GlobalMacroFin这篇。这篇里我就重点讲讲我的一线经历。记住这俩人，几乎凭借了一己之力把巨大的养老金市场毁灭。当然，LDI这个行业的杠杆不能怪他们。 但是没有经验的情况下推出毫无节制的减税政策，是差点让养老金市场突然死亡的导火索。最简单的解释就是， 傻X的减税政策导致利率大幅飙升。 利率大幅飙升导致不少养老金用来对冲利率以及通胀风险的LDI基金里使用的利率（Interest rate swap）短期出现巨额亏损。 巨亏本身不是那么可怕，最可怕的是短期连续的巨亏，导致保证金很快就用光了。从8月底到9月底， 英国30年期利率暴涨了230个基点。这个暴涨的速度对这些持有利率互换的LDI基金有多大影响？ 我们可以初略的估算一下。一个规模10亿的养老金，持有的LDI基金里利率互换的DV01 (一个基点利率变动导致利率互换产生的损益） 是大概两百万。也就是说，过去两个月，因为30年期利率变动了230个基点。利率互换产生的损失就是230* 2m = 460m。 也就是说， 过去2个月，利率互换产生的亏损是这个养老金资产的接近一半！！！这个损失，不是真的亏损。因为这些利率互换是拿来对冲养老金负债端的，利率互换亏了，负债端的价值也下降了。理论上这个是个多空对冲交易不会产生什么损失。但是，但是， 但是,在上个例子里，这么短时间里，亏损了4个亿，那些LDI基金为了交保证金，首先卖出手中流动性最好的英国国债来筹集资金补保证金。懂一点场外交易的朋友会问，为啥这些基金不拿这些英国国债当保证金？ 因为不少场外交易是可以直接用国债当保证金的。 这就要牵扯到另一个话题，就是过去10年里利率互换市场经历了一场大变革。多数利率互换已经从单纯的场外交易变成了中央清算的场外交易。清算所是LCH,现在只能用现金做保证金。那么好了，重点来了， 这也就是死亡螺旋最重要的一步。英国国债利率，和英国利率互换的利率其实是差不多的东西。 因为利率互换亏钱了，基金经理要卖国债补保证金。 大量的抛售国债，导致国债利率上升， 而国债利率上升导致利率互换的利率上升，利率互换上升导致基金经理要卖更多的国债补保证金。。。。金融市场不怕涨，不怕跌，价格低了自然有人买，但是市场最怕这种死亡螺旋。这个养老金市场有多大呢？ 根据PPF的估计，8月底，养老金资产一共大约一共1.5万亿英镑。也就是说，过去两个月，整个养老金的LDI策略亏损导致的保证金的初略估算在6900亿 。 我朋友的LDI desk在上周五一天补交的保证金就是12个亿！对， 一天，一个desk 12亿！在抛售的过程中， 国债卖完了， 只有卖其他资产。 首先就是流动性好的股票。 这就导致股票也跟着跌，而且是无差别的跌。因为这个过程中，养老金由于补保证金的速度有要求(一般是T+0），所以只能闭着眼卖。股票跌就跌了，便宜了自然有人买。 但整个环节另一个要命的点是， 这些养老金过去10年里大幅度增加配置了没有流动性的资产， 比如地产，比如私募股权基金。 这些不是你想赎回就赎回的。 这就产生了一个巨大的问题，流动性错配！卖不了，抱歉交不上保证金那些利率互换的仓位就爆了。 投行交易台就必须要在市场上卖掉这些利率互换头寸。这就导致利率互换的利率继续上升！从而再拖垮其他流动性还不错的养老金。当时整个利率互换市场市场已经瘫痪， 多数做市商已经离场。 以前一年期的英国利率互换的买卖差价也就0.1-0.2 bps,当时已经上升到9-10bps!出现了死亡螺旋之后，唯一能够做的就是等英国央行救市。 好在央行果断出手，祭出QE压住国债利率上升的势头。死亡螺旋被打破。把不少养老金以及那些LDI基金从死亡的边缘拉回来。但不是所有的人都看到了黎明。 几家大的英国资管的LDI基金就爆了。 看看他们的股价就知道。。。。 我就不公布他们的名字了，留点口德。最惨的是那些倒在黎明前夜的养老金，以及靠这些养老金生活的持有人。如果救市再晚两天，整个养老金行业就gg了。而LDI这个行业随着这次巨震，即使活下来的基金也很难继续生存下去， 这个行业的商业模式的最大缺点已经被暴露了。而如果不用杠杆， 这个行业也生存不下去。只能说这个行业在不久的将来很可能会消失。打破了死亡螺旋，50年英国国债一天就上涨了40%！ 谁说国债涨的慢？","news_type":1,"symbols_score_info":{"EWU":0.9}},"isVote":1,"tweetType":1,"viewCount":1123,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":663050865,"gmtCreate":1662698970459,"gmtModify":1676537122763,"author":{"id":"3560270530016088","authorId":"3560270530016088","name":"DKTED","avatar":"https://static.laohu8.com/default-avatar.jpg","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3560270530016088","idStr":"3560270530016088"},"themes":[],"title":"","htmlText":"1","listText":"1","text":"1","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/663050865","repostId":"1159026938","repostType":4,"repost":{"id":"1159026938","kind":"news","pubTimestamp":1662693287,"share":"https://ttm.financial/m/news/1159026938?lang=en_US&edition=fundamental","pubTime":"2022-09-09 11:14","market":"us","language":"zh","title":"Howard Marks' latest memo: the illusion of cognition","url":"https://stock-news.laohu8.com/highlight/detail?id=1159026938","media":"橡树资本Oaktree Capital","summary":"世界上有两类预言家：一类对未来并无所知，而另一类不知道自己并无所知。","content":"<p><html><head></head><body>I began writing my first memo in February 1993, \"The Value of Predictions: Where Does the Rain Come From?\" (The Value of Projections, or Where'd All This Rain Come From) At the beginning, I kept expressing that I disregarded \"prediction\".</p><p>In the years since, I have explained in detail why I am not interested in forecasting—some of my favorite quotes in the following chapters echo my disdain for forecasting—but I have never again written a memo dedicated to explaining why making useful macroeconomic forecasts is so difficult. Hence the memorandum.</p><p><b>Things that introduce deep thought</b></p><p>There are two types of prophets in the world: one type does not know the future, and the other type does not know that they do not know. —Shortly after John Kenneth Galbraith finalized his memo, \"I Beg to Differ,” I attended a luncheon with some experienced investors and those outside the investment community. This is not a social event, but rather an opportunity for those present to exchange views on the investment environment.</p><p>During the session, the host asked a series of questions: How do you expect inflation to develop? Will there be a recession, and if so, how severe? How will the Russia-Ukraine conflict end? What impact might the 2022 and 2024 US elections have? I've heard all sorts of opinions on this.</p><p>Readers who have been following my memos for a long time can probably imagine my thoughts at the time: \"No one in this room is an expert in foreign affairs or politics. No one here has particularly in-depth insights into these topics, and certainly no one knows more than the average person reading this morning's news.\" The ideas conveyed, even on economic issues, seem no more convincing than others, and I absolutely believe that no one can improve investment results. This is the key.</p><p>It was that lunch that got me thinking about writing another memo about the unhelpful macro outlook. Soon after, I discovered some additional material—a book, an article from<i>Bloomberg Opinion (Bloomberg Opinion)</i>Articles and a newspaper article—these materials all support my argument (which could also be my \"confirmation bias\"—that is, people tend to accept and believe information and arguments that can prove their previously held views). That luncheon and these materials together inspired the theme of this memo:<b>There are many reasons why predictions are rarely beneficial.</b></p><p>To obtain something useful—whether in manufacturing, academia, or even the arts—one must have a reliable<b>Process</b>Able to provide the required<b>Input</b>Convert to desired<b>output</b>。 In short, the problem is that I don't think there is a single process that consistently translates a large number of variables (inputs) related to the economy and financial markets into useful macroeconomic forecasts (outputs).</p><p><b>model</b></p><p>The greatest enemy of cognition is not ignorance, but the illusion of cognition. —Daniel Burstein About the First decade of my tenure at First National City Bank, there was a term that was popular at the time but has long since been unheard of: econometrics. Specifically, it refers to a practice of finding correlations in economic data to generate effective forecasts. Or simply put, econometrics studies how to build mathematical models of the economy. Econometricians were hot in the 1970s, but I think their glory has faded. I think this means their model doesn't work.</p><p><b>Regardless of whether the model is complex and precise or hasty and simple, mathematically based or intuitive, the forecaster has no choice but to make judgments based on the model.</b>By definition, a model consists of the assumption: \"If A occurs, then B will occur.\" In other words, the model states relationships and responses. But for us to be willing to accept the model's output, we must be convinced that the model is reliable. But when I thought about modeling the economy, my first reaction was how complicated it would be.</p><p>For example, the United States has a population of approximately 330 million. Except for the particularly young and some particularly old, everyone else is an economic participant. Therefore, there are hundreds of millions of consumers, as well as millions of workers, producers, and middlemen (many of whom meet multiple categories). To predict the path of economic development, we must predict the behavior of these people—if not every participant, then at least the total population.</p><p>A realistic simulation of the U.S. economy must handle billions of interactions or nodes, including interactions with suppliers, customers, and other market participants around the world. Is it possible to do this? For example, is it possible to predict the behavior of consumers under the following circumstances: (i) if they receive an extra dollar in income (what is the \"marginal propensity to consume\"?); (ii) If rising energy prices squeeze other categories in the household budget; (iii) If the price of one commodity rises relative to other commodities (will this produce a \"substitution effect\"?); And (iv) if the geopolitical arena is stirred up by events on other continents?</p><p>Obviously, this level of complexity requires frequent use of simplified assumptions. For example, modeling would be easier if it could be assumed that a consumer would not purchase B instead of A if B was not better or cheaper (or both). It also helps to assume that the cost of producing X is no less than Y, then the producer will not price X below Y.</p><p>But what happens if consumers are still attracted to B's brand effect despite B's higher price (and even because of it)? What would happen if X was produced and developed by entrepreneurs who were willing to lose money for several years to gain market share? Is it possible for models to predict the decisions of consumers who are willing to spend more money and entrepreneurs who are willing to make less money (or even lose money)?</p><p>In addition, the model must predict the behavior of each group of participants in the economy in various environments. But the unpredictable factors are multifaceted. For example, a consumer may behave in one way at one moment and in a different way at another similar moment. Given the large number of variables involved, it seems impossible for two \"similar\" moments to occur in exactly the same way, and it is unlikely that we will see economic actors exhibiting the same behavior.</p><p>In addition, participants' behavior will be influenced by their psychology (or should I say their emotions?), and their psychology may be influenced by qualitative, non-economic development. How are these modeled?</p><p>How can an economic model be comprehensive enough to handle situations that have never been encountered before, or that have not occurred in modern times (i.e., under comparable circumstances)? This is yet another example of how models cannot simply replicate something as complex as the economy.</p><p>Of course, a typical example is the COVID-19 pandemic. It brought most of the world's economies to a standstill, disrupted consumer behavior, and triggered massive government bailouts. What aspects of existing models can predict the impact of the pandemic? Yes, the world experienced a pandemic in 1918, but the situation was so different (there were no iPhones, Zoom calls, etc.) that the economic situation during that period was almost incomparable to that of 2020.</p><p>In addition to factors such as complexity and elusive psychological fluctuations and dynamic processes, one must also consider the inherent limitations of trying to predict things that cannot be expected to remain constant. Shortly after I began writing this memo, I received Morgan Housel's consistently excellent weekly magazine. One of the articles describes many observations in other areas related to our economy and investment.</p><p>The following two are borrowed from the field of statistics, and I think they are relevant to the discussion of economic models and forecasts (\"A Little Way the World Works (Little Ways the World Works)\", Morgan Housel,<i>Collaborative Fund</i>, July 20, 2022):</p><p>Stability: This is an assumption that the main factors influencing the system do not change over time, based on the assumption that history can serve as a guide for future statistics. If you want to know how high to build a levee, look at flood data from the past 100 years and assume that it will be the same in the next 100 years. Stability is a wonderful, science-based concept, and it remains valid until it fails. It is the main driving force behind important events in the economy and politics. [But in our world,] \"things that have never happened before keep happening,\" says Stanford University professor Scott Sagan. Cromwell's Law: Never say something won't happen. ... Even if there is only a one in a billion chance of something coming true, and you will interact with billions of things in your lifetime, you will almost certainly experience some shocking unexpected events, and you should always be open to the possibility of the unbelievable becoming a reality. Stability may be a reasonable assumption in the field of physical science. For example, due to the law of universal gravitation, under given atmospheric conditions, objects can always descend with the same acceleration. The result is always like this, and it will always be like this. But in our field, few processes are smooth, especially when considering psychology, emotions, and human behavior, and they change over time.</p><p>Take the relationship between unemployment and inflation as an example. For the past 60 years or so, economists have relied on the Phillips curve, which suggests that wage inflation will rise as the unemployment rate falls because when there are fewer unemployed workers, employees gain bargaining power and can successfully negotiate higher wages. For decades, an unemployment rate of 5.5 percent was also considered to indicate \"full employment\".</p><p>However, the unemployment rate fell below 5.5% in March 2015 (and reached a 50-year low of 3.5% in September 2019), but inflation (wages or otherwise) did not rise significantly until 2021. The important relationships described by the Phillips curve have been applied to various economic models built over decades, but it does not seem to have been applicable for most of the past decade.</p><p>Cromwell's law is equally important. Unlike the physical sciences, in the realms of markets and economics, there are few things that absolutely must or absolutely cannot happen. Thus, in<i>Cycle</i>（<i>Mastering the Market Cycle</i>In my book, I listed seven terms that investors should remove from their vocabulary: \"never,\" \"always,\" \"forever,\" \"cannot,\" \"will,\" and \"must.\" But if these words really have to be discarded, then the idea of building models that can reliably predict the macroeconomic future must also be discarded. In other words, in our field, almost nothing is immutable.</p><p>The unpredictability of behavior is my favorite topic. The famous physicist Richard Feynman once said, \"Imagine how difficult physics would be if electrons had feelings.\" The laws of physics are reliable precisely because electrons always do what they are supposed to do. They never forget to fulfill their duties. They never resist. They never strike. They never innovate. They never act in the opposite way.