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Thorpe and Simmons: The legendary lives of two godfather investment tycoons
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Judging from Thorp's experience, from defeating casinos to entering Wall Street, OTC options, convertible bonds, stocks, futures and other derivatives, all Dabbled in, worthy of the name All Markets. Taleb says in the preface that his memoir reads like a thriller.</p><p>As a mathematical genius and the godfather of quantitative investment, he pioneered the introduction of probability theory, information theory, and computer programming into financial transactions, which influenced countless Quant bosses in later generations: Bill Gross, David Shaw, Ken Griffin... including the famous James Simons, whose Renaissance Technology company created the myth of the rate of return in financial history. Similarly, Simons' biography The Man Who Solved The Market records in detail the ups and downs of his and his team's conquest of the financial market.</p><p><b>Academic origin</b></p><p>When culture flourishes, people are outstanding. The so-called outstanding people, such as the Huxiang School since the late Ming Dynasty in China, made Hunan the cradle of revolutionaries. In the academic circle, there is a similar phenomenon. If you study the backgrounds of the two bosses carefully, you will find a lot in common. They were both born in the 1930s. They were gifted since childhood, in the academic circle, but they were all dedicated to money. They have two common alma maters: the University of California, Berkeley and MIT. The academics of both universities reached their peak after the war. One of the main reasons was the large-scale military scientific research activities (the famous Manhattan Project, cryptography, information theory and modern computers) spawned by World War II. Both Thorp and Simons happened to catch up with this wave of academic dividends. In the 1950s, Thorp was obsessed with studying roulette with Shannon, while Simons was still immersed in theoretical mathematics, which also made his academic achievements higher (Chern-Simons Theroy). In the 1960s, MIT became the center of the computer revolution, and mathematics and computers were the two keys to Wall Street, and Thorp was the lucky one to hold these two keys.</p><p><b>Casinos vs Wall Street</b></p><p>The popular story nowadays is that Thorp defeated the casino by using the law of large numbers and Kelly's formula, and he became the first person in history to be \"blacked out\" by Las Vegas casinos. By contrast, the hedge fund he founded, PNP (Princeton Newport Partners), has a dim profile. In fact, from 1969 to 1988, the annualized returns of the two PNP funds reached 19.1% and 15.1% respectively, while the average annual growth rate of the S&P index during the same period was 10.2%. In the past 19 years, after two oil crises in the 1970s and the stock market crash in 1987, the two funds have never suffered a single-quarter loss, let alone an annual loss. In the world's largest casino, its performance is unparalleled, and its investment model is 20 years ahead of the wide customers who have filed into Wall Street since then.</p><p>In 1988, Thorp's fund was forced to close because it was implicated in the case of Milken, the king of junk bonds. It was in this year that Simons established the Medallion Fund. He is over 500 years old and can be described as a late bloomer. Before that, he had been groping for 10 years to find a successful investment model, and had been swinging between subjective and quantitative. Although the outside world has always regarded Simons as a master of quantitative investment, in fact, his role is completely different from Thorp's. His main job is not to develop quantitative models, but to dig all kinds of scientists from the academic circle to help the company develop quantitative models, and shape the company's corporate culture as a spiritual leader. As a world-class mathematician + excellent sales, he can deal with different people well, which is a rare ability.</p><p><b>The road to quantification</b></p><p>As a pioneer in quantitative trading, Thorp is good at hedging and arbitrage of various derivatives. The bear market and volatility in the 1970s made this strategy work perfectly. Relying on his mathematical talent and market sense, he discovered new blue oceans: Statistical Arbitrage and factor models-early quant prototypes. The risk under this model is theoretically infinite, especially the upper limit of losses for shorting those overvalued stocks is infinite. Thorp's main risk control strategy is diversified investment. Since then, LTCM has adopted a similar arbitrage model, but lacked a risk control strategy like Thorp and was defeated by the black swan. In order to improve investment efficiency, Thorp turned investment strategies into programs and once again became a pioneer in programmatic trading (Algorithm Trading).</p><p>Simons, in contrast, was less lucky. From early attempts at intuitive investing to trend-based momentum trading, reversal trading to continuous collection and mining of massive amounts of data, including data cleaning, signal mechanism and backtesting. In 1986, the model framework for identifying hidden price trends was used-in 1989, abnormal trading signals were used for short-term high-frequency trading-in 1992, it was changed to only a single model (key breakthrough), and then speech recognition experts helped make various technological breakthroughs (financial models have similarities with speech recognition), and the model has gone through a long process of iterative improvement. In the end, the important core competence of the model was developed: identifying the \"value of transactions\", including: the certainty of price trends, the weight trade-off between trading signals, and the judgment of the impact of trading based on signals on the market. This capability is particularly important for high-frequency full-variety trading.