Last Updated on 24 November, 2021 by Samuelsson

The existence of the momentum factor effects in stocks is an anomaly, which various finance theories, such as the Capital Asset Pricing Model (CAPM), the Arbitrage Pricing Theory, and the Fama-French Three-Factor Model, struggle to explain. According to the efficient-market hypothesis, stock price increases or decreases based on demand and supply imbalance, but that is not the case with the momentum anomaly.

In fact, the anomaly is acknowledged by academics, and smart investors use it and its modifications to create strategies that beat the market. Interestingly, momentum strategies are easy to implement. In this post, we will explore what academics have to say about the momentum factor effect in stocks, but first, let’s find out what it means.

What does the momentum anomaly mean?

In the stock market, the momentum anomaly is a term used to describe the tendency for rising stocks to keep rising and falling ones to keep falling, at least for the foreseeable future. Momentum itself refers to the rate of change of a stock’s price in any direction — that is, the inertia of a price to remain in a trend (either rising or falling) for a particular length of time.

Basically, momentum trading is a trend-following strategy that seeks to enter a trade when the trend is picking up steam. Investors who follow this strategy aim to buy stocks that are rising and sell them when they look to have peaked or are no longer rising. This is because there is a tendency for stocks that have performed well in the past would continue to perform well while stocks that have performed poorly in the past would continue to perform badly.

Buying past winners and selling past losers have been proven to be a profitable strategy in the U.S. stock market, as well as other stock markets. The idea is to rank stocks based on their n-month returns and then buy and hold the stocks with the strongest momentum for x months. While investors can choose any period for their n and x, 12-month momentum and 1-month holding period seem to be very popular.

Academic research has shown that the momentum effect works in stock markets of both developed countries and emerging economies, and it seems to work for both small-cap and large-cap stocks.

Understanding why the momentum factor effect works in stocks

The momentum factor effect has been well-researched over the years, and we want to show you some of the research findings.

Research findings

Perhaps, the oldest and most well-known paper about the momentum anomaly is “Momentum” by Jagadeesh and Titman. Published in 1993, the authors established substantial evidence that stocks that perform the best (worst) over a 3 to 12-month period tend to continue to perform well (poorly) over the subsequent 3 to 12 months. They also showed that stocks with high earnings momentum outperform stocks with low earnings momentum.

Since then, momentum trading strategies that exploit this phenomenon have been consistently profitable in the U.S. markets, as well as most developed markets. However, in the “Momentum (2011 version)”, the authors noted some hiccups in the pure momentum strategy in recent times but also acknowledged that the long-only strategy still works, as stocks with high earnings momentum outperform stocks with low earnings momentum.

In reviewing the works of Jegadeesh and Titman, as well as those of other authors on the momentum topic, Asness, Frazzini, Israel, and Moskowitz in “Fact, Fiction, and Momentum Investing” attempted to clear up much of the confusion about the momentum effect by documenting their findings and disproving many of the often-repeated myths. They highlighted ten myths about momentum and refuted them using results from widely circulated academic papers and analysis from the simplest and best publicly available data.

Similarly, Landis and Skouras in “Momentum Is Higher than We Think” evaluated the momentum factor on international markets based on data from Thompson Datastream. Using a completely altered and corrected daily database from 52 International markets — covering more than 50,000 common stocks — from TDS, they re-examined previous empirical work on International Momentum and found consistently higher momentum returns for the majority of markets and regions of their sample. We established evidence that data outliers create a “Pseudo-Reversal effect” in international Winner minus Loser profits, leading to the overestimation of premiums of loser portfolios and the underestimation of the profits of the momentum strategies. In addition, they reviewed International Momentum premiums from 1964 to 2010 for all markets and regions of their sample and found that momentum continues to be strong in the majority of individual markets and all in regions except Japan.

Considering the effects of trading costs on the strategy, Korajczyk and Sadka in “Are Momentum Profits Robust to Trading Costs?” tested whether momentum-based strategies remain profitable after considering market frictions. They estimated the alternative measures of price impact and applied them to alternative momentum-based trading rules and also evaluated the performance of traditional momentum strategies, as well as strategies designed to reduce the cost of trades. They found that after taking into account the price impact induced by trades, as much as 5 billion dollars may be invested in some momentum-based strategies before the apparent profit opportunities vanish. However, they noted that other extensively studied momentum strategies may not implementable on a large scale.

Also looking at cost, Li, Brooks, and Miffre in “Low-Cost Momentum Strategies” analyzed the impact of trading costs on the profitability of momentum strategies in the UK and concluded that losers are more expensive to trade than winners. According to the authors, the observed asymmetry in the costs of trading winners and losers crucially relates to the high cost of selling loser stocks with small size and low trading volume. Since transaction costs severely impact net momentum profits, they proposed a new low-cost relative-strength strategy, which involves shortlisting from all winner and loser stocks those with the lowest total transaction costs. The study severely questions the profitability of standard momentum strategies, but still concludes that there is still room for momentum-based return enhancement.

Perhaps, what is even more concerning is that, according to data from Kenneth French library, the pure momentum strategy whereby an investor goes long on stocks with the strongest momentum and shorts stocks with the lowest momentum recorded more than 80% drawdown in 2009. However, it has been found that the momentum factor still works well with a long-only strategy — buying stocks with the strongest momentum without shorting the low momentum stocks. In the “Global Momentum Strategies: A Portfolio Perspective“, Griffin, Ji, and Martin found that momentum is generally more profitable on the long side than on the short side and that both price and earnings momentum profits are significant globally.