</p><p><b>However, none of these apply to participants in the economy, and it is precisely because they do not apply that their behavior is unpredictable. If the behavior of participants is unpredictable, how can we model the operation of the economy?</b></p><p><b>We are talking about the future, and there is no way to predict it without making assumptions.</b>Small errors in assumptions about the economic environment and subtle changes in participant behavior can cause serious problems. As mathematician and meteorologist Edward Lorenz famously said, \"A Brazilian butterfly flapping its wings can trigger a tornado in Texas, USA.\" (Historian Niall Ferguson mentions this in an article discussed below.)</p><p>In conclusion, can we consider the economic model to be reliable? Can models replicate reality? Can it describe the behavior of millions of participants and their interactions? Is the process you are trying to model reliable? Can these processes be simplified to mathematics? Can mathematics capture the qualitative nuances of people and their behavior? Can the model predict changes in consumer preferences, changes in corporate behavior, and participants' responses to innovation? In other words, can we trust the output of the model?</p><p>Clearly, economic relationships are not static, and the economy is not governed by schematic diagrams (the diagrams that models attempt to simulate). So, for me, the bottom line is that the model's output points in the right direction most of the time without violating assumptions. But it can't always be accurate, especially at critical moments like inflection points... and that's when accurate predictions are most valuable.</p><p><b>Input</b></p><p>One fact that cannot be ignored is that all your knowledge is about the past, and all your decisions are about the future. —Ian H. Wilson (former General Electric executive) Having considered the incredible complexity of the economy and the need to make simplified assumptions (which would reduce the accuracy of any economic model), let's now consider the inputs needed for a model—the raw materials used to make the predictions. Is the estimated input valid? Can we understand them deeply enough to make meaningful predictions?<b>Or let us simply recall the ultimate truth about models: \"Input garbage, and the output will still be garbage\"?</b>Obviously, no prediction will be of better quality than the input on which it is based.</p><p>The following is Neil Ferguson's statement on July 17th.<i>Bloomberg Opinion (Bloomberg Opinion)</i>Content written:</p><p>Consider what we really want to ask when we ask the question, \"Has inflation peaked? \" We are asking about more than just the supply and demand of 94,000 different goods, manufactured goods, and services. We are still concerned about the future interest rate path set by the Federal Reserve, and aside from the much-touted \"forward guidance,\" its future direction remains far from clear. We are asking how long the strong dollar will last, because it is currently depressing the prices of U.S. imports. But there are still many more questions to be answered. At the same time, the above questions also indirectly ask how long the Russia-Ukraine conflict will last, as the chaos caused by the conflict since February has significantly exacerbated inflation in energy and food prices. We are asking whether oil-producing countries like Saudi Arabia will respond to Western governments' requests to increase crude oil production... We should probably also ask ourselves what impact the latest coronavirus, Omeprone BA.5, will have on Western labor markets. British data show that BA.5 is 35% more infectious than its predecessor BA.2, while BA.2 is more than 20% more infectious than the original Omeprone. If you want to add all these variables to your model, then I wish you good luck. In fact, the future path of inflation, like the future direction of the Russia-Ukraine conflict and the spread of the COVID-19 pandemic, is uncertain. I found Ferguson's article very relevant to the subject of this memo, so I am attaching a link to it here. This article makes many important points, although I disagree with one aspect. Ferguson mentioned above, \"In fact, the future path of inflation, like the future direction of the Russia-Ukraine conflict and the spread of the COVID-19 pandemic, is uncertain.\"</p><p>I believe that accurately predicting inflation is \"less likely\" to happen than predicting the other two issues (if it can be predicted), because accurately predicting inflation requires correct predictions of both events and a thousand other influencing factors. How could anyone possibly get all these things right?</p><p>Let me briefly introduce the forecasting process mentioned in \"The Value of Forecasting\":</p><p>think for most fund managers, the process goes like this: \"I predict the economy will do A. If A happens, interest rates should perform B. If interest rates are B, the stock market should perform C. In this environment, the best-performing sector should be D, and stock E should rise the most.\" Then I build my portfolio accordingly, hoping to achieve the best performance in this situation. But in any case, how likely is E? Remember that E is conditional on A, B, C, and D. In the field of prediction, a two-thirds accuracy rate would be a remarkable achievement. However, if each of the five predictions has a 67% chance of being correct, then the result is that all five predictions are correct and the stock has a 13% chance of performing as expected.<b>Predicting event E based on assumptions about A, B, C, and D is what I call single-scenario prediction.</b>In other words, if the result of the hypothesis about A, B, C, or D proves to be wrong, then the prediction of E is unlikely to be realized. Only when all potential predictions are correct can E obtain a result that is consistent with the predictions, but this is extremely rare. No one can make a wise investment without considering (i) the other possible outcomes of each element, (ii) the likelihood of other scenarios occurring, (iii) what the prerequisites are for making one of the hypotheses a reality, and (iv) what the impact on E is.</p><p>Ferguson's article raises an interesting question about economic modeling: what assumptions should we make about the macroeconomic environment in which economic actors live? this<b>This question illustrates a vicious cycle: in order to predict the overall performance of the economy, we need to make assumptions about aspects such as consumer behavior. But to predict consumer behavior, don't we need to make assumptions about the overall economic environment?</b></p><p>In my first memo about the pandemic, Nobody Knows II (March 2020), I mentioned that when discussing the coronavirus, Harvard epidemiologist Marc Lipsitch said: (a) the facts; (ii) well-founded inferences drawn by analogy with other viruses, and (iii) opinions or speculations. This is our standard practice when dealing with uncertain events. In economic or market forecasting, we have a wealth of history and many similar past events to infer (but not the COVID-19 pandemic). But even if these things are used as input by a well-constructed predictive model, they are still unlikely to predict the future. They can be useful material, or they can be garbage.</p><p>To illustrate this point, people often ask me which cycle I experienced in the past is most similar to the current one. My answer is that current developments bear brief similarities to some past cycles, but there are no absolute similarities.<b>In each case, the differences are enormous and outweigh the similarities.</b></p><p><b>Even if we can find an identical earlier period, to what extent should we rely on this single sample? I think the answer is not many. Investors rely on historical references (and the forecasts they make based on them) because they fear they will act blindly without them. However, this does not mean that this information is reliable.</b></p><p><b>Unpredictable effects</b></p><p>Predictions create mirages where the future is known. —Peter Bernstein<b>Without first determining whether our world is ordered or random, we cannot consider the plausibility of predictions.</b>In short, is it completely predictable, completely unpredictable, or somewhere in between? For me, the conclusion is somewhere in between, but more likely to be unpredictable, so much so that most predictions are useless. Since our world is predictable at some times and unpredictable at others, what good is prediction if we cannot distinguish between predictable and unpredictable times?</p><p>I learned a new word from reading Ferguson's article: \"deterministic\". The Oxford Dictionary defines it as \"causally determined by previous events or natural laws\". The world is much simpler when we follow the rules... just like Feynman's electrons. However, it is clear that economies and markets are not governed by natural laws—thanks to human involvement—and that previous events may be \"prelude\" or \"tend to repeat themselves,\" but events rarely occur in the same way twice. Therefore, I believe that the processes that constitute economic and market operations are not deterministic, which means they are unpredictable.</p><p>Furthermore, the input is obviously unreliable. Many are random, such as weather, earthquakes, accidents, and deaths. Others involve political and geopolitical issues—some known to us, some yet to surface.</p><p>In his Bloomberg Opinion article, Ferguson mentioned the British writer GK Chesterton. This reminds me of a Chesterton quote I quoted in Risk Revisited Again (June 2015):</p><p>The real problem in our world today is not that it is irrational, nor that it is a rational world. The most common question is: the world is almost rational, but not entirely so. Life is not a contradiction, but it is a logician's trap.<b>It looks slightly more precise and regular than it actually is; Its accuracy is obvious, but its imprecision is hidden; Its wildness is also lurking.</b>(Bold text added by the author) Returning to the luncheon introduced on the first page, the host's opening remarks were roughly as follows: \"In recent years, we have experienced events such as the COVID-19 pandemic, the remarkably successful Federal Reserve bailout policy, and the Russia-Ukraine conflict. It has been a very challenging environment because all of this has come out of the blue.\"</p><p>I think for him, this means that attendees should free themselves from the trouble of inaccurate predictions for 2020-2022, continue to predict the future, and bet on their own judgment. But my reaction was completely different: \"There are many events affecting the current environment.<b>Isn't the fact that no one can predict any of them enough to convince those present that they should abandon predictions?</b></p><p>For another example, let's think back to the fall of 2016. There are two things that almost everyone is convinced of: (a) Hillary Clinton will be elected president; (ii) If Donald Trump is elected for some reason, the market will collapse. Nevertheless, the result was that Trump won, and the market soared.</p><p>The past six years have had a profound impact on the economy and markets.<b>I believe that any traditional predictions about the 2016 election at the time would not have been correct.</b>Isn't this enough to convince people that (a) we don't know what the future holds, and (b) we can't understand how the market will react to what happens?</p><p><b>Can the forecast lead to an excess?</b></p><p>What gets us into trouble is not ignorance, but seemingly correct false assertions. —Mark Twain As I mentioned in my recent memo, \"Thinking About Macro,\" in the 1970s we described economists as \"investment directors who never enter the market.\" In other words, economists make numerous predictions; Actual circumstances will prove them right or wrong; Then they went on to make new predictions; But they don't keep track of how often their predictions are correct (or they don't publish statistics).</p><p>Can you imagine hiring a fund manager without reference to track record (or if you were a fund manager, could you imagine being hired in this situation)? However, economists and strategists will not lose their jobs because they do not publish statistics, probably because there are always clients willing to pay for their forecasts.</p><p>Are you a consumer of these predicted results? Are the forecasters and economists employed by your company? Or do you subscribe to their publications and invite them to present, as my former employer did? If so, do you know how often everyone predicts correctly? Have you found a way to strictly determine which of these predictions can be relied upon and which should be ignored? Is there a way to quantify the contribution of these forecasts to your return on investment?</p><p>I asked this series of questions because I hadn't seen or heard of any research on this topic. It is hard to imagine that global information about whether macroeconomic forecasts will lead to excess returns is scarce, especially compared to the number of people who need such information.</p><p>Despite the lack of evidence to prove its value, macroeconomic forecasts continue. Many forecasters are part of equity fund management teams or provide advice and forecasts to these teams.</p><p>One thing is certain: actively managed equity funds have been losing market share for decades due to poor performance of actively managed funds, replaced by index funds and other passive investment vehicles. Actively managed funds now account for less than half of the U.S. equity mutual fund market. Is this the reason why macroeconomic forecasts are inherently unhelpful for investment?</p><p>As far as I know, the only quantitative information available on this issue is the performance of so-called macro hedge funds. The Hedge Fund Research Group (HFR) publishes the Hedge Fund Weighted Composite Index and some sub-strategy indices. The following is the long-term performance of the hedge fund weighted composite index, the macro hedge sub-strategy index, and the S&P 500 index.<img src=\"https://static.tigerbbs.com/79717be010acf96241bf0336e5ac3381\" tg-width=\"963\" tg-height=\"272\" referrerpolicy=\"no-referrer\" width=\"100%\" height=\"auto\"/>*Performance as of July 31, 2022. The hedge fund index shown is a weighted composite index of each fund.