</p><p><b>Winning System: Probabilistic Thinking & Modeling Human Behavior</b></p><p>For Thorp, gambling and investment are games based on probability statistics, and the bet amount is allocated according to the winning percentage (fund management based on Kelly's law). The first major breakthrough of Medallion Fund also comes from the application of Kelly's law and shortening the trading frequency to make its trading more reflective of the law of large numbers. Medallion's system can make money as long as the winning rate is slightly above 50%, regardless of the profit or loss of every sale. Essentially, it is making money by taking advantage of the omissions and mistakes of other traders (market ineffectiveness). Humans are highly predictable in their behavior under high pressure, and they instinctively show panic. The premise of modeling is that humans will constantly repeat past behaviors. Soros once modeled human behavior with the philosophical theory of reflexivity, while Simons's team used data and algorithms to model human behavior to confirm the theory of behavioral finance.</p><p>Unlike traditional value investing, which simplifies the market into a market gentleman, the experience of quantitative investing is that there are far more factors and variables that affect financial markets and investments than most people realize, and the factors that lead to market ineffectiveness can even be said to be encrypted (Thorp spares no effort to refute the efficient market hypothesis in his book). Investors try to find the most basic driving factors, but what they are missing may be an entire dimension of information. Medallion Fund can't explain the logic behind every profit law, just as human beings can't understand Alpha Go, perhaps it exists at a higher latitude.</p><p>Models are abstractions and simplifications of the world, but models are not omnipotent. When data and desire conflict, even rational scientists cannot be completely rational. Simons' original intention was to create an algorithm-driven automatic trading system, which completely shielded human subjective judgment. However, in every crisis, he still couldn't help but intervene manually to reduce his dependence on signals and actively reduce his trading position. The results of the intervention were not very ideal. His colleague Patterson also said: \"<b>Never put too much trust in trading models. The basic mistake of LTCMs is to believe that the model is the truth. We never believe that our model can reflect the whole fact, it only reflects some of it</b>。”</p><p><b>Wide guest student</b></p><p>In fact, the intersection of many big guys is far beyond our imagination. For example, Thorp and Buffett played at the bridge table. After confirming that Buffett would eventually become the richest man in the United States, they decisively invested in BRK stock. Many people think that Xueba may not necessarily have a good life. After all, there is a huge gap between book smart and street smart, and the rules of the real world are much more complicated than those of schools. However, Thorp has practiced the way of thinking of applying abstract thinking to real life, which truly explains that \"a tough life doesn't need to be explained\". Academics, wealth and family are perfect, and he realized early that life itself is higher than making money. Compared with Thorp's splendid life, Simons's life has too many twists and turns. He is divorced, his two sons have suffered misfortune and betrayal by his partners. But in the end, I chose to make peace with life and devote myself to charity. From academic career to lenient students, I explored the true meaning of destiny in the ups and downs, and experience itself was the meaning. As Thorp said at the end of his autobiography: Life is like reading a novel or running a marathon. Reaching the finish line is often not so important, but the journey itself and the experience along the way are more precious.<b>You have dance.</b></p>","source":"lsy1625911325017","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>Thorpe and Simmons: The legendary lives of two godfather investment tycoons</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\">\nThorpe and Simmons: The legendary lives of two godfather investment tycoons\n</h2>\n<h4 class=\"meta\">\n<p class=\"head\">\n<strong class=\"h-name small\">SMARTMATRIX</strong><span class=\"h-time small\">2021-07-10 17:56</span>\n</p>\n</h4>\n</header>\n<article>\n<p>A Man for All Markets is the personal biography of Edward Thorp, the Chinese translation of \"The Man Who Beat All Markets\". Judging from Thorp's experience, from defeating casinos to entering Wall Street, OTC options, convertible bonds, stocks, futures and other derivatives, all Dabbled in, worthy of the name All Markets. Taleb says in the preface that his memoir reads like a thriller.</p><p>As a mathematical genius and the godfather of quantitative investment, he pioneered the introduction of probability theory, information theory, and computer programming into financial transactions, which influenced countless Quant bosses in later generations: Bill Gross, David Shaw, Ken Griffin... including the famous James Simons, whose Renaissance Technology company created the myth of the rate of return in financial history. Similarly, Simons' biography The Man Who Solved The Market records in detail the ups and downs of his and his team's conquest of the financial market.</p><p><b>Academic origin</b></p><p>When culture flourishes, people are outstanding. The so-called outstanding people, such as the Huxiang School since the late Ming Dynasty in China, made Hunan the cradle of revolutionaries. In the academic circle, there is a similar phenomenon. If you study the backgrounds of the two bosses carefully, you will find a lot in common. They were both born in the 1930s. They were gifted since childhood, in the academic circle, but they were all dedicated to money. They have two common alma maters: the University of California, Berkeley and MIT. The academics of both universities reached their peak after the war. One of the main reasons was the large-scale military scientific research activities (the famous Manhattan Project, cryptography, information theory and modern computers) spawned by World War II. Both Thorp and Simons happened to catch up with this wave of academic dividends. In the 1950s, Thorp was obsessed with studying roulette with Shannon, while Simons was still immersed in theoretical mathematics, which also made his academic achievements higher (Chern-Simons Theroy). In the 1960s, MIT became the center of the computer revolution, and mathematics and computers were the two keys to Wall Street, and Thorp was the lucky one to hold these two keys.