Strategy Library

Leveraged ETFs with Systematic Risk Management


In this tutorial, we attempt to beat the returns of the S&P500 Index using leverage and systematic risk management.


When measuring the profitability of a strategy, it is usually not enough to be profitable, as it should also beat the benchmark, for which the SP500 Index is most commonly used. If not, what would be the reason to not just invest in a low-cost SP500 index instead (not accounting for risk)? However, what if we could beat the SP500 with the SP500? This is what Gayed et al. proposed with their strategy of using Leveraged SP500 indices with Systematic Risk Management. They propose that Moving Averages are a good method to assess volatility in the market, and they use it to manage risk, which is especially important since the effects of price swings in a leveraged ETF are magnified due to the leverage. With this method, we hope to outperform the SP500 while at the same time, attempt to reduce drawdown.


We develop hold/liquidate positions based on the 200-day Simple Moving Average (SMA) of our ETF, for which we use SSO, a 2x leveraged SP500 index ETF. With 200 days instead of using fewer days, say 50, we reduce the number of trades per year, thereby reducing transaction costs and the effects of slippage. Moving on, if the current price of SOO is above the 200-day SMA, we hold SSO, and if SSO dips below our 200-day SMA, we sell liquidate our position and rotate our position into short-term treasuries, which is done through SHY, an ETF that tracks 1-3 year U.S. Treasury Bonds. If we are holding SHY, and the current price of SSO moves above the 200-day SMA, then we rotate back into SSO and liquidate SHY.



We use the S&P 500 as our benchmark, which we track by using the SPY ETF. Our strategy yielded a Sharpe Ratio of .732 over the past five years, while buying and holding SPY for the same period yielded a Sharpe Ratio of .572.


  1. Gayed, Michael and Bilello, Charles, Leverage for the Long Run - A Systematic Approach to Managing Risk and Magnifying Returns in Stocks (March 3, 2016). 2016 Charles H. Dow Award. Online Copy.

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