</p><p>In the table above, according to HFR data, the average performance of hedge funds during the study period was far below that of the S&P 500 index, and the average performance of macro hedge sub-strategy funds was much worse (especially between 2012 and 2017). Given that investors continue to entrust approximately $4.5 trillion to hedge fund managers, these funds must provide some benefits beyond returns, but it is unclear what this will be. This seems especially true for macro hedge funds.</p><p>To confirm my prediction, I will now cite a rare example of self-evaluation: a seven-page feature article entitled \"I Was Wrong\" in the \"Sunday View\" column of the New York Times on July 24. In the article, eight New York Times \"Opinion\" columnists revealed their past erroneous predictions and biased advice.</p><p>Most relevant here is a confession by Paul Krugman entitled \"I Was Wrong About Inflation\". I've excerpted some of these and strung them together:</p><p>In early 2021, economists engaged in a heated debate about the possible consequences of the \"American bailout plan\"... I was on the side [of supporting less concern about the impact of inflation]. Of course, it turned out to be a very bad decision... History could not have predicted such overheated inflation. So there's something wrong with my model... One possible reason is that history is misleading... In addition, the disruptions caused to adapt to the pandemic and its consequences may still be playing a large role. Of course, the Russia-Ukraine conflict and the epidemic prevention and control measures in major Chinese cities have undoubtedly pushed this level of interference to a whole new level... In any case, the whole thing has become a humbling lesson. Incredibly, the standard economic model has been working quite well since the 2008 financial crisis, and I thought there was no problem using the same model in 2021. Looking back now, I should have realized that this inference was inherently risky in the new world trends that emerged after the COVID-19 pandemic. (Bold emphasis added) I admire Krugman's remarkable frankness (although I have to say that I don't recall many market forecasts between 2009 and 2010 being optimistic enough to describe the reality of the following decade).<b>Krugman's explanation of his mistake is good in itself, but I don't see him mentioning abandoning modeling, inference, or prediction in the future.</b></p><p>This humility may even permeate the Federal Reserve, one of the world's largest economic forecasters, which employs more than 400 PhDs in economics. The following is what economist Gary Shilling wrote in Bloomberg Opinion on August 22:</p><p>The Fed's forward guidance has been a disaster, challenging its own credibility. Chairman Jerome Powell seems to share this view, suggesting that the outside world should stop speculating about the Federal Reserve's views on interest rates, economic growth, and inflation at different points in the future...<b>The fundamental problem with forward guidance is that it relies on data, which itself comes from the Federal Reserve's past poor forecasting record.</b>The Federal Reserve has been overly optimistic about the economic recovery after the Great Recession of 2007-2009. In September 2014, policymakers predicted real GDP growth of 3.40% in 2015, but by September 2015 they were forced to keep lowering their forecasts to 2.10%.<b>Federal Funds rate is not a market-determined interest rate, but is set and controlled by the Federal Reserve, and no one challenges the Fed's authority. Furthermore, members of the Federal Open Market Committee (FOMC) are notoriously bad at predicting what actions they themselves will take...</b>In 2015, their average forecast for Federal Funds rate in 2016 was 0.90%, and in 2019 it was 3.30%. The actual figures were 0.38% and 2.38% respectively... It is certain that many ongoing events have created market uncertainty, but the Federal Reserve's forward guidance has always been highly sought after and important. Recall that earlier this year, the Federal Reserve also believed that inflation caused by the friction of the pandemic and restarting the economy after supply chain disruptions was temporary. Only later did the Federal Reserve realize that things were not going well and reverse course, raising interest rates and signaling further significant rate hike. The Federal Reserve's erroneous forecasts led to erroneous forward guidance, exacerbating financial market volatility. (Bold added by the author) On this question, I would like to make one last point: where exactly are those people who have made a name (and become rich) by profiting from macroeconomic perspectives? I certainly can't know everyone in the investment world, but among those I know or understand, I believe there are only a few \"macro investors\" who can be considered very successful. When there are few examples of something, as my mother once said, \"the exception just confirms the rule.\"</p><p><b>The pattern in this example is that macroeconomic forecasts rarely lead to outstanding performance. For me, the extraordinary nature of the success stories just proves that this statement is a universal truth.</b></p><p><b>Practitioners' predicted needs</b></p><p>Compared to revealing the future, predictions can reveal the predictor better. —Warren Buffett How many people can make macroeconomic predictions that are valuable most of the time? I don't think so. How many investment managers, economists, and forecasters have tried it? There are at least several thousand. This raises an interesting question: why predict? If macro forecasting doesn't help investment success over time, why do so many practitioners in the investment management industry believe in forecasting and flock to its results? I think the typical reason for this might be:</p><p><ul><li>It's part of the job.</p><p></li><li>Investors have always done this.</p><p></li><li>Everyone I know does this, especially my competitors.</p><p></li><li>I've been doing this—I can't stop now.</p><p></li><li>If I don't do this, I won't be able to attract customers.</p><p></li><li>Since investing involves deploying capital to benefit from future events, how can one expect to do a good job without a perspective on those events? We need predictions, even if they are not perfect.</p><p></li></ul>This summer, my son Andrew recommended I read a very interesting book: \"Making Mistakes (But It's Not My Fault): Why We Make Excuses for Foolish Beliefs, Bad Decisions, and Hurtful Behaviors.\" (Mistakes Were Made (but Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts), The book was written by psychologists Carol Tavris and Elliot Aronson.<b>The theme of the book is self-defense.</b></p><p><b>The authors explain that \"cognitive dissonance\" occurs when people are faced with new evidence that challenges their previously held positions, and when this happens, the subconscious mind will make them try hard to prove and maintain their previous positions.</b>Here are some selections:</p><p>If you hold a set of beliefs that guide your practice, and you learn that some of them are incorrect, you must either admit that you are wrong and change your approach, or reject new evidence. Most people, when confronted directly with evidence that they are wrong, do not change their opinion or plan of action, but instead become more stubborn in their arguments. Once we have established a belief and proven its wisdom, it is obviously hard work to change our minds. It is much easier to put new evidence into an existing framework for psychological argumentation for acceptance than to change the framework. Mechanisms people typically employ when responding to evidence that challenges their beliefs include these (to paraphrase the author):</p><p><ul><li>Unwillingness to listen to disharmonious information;</p><p></li><li>Selectively remember parts of their lives, focusing on those parts that support their views; as well as</p><p></li><li>Acting under cognitive biases allows people to see only what they want to see and seek some kind of confirmation for what they already believe.</p><p></li></ul>I believe these are all factors that lead people to consistently make predictions and rely on them. In this situation, what kind of manifestation will it take?</p><p><ul><li>Consider macroeconomic forecasting as an integral part of investment;</p><p></li><li>Eager to recall correct predictions, especially those that are bold and non-market consensus;</p><p></li><li>Overestimating the accuracy of predictions;</p><p></li><li>Forgetting or downplaying erroneous predictions;</p><p></li><li>Failure to keep records of prediction accuracy or failure to calculate average success rate;</p><p></li><li>Emphasis is placed on the generous rewards that reward accurate predictions;</p><p></li><li>Emphasize that \"everyone should do this\"; as well as</p><p></li><li>Perhaps most importantly, unsuccessful predictions are blamed on being blinded by random or exogenous events. (But, as I said before, this is the crux of the matter: if predictions become so easily inaccurate, why make them?)</p><p></li></ul>Most people—even honest people with good intentions—take positions or actions that serve their own interests, sometimes at the expense of others or objective truth. They themselves are unaware of this situation, but instead believe that what they are doing is the right thing; They also sought many legitimate reasons. As Charlie Munger often quotes Dimosini, \"Nothing is easier than deceiving yourself. Because people always believe what they want.\"</p><p>I don't think forecasters are liars or charlatans. Most of them are smart intellectuals who think they are doing something useful.<b>However, self-interest makes them act a certain way, while self-defense makes them stick to their opinions when faced with contrary evidence.</b>As Morgan Housel stated in a recent current affairs briefing:</p><p>The inability to predict the past does not affect our willingness to predict the future. Certainty is so precious that we will never give up on it, and if people are honest about how unpredictable the future is, most people will never be able to get out of bed in the morning. (From \"Big Beliefs,\" Collaborative Fund, August 24, 2022) A few years ago, on my birthday, Richard Masson, co-founder of Oaktree, gave me a fun gift that was in keeping with his style. The gift that time was<i>The New York times</i>A bound edition. I've been hoping for an opportunity to write about my favorite subheading from the issue of October 30, 1929, when the Dow Jones Industrial Average had just fallen nearly 23% in two days.</p><p><b>The headline reads, \"Bankers Optimistic.\"</b>(However, over the next three years, the Dow Jones Industrial Average fell by about 85%.) Most bankers and fund managers seem innately optimistic about the future. Beyond that, it's in their best interest because it helps them do more business. But their optimism certainly shaped their predictive views and the resulting behavior.</p><p><b>Is it possible or not?</b></p><p>\"I never consider the future—because it is just around the corner.\" — Albert Einstein considers the following aspects of macroscopic forecasting:</p><p><ul><li>Number of assumptions/inputs required,</p><p></li><li>The number of processes/relationships to be included,</p><p></li><li>The inherent unreliability and instability of these processes, and</p><p></li><li>The role of randomness and the possibility of accidents.</p><p></li></ul>For me, the most important thing is that predictions cannot always be correct enough to be worthwhile. I've mentioned it many times, but for the sake of completeness, I'll reiterate my views on the utility (or rather, futility) of macro-forecasting:</p><p><ul><li>Most forecasts consist of inferences about past performance.</p><p></li><li>Since macroeconomic developments usually do not deviate from previous trends, inferences are usually successful.</p><p></li><li>On this basis, most predictions are correct. However, since inferences are usually expected by security prices, those who base their expectations on inferences do not enjoy excess benefits when their inferences hold true.</p><p></li><li>Occasionally, economic behavior does deviate substantially from past patterns. Because this deviation is unexpected by most investors, its occurrence can impact the market, meaning that accurate predictions of deviations can yield substantial profits.</p><p></li><li>However, because the economy does not often deviate from past performance, few can accurately predict deviations, and most deviation predictions turn out to be wrong in hindsight.</p><p></li><li>Therefore, we have (i) inferential predictions, most of which are correct but do not generate excess benefits, and (ii) potentially profitable biased predictions, which are rarely correct and therefore do not usually generate excess benefits.</p><p></li><li>It has been demonstrated that most forecasts do not increase returns.</p><p></li></ul>At the luncheon mentioned at the beginning of this memo, people were asked about their expectations regarding aspects such as Federal Reserve policy and how this would affect their investment stance. One person replied, \"I think the Fed will remain highly concerned about inflation, and therefore will rate hike sharply, leading to a recession. That's why I'm choosing to be risk-averse.\" Another said, \"I expect inflation to slow in the fourth quarter, and the Fed to shift to a dovish stance in January. Start cutting interest rates and stimulating the economy. I'm very optimistic about 2023.\"</p><p>We often hear this statement.<b>However, it must be recognized that these people are using a univariate model:</b>The prediction of the speaker is based on a single variable. Speaking of simplified assumptions: These forecasters implicitly believe that everything is constant except for the Federal Reserve's policies. When they needed to play three-dimensional chess, they were still playing flat checkers.