</p><p><b>Casinos vs Wall Street</b></p><p>The popular story nowadays is that Thorp defeated the casino by using the law of large numbers and Kelly's formula, and he became the first person in history to be \"blacked out\" by Las Vegas casinos. By contrast, the hedge fund he founded, PNP (Princeton Newport Partners), has a dim profile. In fact, from 1969 to 1988, the annualized returns of the two PNP funds reached 19.1% and 15.1% respectively, while the average annual growth rate of the S&P index during the same period was 10.2%. In the past 19 years, after two oil crises in the 1970s and the stock market crash in 1987, the two funds have never suffered a single-quarter loss, let alone an annual loss. In the world's largest casino, its performance is unparalleled, and its investment model is 20 years ahead of the wide customers who have filed into Wall Street since then.</p><p>In 1988, Thorp's fund was forced to close because it was implicated in the case of Milken, the king of junk bonds. It was in this year that Simons established the Medallion Fund. He is over 500 years old and can be described as a late bloomer. Before that, he had been groping for 10 years to find a successful investment model, and had been swinging between subjective and quantitative. Although the outside world has always regarded Simons as a master of quantitative investment, in fact, his role is completely different from Thorp's. His main job is not to develop quantitative models, but to dig all kinds of scientists from the academic circle to help the company develop quantitative models, and shape the company's corporate culture as a spiritual leader. As a world-class mathematician + excellent sales, he can deal with different people well, which is a rare ability.</p><p><b>The road to quantification</b></p><p>As a pioneer in quantitative trading, Thorp is good at hedging and arbitrage of various derivatives. The bear market and volatility in the 1970s made this strategy work perfectly. Relying on his mathematical talent and market sense, he discovered new blue oceans: Statistical Arbitrage and factor models-early quant prototypes. The risk under this model is theoretically infinite, especially the upper limit of losses for shorting those overvalued stocks is infinite. Thorp's main risk control strategy is diversified investment. Since then, LTCM has adopted a similar arbitrage model, but lacked a risk control strategy like Thorp and was defeated by the black swan. In order to improve investment efficiency, Thorp turned investment strategies into programs and once again became a pioneer in programmatic trading (Algorithm Trading).</p><p>Simons, in contrast, was less lucky. From early attempts at intuitive investing to trend-based momentum trading, reversal trading to continuous collection and mining of massive amounts of data, including data cleaning, signal mechanism and backtesting. In 1986, the model framework for identifying hidden price trends was used-in 1989, abnormal trading signals were used for short-term high-frequency trading-in 1992, it was changed to only a single model (key breakthrough), and then speech recognition experts helped make various technological breakthroughs (financial models have similarities with speech recognition), and the model has gone through a long process of iterative improvement. In the end, the important core competence of the model was developed: identifying the \"value of transactions\", including: the certainty of price trends, the weight trade-off between trading signals, and the judgment of the impact of trading based on signals on the market. This capability is particularly important for high-frequency full-variety trading.</p><p><b>Winning System: Probabilistic Thinking & Modeling Human Behavior</b></p><p>For Thorp, gambling and investment are games based on probability statistics, and the bet amount is allocated according to the winning percentage (fund management based on Kelly's law). The first major breakthrough of Medallion Fund also comes from the application of Kelly's law and shortening the trading frequency to make its trading more reflective of the law of large numbers. Medallion's system can make money as long as the winning rate is slightly above 50%, regardless of the profit or loss of every sale. Essentially, it is making money by taking advantage of the omissions and mistakes of other traders (market ineffectiveness). Humans are highly predictable in their behavior under high pressure, and they instinctively show panic. The premise of modeling is that humans will constantly repeat past behaviors. Soros once modeled human behavior with the philosophical theory of reflexivity, while Simons's team used data and algorithms to model human behavior to confirm the theory of behavioral finance.</p><p>Unlike traditional value investing, which simplifies the market into a market gentleman, the experience of quantitative investing is that there are far more factors and variables that affect financial markets and investments than most people realize, and the factors that lead to market ineffectiveness can even be said to be encrypted (Thorp spares no effort to refute the efficient market hypothesis in his book). Investors try to find the most basic driving factors, but what they are missing may be an entire dimension of information. Medallion Fund can't explain the logic behind every profit law, just as human beings can't understand Alpha Go, perhaps it exists at a higher latitude.</p><p>Models are abstractions and simplifications of the world, but models are not omnipotent. When data and desire conflict, even rational scientists cannot be completely rational. Simons' original intention was to create an algorithm-driven automatic trading system, which completely shielded human subjective judgment. However, in every crisis, he still couldn't help but intervene manually to reduce his dependence on signals and actively reduce his trading position. The results of the intervention were not very ideal. His colleague Patterson also said: \"<b>Never put too much trust in trading models. The basic mistake of LTCMs is to believe that the model is the truth. We never believe that our model can reflect the whole fact, it only reflects some of it</b>。”