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The short-term contrarian strategy of buying stocks, which are past losers and selling stocks, which are past winners, is well documented in the academic literature. But does this affect work within different markets and with different instruments?
Recent research shows that short term reversal works not only in the equity market, but it is also applicable to futures. Research also suggests that trading volume contains information about future market movements. This "forecastability" can be enhanced with open interest as it provides an additional measure of trading activity. Therefore this contrarian strategy is most profitable if it is implemented on high-volume low-open interest contracts.
Fundamental reason
Evidence of short-horizon return predictability is consistent with the overreaction hypothesis; namely, traders over-adjust their posterior beliefs to news more than it is warranted by fundamentals. Overconfidence and overreaction themselves imply a large volume of trading, and they are thus positively related to the magnitude of price reversals. Therefore an irrationality-induced market inefficiency gives rise to a negative relation between volume and expected returns. Open interest represents uninformed trading by hedgers or hedging activity and thus is also an important determinant of the market state.
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Market Factors
Confidence in Anomaly's Validity
Period of Rebalancing
Number of Traded Instruments
Notes to Number of Traded Instruments
Complexity Evaluation
Financial instruments
Backtest period from source paper
Indicative Performance
Notes to Indicative Performance
Estimated Volatility
Notes to Estimated Volatility
Maximum Drawdown
Notes to Maximum drawdown
Sharpe Ratio
Regions
Simple trading strategy
The investment universe consists of 24 types of US futures contracts (4 currencies, five financials, eight agricultural, seven commodities). A weekly time frame is used - a Wednesday- Wednesday interval. The contract closest to expiration is used, except within the delivery month, in which the second-nearest contract is used. Rolling into the second nearest contract is done at the beginning of the delivery month.
The contract is defined as the high- (low-) volume contract if the contract's volume changes between period from t-1 to t and period from t-2 to t-1 is above (below) the median volume change of all contracts (weekly trading volume is detrended by dividing the trading volume by its sample mean to make the volume measure comparable across markets).
All contracts are also assigned to either high-open interest (top 50% of changes in open interest) or low-open interest groups (bottom 50% of changes in open interest) based on lagged changes in open interest between the period from t-1 to t and period from t-2 to t-1. The investor goes long (short) on futures from the high-volume, low-open interest group with the lowest (greatest) returns in the previous week. The weight of each contract is proportional to the difference between the return of the contract over the past one week and the equal-weighted average of returns on the N (number of contracts in a group) contracts during that period.
Hedge for stocks during bear markets
Partially – The source research paper doesn't offer insight into the correlation structure of the proposed trading strategy to equity market risk; therefore, we do not know if this strategy can be used as a hedge/diversification during the time of market crisis. Short term reversal strategy is usually a type of "liquidity providing" strategy, and as such, it usually performs well during market crises. However, reversal strategy is also naturally a "short volatility" strategy; its return increases mainly in the weeks following large stock market declines. Traders must be cautious during crisis during days with high volatility as a reversal strategy usually force traders to buy assets which performed especially bad (and to sell short assets with an extremely positive short term performance).
Out-of-sample strategy's implementation/validation in QuantConnect's framework(chart, statistics & code)
Related picture
Source paper
Wang, Yu: Trading activity and price reversals in futures markets
Abstract: We use the standard contrarian portfolio approach to examine short-horizon return predictability in 24 US futures markets. We find strong evidence of weekly return reversals, similar to the findings from equity market studies. When interacting between past returns and lagged changes in trading activity (volume and/or open interest), we find that the profits to contrarian portfolio strategies are, on average, positively associated with lagged changes in trading volume, but negatively related to lagged changes in open interest. We also show that futures return predictability is more pronounced if interacting between past returns and lagged changes in both volume and open interest. Our results suggest that futures market overreaction exists, and both past prices and trading activity contain useful information about future market movements. These findings have implications for futures market efficiency and are useful for futures market participants, particularly commodity pool operators.
Other papers
Zhi Da, Ke Tang, Yubo Tao and Liyan Yang: Financialization and Commodity Markets Serial Dependence
Abstract: Recent financialization in commodity markets makes it easier for institutional investors to trade a portfolio of commodities via various commodity-indexed products. We present several pieces of novel causal evidence that daily exposure to such index trading results in price overshoots and reversals, as reflected in a negative daily return autocorrelations, only among commodities in that index. This is because index trading propagates non-fundamental noises to all indexed commodities. We present direct evidence for such noise propagation using commodity news sentiment data.
Micaletti, Raymond: A Comparison of Short-Term Mean-Reversion Indicators for Global Equities
Abstract: We examine an array of short-term mean-reversion indicators for global equities. The indicators encompass the most widely known price oscillators from the field of technical analysis along with several modified versions first developed by the author in the 2009- 2010 time frame. Constructing simple trading strategies from a wide range of indicator parameters, triggering thresholds, and holding periods, we find the modified oscillators tend to dominate the performance rankings on both the long and short sides of the market. Consequently, this study may serve as a point of reference for day traders, swing traders, or even asset managers looking to better time their rebalances.