In this article, we include backtesting results of a long-short strategy for factor ETFs. In the test period, the strategy had a low drawdown and a respectable Sharpe ratio. Access to the full article requires a Premium Articles subscription or an All in One subscription.
Some large funds employ factor long-short strategies because they offer convexity and have the potential of outperforming the stock market during sharp decline periods. This is true this year with the S&P 500 down 14%, while long-short factor strategies outperform by a margin depending on the particular method used.
Large funds do not use ETFs due to liquidity constraints but instead replicate the factors with baskets of large-cap stocks. Retail investors and traders have more flexibility and can use ETFs with long-short strategies.
Below is the yearly performance of a long-short strategy based on ETFs. The testing period is from 01/02/2015 to 06/01/2022.
The strategy is always long and short one ETF. The ranking and scoring are based on a mathematical formula. Weak long and short ETFs are dropped and replaced by strong long and short ETFs based on the ranking results. The rank is calculated daily but the strategy has low turnover.
It may be seen that 2020 was a good year for the long-short factor strategy and year-to-date it is slightly in the black while the S&P 500 is down 14%.
Below is the equity curve with key performance metrics.
The annualized return is 4.3%. The maximum drawdown is -7.8%, while in the same period the maximum drawdown for the S&P 500 was -34%. The Sharpe ratio is 0.72 but not close to 1, as we would like it to be.
Below is the drawdown profile of the strategy.
The maximum drawdown is -7.8% and occurred in April of the year. The current drawdown is -3.4%. The average drawdown in the test period is a little less than -2%.
Monte Carlo Simulation results based on equity curve changes are included below. Caveat emptor: Monte Carlo analysis has several limitations we have discussed several times in this blog but included for informational purposes.
There is a 5% probability of 18% or higher drawdown.
The probability of a negative annual return is less than 5%. Below is a summary of performance and comparison to SPY buy and hold.
| Long-Short Factor ETFs | SPY Buy and Hold | |
| CAGR | 4.3% | 11.7% |
| Max. DD | -7.8% | -33.7% |
| Sharpe ratio | 0.72 | 0.65 |
| Volatility | 5.9% | 18.1% |
| MAR (CAGR/Max. DD) | 0.56 | 0.35 |
| Number of long trades | 27 | 1 |
| Number of short trades | 27 | – |
| Win rate | 50% | – |
This type of long-short strategy can allow “leveraged alpha” and could still have lower volatility and maximum drawdown than buy and hold. We plan to add a similar strategy to our group of systematic strategies for next year.
More details about the strategy and its rules are included below for premium subscribers.
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Specific disclaimer: This report includes charts that may reference price target levels determined by technical and/or quantitative analysis. No updates to charts will be provided if market condition changes occur that affect the levels on the charts and/or any analysis based on them. All charts in this report are for informational purposes only. See the disclaimer for more information.
Disclaimer: No part of the analysis in this blog constitutes a trade recommendation. The past performance of any trading system or methodology is not necessarily indicative of future results. Read the full disclaimer here.
Charting and backtesting program: Amibroker. Data provider: Norgate Data
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