On the aspect of risk management, Barroso and Santa-Clara in “Managing the Risk of Momentum“ found that compared to the market, value, or size risk factors, momentum has offered investors the highest Sharpe ratio. Noting the impact of the terrible momentum crashes on investors with reasonable risk aversion, they found that the risk of momentum is highly variable over time and can be quite predictable; however, the major source of predictability does not come from systematic risk but specific risk. The authors maintained that managing this time-varying risk virtually eliminates crashes and nearly doubles the Sharpe ratio of the momentum strategy.

Interestingly, the momentum appears to be quite tax-effective, according to Israel and Moskowitz in “How Tax Efficient are Equity Styles?“. The authors discovered that on an after-tax basis, value and momentum portfolios outperform, while growth underperforms, the market. They found that momentum, despite its higher turnover, is often more tax-efficient than value, because it generates substantial short-term losses and lower dividend income. According to them, while ax optimization improves the returns to all equity styles — with the biggest improvements accruing to value and momentum styles — only momentum allows significant tax minimization without incurring significant style drift.”

The explanations

By and large, most academic research shows the existence of the momentum factor effect, but the explanations differ. But the most common explanations for the persistence of the momentum effect are investors’ overreaction and underreaction, confirmation and other cognitive biases, and herd mentality (especially fear of missing out or FOMO). In other words, that investors are presumed to be irrational in the way they react to new information. However, much as in the case of price bubbles, other researchers — such as Crombez in “Momentum, Rational Agents and Efficient Markets” — have argued that momentum can be observed even with perfectly rational traders.

There are also other explanations. For example, Rachwalski and Wen in “Momentum, Risk, and Underreaction” stated that momentum profits can be explained by exposure to risks omitted from common factor models and underreaction to innovations in these omitted risks. Quoting the authors, “Consistent with risk as a partial explanation of momentum profits, long formation period momentum strategies earn higher returns and are more highly correlated with factors designed to measure risk than short formation period momentum strategies.”

Also, in “Momentum and Funding Conditions”, Garcia-Feijoo, Jensen, and Jensen found strong evidence linking the momentum pattern in equity returns with a prominent measure of macroeconomic conditions — specifically the funding environment. They found that the size and consistency of the momentum premium vary systematically across funding states, and there’s evidence that the relationship between momentum returns and firm characteristics (documented in previous research) is conditional on the funding environment. The authors found that, after controlling for the funding state, the importance of market states and return dispersion disappears, and even after adjusting for the influence of market states and return dispersion, funding conditions appear to contain incremental information about the momentum premium. By and large, their results are consistent with the idea that transitions in the funding environment encourage investors to revise their portfolio allocations and, by doing so, produce inter-temporal variation in the momentum return pattern.

Another explanation is offered by Israel and Moskowitz in “The Role of Shorting, Firm Size, and Time on Market Anomalies.” The authors examined the role of shorting, firm size, and time on the profitability of size, value, and momentum strategies. Quoting the authors: “We find that long positions comprise almost all of the size, 60% of value, and half of the momentum profits. Shorting becomes less important for momentum and more important for value as firm size decreases. The value premium decreases with firm size and is weak among the largest stocks. Momentum profits, however, exhibit no reliable relation with size. These effects are robust over 86 years of U.S. equity data and almost 40 years of data across four international equity markets and five asset classes. Variation over time and across markets of these effects is consistent with random chance. We find little evidence that size, value, and momentum returns are significantly affected by changes in trading costs or institutional and hedge fund ownership over time.”

Lastly, Cakici and Tan in “Size, Value, and Momentum in Developed Country Equity Returns: Macroeconomic and Liquidity Exposures” investigated value and momentum factors in 23 developed international stock markets and found that value and momentum premia are typically smaller and more negatively correlated for large market capitalization stocks relative to small; momentum factors are more highly correlated internationally relative to value. They sought international evidence on three sets of risk exposures of value and momentum returns — macroeconomic risk, funding liquidity risk, and stock market liquidity risk — and found that value returns are typically lower before a recession while momentum returns often exhibit little sensitivity. While value returns are typically lower in times of poor funding liquidity, with notable exceptions, momentum returns are typically unaffected. Also, for almost all countries, value returns are high in poor stock market liquidity conditions.

How to apply the momentum strategy in your trading

From our discussions so far, the best approach is to use the long-only momentum strategy. To apply this strategy, follow these steps:

  1. Create an investment universe of stocks on U.S. stock exchanges (NYSE, AMEX, and NASDAQ).
  2. Rank the stocks according to their 12-month performance (subtract the most recent month’s return to avoid the influence of the short-term reversal effect).
  3. Go long on the top 5 stocks with the best 12– month performance.
  4. Rebalance your portfolio every month by selling any of the 5 stocks that dropped from the top 5 and using the fund to buy the ones that replaced them in the ranking.

Why the momentum strategy doesn’t work in bear markets

Both the pure momentum strategy (both long and short portfolios) and the long-only momentum strategy don’t work so well in bear markets, especially when the market rebounds following previous large declines. This has been linked to the time-varying systematic risk of the momentum strategy, as momentum has significant negative beta following bear markets.

Read More: Currency Momentum Factor

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