</p><p><b>Wide guest student</b></p><p>In fact, the intersection of many big guys is far beyond our imagination. For example, Thorp and Buffett played at the bridge table. After confirming that Buffett would eventually become the richest man in the United States, they decisively invested in BRK stock. Many people think that Xueba may not necessarily have a good life. After all, there is a huge gap between book smart and street smart, and the rules of the real world are much more complicated than those of schools. However, Thorp has practiced the way of thinking of applying abstract thinking to real life, which truly explains that \"a tough life doesn't need to be explained\". Academics, wealth and family are perfect, and he realized early that life itself is higher than making money. Compared with Thorp's splendid life, Simons's life has too many twists and turns. He is divorced, his two sons have suffered misfortune and betrayal by his partners. But in the end, I chose to make peace with life and devote myself to charity. From academic career to lenient students, I explored the true meaning of destiny in the ups and downs, and experience itself was the meaning. As Thorp said at the end of his autobiography: Life is like reading a novel or running a marathon. Reaching the finish line is often not so important, but the journey itself and the experience along the way are more precious.<b>You have dance.</b></p>\n<div class=\"bt-text\">\n\n\n<p> source：<a href=\"https://mp.weixin.qq.com/s/g5Zdx-uS3wl9QbsHZm1DVw\">SMARTMATRIX</a></p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/388d882133df2db2363aa871ff756c47","relate_stocks":{".DJI":"道琼斯"},"source_url":"https://mp.weixin.qq.com/s/g5Zdx-uS3wl9QbsHZm1DVw","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1124741749","content_text":"A Man for All Markets是Edward Thorp的个人传记，中文翻译《战胜一切市场的人》，从Thorp的经历来看，从打败赌场到进入华尔街，OTC期权、可转债、股票、期货等衍生品，全部涉猎，名副其实的All Markets。塔勒布在序言里说，他的回忆录读起来像一部惊悚小说。\n作为一个数学天才、量化投资教父级人物，他开创性的将概率论、信息论、计算机编程引入金融交易，影响了后世无数Quant大佬：Bill Gross、David Shaw、Ken Griffin...其中也包括大名鼎鼎的James Simons，后者的文艺复兴科技公司创造了金融史上的回报率神话，同样，讲述Simons的传记The Man Who Solved The Market，详细记录了他和他的团队征服金融市场的起起落落，虽是一位华尔街日报作家根据采访汇编而成，但其中不少以前从未披露过的精彩故事。\n学术源流\n文化兴，则人杰出，所谓的人杰地灵，比如中国明末以来的湖湘学派让湖南成为革命党人的摇篮。在学术圈，也有类似的现象。仔细研究两位大佬的背景，会发现很多共通点，他们都出生于30年代，自幼天赋异禀、身在学术圈但都一心向钱，有两个共同的母校：加州大学伯克利分校和MIT。两校的学术在战后都达到了巅峰，主要一个原因就是二战催生的大规军事科研活动（著名的曼哈顿计划、密码学、信息论和现代计算机），Thorp和Simons都恰好赶上了这波学术红利。50年代，Thorp醉心于和香农一起研究轮盘赌，而Simons仍埋头于理论数学问题，这也使得其在学术上的成就更高（Chern-Simons Theroy）。60年代，MIT成为计算机革命的中心，而数学和计算机正是通向华尔街的两把钥匙，Thorp正是手握这两把钥匙的幸运儿。\n赌场vs华尔街\n如今为人津津乐道的故事是Thorp利用大数定律和凯利公式打败了赌场，他也成了历史上第一个被拉斯维加斯赌场“拉黑”的人。相比之下，他创设的对冲基金PNP（Princeton Newport Partners）知名度黯淡不少。实际上，从1969年到1988年，PNP两支基金的年化收益率分别达到19.1%和15.1%，同期标普指数年均增长率为10.2%。19年间历经70年代两次石油危机、87年股灾，两只基金从未发生单季亏损，更没有年度亏损。在世间最大的赌场，其业绩冠绝其时，其投资模式，领先此后鱼贯进入华尔街的宽客们20年。\n1988年，Thorp的基金因为受到垃圾债券之王米尔肯一案的牵连被迫关闭。正是在这一年，Simons成立大奖章基金，已年过半百的他，可谓大器晚成，在此前为了寻找成功的投资模型已经摸索了10年之久，一直在主观和量化之间摇摆。尽管外界一直都把Simons视作量化投资大师，但实际上他点角色和Thorp完全不同，他的主要工作并不是开发量化模型，而是从学术圈挖掘各类科学家来帮助公司开发量化模型，并且作为精神领袖塑造公司企业文化。作为一名世界级的数学家+卓越的销售，他与不同的人都能融洽的打交道，这是一种罕见的能力。\n量化之路\n作为量化交易的先驱，Thorp擅长各种衍生品的对冲套利，70年代的熊市和波动率让这种策略运行的非常完美。依靠自己的数学天赋和市场嗅觉发现了新的蓝海：统计套利（Statistical Arbitrage）和因子模型（factors model）——早期的quant原型。这种模式下的风险理论上是无穷的，尤其是做空那些价格高估的股票的损失上限是无穷大，Thorp主要风控策略是分散化投资。此后的LTCM采用类似的套利模式，但缺少Thorp这样的风控策略，被黑天鹅击败。为了提升投资效率，Thorp将投资策略变成程序，再次成为程序化交易（Algorithm Trading）的先驱。\n相比之下，Simons就没那么幸运了。从早期尝试直觉投资到基于趋势的动量交易、反转交易再到持续收集挖掘海量数据包括数据清洗、信号机制和回溯测试。1986年使用识别隐藏价格趋势的模型框架——1989年利用异常交易信号进行短期高频交易——1992年改为只用单一模型（关键性突破），而后语音识别专家帮助进行各种技术突破（金融模型与语音识别有相似之处），模型经历了漫长迭代改进的过程。最终练就了模型重要核心能力：识别出“交易的价值”，包括：价格趋势的确定性大小、交易信号之间的权重取舍、根据信号进行交易对市场造成的影响的判断。这项能力对于高频全品种交易尤为重要。\n取胜系统：概率思考&对人类行为建模\n对Thorp来说，赌博和投资都是以概率统计为基础的游戏，根据胜率的大小来分配下注金额的大小（基于凯利法则的资金管理），而大奖章基金的第一次重大突破也来自于对凯利法则的运用以及缩短交易频率使其交易更体现大数定律。大奖章的系统只要胜率略高于50%就能赚钱，而不在乎每一笔买卖的盈亏。本质上，是在利用其他交易者的疏忽和错误赚钱（市场无效）。人类在高压下的行为具有很高的可预测性，他们会本能地表现出恐慌。建模的前提是人类会不断重复过去的行为。索罗斯曾以反身性的哲学理论对人类行为建模，而Simons的团队利用数据和算法对人类行为建模，以此印证行为金融学的理论。\n与传统的价值投资把市场面简化成一位市场先生不同，量化投资的经验是，影响金融市场和投资的因素和变量远远比大多数人意识到的更多，导致市场无效的因素甚至可以说是加密的（Thorp在书中对有效市场假说也不遗余力的进行驳斥）。投资者努力寻找最基本的推动因素，但是遗漏的也许是一整个维度的信息。大奖章基金无法对每一条盈利的规律背后的逻辑进行解释，就如同人类无法理解阿尔法围棋一样，也许是更高纬度的存在。\n模型是对世界的抽象和简化，但模型并不是万能的。当数据和欲望相冲突，即便是理性的科学家，也无法做到完全理性。Simons的初心是创建的算法驱动的自动交易系统，完全屏蔽人类的主观判断，但每一次危机，他仍忍不住会手动干预，减少对信号的依赖，主动缩减交易头寸，可干预的结果并不十分理想。他的同事帕特森也说：”永远不要对交易模型过于信任。长期资本管理公司的基本错误是认为模型就是事实真相，我们从未相信我们的模型能够反映全部事实，它只反映事实的一部分。”\n宽客人生\n其实很多大佬的交集，远远超过我们想象。比如Thorp和巴菲特在桥牌桌上过过招，在确认巴菲特最终会成为全美最富有的人之后，果断投资了BRK的股票。很多人以为，学霸不一定会拥有好人生，毕竟，book smart和street smart之间的有极大的鸿沟，现实世界的规则比学校要复杂太多，但Thorp践行了将抽象思维运用到现实生活中的思维方式，真正诠释了“彪悍的人生不需要解释”，学术、财富、家庭圆满，很早就意识到在生活本身高于赚钱。相比较Thorp精彩纷呈的人生，Simons的人生曲折太多，离过婚，他的两个儿子先后遭受不幸，还遭遇过伙伴背叛。但最终还是选择和生活讲和，并投身慈善事业，从学术生涯到宽客人生，在跌宕起伏中探寻命运的真谛，而经历本身就是意义所在。就像Thorp在自传末尾所说：生活像是读一本小说或者跑一场马拉松，到达终点往往不是那么重要，旅途本身和沿途的体验更为珍贵。No body can take away the dance you have danced.","news_type":1,"symbols_score_info":{".DJI":0.9}},"isVote":1,"tweetType":1,"viewCount":837,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":148563357,"gmtCreate":1625989477879,"gmtModify":1703751718719,"author":{"id":"3585637828990587","authorId":"3585637828990587","name":"yuenkeat","avatar":"https://static.tigerbbs.com/84dbf8826e1cc07c9e9417a8755a21bf","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3585637828990587","idStr":"3585637828990587"},"themes":[],"htmlText":"?","listText":"?","text":"?","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/148563357","repostId":"1155854665","repostType":4,"isVote":1,"tweetType":1,"viewCount":1299,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}],"hots":[{"id":148563357,"gmtCreate":1625989477879,"gmtModify":1703751718719,"author":{"id":"3585637828990587","authorId":"3585637828990587","name":"yuenkeat","avatar":"https://static.tigerbbs.com/84dbf8826e1cc07c9e9417a8755a21bf","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3585637828990587","idStr":"3585637828990587"},"themes":[],"htmlText":"?","listText":"?","text":"?","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":1,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/148563357","repostId":"1155854665","repostType":4,"isVote":1,"tweetType":1,"viewCount":1299,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0},{"id":148561622,"gmtCreate":1625989628466,"gmtModify":1703751720019,"author":{"id":"3585637828990587","authorId":"3585637828990587","name":"yuenkeat","avatar":"https://static.tigerbbs.com/84dbf8826e1cc07c9e9417a8755a21bf","crmLevel":1,"crmLevelSwitch":0,"followedFlag":false,"authorIdStr":"3585637828990587","idStr":"3585637828990587"},"themes":[],"htmlText":"?","listText":"?","text":"?","images":[],"top":1,"highlighted":1,"essential":1,"paper":1,"likeSize":0,"commentSize":0,"repostSize":0,"link":"https://ttm.financial/post/148561622","repostId":"1124741749","repostType":4,"repost":{"id":"1124741749","kind":"news","pubTimestamp":1625910991,"share":"https://ttm.financial/m/news/1124741749?lang=en_US&edition=fundamental","pubTime":"2021-07-10 