</p><p>Aside from the impossibility of predicting the Fed's behavior, the impact of inflation on such behavior, and the market's reaction to inflation, what other important considerations are there? If a thousand things play a role in determining the future direction of the economy and markets, what are the other 999 things? What will be the impact of wage negotiations, midterm elections, the Russia-Ukraine conflict, and oil prices?</p><p>The truth is that people can only remember a very limited number of things in their minds at any given time.<b>It is difficult to take into account a large number of factors, and it is even more difficult to understand how a large number of things will interact (correlation is always a real thinking problem).</b></p><p>Even if you somehow manage to get the economic forecast right, that's only half the battle. You still need to predict how economic activity will translate into market outcomes. This requires a completely different prediction and involves countless variables, many of which are related to psychological factors and are therefore almost unknowable.</p><p>According to student Warren Buffett's recollection, Ben Graham once said, \"In the short run, the market is a voting machine, but in the long run, it's a weighing machine.\" How can we predict investors' short-term choices? Some economic forecasters have concluded that the actions announced by the Federal Reserve and the Treasury Department in March 2020 will save the U.S. economy and help the economic recovery. But I don't know who predicted that a hot bull market had already begun before the recovery began.</p><p>As I mentioned earlier, Buffett shared his views on macroeconomic forecasting with me in 2016. \"For a piece of information to be useful, it must meet two criteria: First, it must<b>important</b>Secondly, it is necessary<b>It is known</b>。\"</p><p><ul><li><b>Of course, the macro outlook is important.</b>Today, investors seem to have grasped the rhetoric of every forecaster, macroeconomic events, and signals of the Federal Reserve's intermittent tightening actions. Unlike in my early days in this industry, it seems that macro factors are everything now, and corporate development is not given as much attention.</p><p></li><li><b>But I strongly agree with Buffett that the macro future is unknowable,</b>Or at least almost no one consistently knows more than the vast majority of investors, which is the key to trying to gain a cognitive edge and make excellent investment decisions.</p><p></li></ul>Clearly, Buffett's name ranks high on the list of successful investors. He avoids macro forecasting and focuses more on the \"micro\" areas than others: companies, industries, and securities, which has led to his success.</p><p>I introduced the concepts of the \"knowable\" and \"agnostic\" schools in a 2001 memo entitled \"What's It All About, Alpha?\", and elaborated on Them in 2004 in my article \"Us and Them\". As a conclusion to the current memo, I will insert something I wrote about these two genres in the latter:</p><p>Most of the investors I've met over the years have been of the \"knowable\" school of thought. This was true when I analyzed stocks between 1968 and 1978, and even when I turned to non-mainstream investing between 1978 and 1995, but still worked for an investment management company centered on stocks.</p><p>Identifying members of the \"knowledge\" school is easy:</p><p><ul><li>They believe that understanding the future direction of the economy, interest rates, markets, and widely watched mainstream stocks is crucial for investment success.</p><p></li><li>They are confident that they can achieve this.</p><p></li><li>They knew they could do it.</p><p></li><li>They know that many people are also trying to do this, but they think that either (a) everyone can succeed at the same time, or (b) only a few people can do it, but they are one of them.</p><p></li><li>They are willing to invest according to their views on the future.</p><p></li><li>They are also happy to share their opinions with others, although correct predictions should be priceless and no one gives them away for free.</p><p></li><li>They rarely look back and seriously review their achievements as forecasters.</p><p></li></ul>\"Confidence\" is the key word to describe the members of this genre. On the other hand, for the \"agnostic\" school, the word should be \"cautious\", especially when looking at the macroeconomic future.<b>Its believers generally believe that the future cannot be predicted; There is no need to predict the future; The right goal should be to do your best to invest well, while acknowledging that you lack this understanding.</b></p><p>As a member of the \"knowable\" school, you can express your opinion about the future (and perhaps someone else will take notes on this subject). You may be sought after and seen as an ideal dinner guest... especially when the stock market is rising.</p><p>If you join the \"agnostic\" school, the results are even more complicated. You will soon get tired of expressing \"agnosticism\" to friends and strangers. Before long, even relatives will no longer ask you for your opinion on market trends. You will never enjoy that one-thousandth surprise moment when the prediction comes true, nor will you enjoy the joy of having your photo published in the Wall Street Journal.</p><p>On the other hand, you are also protected from forecasting errors and from losses resulting from investing based on overconfidence in the future.<b>But how do you think it feels when a potential customer asks you about your investment prospects and you have to say \"I don't know\"?</b></p><p>For me, the best bottom line for judging which school of thought is based on a famous quote from the late Stanford University behavioral scientist Amos Tversky:<b>\"It's scary to realize that you may not know something, but it's even scarier to realize that, in general, the world is run by people who firmly believe they know exactly what's happening.\"</b></p><p>In investment management, it is certainly standard practice to make macro forecasts, share them upon request, and use them as a basis for entrusted client investments. It seems to be common practice for fund managers to believe in predictions, especially their own. As mentioned above, not doing so seems out of place. But are their beliefs realistic? I'd love to hear what everyone thinks.</p><p>Years ago, a well-respected sell-side economist (an old acquaintance of mine from my time at Citi) called me and said, \"You changed my life,\" he said. \"I stopped making predictions a long time ago. Instead, I just told people what happened today and what I think it might have on the future. Life became better from then on.\" Can I help you achieve the same state of happiness?</p><p>Author: Howard Marks</p><p></body></html></p>","source":"lsy1658993322555","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" content=\"width=device-width,initial-scale=1.0,minimum-scale=1.0,maximum-scale=1.0,user-scalable=no\"/>\n<meta name=\"format-detection\" content=\"telephone=no,email=no,address=no\" />\n<title>Howard Marks' latest memo: the illusion of cognition</title>\n<style type=\"text/css\">\na,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,\nem,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,\nobject,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{ font:inherit;margin:0;padding:0;vertical-align:baseline;border:0 }\nbody{ font-size:16px; line-height:1.5; color:#999; background:transparent; }\n.wrapper{ overflow:hidden;word-break:break-all;padding:10px; }\nh1,h2{ font-weight:normal; line-height:1.35; margin-bottom:.6em; }\nh3,h4,h5,h6{ line-height:1.35; margin-bottom:1em; }\nh1{ font-size:24px; }\nh2{ font-size:20px; }\nh3{ font-size:18px; }\nh4{ font-size:16px; }\nh5{ font-size:14px; }\nh6{ font-size:12px; }\np,ul,ol,blockquote,dl,table{ margin:1.2em 0; }\nul,ol{ margin-left:2em; }\nul{ list-style:disc; }\nol{ list-style:decimal; }\nli,li p{ margin:10px 0;}\nimg{ max-width:100%;display:block;margin:0 auto 1em; }\nblockquote{ color:#B5B2B1; border-left:3px solid #aaa; padding:1em; }\nstrong,b{font-weight:bold;}\nem,i{font-style:italic;}\ntable{ width:100%;border-collapse:collapse;border-spacing:1px;margin:1em 0;font-size:.9em; }\nth,td{ padding:5px;text-align:left;border:1px solid #aaa; }\nth{ font-weight:bold;background:#5d5d5d; }\n.symbol-link{font-weight:bold;}\n/* header{ border-bottom:1px solid #494756; } */\n.title{ margin:0 0 8px;line-height:1.3;color:#ddd; }\n.meta {color:#5e5c6d;font-size:13px;margin:0 0 .5em; }\na{text-decoration:none; color:#2a4b87;}\n.meta .head { display: inline-block; overflow: hidden}\n.head .h-thumb { width: 30px; height: 30px; margin: 0; padding: 0; border-radius: 50%; float: left;}\n.head .h-content { margin: 0; padding: 0 0 0 9px; float: left;}\n.head .h-name {font-size: 13px; color: #eee; margin: 0;}\n.head .h-time {font-size: 12.5px; color: #7E829C; margin: 0;}\n.small {font-size: 12.5px; display: inline-block; transform: scale(0.9); -webkit-transform: scale(0.9); transform-origin: left; -webkit-transform-origin: left;}\n.smaller {font-size: 12.5px; display: inline-block; transform: scale(0.8); -webkit-transform: scale(0.8); transform-origin: left; -webkit-transform-origin: left;}\n.bt-text {font-size: 12px;margin: 1.5em 0 0 0}\n.bt-text p {margin: 0}\n</style>\n</head>\n<body>\n<div class=\"wrapper\">\n<header>\n<h2 class=\"title\">\nHoward Marks' latest memo: the illusion of cognition\n</h2>\n<h4 class=\"meta\">\n<p class=\"head\">\n<strong class=\"h-name small\">橡树资本Oaktree Capital</strong><span class=\"h-time small\">2022-09-09 11:14</span>\n</p>\n</h4>\n</header>\n<article>\n<p><html><head></head><body>I began writing my first memo in February 1993, \"The Value of Predictions: Where Does the Rain Come From?\" (The Value of Projections, or Where'd All This Rain Come From) At the beginning, I kept expressing that I disregarded \"prediction\".</p><p>In the years since, I have explained in detail why I am not interested in forecasting—some of my favorite quotes in the following chapters echo my disdain for forecasting—but I have never again written a memo dedicated to explaining why making useful macroeconomic forecasts is so difficult. Hence the memorandum.</p><p><b>Things that introduce deep thought</b></p><p>There are two types of prophets in the world: one type does not know the future, and the other type does not know that they do not know. —Shortly after John Kenneth Galbraith finalized his memo, \"I Beg to Differ,” I attended a luncheon with some experienced investors and those outside the investment community. This is not a social event, but rather an opportunity for those present to exchange views on the investment environment.</p><p>During the session, the host asked a series of questions: How do you expect inflation to develop? Will there be a recession, and if so, how severe? How will the Russia-Ukraine conflict end? What impact might the 2022 and 2024 US elections have? I've heard all sorts of opinions on this.</p><p>Readers who have been following my memos for a long time can probably imagine my thoughts at the time: \"No one in this room is an expert in foreign affairs or politics. No one here has particularly in-depth insights into these topics, and certainly no one knows more than the average person reading this morning's news.\" The ideas conveyed, even on economic issues, seem no more convincing than others, and I absolutely believe that no one can improve investment results. This is the key.</p><p>It was that lunch that got me thinking about writing another memo about the unhelpful macro outlook. Soon after, I discovered some additional material—a book, an article from<i>Bloomberg Opinion (Bloomberg Opinion)</i>Articles and a newspaper article—these materials all support my argument (which could also be my \"confirmation bias\"—that is, people tend to accept and believe information and arguments that can prove their previously held views). That luncheon and these materials together inspired the theme of this memo:<b>There are many reasons why predictions are rarely beneficial.</b></p><p>To obtain something useful—whether in manufacturing, academia, or even the arts—one must have a reliable<b>Process</b>Able to provide the required<b>Input</b>Convert to desired<b>output</b>。 In short, the problem is that I don't think there is a single process that consistently translates a large number of variables (inputs) related to the economy and financial markets into useful macroeconomic forecasts (outputs).</p><p><b>model</b></p><p>The greatest enemy of cognition is not ignorance, but the illusion of cognition. —Daniel Burstein About the First decade of my tenure at First National City Bank, there was a term that was popular at the time but has long since been unheard of: econometrics. Specifically, it refers to a practice of finding correlations in economic data to generate effective forecasts. Or simply put, econometrics studies how to build mathematical models of the economy. Econometricians were hot in the 1970s, but I think their glory has faded. I think this means their model doesn't work.</p><p><b>Regardless of whether the model is complex and precise or hasty and simple, mathematically based or intuitive, the forecaster has no choice but to make judgments based on the model.</b>By definition, a model consists of the assumption: \"If A occurs, then B will occur.\" In other words, the model states relationships and responses. But for us to be willing to accept the model's output, we must be convinced that the model is reliable. But when I thought about modeling the economy, my first reaction was how complicated it would be.</p><p>For example, the United States has a population of approximately 330 million. Except for the particularly young and some particularly old, everyone else is an economic participant. Therefore, there are hundreds of millions of consumers, as well as millions of workers, producers, and middlemen (many of whom meet multiple categories). To predict the path of economic development, we must predict the behavior of these people—if not every participant, then at least the total population.