Momentum Factor Effect in Stocks - QuantPedia (2024)

Momentum Factor Effect in Stocks

Nowadays, momentum strategies are well-known and generally accepted in both the public and academic worlds. Yet, the momentum strategy is based on a simple idea, the theory about momentum states that stocks which have performed well in the past would continue to perform well. On the other hand, stocks which have performed poorly in the past would continue to perform badly. This results in a profitable but straightforward strategy of buying past winners and selling past losers. Moreover, the strategy selects stocks based on returns over the past J months. It holds them for K months, the selection of J and K is purely dependent on the choice of the investor, but we are presenting results of 12-1 month momentum strategy. To sum it up, the stocks which have outperformed peers during the K months period tends to perform well in the upcoming period and vice versa.
Additionally, momentum strategies are also profitable outside the United States. Academic research proved that this effect works in stock markets in other developed countries and also in emerging markets. Moreover, the momentum effect works in a small-cap universe as well as in a large-cap universe, and it is safe to say that momentum is one of the most academically investigated effects with strong persistence. Pure momentum portfolios are created in a way that investor longs stocks with the strongest momentum and shorts stocks with the lowest momentum. However, this pure momentum portfolio recorded the disastrous year 2009 with more than 80% drawdown (data from Kenneth French library). Despite the crash, the momentum factor is still a strong performance contributor in long-only portfolios (long stocks with the strongest momentum without shorting the market or low momentum stocks). This supports, for example, Griffin, Ji, and Martin in the “Global Momentum Strategies: A Portfolio Perspective“. The authors have found that momentum is generally more profitable on the long side than on the short side, making it accessible to a broad range of institutional capital. Additionally, both price and earnings momentum profits are significant globally.
An interesting point of view on this topic have Barroso and Santa-Clara in their work “Managing the Risk of Momentum“. Quoting the authors: “Compared to the market, value or size risk factors, momentum has offered investors the highest Sharpe ratio. However, momentum has also had the worst crashes, making the strategy unappealing to investors with reasonable risk aversion. We find that the risk of momentum is highly variable over time and quite predictable. The major source of predictability does not come from systematic risk but specific risk. Managing this time-varying risk eliminates crashes and nearly doubles the Sharpe ratio of the momentum strategy.”
The oldest and most well-known paper about this topic is by Jagadeesh and Titman. We decided to draw data from newer research for more updated information.

* For those interested in systematic quantitative momentum factor ETF implementation, here is a link to the Alpha Architect Quantitative Momentum ETF (strategy background), our partner. *

Fundamental reason

Overall, academic research shows strong support for the momentum effect. The most common explanations and probably the main reasons for the persistence of the momentum anomaly are behavioral biases like investor herding, investor over and underreaction, and lastly, the confirmation bias. For example, if a firm releases good news and the stock price reacts only partially to the good news, then buying the stock after the initial release of the news will generate profits.
Rachwalski and Wen in the “Momentum, Risk and Underreaction” state that momentum profits can be explained by exposure to risks omitted from common factor models and underreaction to innovations in these omitted risks. Consistent with risk as a partial explanation of momentum profits, long formation period momentum strategies earn higher returns. They are more highly correlated with factors designed to measure risk than short formation period momentum strategies.
Interestingly, the momentum appears to be quite tax-effective, as it was found in the work of Israel and Moskowitz: “How Tax Efficient are Equity Styles?“. Quoting the authors: “On an after-tax basis, value and momentum portfolios outperform, and growth underperforms the market. We find that momentum, despite its higher turnover, is often more tax-efficient than value, because it generates substantial short-term losses and lower dividend income. Tax optimization improves the returns to all equity styles, with the biggest improvements accruing to value and momentum styles. However, the only momentum allows significant tax minimization without incurring significant style drift.”

Keywordsfactor investingmomentummomentum in stockssmart betastock picking

Simple trading strategy

The investment universe consists of NYSE, AMEX, and NASDAQ stocks. We define momentum as the past 12-month return, skipping the most recent month’s return (to avoid microstructure and liquidity biases). To capture “momentum”, UMD portfolio goes long stocks that have high relative past one-year returns and short stocks that have low relative past one-year returns.

Hedge for stocks during bear markets

No - Pure long-only equity momentum strategy implicitly can’t be used as a hedge. The long-short equity momentum factor is also a troublesome for hedging as a momentum factor is prone to “momentum crashes”. Equity momentum factor performs well during the first stages of crises (as it usually shorts stocks with strong downward momentum and buys stocks which are not falling fast). Momentum crashes usually occurred right as the market rebounded following previous large declines. One explanation for this pattern is the time-varying systematic risk of the momentum strategy because momentum has significant negative beta following bear markets. Numerous amended versions of the basic momentum strategy appeared after the 2008 bear market. These adjusted strategies may offer a better hedge against equity market risk.

Source paper

Out-of-sample strategy's implementation/validation in QuantConnect's framework (chart+statistics+code)

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