17:56","market":"us","language":"zh","title":"Thorpe and Simmons: The legendary lives of two godfather investment tycoons","url":"https://stock-news.laohu8.com/highlight/detail?id=1124741749","media":"SMARTMATRIX","summary":"他们都出生于30年代，自幼天赋异禀、身在学术圈但都一心向钱，有两个共同的母校。","content":"<p>A Man for All Markets is the personal biography of Edward Thorp, the Chinese translation of \"The Man Who Beat All Markets\". Judging from Thorp's experience, from defeating casinos to entering Wall Street, OTC options, convertible bonds, stocks, futures and other derivatives, all Dabbled in, worthy of the name All Markets. Taleb says in the preface that his memoir reads like a thriller.</p><p>As a mathematical genius and the godfather of quantitative investment, he pioneered the introduction of probability theory, information theory, and computer programming into financial transactions, which influenced countless Quant bosses in later generations: Bill Gross, David Shaw, Ken Griffin... including the famous James Simons, whose Renaissance Technology company created the myth of the rate of return in financial history. Similarly, Simons' biography The Man Who Solved The Market records in detail the ups and downs of his and his team's conquest of the financial market.</p><p><b>Academic origin</b></p><p>When culture flourishes, people are outstanding. The so-called outstanding people, such as the Huxiang School since the late Ming Dynasty in China, made Hunan the cradle of revolutionaries. In the academic circle, there is a similar phenomenon. If you study the backgrounds of the two bosses carefully, you will find a lot in common. They were both born in the 1930s. They were gifted since childhood, in the academic circle, but they were all dedicated to money. They have two common alma maters: the University of California, Berkeley and MIT. The academics of both universities reached their peak after the war. One of the main reasons was the large-scale military scientific research activities (the famous Manhattan Project, cryptography, information theory and modern computers) spawned by World War II. Both Thorp and Simons happened to catch up with this wave of academic dividends. In the 1950s, Thorp was obsessed with studying roulette with Shannon, while Simons was still immersed in theoretical mathematics, which also made his academic achievements higher (Chern-Simons Theroy). In the 1960s, MIT became the center of the computer revolution, and mathematics and computers were the two keys to Wall Street, and Thorp was the lucky one to hold these two keys.</p><p><b>Casinos vs Wall Street</b></p><p>The popular story nowadays is that Thorp defeated the casino by using the law of large numbers and Kelly's formula, and he became the first person in history to be \"blacked out\" by Las Vegas casinos. By contrast, the hedge fund he founded, PNP (Princeton Newport Partners), has a dim profile. In fact, from 1969 to 1988, the annualized returns of the two PNP funds reached 19.1% and 15.1% respectively, while the average annual growth rate of the S&P index during the same period was 10.2%. In the past 19 years, after two oil crises in the 1970s and the stock market crash in 1987, the two funds have never suffered a single-quarter loss, let alone an annual loss. In the world's largest casino, its performance is unparalleled, and its investment model is 20 years ahead of the wide customers who have filed into Wall Street since then.</p><p>In 1988, Thorp's fund was forced to close because it was implicated in the case of Milken, the king of junk bonds. It was in this year that Simons established the Medallion Fund. He is over 500 years old and can be described as a late bloomer. Before that, he had been groping for 10 years to find a successful investment model, and had been swinging between subjective and quantitative. Although the outside world has always regarded Simons as a master of quantitative investment, in fact, his role is completely different from Thorp's. His main job is not to develop quantitative models, but to dig all kinds of scientists from the academic circle to help the company develop quantitative models, and shape the company's corporate culture as a spiritual leader. As a world-class mathematician + excellent sales, he can deal with different people well, which is a rare ability.</p><p><b>The road to quantification</b></p><p>As a pioneer in quantitative trading, Thorp is good at hedging and arbitrage of various derivatives. The bear market and volatility in the 1970s made this strategy work perfectly. Relying on his mathematical talent and market sense, he discovered new blue oceans: Statistical Arbitrage and factor models-early quant prototypes. The risk under this model is theoretically infinite, especially the upper limit of losses for shorting those overvalued stocks is infinite. Thorp's main risk control strategy is diversified investment. Since then, LTCM has adopted a similar arbitrage model, but lacked a risk control strategy like Thorp and was defeated by the black swan. In order to improve investment efficiency, Thorp turned investment strategies into programs and once again became a pioneer in programmatic trading (Algorithm Trading).