</p><p>A realistic simulation of the U.S. economy must handle billions of interactions or nodes, including interactions with suppliers, customers, and other market participants around the world. Is it possible to do this? For example, is it possible to predict the behavior of consumers under the following circumstances: (i) if they receive an extra dollar in income (what is the \"marginal propensity to consume\"?); (ii) If rising energy prices squeeze other categories in the household budget; (iii) If the price of one commodity rises relative to other commodities (will this produce a \"substitution effect\"?); And (iv) if the geopolitical arena is stirred up by events on other continents?</p><p>Obviously, this level of complexity requires frequent use of simplified assumptions. For example, modeling would be easier if it could be assumed that a consumer would not purchase B instead of A if B was not better or cheaper (or both). It also helps to assume that the cost of producing X is no less than Y, then the producer will not price X below Y.</p><p>But what happens if consumers are still attracted to B's brand effect despite B's higher price (and even because of it)? What would happen if X was produced and developed by entrepreneurs who were willing to lose money for several years to gain market share? Is it possible for models to predict the decisions of consumers who are willing to spend more money and entrepreneurs who are willing to make less money (or even lose money)?</p><p>In addition, the model must predict the behavior of each group of participants in the economy in various environments. But the unpredictable factors are multifaceted. For example, a consumer may behave in one way at one moment and in a different way at another similar moment. Given the large number of variables involved, it seems impossible for two \"similar\" moments to occur in exactly the same way, and it is unlikely that we will see economic actors exhibiting the same behavior.</p><p>In addition, participants' behavior will be influenced by their psychology (or should I say their emotions?), and their psychology may be influenced by qualitative, non-economic development. How are these modeled?</p><p>How can an economic model be comprehensive enough to handle situations that have never been encountered before, or that have not occurred in modern times (i.e., under comparable circumstances)? This is yet another example of how models cannot simply replicate something as complex as the economy.</p><p>Of course, a typical example is the COVID-19 pandemic. It brought most of the world's economies to a standstill, disrupted consumer behavior, and triggered massive government bailouts. What aspects of existing models can predict the impact of the pandemic? Yes, the world experienced a pandemic in 1918, but the situation was so different (there were no iPhones, Zoom calls, etc.) that the economic situation during that period was almost incomparable to that of 2020.</p><p>In addition to factors such as complexity and elusive psychological fluctuations and dynamic processes, one must also consider the inherent limitations of trying to predict things that cannot be expected to remain constant. Shortly after I began writing this memo, I received Morgan Housel's consistently excellent weekly magazine. One of the articles describes many observations in other areas related to our economy and investment.</p><p>The following two are borrowed from the field of statistics, and I think they are relevant to the discussion of economic models and forecasts (\"A Little Way the World Works (Little Ways the World Works)\", Morgan Housel,<i>Collaborative Fund</i>, July 20, 2022):</p><p>Stability: This is an assumption that the main factors influencing the system do not change over time, based on the assumption that history can serve as a guide for future statistics. If you want to know how high to build a levee, look at flood data from the past 100 years and assume that it will be the same in the next 100 years. Stability is a wonderful, science-based concept, and it remains valid until it fails. It is the main driving force behind important events in the economy and politics. [But in our world,] \"things that have never happened before keep happening,\" says Stanford University professor Scott Sagan. Cromwell's Law: Never say something won't happen. ... Even if there is only a one in a billion chance of something coming true, and you will interact with billions of things in your lifetime, you will almost certainly experience some shocking unexpected events, and you should always be open to the possibility of the unbelievable becoming a reality. Stability may be a reasonable assumption in the field of physical science. For example, due to the law of universal gravitation, under given atmospheric conditions, objects can always descend with the same acceleration. The result is always like this, and it will always be like this. But in our field, few processes are smooth, especially when considering psychology, emotions, and human behavior, and they change over time.</p><p>Take the relationship between unemployment and inflation as an example. For the past 60 years or so, economists have relied on the Phillips curve, which suggests that wage inflation will rise as the unemployment rate falls because when there are fewer unemployed workers, employees gain bargaining power and can successfully negotiate higher wages. For decades, an unemployment rate of 5.5 percent was also considered to indicate \"full employment\".</p><p>However, the unemployment rate fell below 5.5% in March 2015 (and reached a 50-year low of 3.5% in September 2019), but inflation (wages or otherwise) did not rise significantly until 2021. The important relationships described by the Phillips curve have been applied to various economic models built over decades, but it does not seem to have been applicable for most of the past decade.</p><p>Cromwell's law is equally important. Unlike the physical sciences, in the realms of markets and economics, there are few things that absolutely must or absolutely cannot happen. Thus, in<i>Cycle</i>（<i>Mastering the Market Cycle</i>In my book, I listed seven terms that investors should remove from their vocabulary: \"never,\" \"always,\" \"forever,\" \"cannot,\" \"will,\" and \"must.\" But if these words really have to be discarded, then the idea of building models that can reliably predict the macroeconomic future must also be discarded. In other words, in our field, almost nothing is immutable.</p><p>The unpredictability of behavior is my favorite topic. The famous physicist Richard Feynman once said, \"Imagine how difficult physics would be if electrons had feelings.\" The laws of physics are reliable precisely because electrons always do what they are supposed to do. They never forget to fulfill their duties. They never resist. They never strike. They never innovate. They never act in the opposite way.</p><p><b>However, none of these apply to participants in the economy, and it is precisely because they do not apply that their behavior is unpredictable. If the behavior of participants is unpredictable, how can we model the operation of the economy?</b></p><p><b>We are talking about the future, and there is no way to predict it without making assumptions.</b>Small errors in assumptions about the economic environment and subtle changes in participant behavior can cause serious problems. As mathematician and meteorologist Edward Lorenz famously said, \"A Brazilian butterfly flapping its wings can trigger a tornado in Texas, USA.\" (Historian Niall Ferguson mentions this in an article discussed below.)</p><p>In conclusion, can we consider the economic model to be reliable? Can models replicate reality? Can it describe the behavior of millions of participants and their interactions? Is the process you are trying to model reliable? Can these processes be simplified to mathematics? Can mathematics capture the qualitative nuances of people and their behavior? Can the model predict changes in consumer preferences, changes in corporate behavior, and participants' responses to innovation? In other words, can we trust the output of the model?</p><p>Clearly, economic relationships are not static, and the economy is not governed by schematic diagrams (the diagrams that models attempt to simulate). So, for me, the bottom line is that the model's output points in the right direction most of the time without violating assumptions. But it can't always be accurate, especially at critical moments like inflection points... and that's when accurate predictions are most valuable.</p><p><b>Input</b></p><p>One fact that cannot be ignored is that all your knowledge is about the past, and all your decisions are about the future. —Ian H. Wilson (former General Electric executive) Having considered the incredible complexity of the economy and the need to make simplified assumptions (which would reduce the accuracy of any economic model), let's now consider the inputs needed for a model—the raw materials used to make the predictions. Is the estimated input valid? Can we understand them deeply enough to make meaningful predictions?<b>Or let us simply recall the ultimate truth about models: \"Input garbage, and the output will still be garbage\"?</b>Obviously, no prediction will be of better quality than the input on which it is based.</p><p>The following is Neil Ferguson's statement on July 17th.<i>Bloomberg Opinion (Bloomberg Opinion)</i>Content written:</p><p>Consider what we really want to ask when we ask the question, \"Has inflation peaked? \" We are asking about more than just the supply and demand of 94,000 different goods, manufactured goods, and services. We are still concerned about the future interest rate path set by the Federal Reserve, and aside from the much-touted \"forward guidance,\" its future direction remains far from clear. We are asking how long the strong dollar will last, because it is currently depressing the prices of U.S. imports. But there are still many more questions to be answered. At the same time, the above questions also indirectly ask how long the Russia-Ukraine conflict will last, as the chaos caused by the conflict since February has significantly exacerbated inflation in energy and food prices. We are asking whether oil-producing countries like Saudi Arabia will respond to Western governments' requests to increase crude oil production... We should probably also ask ourselves what impact the latest coronavirus, Omeprone BA.5, will have on Western labor markets. British data show that BA.5 is 35% more infectious than its predecessor BA.2, while BA.2 is more than 20% more infectious than the original Omeprone. If you want to add all these variables to your model, then I wish you good luck. In fact, the future path of inflation, like the future direction of the Russia-Ukraine conflict and the spread of the COVID-19 pandemic, is uncertain. I found Ferguson's article very relevant to the subject of this memo, so I am attaching a link to it here. This article makes many important points, although I disagree with one aspect. Ferguson mentioned above, \"In fact, the future path of inflation, like the future direction of the Russia-Ukraine conflict and the spread of the COVID-19 pandemic, is uncertain.\"</p><p>I believe that accurately predicting inflation is \"less likely\" to happen than predicting the other two issues (if it can be predicted), because accurately predicting inflation requires correct predictions of both events and a thousand other influencing factors. How could anyone possibly get all these things right?</p><p>Let me briefly introduce the forecasting process mentioned in \"The Value of Forecasting\":</p><p>think for most fund managers, the process goes like this: \"I predict the economy will do A. If A happens, interest rates should perform B. If interest rates are B, the stock market should perform C. In this environment, the best-performing sector should be D, and stock E should rise the most.\" Then I build my portfolio accordingly, hoping to achieve the best performance in this situation. But in any case, how likely is E? Remember that E is conditional on A, B, C, and D. In the field of prediction, a two-thirds accuracy rate would be a remarkable achievement. However, if each of the five predictions has a 67% chance of being correct, then the result is that all five predictions are correct and the stock has a 13% chance of performing as expected.<b>Predicting event E based on assumptions about A, B, C, and D is what I call single-scenario prediction.</b>In other words, if the result of the hypothesis about A, B, C, or D proves to be wrong, then the prediction of E is unlikely to be realized. Only when all potential predictions are correct can E obtain a result that is consistent with the predictions, but this is extremely rare. No one can make a wise investment without considering (i) the other possible outcomes of each element, (ii) the likelihood of other scenarios occurring, (iii) what the prerequisites are for making one of the hypotheses a reality, and (iv) what the impact on E is.</p><p>Ferguson's article raises an interesting question about economic modeling: what assumptions should we make about the macroeconomic environment in which economic actors live? this<b>This question illustrates a vicious cycle: in order to predict the overall performance of the economy, we need to make assumptions about aspects such as consumer behavior. But to predict consumer behavior, don't we need to make assumptions about the overall economic environment?</b></p><p>In my first memo about the pandemic, Nobody Knows II (March 2020), I mentioned that when discussing the coronavirus, Harvard epidemiologist Marc Lipsitch said: (a) the facts; (ii) well-founded inferences drawn by analogy with other viruses, and (iii) opinions or speculations. This is our standard practice when dealing with uncertain events. In economic or market forecasting, we have a wealth of history and many similar past events to infer (but not the COVID-19 pandemic). But even if these things are used as input by a well-constructed predictive model, they are still unlikely to predict the future. They can be useful material, or they can be garbage.</p><p>To illustrate this point, people often ask me which cycle I experienced in the past is most similar to the current one. My answer is that current developments bear brief similarities to some past cycles, but there are no absolute similarities.