As a group of mathematicians and physicists entered Wall Street since the 1980s, quantitative investment strategies have gradually become the fad. The successful icons of this move were Jim Simons' Renaissance Technologies and D.E. Shaw's eponymous quant fund. This shift led to the increasing desertion and skepticism toward qualitative strategies, a trend that closely aligns with what I observed during my tenure on Wall Street, intermingling with various institutions.
Of all quant strategies, a widely favored and easy-to-implement framework is the multi-factor strategy. This approach simply extracts/mining various factors from a factor zoo and uses back testing to determine their efficacy and weights.
However, in an era where factors are becoming crowded, multi-factor strategies have undoubtedly fallen into a game-theory trap. As a result, the effectiveness of many factors has quickly diminished, with their functioning windows shrinking.
The best-performing stocks of 2024 and the factors they are exposed to.
In 2024, although leading AI stocks continued to perform, we found that S&P 500 stocks gaining the most were AppLovin Corp. (APP), NuScale Power Corp. (SMR), Root Inc. (ROOT), and Longboard Pharmaceuticals Inc. (LBPH).
From a factor-level breakdown, we observe that
Equity momentum was the most notable factor this year, far outperforming the value factor. This means that qualitative value investing is likely underperformed the market this year. On the other hand, institutions holding momentum stocks—beside the four mentioned above—also profited from owning big-winners such as Amazon, Nvidia, Tesla, and Google. These “Magnificent Seven” were the clear standouts of the year.
Early this year, many buy-side managers publicly voiced concerns about the U.S. stock market, especially the Mag 7, their arguments are primarily based on valuation parameter. As a result, many of these fund managers have underperformed the S&P 500. In this context, using quantitative models to support subjective decision-making can help correct certain biases and errors in human judgment.
But is the quantitative factor strategy flawless?
In fact, when we delve deeper, we find that since the U.S. stock market entered Q3/Q4, especially after the November elections, there has been a significant shift in efficacious factors. This shift is manifested as the following:
★ Momentum Factor Weakening: The momentum of many stocks that surged in the first half of the year gradually faded, even if their upward trend remained. This is particularly evident in once fore-running stocks excluding BTC and micro-cap speculative sectors.
★ Value Factor Effectiveness Increased in the Second Half of this year: (See the chart below)
★ Short Squeeze Factor Contribution: The impact of the short squeeze factor increased, which is also why we are seeing ascent slopes in many high-flying stocks recently.
★ Interesting Trend: The R-vol factor, which has gained popularity in recent years, became the leading factor from November.
★ Declining Appeal of Large-Cap Stocks: The attractiveness of large-cap stocks has also gradually diminished, which aligns with the momentum characteristics of mega-cap stocks.
So, what can we infer from these phenomena?
1. Valuation factors are gradually reverting to mean: In the long run, value/quality factors are bound to follow a reversion pattern or Pendulum Effect. (Buffett can rest assured.)
2. Institutions adhering to a specific Strategy (e.g., Momentum Strategy) could easily go from stardom to sluggishness: From the perspective of the emerging market, this can be likened to the experience of some renowned investors (or "big players"): the performance deterioration of certain prominent investors and fund managers often reflect the outdated nature of their rigid strategy and cognitive frameworks.
3. At Certain Time Periods, speculative products indeed exhibited excess return: At times, speculative/meme-like factors can outperform, providing remarkable returns.
Subjective Strategies Are Still Worth Looking Forward To
Overall, subjective funds with consistent value and growth philosophies have long life expectancy, even though they may underperform the market during certain periods. Clearly, value funds did perform poorly in the past 12 months, but over the long term, we will see the catching-up of value factors.
On the other hand, quantitative multi-factor strategies, if lacking high sensitivity, struggle to outperform the market across different cycles. The timely and rapid recalibration of factors often requires human intervention. From this perspective, even arbitrage and smart beta strategies are still heavily reliant on subjective insights.
In simpler terms, in today’s global market, quantitative and qualitative strategies must be integrated and intertwined. Subjective strategies, in the medium to short term, cannot do without dynamic benchmarks derived from data analysis. Quantitative strategies, meanwhile, depend on individuals with innate talents, like Jim Simons, who have a gifted understanding to market behaviors. These cannot be resolved by simple, direct mathematical formulas packed by Greek letters. In today’s factor-crowded environment, the mechanical application of these models has been diminished. This is also why, after Simons' passing, concerns have grown about the sustainability of Renaissance Technologies' performance.
Some successful quantitative or hedge funds, such as AQR and Citadel, now combine value measurements with mathematical models, achieving extraordinary results. Firms like Bridgewater, with their diversified portfolio approach and combination of quantitative and subjective strategies, have earned respect from many domestic institutions.
(As for how to improve strategy sensitivity and allocation efficiency, the investment clock can provide considerable reference value at present. We look forward to discussing the specifics in the future. Forb Research’s strategy, for example, integrates quantitative models and investment clock sensitivity to investment cycles, using this as the foundation for asset selection and allocation.)
There may be friends from the quantitative industry who disagree with us, and we welcome the battle and debate.
As for Technical Analysis-Based Investing
Finally, can technical tools like MACD, Bollinger Bands, and the Turtle Trading method still be useful? Many of our friends participate in various technical analysis courses, and many live streams and videos are centered around technical analysis. Forb Research will utilize extensive back testing data for a special discussion on technical analysis in the near future. This discussion might challenge some individual investors’ beliefs.
$Tesla Motors(TSLA)$ $Palantir Technologies Inc.(PLTR)$ $NVIDIA(NVDA)$ $Broadcom(AVGO)$ $PayPal(PYPL)$
Comments