The momentum anomaly is one of the strongest and oldest academically described anomalies. However, is it easily exploitable?
Academic research usually uses portfolios filled by thousands of stocks to compute momentum factor returns. But this is not possible for small retail investors with small portfolios. They are constrained compared to big hedge funds and cannot diversify so well. Recent academic research shows that a small portfolio is not a problem in momentum investing. The momentum effect could be easily captured even with a portfolio consisting of up to 50 stocks.
Academic studies show strong support for momentum effects. The main reasons for anomaly persistence are behavioral biases like investor herding, investor over and underreaction, and confirmation bias. Another natural interpretation of momentum profits is that stocks underreact to information. For example, if a firm releases good news, and the stock price only reacts partially to the good news, then buying the stock after the initial release of the news will generate profits.
Confidence in anomaly's validity
Backtest period from source paper
Notes to Confidence in Anomaly's Validity
Period of Rebalancing
Notes to Indicative Performance
net return per annum, annualized (geometrically) monthly return 2.34%, data from table 6 assuming 10 000 pounds in a portfolio and 10 stocks long/short, return could be enhanced by lowering number of stocks in a portfolio or by having more money (lower impact of fees)
Notes to Period of Rebalancing
Number of Traded Instruments
Notes to Estimated Volatility
Notes to Number of Traded Instruments
Notes to Maximum drawdown
Notes to Complexity Evaluation
Simple trading strategy
The investment universe consists of all UK listed companies (this is the investment universe used in the source academic study, and it could be easily changed into any other market – see Ammann, Moellenbeck, Schmid: Feasible Momentum Strategies in the US Stock Market). Stocks with the lowest market capitalization (25% of the universe) are excluded due to liquidity reasons. Momentum profits are calculated by ranking companies on the basis of their stock market performance over the previous 12 months (the rank period). The investor goes long in the 10 stocks with the highest performance and goes short in the 10 stocks with the lowest performance. The portfolio is equally weighted and rebalanced yearly. We assume the investor has an account size of 10 000 pounds.
Hedge for stocks during bear markets
No - Pure long only equity momementum strategy implicitly can’t be used as a hedge. 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 first stages of crises (as it usually shorts stocks with astrong downward momemtum and buys stocks which are not falling fast). Momentum crashes usually occurred right as the market rebounded following large previous 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 basic momentum strategy appeared after 2008 bear market. These adjusted strategies may offer better hedge against equity market risk.
Siganos: Can small investors exploit the momentum effect?
This study uses U.K. data and investigates whether small investors can exploit the continuation effect in share prices. Individual traders are not in a financial position to buy and sell short hundreds of firms, as suggested by existing academic research, and thus this study uses extreme performance companies to implement the strategy. We find that strong momentum gains appear when extreme winners and losers are employed. These returns remain strong even after considering the transaction costs of implementing such strategies, including commissions, stamp duty, selling-short costs, and bid-ask spread. Overall, we show that a relatively large number of small investors can enjoy momentum gains, providing some evidence against stock market efficiency.
Strategy's implementation in QuantConnect's framework
Ammann, Moellenbeck, Schmid: Feasible Momentum Strategies in the US Stock Market
While there is a large literature documenting the profitability of momentum strategies, their implementation is afflicted with many difficulties. Most importantly, high turnover and costs to hold short positions, especially in small-cap stocks, result in high transaction costs. We restrict our investment universe to large-capitalized stocks included in the S&P 100 index. Moreover, we implement simple investment strategies that invest long in single stocks and short in the stock index. Such simple and cost-saving momentum strategies generate economically high and statistically significant abnormal returns. These results are robust to various risk-adjustments including the CAPM, the Fama French (1993) three-factor model, and a conditional version of the Fama and French (1993) three-factor model.
Foltice, Langer: Profitable Momentum Trading Strategies for Individual Investors
For nearly three decades, scientific studies have explored momentum investing strategies and observed stable excess returns in various financial markets. However, the trading strategies typically analyzed in such research are not accessible to individual investors due to short selling constraints, nor are they profitable due to high trading costs. Incorporating these constraints, we suggest and explore a simplified momentum trading strategy that only exploits excess returns from topside momentum for a small number of individual stocks. Building on US data from the New York Stock Exchange from 1991-2010, we analyze whether such a simplified momentum strategy outperforms the benchmark after factoring in realistic transaction costs and risks. We find that it is indeed possible for individual investors with initial investment amounts of at least $5,000. In further attempts to improve this practical trading strategy we also analyze an overlapping momentum trading strategy consisting of a more frequent trading of a smaller number of “winner” stocks. We find that increasing the trading frequency initially increases the risk-adjusted returns of these portfolios up to an optimal point when excessive transaction costs begin to dominate the scene. In a calibration study, we find that, depending on the initial investment amount of the portfolio, the optimal momentum trading frequency ranges from bi-yearly to monthly.