</p><p>Simons, in contrast, was less lucky. From early attempts at intuitive investing to trend-based momentum trading, reversal trading to continuous collection and mining of massive amounts of data, including data cleaning, signal mechanism and backtesting. In 1986, the model framework for identifying hidden price trends was used-in 1989, abnormal trading signals were used for short-term high-frequency trading-in 1992, it was changed to only a single model (key breakthrough), and then speech recognition experts helped make various technological breakthroughs (financial models have similarities with speech recognition), and the model has gone through a long process of iterative improvement. In the end, the important core competence of the model was developed: identifying the \"value of transactions\", including: the certainty of price trends, the weight trade-off between trading signals, and the judgment of the impact of trading based on signals on the market. This capability is particularly important for high-frequency full-variety trading.</p><p><b>Winning System: Probabilistic Thinking & Modeling Human Behavior</b></p><p>For Thorp, gambling and investment are games based on probability statistics, and the bet amount is allocated according to the winning percentage (fund management based on Kelly's law). The first major breakthrough of Medallion Fund also comes from the application of Kelly's law and shortening the trading frequency to make its trading more reflective of the law of large numbers. Medallion's system can make money as long as the winning rate is slightly above 50%, regardless of the profit or loss of every sale. Essentially, it is making money by taking advantage of the omissions and mistakes of other traders (market ineffectiveness). Humans are highly predictable in their behavior under high pressure, and they instinctively show panic. The premise of modeling is that humans will constantly repeat past behaviors. Soros once modeled human behavior with the philosophical theory of reflexivity, while Simons's team used data and algorithms to model human behavior to confirm the theory of behavioral finance.</p><p>Unlike traditional value investing, which simplifies the market into a market gentleman, the experience of quantitative investing is that there are far more factors and variables that affect financial markets and investments than most people realize, and the factors that lead to market ineffectiveness can even be said to be encrypted (Thorp spares no effort to refute the efficient market hypothesis in his book). Investors try to find the most basic driving factors, but what they are missing may be an entire dimension of information. Medallion Fund can't explain the logic behind every profit law, just as human beings can't understand Alpha Go, perhaps it exists at a higher latitude.</p><p>Models are abstractions and simplifications of the world, but models are not omnipotent. When data and desire conflict, even rational scientists cannot be completely rational. Simons' original intention was to create an algorithm-driven automatic trading system, which completely shielded human subjective judgment. However, in every crisis, he still couldn't help but intervene manually to reduce his dependence on signals and actively reduce his trading position. The results of the intervention were not very ideal. His colleague Patterson also said: \"<b>Never put too much trust in trading models. The basic mistake of LTCMs is to believe that the model is the truth. We never believe that our model can reflect the whole fact, it only reflects some of it</b>。”</p><p><b>Wide guest student</b></p><p>In fact, the intersection of many big guys is far beyond our imagination. For example, Thorp and Buffett played at the bridge table. After confirming that Buffett would eventually become the richest man in the United States, they decisively invested in BRK stock. Many people think that Xueba may not necessarily have a good life. After all, there is a huge gap between book smart and street smart, and the rules of the real world are much more complicated than those of schools. However, Thorp has practiced the way of thinking of applying abstract thinking to real life, which truly explains that \"a tough life doesn't need to be explained\". Academics, wealth and family are perfect, and he realized early that life itself is higher than making money. Compared with Thorp's splendid life, Simons's life has too many twists and turns. He is divorced, his two sons have suffered misfortune and betrayal by his partners. But in the end, I chose to make peace with life and devote myself to charity. From academic career to lenient students, I explored the true meaning of destiny in the ups and downs, and experience itself was the meaning. As Thorp said at the end of his autobiography: Life is like reading a novel or running a marathon. Reaching the finish line is often not so important, but the journey itself and the experience along the way are more precious.<b>You have dance.</b></p>","source":"lsy1625911325017","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>Thorpe and Simmons: The legendary lives of two godfather investment tycoons</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\">\nThorpe and Simmons: The legendary lives of two godfather investment tycoons\n</h2>\n<h4 class=\"meta\">\n<p class=\"head\">\n<strong class=\"h-name small\">SMARTMATRIX</strong><span class=\"h-time small\">2021-07-10 17:56</span>\n</p>\n</h4>\n</header>\n<article>\n<p>A Man for All Markets is the personal biography of Edward Thorp, the Chinese translation of \"The Man Who Beat All Markets\". Judging from Thorp's experience, from defeating casinos to entering Wall Street, OTC options, convertible bonds, stocks, futures and other derivatives, all Dabbled in, worthy of the name All Markets. Taleb says in the preface that his memoir reads like a thriller.</p><p>As a mathematical genius and the godfather of quantitative investment, he pioneered the introduction of probability theory, information theory, and computer programming into financial transactions, which influenced countless Quant bosses in later generations: Bill Gross, David Shaw, Ken Griffin... including the famous James Simons, whose Renaissance Technology company created the myth of the rate of return in financial history. Similarly, Simons' biography The Man Who Solved The Market records in detail the ups and downs of his and his team's conquest of the financial market.