<b>In each case, the differences are enormous and outweigh the similarities.</b></p><p><b>Even if we can find an identical earlier period, to what extent should we rely on this single sample? I think the answer is not many. Investors rely on historical references (and the forecasts they make based on them) because they fear they will act blindly without them. However, this does not mean that this information is reliable.</b></p><p><b>Unpredictable effects</b></p><p>Predictions create mirages where the future is known. —Peter Bernstein<b>Without first determining whether our world is ordered or random, we cannot consider the plausibility of predictions.</b>In short, is it completely predictable, completely unpredictable, or somewhere in between? For me, the conclusion is somewhere in between, but more likely to be unpredictable, so much so that most predictions are useless. Since our world is predictable at some times and unpredictable at others, what good is prediction if we cannot distinguish between predictable and unpredictable times?</p><p>I learned a new word from reading Ferguson's article: \"deterministic\". The Oxford Dictionary defines it as \"causally determined by previous events or natural laws\". The world is much simpler when we follow the rules... just like Feynman's electrons. However, it is clear that economies and markets are not governed by natural laws—thanks to human involvement—and that previous events may be \"prelude\" or \"tend to repeat themselves,\" but events rarely occur in the same way twice. Therefore, I believe that the processes that constitute economic and market operations are not deterministic, which means they are unpredictable.</p><p>Furthermore, the input is obviously unreliable. Many are random, such as weather, earthquakes, accidents, and deaths. Others involve political and geopolitical issues—some known to us, some yet to surface.</p><p>In his Bloomberg Opinion article, Ferguson mentioned the British writer GK Chesterton. This reminds me of a Chesterton quote I quoted in Risk Revisited Again (June 2015):</p><p>The real problem in our world today is not that it is irrational, nor that it is a rational world. The most common question is: the world is almost rational, but not entirely so. Life is not a contradiction, but it is a logician's trap.<b>It looks slightly more precise and regular than it actually is; Its accuracy is obvious, but its imprecision is hidden; Its wildness is also lurking.</b>(Bold text added by the author) Returning to the luncheon introduced on the first page, the host's opening remarks were roughly as follows: \"In recent years, we have experienced events such as the COVID-19 pandemic, the remarkably successful Federal Reserve bailout policy, and the Russia-Ukraine conflict. It has been a very challenging environment because all of this has come out of the blue.\"</p><p>I think for him, this means that attendees should free themselves from the trouble of inaccurate predictions for 2020-2022, continue to predict the future, and bet on their own judgment. But my reaction was completely different: \"There are many events affecting the current environment.<b>Isn't the fact that no one can predict any of them enough to convince those present that they should abandon predictions?</b></p><p>For another example, let's think back to the fall of 2016. There are two things that almost everyone is convinced of: (a) Hillary Clinton will be elected president; (ii) If Donald Trump is elected for some reason, the market will collapse. Nevertheless, the result was that Trump won, and the market soared.</p><p>The past six years have had a profound impact on the economy and markets.<b>I believe that any traditional predictions about the 2016 election at the time would not have been correct.</b>Isn't this enough to convince people that (a) we don't know what the future holds, and (b) we can't understand how the market will react to what happens?</p><p><b>Can the forecast lead to an excess?</b></p><p>What gets us into trouble is not ignorance, but seemingly correct false assertions. —Mark Twain As I mentioned in my recent memo, \"Thinking About Macro,\" in the 1970s we described economists as \"investment directors who never enter the market.\" In other words, economists make numerous predictions; Actual circumstances will prove them right or wrong; Then they went on to make new predictions; But they don't keep track of how often their predictions are correct (or they don't publish statistics).</p><p>Can you imagine hiring a fund manager without reference to track record (or if you were a fund manager, could you imagine being hired in this situation)? However, economists and strategists will not lose their jobs because they do not publish statistics, probably because there are always clients willing to pay for their forecasts.</p><p>Are you a consumer of these predicted results? Are the forecasters and economists employed by your company? Or do you subscribe to their publications and invite them to present, as my former employer did? If so, do you know how often everyone predicts correctly? Have you found a way to strictly determine which of these predictions can be relied upon and which should be ignored? Is there a way to quantify the contribution of these forecasts to your return on investment?</p><p>I asked this series of questions because I hadn't seen or heard of any research on this topic. It is hard to imagine that global information about whether macroeconomic forecasts will lead to excess returns is scarce, especially compared to the number of people who need such information.</p><p>Despite the lack of evidence to prove its value, macroeconomic forecasts continue. Many forecasters are part of equity fund management teams or provide advice and forecasts to these teams.</p><p>One thing is certain: actively managed equity funds have been losing market share for decades due to poor performance of actively managed funds, replaced by index funds and other passive investment vehicles. Actively managed funds now account for less than half of the U.S. equity mutual fund market. Is this the reason why macroeconomic forecasts are inherently unhelpful for investment?</p><p>As far as I know, the only quantitative information available on this issue is the performance of so-called macro hedge funds. The Hedge Fund Research Group (HFR) publishes the Hedge Fund Weighted Composite Index and some sub-strategy indices. The following is the long-term performance of the hedge fund weighted composite index, the macro hedge sub-strategy index, and the S&P 500 index.<img src=\"https://static.tigerbbs.com/79717be010acf96241bf0336e5ac3381\" tg-width=\"963\" tg-height=\"272\" referrerpolicy=\"no-referrer\" width=\"100%\" height=\"auto\"/>*Performance as of July 31, 2022. The hedge fund index shown is a weighted composite index of each fund.</p><p>In the table above, according to HFR data, the average performance of hedge funds during the study period was far below that of the S&P 500 index, and the average performance of macro hedge sub-strategy funds was much worse (especially between 2012 and 2017). Given that investors continue to entrust approximately $4.5 trillion to hedge fund managers, these funds must provide some benefits beyond returns, but it is unclear what this will be. This seems especially true for macro hedge funds.</p><p>To confirm my prediction, I will now cite a rare example of self-evaluation: a seven-page feature article entitled \"I Was Wrong\" in the \"Sunday View\" column of the New York Times on July 24. In the article, eight New York Times \"Opinion\" columnists revealed their past erroneous predictions and biased advice.</p><p>Most relevant here is a confession by Paul Krugman entitled \"I Was Wrong About Inflation\". I've excerpted some of these and strung them together:</p><p>In early 2021, economists engaged in a heated debate about the possible consequences of the \"American bailout plan\"... I was on the side [of supporting less concern about the impact of inflation]. Of course, it turned out to be a very bad decision... History could not have predicted such overheated inflation. So there's something wrong with my model... One possible reason is that history is misleading... In addition, the disruptions caused to adapt to the pandemic and its consequences may still be playing a large role. Of course, the Russia-Ukraine conflict and the epidemic prevention and control measures in major Chinese cities have undoubtedly pushed this level of interference to a whole new level... In any case, the whole thing has become a humbling lesson. Incredibly, the standard economic model has been working quite well since the 2008 financial crisis, and I thought there was no problem using the same model in 2021. Looking back now, I should have realized that this inference was inherently risky in the new world trends that emerged after the COVID-19 pandemic. (Bold emphasis added) I admire Krugman's remarkable frankness (although I have to say that I don't recall many market forecasts between 2009 and 2010 being optimistic enough to describe the reality of the following decade).<b>Krugman's explanation of his mistake is good in itself, but I don't see him mentioning abandoning modeling, inference, or prediction in the future.</b></p><p>This humility may even permeate the Federal Reserve, one of the world's largest economic forecasters, which employs more than 400 PhDs in economics. The following is what economist Gary Shilling wrote in Bloomberg Opinion on August 22:</p><p>The Fed's forward guidance has been a disaster, challenging its own credibility. Chairman Jerome Powell seems to share this view, suggesting that the outside world should stop speculating about the Federal Reserve's views on interest rates, economic growth, and inflation at different points in the future...<b>The fundamental problem with forward guidance is that it relies on data, which itself comes from the Federal Reserve's past poor forecasting record.</b>The Federal Reserve has been overly optimistic about the economic recovery after the Great Recession of 2007-2009. In September 2014, policymakers predicted real GDP growth of 3.40% in 2015, but by September 2015 they were forced to keep lowering their forecasts to 2.10%.<b>Federal Funds rate is not a market-determined interest rate, but is set and controlled by the Federal Reserve, and no one challenges the Fed's authority. Furthermore, members of the Federal Open Market Committee (FOMC) are notoriously bad at predicting what actions they themselves will take...</b>In 2015, their average forecast for Federal Funds rate in 2016 was 0.90%, and in 2019 it was 3.30%. The actual figures were 0.38% and 2.38% respectively... It is certain that many ongoing events have created market uncertainty, but the Federal Reserve's forward guidance has always been highly sought after and important. Recall that earlier this year, the Federal Reserve also believed that inflation caused by the friction of the pandemic and restarting the economy after supply chain disruptions was temporary. Only later did the Federal Reserve realize that things were not going well and reverse course, raising interest rates and signaling further significant rate hike. The Federal Reserve's erroneous forecasts led to erroneous forward guidance, exacerbating financial market volatility. (Bold added by the author) On this question, I would like to make one last point: where exactly are those people who have made a name (and become rich) by profiting from macroeconomic perspectives? I certainly can't know everyone in the investment world, but among those I know or understand, I believe there are only a few \"macro investors\" who can be considered very successful. When there are few examples of something, as my mother once said, \"the exception just confirms the rule.\"</p><p><b>The pattern in this example is that macroeconomic forecasts rarely lead to outstanding performance. For me, the extraordinary nature of the success stories just proves that this statement is a universal truth.</b></p><p><b>Practitioners' predicted needs</b></p><p>Compared to revealing the future, predictions can reveal the predictor better. —Warren Buffett How many people can make macroeconomic predictions that are valuable most of the time? I don't think so. How many investment managers, economists, and forecasters have tried it? There are at least several thousand. This raises an interesting question: why predict? If macro forecasting doesn't help investment success over time, why do so many practitioners in the investment management industry believe in forecasting and flock to its results? I think the typical reason for this might be:</p><p><ul><li>It's part of the job.</p><p></li><li>Investors have always done this.</p><p></li><li>Everyone I know does this, especially my competitors.</p><p></li><li>I've been doing this—I can't stop now.</p><p></li><li>If I don't do this, I won't be able to attract customers.</p><p></li><li>Since investing involves deploying capital to benefit from future events, how can one expect to do a good job without a perspective on those events? We need predictions, even if they are not perfect.</p><p></li></ul>This summer, my son Andrew recommended I read a very interesting book: \"Making Mistakes (But It's Not My Fault): Why We Make Excuses for Foolish Beliefs, Bad Decisions, and Hurtful Behaviors.\" (Mistakes Were Made (but Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts), The book was written by psychologists Carol Tavris and Elliot Aronson.<b>The theme of the book is self-defense.</b></p><p><b>The authors explain that \"cognitive dissonance\" occurs when people are faced with new evidence that challenges their previously held positions, and when this happens, the subconscious mind will make them try hard to prove and maintain their previous positions.