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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.
* 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
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.
- Unlocked Screener & 300+ Advanced Charts
- 700+ uncommon trading strategy ideas
- New strategies on a bi-weekly basis
- 2000+ links to academic research papers
- 500+ out-of-sample backtests
- Design multi-factor multi-asset portfolios
Backtest period from source paper
1988-2006
Confidence in anomaly's validity
Moderately Strong
Indicative Performance
32%
Notes to Confidence in Anomaly's Validity
OOS back-test shows slightly negative performance. It looks, that strategy’s alpha is deteriorating in the out-of-sample period.
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)
Period of Rebalancing
Yearly
Notes to Period of Rebalancing
Notes to Estimated Volatility
Number of Traded Instruments
20
Notes to Number of Traded Instruments
Notes to Maximum drawdown
Complexity Evaluation
Simple strategy
Notes to Complexity Evaluation
Financial instruments
stocks
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 based on their stock market performance over the previous 12 months (the rank period). The investor goes long in the ten stocks with the highest performance and goes short in the ten 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 momentum strategy implicitly can’t be used as a hedge. The long-short equity momentum factor is also 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.
Out-of-sample strategy's implementation/validation in QuantConnect's framework
(chart+statistics+code)