</p><p><b>Academic origin</b></p><p>When culture flourishes, people are outstanding. The so-called outstanding people, such as the Huxiang School since the late Ming Dynasty in China, made Hunan the cradle of revolutionaries. In the academic circle, there is a similar phenomenon. If you study the backgrounds of the two bosses carefully, you will find a lot in common. They were both born in the 1930s. They were gifted since childhood, in the academic circle, but they were all dedicated to money. They have two common alma maters: the University of California, Berkeley and MIT. The academics of both universities reached their peak after the war. One of the main reasons was the large-scale military scientific research activities (the famous Manhattan Project, cryptography, information theory and modern computers) spawned by World War II. Both Thorp and Simons happened to catch up with this wave of academic dividends. In the 1950s, Thorp was obsessed with studying roulette with Shannon, while Simons was still immersed in theoretical mathematics, which also made his academic achievements higher (Chern-Simons Theroy). In the 1960s, MIT became the center of the computer revolution, and mathematics and computers were the two keys to Wall Street, and Thorp was the lucky one to hold these two keys.</p><p><b>Casinos vs Wall Street</b></p><p>The popular story nowadays is that Thorp defeated the casino by using the law of large numbers and Kelly's formula, and he became the first person in history to be \"blacked out\" by Las Vegas casinos. By contrast, the hedge fund he founded, PNP (Princeton Newport Partners), has a dim profile. In fact, from 1969 to 1988, the annualized returns of the two PNP funds reached 19.1% and 15.1% respectively, while the average annual growth rate of the S&P index during the same period was 10.2%. In the past 19 years, after two oil crises in the 1970s and the stock market crash in 1987, the two funds have never suffered a single-quarter loss, let alone an annual loss. In the world's largest casino, its performance is unparalleled, and its investment model is 20 years ahead of the wide customers who have filed into Wall Street since then.</p><p>In 1988, Thorp's fund was forced to close because it was implicated in the case of Milken, the king of junk bonds. It was in this year that Simons established the Medallion Fund. He is over 500 years old and can be described as a late bloomer. Before that, he had been groping for 10 years to find a successful investment model, and had been swinging between subjective and quantitative. Although the outside world has always regarded Simons as a master of quantitative investment, in fact, his role is completely different from Thorp's. His main job is not to develop quantitative models, but to dig all kinds of scientists from the academic circle to help the company develop quantitative models, and shape the company's corporate culture as a spiritual leader. As a world-class mathematician + excellent sales, he can deal with different people well, which is a rare ability.</p><p><b>The road to quantification</b></p><p>As a pioneer in quantitative trading, Thorp is good at hedging and arbitrage of various derivatives. The bear market and volatility in the 1970s made this strategy work perfectly. Relying on his mathematical talent and market sense, he discovered new blue oceans: Statistical Arbitrage and factor models-early quant prototypes. The risk under this model is theoretically infinite, especially the upper limit of losses for shorting those overvalued stocks is infinite. Thorp's main risk control strategy is diversified investment. Since then, LTCM has adopted a similar arbitrage model, but lacked a risk control strategy like Thorp and was defeated by the black swan. In order to improve investment efficiency, Thorp turned investment strategies into programs and once again became a pioneer in programmatic trading (Algorithm Trading).</p><p>Simons, in contrast, was less lucky. From early attempts at intuitive investing to trend-based momentum trading, reversal trading to continuous collection and mining of massive amounts of data, including data cleaning, signal mechanism and backtesting. In 1986, the model framework for identifying hidden price trends was used-in 1989, abnormal trading signals were used for short-term high-frequency trading-in 1992, it was changed to only a single model (key breakthrough), and then speech recognition experts helped make various technological breakthroughs (financial models have similarities with speech recognition), and the model has gone through a long process of iterative improvement. In the end, the important core competence of the model was developed: identifying the \"value of transactions\", including: the certainty of price trends, the weight trade-off between trading signals, and the judgment of the impact of trading based on signals on the market. This capability is particularly important for high-frequency full-variety trading.</p><p><b>Winning System: Probabilistic Thinking & Modeling Human Behavior</b></p><p>For Thorp, gambling and investment are games based on probability statistics, and the bet amount is allocated according to the winning percentage (fund management based on Kelly's law). The first major breakthrough of Medallion Fund also comes from the application of Kelly's law and shortening the trading frequency to make its trading more reflective of the law of large numbers. Medallion's system can make money as long as the winning rate is slightly above 50%, regardless of the profit or loss of every sale. Essentially, it is making money by taking advantage of the omissions and mistakes of other traders (market ineffectiveness). Humans are highly predictable in their behavior under high pressure, and they instinctively show panic. The premise of modeling is that humans will constantly repeat past behaviors. Soros once modeled human behavior with the philosophical theory of reflexivity, while Simons's team used data and algorithms to model human behavior to confirm the theory of behavioral finance.