</b>Here are some selections:</p><p>If you hold a set of beliefs that guide your practice, and you learn that some of them are incorrect, you must either admit that you are wrong and change your approach, or reject new evidence. Most people, when confronted directly with evidence that they are wrong, do not change their opinion or plan of action, but instead become more stubborn in their arguments. Once we have established a belief and proven its wisdom, it is obviously hard work to change our minds. It is much easier to put new evidence into an existing framework for psychological argumentation for acceptance than to change the framework. Mechanisms people typically employ when responding to evidence that challenges their beliefs include these (to paraphrase the author):</p><p><ul><li>Unwillingness to listen to disharmonious information;</p><p></li><li>Selectively remember parts of their lives, focusing on those parts that support their views; as well as</p><p></li><li>Acting under cognitive biases allows people to see only what they want to see and seek some kind of confirmation for what they already believe.</p><p></li></ul>I believe these are all factors that lead people to consistently make predictions and rely on them. In this situation, what kind of manifestation will it take?</p><p><ul><li>Consider macroeconomic forecasting as an integral part of investment;</p><p></li><li>Eager to recall correct predictions, especially those that are bold and non-market consensus;</p><p></li><li>Overestimating the accuracy of predictions;</p><p></li><li>Forgetting or downplaying erroneous predictions;</p><p></li><li>Failure to keep records of prediction accuracy or failure to calculate average success rate;</p><p></li><li>Emphasis is placed on the generous rewards that reward accurate predictions;</p><p></li><li>Emphasize that \"everyone should do this\"; as well as</p><p></li><li>Perhaps most importantly, unsuccessful predictions are blamed on being blinded by random or exogenous events. (But, as I said before, this is the crux of the matter: if predictions become so easily inaccurate, why make them?)</p><p></li></ul>Most people—even honest people with good intentions—take positions or actions that serve their own interests, sometimes at the expense of others or objective truth. They themselves are unaware of this situation, but instead believe that what they are doing is the right thing; They also sought many legitimate reasons. As Charlie Munger often quotes Dimosini, \"Nothing is easier than deceiving yourself. Because people always believe what they want.\"</p><p>I don't think forecasters are liars or charlatans. Most of them are smart intellectuals who think they are doing something useful.<b>However, self-interest makes them act a certain way, while self-defense makes them stick to their opinions when faced with contrary evidence.</b>As Morgan Housel stated in a recent current affairs briefing:</p><p>The inability to predict the past does not affect our willingness to predict the future. Certainty is so precious that we will never give up on it, and if people are honest about how unpredictable the future is, most people will never be able to get out of bed in the morning. (From \"Big Beliefs,\" Collaborative Fund, August 24, 2022) A few years ago, on my birthday, Richard Masson, co-founder of Oaktree, gave me a fun gift that was in keeping with his style. The gift that time was<i>The New York times</i>A bound edition. I've been hoping for an opportunity to write about my favorite subheading from the issue of October 30, 1929, when the Dow Jones Industrial Average had just fallen nearly 23% in two days.</p><p><b>The headline reads, \"Bankers Optimistic.\"</b>(However, over the next three years, the Dow Jones Industrial Average fell by about 85%.) Most bankers and fund managers seem innately optimistic about the future. Beyond that, it's in their best interest because it helps them do more business. But their optimism certainly shaped their predictive views and the resulting behavior.</p><p><b>Is it possible or not?</b></p><p>\"I never consider the future—because it is just around the corner.\" — Albert Einstein considers the following aspects of macroscopic forecasting:</p><p><ul><li>Number of assumptions/inputs required,</p><p></li><li>The number of processes/relationships to be included,</p><p></li><li>The inherent unreliability and instability of these processes, and</p><p></li><li>The role of randomness and the possibility of accidents.</p><p></li></ul>For me, the most important thing is that predictions cannot always be correct enough to be worthwhile. I've mentioned it many times, but for the sake of completeness, I'll reiterate my views on the utility (or rather, futility) of macro-forecasting:</p><p><ul><li>Most forecasts consist of inferences about past performance.</p><p></li><li>Since macroeconomic developments usually do not deviate from previous trends, inferences are usually successful.</p><p></li><li>On this basis, most predictions are correct. However, since inferences are usually expected by security prices, those who base their expectations on inferences do not enjoy excess benefits when their inferences hold true.</p><p></li><li>Occasionally, economic behavior does deviate substantially from past patterns. Because this deviation is unexpected by most investors, its occurrence can impact the market, meaning that accurate predictions of deviations can yield substantial profits.</p><p></li><li>However, because the economy does not often deviate from past performance, few can accurately predict deviations, and most deviation predictions turn out to be wrong in hindsight.</p><p></li><li>Therefore, we have (i) inferential predictions, most of which are correct but do not generate excess benefits, and (ii) potentially profitable biased predictions, which are rarely correct and therefore do not usually generate excess benefits.</p><p></li><li>It has been demonstrated that most forecasts do not increase returns.</p><p></li></ul>At the luncheon mentioned at the beginning of this memo, people were asked about their expectations regarding aspects such as Federal Reserve policy and how this would affect their investment stance. One person replied, \"I think the Fed will remain highly concerned about inflation, and therefore will rate hike sharply, leading to a recession. That's why I'm choosing to be risk-averse.\" Another said, \"I expect inflation to slow in the fourth quarter, and the Fed to shift to a dovish stance in January. Start cutting interest rates and stimulating the economy. I'm very optimistic about 2023.\"</p><p>We often hear this statement.<b>However, it must be recognized that these people are using a univariate model:</b>The prediction of the speaker is based on a single variable. Speaking of simplified assumptions: These forecasters implicitly believe that everything is constant except for the Federal Reserve's policies. When they needed to play three-dimensional chess, they were still playing flat checkers.</p><p>Aside from the impossibility of predicting the Fed's behavior, the impact of inflation on such behavior, and the market's reaction to inflation, what other important considerations are there? If a thousand things play a role in determining the future direction of the economy and markets, what are the other 999 things? What will be the impact of wage negotiations, midterm elections, the Russia-Ukraine conflict, and oil prices?</p><p>The truth is that people can only remember a very limited number of things in their minds at any given time.<b>It is difficult to take into account a large number of factors, and it is even more difficult to understand how a large number of things will interact (correlation is always a real thinking problem).</b></p><p>Even if you somehow manage to get the economic forecast right, that's only half the battle. You still need to predict how economic activity will translate into market outcomes. This requires a completely different prediction and involves countless variables, many of which are related to psychological factors and are therefore almost unknowable.</p><p>According to student Warren Buffett's recollection, Ben Graham once said, \"In the short run, the market is a voting machine, but in the long run, it's a weighing machine.\" How can we predict investors' short-term choices? Some economic forecasters have concluded that the actions announced by the Federal Reserve and the Treasury Department in March 2020 will save the U.S. economy and help the economic recovery. But I don't know who predicted that a hot bull market had already begun before the recovery began.</p><p>As I mentioned earlier, Buffett shared his views on macroeconomic forecasting with me in 2016. \"For a piece of information to be useful, it must meet two criteria: First, it must<b>important</b>Secondly, it is necessary<b>It is known</b>。\"</p><p><ul><li><b>Of course, the macro outlook is important.</b>Today, investors seem to have grasped the rhetoric of every forecaster, macroeconomic events, and signals of the Federal Reserve's intermittent tightening actions. Unlike in my early days in this industry, it seems that macro factors are everything now, and corporate development is not given as much attention.</p><p></li><li><b>But I strongly agree with Buffett that the macro future is unknowable,</b>Or at least almost no one consistently knows more than the vast majority of investors, which is the key to trying to gain a cognitive edge and make excellent investment decisions.</p><p></li></ul>Clearly, Buffett's name ranks high on the list of successful investors. He avoids macro forecasting and focuses more on the \"micro\" areas than others: companies, industries, and securities, which has led to his success.</p><p>I introduced the concepts of the \"knowable\" and \"agnostic\" schools in a 2001 memo entitled \"What's It All About, Alpha?\", and elaborated on Them in 2004 in my article \"Us and Them\". As a conclusion to the current memo, I will insert something I wrote about these two genres in the latter:</p><p>Most of the investors I've met over the years have been of the \"knowable\" school of thought. This was true when I analyzed stocks between 1968 and 1978, and even when I turned to non-mainstream investing between 1978 and 1995, but still worked for an investment management company centered on stocks.</p><p>Identifying members of the \"knowledge\" school is easy:</p><p><ul><li>They believe that understanding the future direction of the economy, interest rates, markets, and widely watched mainstream stocks is crucial for investment success.</p><p></li><li>They are confident that they can achieve this.</p><p></li><li>They knew they could do it.</p><p></li><li>They know that many people are also trying to do this, but they think that either (a) everyone can succeed at the same time, or (b) only a few people can do it, but they are one of them.</p><p></li><li>They are willing to invest according to their views on the future.</p><p></li><li>They are also happy to share their opinions with others, although correct predictions should be priceless and no one gives them away for free.</p><p></li><li>They rarely look back and seriously review their achievements as forecasters.</p><p></li></ul>\"Confidence\" is the key word to describe the members of this genre. On the other hand, for the \"agnostic\" school, the word should be \"cautious\", especially when looking at the macroeconomic future.<b>Its believers generally believe that the future cannot be predicted; There is no need to predict the future; The right goal should be to do your best to invest well, while acknowledging that you lack this understanding.</b></p><p>As a member of the \"knowable\" school, you can express your opinion about the future (and perhaps someone else will take notes on this subject). You may be sought after and seen as an ideal dinner guest... especially when the stock market is rising.</p><p>If you join the \"agnostic\" school, the results are even more complicated. You will soon get tired of expressing \"agnosticism\" to friends and strangers. Before long, even relatives will no longer ask you for your opinion on market trends. You will never enjoy that one-thousandth surprise moment when the prediction comes true, nor will you enjoy the joy of having your photo published in the Wall Street Journal.</p><p>On the other hand, you are also protected from forecasting errors and from losses resulting from investing based on overconfidence in the future.<b>But how do you think it feels when a potential customer asks you about your investment prospects and you have to say \"I don't know\"?</b></p><p>For me, the best bottom line for judging which school of thought is based on a famous quote from the late Stanford University behavioral scientist Amos Tversky:<b>\"It's scary to realize that you may not know something, but it's even scarier to realize that, in general, the world is run by people who firmly believe they know exactly what's happening.\"</b></p><p>In investment management, it is certainly standard practice to make macro forecasts, share them upon request, and use them as a basis for entrusted client investments. It seems to be common practice for fund managers to believe in predictions, especially their own. As mentioned above, not doing so seems out of place. But are their beliefs realistic? I'd love to hear what everyone thinks.</p><p>Years ago, a well-respected sell-side economist (an old acquaintance of mine from my time at Citi) called me and said, \"You changed my life,\" he said. \"I stopped making predictions a long time ago. Instead, I just told people what happened today and what I think it might have on the future. Life became better from then on.\" Can I help you achieve the same state of happiness?</p><p>Author: Howard Marks</p><p></body></html></p>\n<div class=\"bt-text\">\n\n\n<p> source：<a href=\"https://mp.weixin.qq.com/s/Ipkl8u3LTMsZu6vV05TfWg\">橡树资本Oaktree Capital</a></p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/ec9d546348d262a35388609835ccbfe2","relate_stocks":{".DJI":"道琼斯"},"source_url":"https://mp.weixin.qq.com/s/Ipkl8u3LTMsZu6vV05TfWg","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1159026938","content_text":"自1993年2月开始写第一篇备忘录，《预测的价值，雨源自何处》（The Value of Projections, or Where'd All This Rain Come From）开始，我一直在表达我将\"预测\"置之度外。自那之后的多年里，我详细地解释了为何我对预测不感兴趣——以下章节中一些我非常喜欢的引述也呼应了我对预测之不屑一顾——但我从来没有再专门写一篇备忘录来解释过为何作出有益的宏观预测如此之难。因此就有了这篇备忘录。引入深思的事情世界上有两类预言家：一类对未来并无所知，而另一类不知道自己并无所知。——约翰·肯尼斯·加尔布雷思最后润色备忘录《敢于另辟蹊径》（I Beg to Differ）后不久，我与一些经验丰富的投资者以及投资圈外的人士一同出席了一次午餐会。这并非一项社交活动，而是为在场的人提供了就投资环境交流彼此观点的机会。