</p><p>Unlike traditional value investing, which simplifies the market into a market gentleman, the experience of quantitative investing is that there are far more factors and variables that affect financial markets and investments than most people realize, and the factors that lead to market ineffectiveness can even be said to be encrypted (Thorp spares no effort to refute the efficient market hypothesis in his book). Investors try to find the most basic driving factors, but what they are missing may be an entire dimension of information. Medallion Fund can't explain the logic behind every profit law, just as human beings can't understand Alpha Go, perhaps it exists at a higher latitude.</p><p>Models are abstractions and simplifications of the world, but models are not omnipotent. When data and desire conflict, even rational scientists cannot be completely rational. Simons' original intention was to create an algorithm-driven automatic trading system, which completely shielded human subjective judgment. However, in every crisis, he still couldn't help but intervene manually to reduce his dependence on signals and actively reduce his trading position. The results of the intervention were not very ideal. His colleague Patterson also said: \"<b>Never put too much trust in trading models. The basic mistake of LTCMs is to believe that the model is the truth. We never believe that our model can reflect the whole fact, it only reflects some of it</b>。”</p><p><b>Wide guest student</b></p><p>In fact, the intersection of many big guys is far beyond our imagination. For example, Thorp and Buffett played at the bridge table. After confirming that Buffett would eventually become the richest man in the United States, they decisively invested in BRK stock. Many people think that Xueba may not necessarily have a good life. After all, there is a huge gap between book smart and street smart, and the rules of the real world are much more complicated than those of schools. However, Thorp has practiced the way of thinking of applying abstract thinking to real life, which truly explains that \"a tough life doesn't need to be explained\". Academics, wealth and family are perfect, and he realized early that life itself is higher than making money. Compared with Thorp's splendid life, Simons's life has too many twists and turns. He is divorced, his two sons have suffered misfortune and betrayal by his partners. But in the end, I chose to make peace with life and devote myself to charity. From academic career to lenient students, I explored the true meaning of destiny in the ups and downs, and experience itself was the meaning. As Thorp said at the end of his autobiography: Life is like reading a novel or running a marathon. Reaching the finish line is often not so important, but the journey itself and the experience along the way are more precious.<b>You have dance.</b></p>\n<div class=\"bt-text\">\n\n\n<p> source：<a href=\"https://mp.weixin.qq.com/s/g5Zdx-uS3wl9QbsHZm1DVw\">SMARTMATRIX</a></p>\n\n\n</div>\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"https://static.tigerbbs.com/388d882133df2db2363aa871ff756c47","relate_stocks":{".DJI":"道琼斯"},"source_url":"https://mp.weixin.qq.com/s/g5Zdx-uS3wl9QbsHZm1DVw","is_english":false,"share_image_url":"https://static.laohu8.com/e9f99090a1c2ed51c021029395664489","article_id":"1124741749","content_text":"A Man for All Markets是Edward Thorp的个人传记，中文翻译《战胜一切市场的人》，从Thorp的经历来看，从打败赌场到进入华尔街，OTC期权、可转债、股票、期货等衍生品，全部涉猎，名副其实的All Markets。塔勒布在序言里说，他的回忆录读起来像一部惊悚小说。\n作为一个数学天才、量化投资教父级人物，他开创性的将概率论、信息论、计算机编程引入金融交易，影响了后世无数Quant大佬：Bill Gross、David Shaw、Ken Griffin...其中也包括大名鼎鼎的James Simons，后者的文艺复兴科技公司创造了金融史上的回报率神话，同样，讲述Simons的传记The Man Who Solved The Market，详细记录了他和他的团队征服金融市场的起起落落，虽是一位华尔街日报作家根据采访汇编而成，但其中不少以前从未披露过的精彩故事。\n学术源流\n文化兴，则人杰出，所谓的人杰地灵，比如中国明末以来的湖湘学派让湖南成为革命党人的摇篮。在学术圈，也有类似的现象。仔细研究两位大佬的背景，会发现很多共通点，他们都出生于30年代，自幼天赋异禀、身在学术圈但都一心向钱，有两个共同的母校：加州大学伯克利分校和MIT。两校的学术在战后都达到了巅峰，主要一个原因就是二战催生的大规军事科研活动（著名的曼哈顿计划、密码学、信息论和现代计算机），Thorp和Simons都恰好赶上了这波学术红利。50年代，Thorp醉心于和香农一起研究轮盘赌，而Simons仍埋头于理论数学问题，这也使得其在学术上的成就更高（Chern-Simons Theroy）。60年代，MIT成为计算机革命的中心，而数学和计算机正是通向华尔街的两把钥匙，Thorp正是手握这两把钥匙的幸运儿。\n赌场vs华尔街\n如今为人津津乐道的故事是Thorp利用大数定律和凯利公式打败了赌场，他也成了历史上第一个被拉斯维加斯赌场“拉黑”的人。相比之下，他创设的对冲基金PNP（Princeton Newport Partners）知名度黯淡不少。实际上，从1969年到1988年，PNP两支基金的年化收益率分别达到19.1%和15.1%，同期标普指数年均增长率为10.2%。19年间历经70年代两次石油危机、87年股灾，两只基金从未发生单季亏损，更没有年度亏损。在世间最大的赌场，其业绩冠绝其时，其投资模式，领先此后鱼贯进入华尔街的宽客们20年。\n1988年，Thorp的基金因为受到垃圾债券之王米尔肯一案的牵连被迫关闭。正是在这一年，Simons成立大奖章基金，已年过半百的他，可谓大器晚成，在此前为了寻找成功的投资模型已经摸索了10年之久，一直在主观和量化之间摇摆。尽管外界一直都把Simons视作量化投资大师，但实际上他点角色和Thorp完全不同，他的主要工作并不是开发量化模型，而是从学术圈挖掘各类科学家来帮助公司开发量化模型，并且作为精神领袖塑造公司企业文化。作为一名世界级的数学家+卓越的销售，他与不同的人都能融洽的打交道，这是一种罕见的能力。\n量化之路\n作为量化交易的先驱，Thorp擅长各种衍生品的对冲套利，70年代的熊市和波动率让这种策略运行的非常完美。依靠自己的数学天赋和市场嗅觉发现了新的蓝海：统计套利（Statistical Arbitrage）和因子模型（factors model）——早期的quant原型。这种模式下的风险理论上是无穷的，尤其是做空那些价格高估的股票的损失上限是无穷大，Thorp主要风控策略是分散化投资。此后的LTCM采用类似的套利模式，但缺少Thorp这样的风控策略，被黑天鹅击败。为了提升投资效率，Thorp将投资策略变成程序，再次成为程序化交易（Algorithm Trading）的先驱。\n相比之下，Simons就没那么幸运了。从早期尝试直觉投资到基于趋势的动量交易、反转交易再到持续收集挖掘海量数据包括数据清洗、信号机制和回溯测试。1986年使用识别隐藏价格趋势的模型框架——1989年利用异常交易信号进行短期高频交易——1992年改为只用单一模型（关键性突破），而后语音识别专家帮助进行各种技术突破（金融模型与语音识别有相似之处），模型经历了漫长迭代改进的过程。最终练就了模型重要核心能力：识别出“交易的价值”，包括：价格趋势的确定性大小、交易信号之间的权重取舍、根据信号进行交易对市场造成的影响的判断。这项能力对于高频全品种交易尤为重要。\n取胜系统：概率思考&对人类行为建模\n对Thorp来说，赌博和投资都是以概率统计为基础的游戏，根据胜率的大小来分配下注金额的大小（基于凯利法则的资金管理），而大奖章基金的第一次重大突破也来自于对凯利法则的运用以及缩短交易频率使其交易更体现大数定律。大奖章的系统只要胜率略高于50%就能赚钱，而不在乎每一笔买卖的盈亏。本质上，是在利用其他交易者的疏忽和错误赚钱（市场无效）。人类在高压下的行为具有很高的可预测性，他们会本能地表现出恐慌。建模的前提是人类会不断重复过去的行为。索罗斯曾以反身性的哲学理论对人类行为建模，而Simons的团队利用数据和算法对人类行为建模，以此印证行为金融学的理论。\n与传统的价值投资把市场面简化成一位市场先生不同，量化投资的经验是，影响金融市场和投资的因素和变量远远比大多数人意识到的更多，导致市场无效的因素甚至可以说是加密的（Thorp在书中对有效市场假说也不遗余力的进行驳斥）。投资者努力寻找最基本的推动因素，但是遗漏的也许是一整个维度的信息。大奖章基金无法对每一条盈利的规律背后的逻辑进行解释，就如同人类无法理解阿尔法围棋一样，也许是更高纬度的存在。\n模型是对世界的抽象和简化，但模型并不是万能的。当数据和欲望相冲突，即便是理性的科学家，也无法做到完全理性。Simons的初心是创建的算法驱动的自动交易系统，完全屏蔽人类的主观判断，但每一次危机，他仍忍不住会手动干预，减少对信号的依赖，主动缩减交易头寸，可干预的结果并不十分理想。他的同事帕特森也说：”永远不要对交易模型过于信任。长期资本管理公司的基本错误是认为模型就是事实真相，我们从未相信我们的模型能够反映全部事实，它只反映事实的一部分。”\n宽客人生\n其实很多大佬的交集，远远超过我们想象。比如Thorp和巴菲特在桥牌桌上过过招，在确认巴菲特最终会成为全美最富有的人之后，果断投资了BRK的股票。很多人以为，学霸不一定会拥有好人生，毕竟，book smart和street smart之间的有极大的鸿沟，现实世界的规则比学校要复杂太多，但Thorp践行了将抽象思维运用到现实生活中的思维方式，真正诠释了“彪悍的人生不需要解释”，学术、财富、家庭圆满，很早就意识到在生活本身高于赚钱。相比较Thorp精彩纷呈的人生，Simons的人生曲折太多，离过婚，他的两个儿子先后遭受不幸，还遭遇过伙伴背叛。但最终还是选择和生活讲和，并投身慈善事业，从学术生涯到宽客人生，在跌宕起伏中探寻命运的真谛，而经历本身就是意义所在。就像Thorp在自传末尾所说：生活像是读一本小说或者跑一场马拉松，到达终点往往不是那么重要，旅途本身和沿途的体验更为珍贵。No body can take away the dance you have danced.","news_type":1,"symbols_score_info":{".DJI":0.9}},"isVote":1,"tweetType":1,"viewCount":837,"authorTweetTopStatus":1,"verified":2,"comments":[],"imageCount":0,"langContent":"EN","totalScore":0}],"lives":[]}