期间，主持人提出了一系列问题：您预期通胀会如何发展？会不会出现经济衰退，如果会，情况有多严重？俄乌冲突将以何种方式结束？2022年和2024年美国大选可能会产生什么影响？对此，我听到了各种各样的观点。长期追踪我备忘录的读者应该可以想象到我当时的想法：\"这个房间里没有人是外交事务或政治方面的专家。在场没有人对这些话题有特别深入的见解，当然也不会比阅读今天早上新闻的普通人知道得更多。\"所传达的思想，即使是针对经济问题，似乎也没有比其他人更具说服力，而且我绝对相信，没有人能够改善投资结果。这就是关键。正是那次午餐会让我开始考虑写另一篇关于宏观展望无益的备忘录。不久之后，我发现一些额外的素材——一本书、一篇来自彭博观点（Bloomberg Opinion）的文章和一篇报纸上的文章——这些素材都支持我的论点（也可能是我的\"证实偏差\"——即人们倾向于接受和相信能够证明自己先前已有观点的信息和论据）。那次午餐会和这些素材共同启发了这份备忘录的主题：预测鲜有益处的诸多原因。为了获得有用的东西——无论是在制造业、学术界，甚至是艺术领域——必须有一个可靠的过程，能够将所需的输入转换为期望的输出。简言之，问题在于，我认为没有一个过程能够始终如一地将大量与经济和金融市场相关的变量（输入）转化为有用的宏观预测（输出）。模型认知最大的敌人并非无知，而是对认知的错觉。——丹尼尔·布尔斯廷大约在我任职于第一花旗银行（First National City Bank）的头十年，有一个在当时很热门但现在已经很久没听到过的词：计量经济学。具体是指在经济数据中寻找关联从而产生有效预测的一种做法。或者简言之，计量经济学研究如何建立经济的数学模型。在上世纪70年代，计量经济学者们炙手可热，但我觉得他们现已风光不再。我认为这意味着他们的模型不起作用。无论模型是复杂精密的还是潦草简单的、基于数学的还是出于直觉的，预测者都别无选择只能根据模型做出判断。模型从定义而言是由假设组成的：\"如果A发生，那么B就会发生。\"换句话说，模型陈述了关系与响应。但要我们愿意采纳模型的输出结果，就必须让我们相信这个模型是可靠的。可当我想到要为经济建模时，我的第一反应是这会多么的复杂。例如，美国大约有3.3亿人口。除去特别年幼的和一些特别年老的，其余的人都是经济的参与者。因此，有数以亿计的消费者，以及数以百万计的工人、生产商和中间商（许多人满足多个分类）。要预测经济的发展路径，就必须预测这些人的行为——就算不预测每位参与者，至少也要预测群体总量。美国经济的真实模拟必须处理数十亿的互动或节点，包括与全球各地的供应商、客户和其他市场参与者的互动。是否有可能做到这一点？例如，是否能预测消费者在下列情况下做出的行为：（一）如果他们获得额外一美元的收入（\"边际消费倾向\"是多少？）；（二）如果能源价格上涨，挤压了家庭预算中的其他类别；（三）如果一种商品的价格相对于其他商品上涨（是否会产生\"替代效应\"？）；以及（四）如果地缘政治舞台被其他大洲的事件搅动？显然，这种复杂程度需要频繁使用经简化的假设。例如，如果可以假设在B并非更好或更便宜（或两者兼而有之）的情况下，消费者不会购买B来代替A，那么建模会更容易。如果假设生产X的成本不低于Y，那么生产者不会将X定价低于Y，这也会有所帮助。但尽管B的价格更高（甚至正因如此），消费者仍被B的品牌效应所吸引，结果会怎样？如果X是由愿意用亏损几年以获取市场份额的企业家生产开发的，结果会如何？模型是否有可能预测消费者愿意多花钱和企业家愿意少赚钱（甚至亏损）的决定？此外，模型必须预测经济中每组参与者在各种环境中的行为。但变幻莫测的因素是多方面的。例如，消费者可能在某一时刻是一种行为方式，而在另一类似时刻则是不同的行为方式。考虑到所涉及的大量变量，两个\"相似\"时刻似乎不可能以完全相同的方式发生，而我们也不太可能看到经济参与者表现出相同的行为。除此之外，参与者的行为将受到他们的心理（或者我应该说他们的情绪？）的影响，而且他们的心理可能会受到定性的、非经济发展的影响。这些如何建模？一个经济模型如何能全面到足以处理以前从未遇到过的情况，或者在现代（即在可比情况下）未曾出现过的情况？这是又一个例证，说明模型无法简单复制像经济这样复杂的事物。当然，其中一个典型例子就是新冠疫情。它导致全球大部分经济体停摆，颠覆了消费者行为，并激发了政府大规模的发钱纾困政策。已有模型的哪个方面能够预测疫情影响？是的，世界曾在1918年经历过一场疫情，但情况截然不同（当时没有iPhone、Zoom通话等等），以至于那个时期的经济事态与2020年几乎没有任何可比性。除了复杂程度和难以捕捉的心理波动和动态过程等因素外，还要考虑到试图对不能预期保持不变的事物进行预测本身就具有局限性。在开始撰写本备忘录后不久，我收到了Morgan Housel一贯精彩的周刊。其中一篇文章描述了很多与我们的经济和投资相关的其他领域的观察结果。以下两个是从统计学领域借用的，我认为它们与经济模型和预测的讨论有关（\"世界运作的小方法 （Little Ways the World Works ）\"，Morgan Housel，Collaborative Fund，2022年7月20日）：平稳性：这是一种假设，基于影响系统的主要因素不会随时间推移而变化，该假设认为历史可以作为未来统计的指导。如果想知道要建造多高的堤坝，就查看过去100年的洪水数据，并假设未来100年也会相同。平稳性是一个奇妙的、基于科学的概念，且在它失效之前一直有效。它是经济和政治中重要事件的主要驱动力。[但在我们的世界中，]\"以前从未发生过的事情一直在发生，\"斯坦福大学教授Scott Sagan说。克伦威尔法则：永远不要说某事不会发生。……即使某件事仅有十亿分之一的可能性成真，而你在一生中会与数十亿件事物互动，因此你几乎肯定会经历一些令人震惊的意外事件，并应该始终对不可思议的事情成为现实的可能性持开放态度。平稳性在物理科学领域可能是合理的假设。例如，因万有引力定律，在既定的大气条件下，物体总是能以相同的加速度下降。结果总是这样，而且将永远这样。但在我们的领域里，很少有过程是平稳的，特别是考虑到心理、情感和人类行为，并且它们会随着时间的推移而变化。以失业率和通胀之间的关系为例。在过去约60年里，经济学家依赖菲利普斯曲线，该曲线认为工资通胀将随着失业率的下降而上升，因为当未就业的工人减少时，员工获得议价能力，并可成功地通过谈判获得更高的工资。几十年来，人们还认为5.5%的失业率表明\"充分就业\"。但失业率在2015年3月降至5.5%以下（并在2019年9月达到3.5%的50年以来低位），但直到2021年通胀（工资或其他方面）都没有显著上升。菲利普斯曲线描述的重要关系应用在了几十年来建立的各种经济模型中，但它在过去十年的大部分时间里似乎并不适用。克伦威尔法则也同样重要。与物理科学不同，在市场和经济领域里，很少有绝对必须发生或绝对不能发生的事情。因此，在《周期》（Mastering the Market Cycle） 一书中，我列出了投资者应该从词汇表中清除的七个术语：\"从不\"、\"总是\"、\"永远\"、\"不能\"、\"不会\"、\"将\" 和 \"必须\"。但如果这些词真的必须被摒弃，那么也必须摒弃能建立可靠地预测宏观未来的模型的想法。换言之，在我们的领域里，几乎没有什么是不可变的。行为的不可预测性是我最喜欢的话题。著名物理学家理查德·费曼 （Richard Feynman） 曾经说过：\"想象一下，如果电子有感觉，物理学将会多难。\"物理规则是可靠的，正是因为电子总是做它们应该做的事情。它们永远不会忘记履行自己的职责。它们从不反抗。它们从不罢工。它们从不创新。它们从不以相反的方式行事。但这些都不适用于经济中的参与者，正是因为不适用才导致参与者的行为是不可预测的。如果参与者的行为是不可预测的，那么如何对经济的运行进行建模?我们在谈论未来，没有任何一种方法可在不需要做出假设的情况下预测未来。有关经济环境假设的小错误和参与者行为的细微变化都可能造成严重问题。正如数学与气象学家爱德华·洛伦茨 （Edward Lorenz） 的名言：\"一只巴西的蝴蝶扇动翅膀就可能在美国德克萨斯州引发龙卷风。\"（历史学家尼尔·弗格森 （Niall Ferguson） 在下文讨论的一篇文章中提到了这一点。）综上所述，我们能否认为经济模型是可靠的？模型可否复制现实？它能否描述数以百万计的参与者行为及他们之间的互动？试图建模的过程是否可靠？这些过程可否简化为数学？数学能否捕捉人及其行为的定性细微差别？模型能否预测消费者偏好的变化、企业行为的变化以及参与者对创新的反应？换言之，我们能否相信模型的输出结果？显然，经济关系并非一成不变，经济也不受示意图（模型试图模拟的示意图）所支配。因此，对我来说，底线是，在不违反假设的情况下，模型的输出结果大部分时间指向正确方向。但它不可能总是准确的，尤其是在拐点等关键时刻……而这正是准确预测最有价值的时候。输入无法忽略的一个事实是，你所有的知识都是关于过去的，你所有的决定都是关乎未来的。——伊恩·威尔逊 （Ian H.Wilson ）（通用电气前高管）在考虑了经济不可思议的复杂性，以及需要做出经简化的假设（这将降低任何经济模型的准确性），现在让我们来考虑一个模型所需的输入——制造预测的原材料。预估的输入是否有效？我们能否对它们有足够深入的了解，从而得出有意义的预测？还是让我们简单地想起关于模型的终极真理：\"输入垃圾，输出的还是垃圾\"？显然，没有任何预测的质量会比它所基于的输入的质量更好。以下是尼尔·弗格森7月17日在彭博观点 （Bloomberg Opinion） 撰写的内容：考虑一下当我们提出\"通胀是否已见顶？\"这个问题时真正想问的。我们在问的不仅仅是94,000种不同商品、制成品和服务的供需情况。我们还在关心美联储设定的未来利率路径，撇开备受吹捧的\"前瞻性指引\"不谈，其去向何方仍远未明确。我们在问的是美元强势还会持续多久，因为它目前正在压低美国进口商品的价格。但还有更多的问题有待解答。与此同时，以上问题也在间接地询问，俄乌冲突还会持续多久，因为自2月份以来，俄乌冲突造成的混乱已经显著加剧了能源和食品价格的通胀。我们是在问沙特阿拉伯等产油国是否会回应西方政府增加原油产量的请求......我们可能还应该问问自己，最新的新冠病毒奥密克戎BA.5将对西方劳动力市场产生什么影响。英国数据表明，BA.5的传染性比其前身BA.2高35%，而BA.2的传染性又比原始奥密克戎高20%以上。如果要将所有这些变量添加到你的模型中，那我祝你好运。事实上，通胀的未来路径，如同俄乌冲突的未来走向和新冠疫情的传播路径一样，都无法确定。我发现弗格森的文章与本备忘录的主题非常相关，因此我在此处附上该文章的链接。该文章提出了很多重要的观点，尽管我在某一方面不敢苟同。弗格森在上文提到，\"事实上，通胀的未来路径，如同俄乌冲突的未来走向和新冠疫情的传播路径一样，都无法确定。\"我认为准确预测通胀比预测其他两个问题\"更不可能\"实现（如果真可以预测的话），因为准确预测通胀需要对这两个事件以及其他一千个影响因素的预判都是正确的。怎么可能有人把所有这些事情都做对呢?我在此粗略地介绍一下《预测的价值》中提及的预测过程：我想，对于大多数基金管理人来说，该过程是这样的：\"我预测经济会做A。如果A发生，利率应该会呈现B。如果利率为B，股市应该呈现C。在此环境下，表现最好的板块应该是D，而股票E应该上涨最多。\"然后据此构建投资组合，以期在这种情况下实现最好的表现。但无论如何，E的可能性有多大？请记住，E以A、B、C和D为条件。在预测领域中，三分之二的正确率将是了不得的成就。但如果五个预测中，每一个都有67%的可能性是正确的，则结果是，所有五个预测都是正确的并且股票将按预期表现的可能性为13%。基于对A、B、C和D的假设来预测事件E，就是我所说的单情景预测。换言之，如果关于A、B、C或D的假设结果证明是错误的，则E的预测结果就不太可能实现。只有所有潜在的预测都是正确的，E才能得到如预测一致的结果，但这是极罕见的。如果不考虑（一）每个要素的其他可能结果，（二）其他场景出现的可能性，（三）让其中一个假设成为现实的前提条件是什么，以及（四）对E的影响是什么，则任何人都无法进行明智的投资。弗格森的文章提出了一个关于经济建模的有趣问题：关于经济参与者身处何种宏观环境，我们应该作出什么假设？这个问题恰好展示了一个死循环：为了预测经济的整体表现，我们需要对消费者行为等方面做出假设。但要预测消费者行为，难道我们不需要对整体经济环境做出假设吗？在我首份关于疫情的备忘录《无人知晓（二）》（Nobody Knows II）（2020年3月）中，我提到在讨论冠状病毒时，哈佛流行病学家马克·利普希奇 （Marc Lipsitch） 曾说过：（一）事实；（二）类比其他病毒所得出的有根据的推论，以及（三）观点或推测。这是我们处理不确定事件时的标准做法。在经济或市场预测中，我们有大量的历史和许多类似的过去事件可以推断（但新冠疫情都没有）。但即使这些东西被一个构造良好的预测模型用作输入，它们仍不太可能预测未来。它们可能是有用的素材，也可能是垃圾。为了说明这一点，人们经常问我过去所经历的哪个周期与当前最相似。我的回答是，当前的发展与过去的一些周期有短暂的相似之处，但没有绝对的相似之处。在每种情况下，差异都是巨大的，并且超过了相似之处。即使我们可以找到一个相同的前一时期，我们应该在多大程度上依赖于这个单一样本？我想答案是不多。投资者依赖历史参考资料（以及他们据此提出的预测），因为他们担心如果没有这些参考资料，他们会盲目行事。但这并不意味着这些资料是可靠的。不可预测的影响预测创造了未来是可知的海市蜃楼。——彼得·伯恩斯坦如果不首先确定我们的世界是有序的还是随机的，我们就无法考虑预测的合理性。简言之，它是完全可预测的、完全不可预测的，还是介于两者之间？对我来说，结论是介于两者之间，但更倾向于无法预测，以至于大多数预测都无济于事。既然我们的世界在某些时候是可以预测的，而在另一些时候是不可预测的，那么如果我们不能区分什么时候是可预测的，什么时候是不可预测的，预测又有什么用呢？我从阅读弗格森的文章中学到了一个新词：\"确定性的 （deterministic）\"。牛津词典 将其定义为\"由先前的事件或自然规律因果决定的\"。当我们按照规则处理事情时，世界就简单多了……就像费曼的电子一样。但很明显，经济和市场不受自然规律支配——这要归功于人类的参与——之前的事件可能是\"铺垫\"或\"倾向于重复\"，但事件很少会以同样的方式发生两次。因此，我认为构成经济和市场运行的过程不是确定性的，这意味着它们是不可预测的。此外，输入显然是不可靠的。很多都是随机的，例如天气、地震、事故和死亡。其他的则涉及政治和地缘政治问题——一些我们已知，一些还没有浮出水面。在彭博观点 （Bloomberg Opinion） 的文章中，弗格森提到了英国作家G.K.切斯特顿 （G.K.Chesterton G.K. Chesterton）。这让我想起了我在《重新再谈风险》（Risk Revisited Again）（2015年6月）中引用的切斯特顿名言：我们如今这世界真正的问题不是这个世界不理性，也并非这是个理性的世界。最常见的问题是：这个世界几近理性，但却不完全是。生活不是一个矛盾，但却是逻辑学家的陷阱。它看起来比实际上要略微精准和有规律；其精准显而易见，但其不精准的一面却隐藏了起来；其野性也在潜伏以待。（粗体为笔者所加）回到第一页所介绍的午餐会，主持人的开场白大致如下：\"近年来，我们经历了新冠疫情、取得惊人成功的美联储救市政策以及俄乌冲突等事件。这是一个非常富有挑战性的环境，因为所有这些都突如其来。\"我想，对他来说，这意味着与会者应该让自己摆脱对2020年-2022年预测不准确的困扰，继续预测未来，并押注于自己的判断。但我的反应完全不同：\"影响当前环境的事件有很多。而没有人能够预测其中任何一件，这一事实难道不足以让在场的人相信他们应该放弃预测吗?\"再举一个例子，让我们回想一下2016年的秋天。有两件事几乎每个人都深信不疑：（一）希拉里·克林顿将当选总统；（二）若出于某种原因唐纳德·特朗普当选，市场将会崩溃。尽管如此，结果是特朗普赢了，市场飙升。过去六年对经济和市场影响深远，我相信，当时任何对2016年大选持传统观点的预测都不会是正确的。这难道还不足以让人们相信：（一）我们不知道未来会发生什么，（二）我们无法了解市场将如何对所发生的事情做出反应？预测能否带来超额？让我们陷入困境的不是无知，而是看似正确的谬误论断。——马克·吐温正如我在最近的备忘录《关于宏观问题的思考》（Thinking About Macro） 中提到的，在1970年代，我们曾经将经济学家描述为\"从不入市的投资总监。\"换言之，经济学家做出众多预测；实际情况会证明他们是对还是错；然后他们继续做新的预测；但他们并不对预测正确的频率进行追踪（或者，他们并没有发布统计数据）。您能否想象不参考业绩记录就聘请一位基金经理（或换做您是一位基金经理，您能否想象在此情境下受到聘任）？但，经济学家和策略师却不会因为不发布统计数据而丢了工作，原因可能是总有客户愿意为他们的预测买单。您是这些预测结果的消费者吗？预测者和经济学家是否是贵司的员工？或者您是否订阅他们的出版物并邀请他们进行简报，就像我以前的雇主一样？如果是这样，您是否知道每个人预测正确的频率？您有没有找到一种方法来严格确定这些预测当中，哪些是可以依赖的，哪些是要忽略的？是否有方法可以量化这些预测对您投资回报的贡献？我问出了这一连串的问题，因为我尚未看到或听说过任何这方面的研究。令人难以想象的是，全球有关宏观预测是否会带来超额收益的信息十分匮乏，尤其是与需要这类信息的人数相比极不相称。尽管缺乏证明其价值的证据，但宏观预测却仍在继续。许多预测者是股票基金管理团队中的一员，或者在为这些团队提供建议和预测。我们可以肯定的一点是，由于主动管理的业绩不佳，主动管理型股票基金几十年来一直在失去市场份额，被指数型基金和其他被动投资型工具所取代，主动管理型基金现在在美国股票共同基金市场中所占份额少于一半。宏观预测在本质上对投资并无帮助，是否是其中的原因？据我所知，有关这个问题，唯一可以找到量化信息的是所谓的宏观对冲基金的表现。对冲基金研究组织 （HFR） 发布了对冲基金加权综合指数以及一些子策略指数。以下是对冲基金加权综合指数、宏观对冲子策略指数和标普500指数的长期表现。*业绩表现截至2022年7月31日。所显示的对冲基金指数为各基金的加权综合指数。上表中，根据HFR的数据，在研究期间，对冲基金的平均表现远低于标准普尔500指数，而宏观对冲子策略基金的平均表现更是差得多（尤其是在2012年至2017年期间）。鉴于投资者继续将大约4.5万亿美元的资金委托给对冲基金管理人，这些基金必须提供回报以外的一些利益，但目前尚不清楚这会是什么。对于宏观对冲基金来说，似乎尤其如此。为了证实我对于预测的看法，接下来我要举一个很少见的有关自我评估的例子：7月24日《纽约时报》\"周日观点\"专栏刊出一篇长达七页的专题文章，题为\"我错了\"。文章中，八位《纽约时报》\"观点\"专栏作者公开了他们曾做过的错误预测以及给出的有失偏颇的建议。这里最相关的是保罗·克鲁格曼 （Paul Krugman） 所写的一篇题为\" 我看错了通胀 （I Was Wrong About Inflation）\"的自白书。我把其中的一些内容摘录并串连起来：2021年初，经济学家们就\"美国救助计划\"的可能后果展开了激烈的辩论……我当时站在[支持不太担忧通胀影响的一边]。当然，事实证明，这是一个非常糟糕的决定…………历史无法让我们预料到会有如此过热的通胀。所以我的模型出了问题……一种可能的原因是历史具有误导性……此外，为适应疫情及其后果而产生的扰动可能仍在发挥很大角色。当然，俄乌冲突以及中国各大城市的疫情防控措施无疑将这种干扰程度推升至一个全新层面……无论如何，整件事都成了一场谦逊的教训。令人难以置信的是，在2008年金融危机之后，标准经济模型一直运作得相当好，我当时认为在2021年运用同样的模型没有问题。现在回想起来，我当时就该意识到在新冠疫情后所呈现的新世界趋势中，这种推断本身就存在风险。（粗体为笔者所加）我很钦佩克鲁格曼能表现出如此惊人的坦率（虽然我不得不说，我并不记得在2009年到2010年间有很多市场预测乐观到足以描绘随后十年实际情况的程度）。克鲁格曼对他的错误的解释就其本身而言是很好的，但我并未看到他提及在未来放弃建模、推断或预测。这种谦逊甚至可能渗透到世界上最大经济预测机构之一的美联储，那里有400多名经济学博士。以下是经济学家加里·席林 （Gary Shilling） 于8月22日在\"彭博观点 （Bloomberg Opinion）\"中所写的：美联储的前瞻性指引成了一场灾难，导致其本身的公信力面临挑战。主席杰罗姆·鲍威尔 （Jerome Powell） 似乎也持相同看法，外界应该停止揣测美联储在未来不同时间节点有关利率、经济增长和通胀的看法……前瞻性指引的根本问题在于其依赖于数据，而数据本身来自美联储以往那些糟糕的预测记录。美联储一直对2007年-2009年大衰退后的经济复苏过于乐观。2014年9月，政策制定者预测2015年实际GDP增长率为3.40%，但到2015年9月却被迫不断将预期值下调至2.10%。联邦基金利率不是市场决定的利率，而是由美联储设定并管控的，并且无人挑战美联储的权威。此外，联邦公开市场委员会 （FOMC） 成员在预测他们自身将会采取何种行动方面也是出了名的糟糕……2015年，他们对2016年联邦基金利率的平均预测为0.90%，2019年为3.30%。实际数字分别为0.38%和2.38%……可以肯定的是，许多正在发生的事件都造成了市场的不确定性，但美联储的前瞻性指引一直备受追捧且具有重要性。回想一下，今年早些时候，美联储还认为疫情和供应链中断后重启经济的摩擦造成的通胀是暂时性的。直到后来美联储才发现情势不妙而调转方向，提高利率，并发出了进一步大幅加息的信号。美联储的错误预测导致错误的前瞻性指引，加剧了金融市场波动。（粗体为笔者所加）关于这个问题我想最后再提一点，即那些通过宏观观点获利而成名（和致富）的人究竟在哪里？我当然不可能认识投资界的每个人，但在我了解或知道的人里面，我认为只有很少几位堪称非常成功的\"宏观投资者\"。当某件事的实例很少时，正如我母亲曾经说过的那样，\"例外恰恰印证了规律\"。这个例子中的规律就是，宏观预测很少能带来出色的业绩表现。对我来说，成功案例的非比寻常，恰好证明了这一说法是普遍真理。从业者的预测需求相比于揭示未来，预测更能揭示预测者。——沃伦·巴菲特有多少人能够作出大多数时候都有价值的宏观预测？我认为并不多。又有多少投资管理人、经济学家和预测者尝试过？少说也数以千计。这就产生了一个有趣的问题：为什么要预测？如果宏观预测不会随着时间的推移助力投资成功，为什么投资管理行业有这么多从业者信奉预测并对预测结果趋之若鹜？我认为其中典型的原因可能是：这是工作的一部分。投资者向来这样做。我认识的每个人都这样做，尤其是我的竞争对手。我一直都在这样做——我现在不能就此罢手。如果我不这样做，我将无法吸引客户。既然投资涉及部署资本以便从未来事件中受益，那么如果没有对这些事件的看法，怎么能指望做好工作？我们需要预测，即使它们并不完美。今年夏天，我儿子安德鲁推荐我读了一本非常有趣的书：《犯了错误（但错不在我）：为什么我们要为愚蠢的信仰、糟糕的决定和伤害行为找借口》（Mistakes Were Made （but Not by Me）: Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts），该书由心理学家卡罗尔·塔维斯 （Carol Tavris） 和艾略特·阿伦森 （Elliot Aronson） 撰写。书的主题是自我辩护。作者解释说，当人们面对新的证据来质疑他们先前所秉持的立场时，就会出现\"认知失调\"，而当这种情况发生时，潜意识会使他们极力去证明和维护先前的立场。以下是一些精选片段：如果您持有一套指导您实践的信念，并且您了解到其中一些是不正确的，您必须要么承认自己错了并改变您的方法，要么拒绝新的证据。大多数人，当直接面对他们做错的证据时，不会改变他们的观点或行动计划，而是更加顽固地予以辩驳。一旦我们认定某个信念，并证明了它的智慧，要想改变我们的想法显然是一项艰苦的工作。将新证据放入现有框架中进行心理论证以便接纳，比改变框架要容易得多。人们在回应使他们的信念受到质疑的证据时通常采用的机制包括这些（转述作者的话）：不愿意听从不和谐的信息；有选择地记住他们生活的一部分，专注于那些支持自己观点的部分；以及在认知偏见下行事，让人们只看到他们想看到的事物，并为他们已经相信的内容寻求某种确认。我相信，这些都是导致人们持续做出预测并依赖预测的因素。那在这种情况下，会有什么样的表现形式？将宏观预测视为投资不可或缺的一部分；热衷于回忆正确的预测，尤其是那些大胆的、非市场共识的预测；高估预测的正确率；遗忘或淡化错误的预测；不去保留有关预测准确性的记录或未能计算平均成功率；重视奖励给准确预测的丰厚回报；强调\"每个人都这样做\"；以及也许最重要的是，将不成功的预测归咎于被随机事件或外生事件所蒙蔽。（但是，正如我之前所说，这就是问题的关键：如果预测如此轻易地变得不准确，为什么要进行预测？）大多数人——即便是心地善良的老实人——都会采取符合自己利益的立场或行动，有时以牺牲他人或客观真理为代价。他们自己无法察觉这种情景，反而认为自身所做皆为正确的事情；他们也寻求了很多正当理由。正如查理·芒格 （Charlie Munger） 经常引用狄摩西尼的名言，\"没有什么比自欺欺人更容易。因为人总是相信自己所希望的。\"我不认为预测者是骗子或江湖术士。他们之中大多数都是聪明的知识分子，他们认为自己正在做有用的事情。但是，自我利益使他们以某种方式行事，而自我辩护使他们在面对相反的证据时坚持己见。正如摩根·豪斯尔 （Morgan Housel） 在最近的一份时事简报中所说：无法预测过去对我们预测未来的意愿并无影响。确定性是如此宝贵，以至于我们永远不会放弃对它的追求，如果人们诚实地面对未来是多么难以预料，那大多数人都无法在清晨从床上爬起来。（摘自\"大信念\"，联合基金（Collaborative Fund），2022年8月24日）几年前我过生日时，橡树的联合创始人理查德·马森 （Richard Masson） 给了我一件符合他风格的有趣礼物。那次的礼物是《纽约时报》的合订本。我一直希望有机会写一写我最喜欢的1929年10月30日那一期的小标题，道琼斯工业指数刚于两天内下跌了近23%。标题是这样写的，\"银行家表示乐观 （Bankers Optimistic）\"（然而之后的三年内，道琼斯指数大约下跌了85%）。大多数银行家和基金经理似乎先天就对未来持乐观态度。除此之外，这符合他们的最佳利益，因为这有助于他们做更多的生意。但他们的乐观态度肯定造就了他们的预测观点和由此产生的行为。能还是不能？\"我从不考虑未来——因为它马上就要来临了。\"——艾尔伯特·爱因斯坦考虑宏观预测的以下方面：所需假设／输入的数量，须纳入的过程／关系的数量，这些过程固有的不可靠性和不稳定性，以及随机性的作用及发生意外的可能性。对我来说，最重要的是，预测不可能经常正确以达到具备价值的程度。我已经提过很多次了，但为了完整起见，我还是要重申我对宏观预测效用（或者更确切地说，徒劳）的看法：大多数预测由对过去表现的推断组成。由于宏观发展通常不会偏离先前的趋势，因此推断通常是成功的。在这个基础上，大多数预测都是正确的。但是，由于推断通常是由证券价格来预期的，那些基于推断预期的人在推断成立时并不会享受到超额利益。偶尔，经济行为确实会在实质上偏离过去的模式。由于这种偏离出乎大多数投资者的意料，它的出现会影响市场，这意味着对偏离的准确预测将带来丰厚的利润。然而，由于经济不会经常偏离过去的表现，因此能对偏离作出准确预测的很少，并且大多数偏离预测事后被证明是错误的。因此，我们有（一）推断预测，其中大部分是正确的，但不会产生超额利益，以及（二）潜在的有利可图的偏差预测，这些预测很少会是正确的，因此通常也不会产生超额利益。经论证：大多数预测不会增加回报。在本备忘录开头提到的午餐会中，人们被问及对美联储政策等方面的预期，以及这对他们的投资立场有何影响。有一个人回答说：\"我认为美联储仍将高度担心通胀，因此将大幅加息，从而导致经济衰退。所以我选择避险。\"另一位说：\"我预计通胀将在第四季度放缓，而美联储将在明年一月份转向鸽派。开始降息并刺激经济发展。我非常看好2023年。\"我们经常听到这样的说法。但必须认识到，这些人正在运用单因素模型：说话者的预测基于单个变量。说到简化假设：这些预测者隐含地认为，除了美联储的政策之外，一切都是不变的。当需要下三维国际象棋时，他们却还在玩平面跳棋。撇开预测美联储行为的不可能性、通胀对这种行为的影响以及市场对通胀的反应，还有其他重要的考虑因素呢？如果有一千件事情在决定经济和市场的未来方向方面发挥了作用，那么其他999件事情是什么？工资谈判、中期选举、俄乌冲突和石油价格的影响又将如何？事实是，人们在任何时候只能在脑海中记住非常有限的事物。很难将大量的因素纳入考虑，就更难理解大量事物将如何相互作用（相关性始终是真正的思考难题）。即使您以某种方式设法得到正确的经济预测，那只是成功的一半。您仍然需要预测经济活动将如何转化为市场结果。这需要一个完全不同的预测，也涉及无数的变量，其中许多与心理因素有关，因此几乎是不可知的。根据学生沃伦·巴菲特回忆，本·格雷厄姆 （Ben Graham） 曾表示：\"从短期看，市场是一台投票机，但从长远来看，它是一台称重机。\"如何预测投资者的短期选择？一些经济预测人士得出的结论是，美联储和财政部在2020年3月宣布的行动将拯救美国经济并助力经济复苏。但我不知道有谁预测到了在复苏开始之前就已掀起炙手可热的牛市。正如我之前所述，2016年巴菲特与我分享了他对宏观预测的看法。\"要使一条信息有效用，它必须满足两个标准：首先必须重要，其次必须可知。\"当然，宏观前景很重要。如今，投资者似乎把握住了每位预测者的言论、宏观事件以及美联储间歇性紧缩行动的信号。与我从事这个行业的早期不同，现今似乎宏观因素就是一切，而企业发展没那么受关注。但我强烈同意巴菲特的观点，即宏观未来是不可知的，或者至少几乎没人能始终如一地比广大投资者了解更多，而这才是试图获得认知优势并作出卓越投资决策的关键。显然，巴菲特的名字在成功投资者名单中名列前茅，他回避宏观预测，比其他人更注重\"微观\"领域：公司、行业和证券，从而获得成功。我于2001年的一篇名为《阿尔法究竟是什么？》（What’s It All About, Alpha?） 的备忘录中，引入了\"可知论\"流派和\"不可知论\"流派的概念，并于2004年，在《我们和他们》（Us and Them） 一文中对此进行了详细阐述。作为当前备忘录的收尾，我将插入我在后者中所撰写的关于这两种流派的一些内容：这些年来，我遇到的大多数投资者都属于\"可知论\"流派。在1968年-1978年期间，我分析股票时如此，甚至在1978年-1995年期间，我转向非主流投资、但仍在以股票为中心的投资管理公司工作时，情况亦是如此。识别\"可知论\"流派的成员很容易：他们认为，了解经济的未来方向、利率、市场和受广泛关注的主流股票，对投资成功至关重要。他们有信心可以实现这点。他们知道自己能做到这点。他们知道很多人也在努力做到这点，但他们认为要么（一）每个人都可以同时成功，要么（二）只有少数人能做到，但他们就是其中之一。他们愿意根据自己对未来的看法进行投资。他们也很乐意与他人分享自己的观点，尽管正确的预测应价值千金，没有人会免费赠送。他们很少回顾过去，认真复盘他们作为预测者的成绩。\"自信\"是形容该流派成员的关键词。另一方面，对于\"不可知论\"流派而言，这个词，尤其是在看待宏观未来时，应是\"谨慎\"。其信奉者通常认为无法预知未来；也不必预知未来；正确的目标应是在承认不具备这种认知的基础上，尽最大努力做好投资。作为\"可知论\"流派的一员，您可以对未来发表意见（也许还有人特此做笔记）。您可能会受人追捧，并被视为理想的晚宴嘉宾……特别是在股市上涨的时候。如果加入\"不可知论\"流派，结果则更加复杂。您很快就会厌倦对朋友和陌生人表达\"不可知论\"。过不了多久，即使是亲戚也不再问您关于市场走势的看法。您永远不会享受到预测成真时那千分之一的惊喜时刻，也享受不到《华尔街日报》刊载您照片的喜悦。另一方面，您也免于面对预测错误，也免于遭受基于对未来过度确信进行投资而导致的损失。但是，当潜在客户询问您投资前景，而您不得不说\"我不知道\"时，您认为这会是什么感觉？对我来说，哪种流派最好的底线评判标准，出自已故的斯坦福大学行为科学家阿莫斯·特沃斯基 （Amos Tversky） 的名言：\"意识到您可能不知道某些事情是可怕的，但更可怕的是意识到，总的来说，世界是由那些坚信自己确切知道所发生的事情的人来管理的。\"在投资管理业务中，提出宏观预测，应要求进行分享，并以此为据受托为客户投资，这当然是标准做法。基金经理相信预测，尤其是自己的预测，似乎也是惯例。如上所述，不这样做显得格格不入。但他们的信念实事求是吗？我很想听听大家的看法。多年前，一位备受尊敬的卖方经济学家（我在花旗任职时的一位旧识）打电话给我：\"您改变了我的人生，\"他说。\"我早已不再做预测了。取而代之的是，我只是告诉人们今天发生了什么，以及我认为可能会对未来产生的影响。生活从此变得更加美好。\"我能帮您达到同样的幸福状态吗？本文作者：霍华德·马克斯","news_type":1,"symbols_score_info":{".DJI":0.9}},"isVote":1,"tweetType":1,"viewCount":1342,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}],"lives":[]}
