Backtest: Buy XLE at the close when Brent crude's 20-day realized volatility is in the...
The setup sounds intuitive, but the backtest’s edge was thin: +1.71% on $100,000 starting capital, while SPY buy-and-hold returned +76.34% over the same window. That gap is the story.
The study bought XLE at the close when Brent crude’s 20-day realized volatility sat in the bottom quintile of its prior 252 sessions and XLE closed below its 20-day simple moving average. It exited when XLE closed above its 5-day simple moving average or after five trading days, whichever came first. The thesis: a sector dip in a low-oil-vol regime is positioning, not a repricing of supply risk, so XLE tends to snap back once forced selling clears.
The full trade-by-trade evidence is in the analysis below.
Buy XLE at the close when Brent crude's 20-day realized volatility is in the bottom quintile of its prior 252 sessions and XLE closes below its 20-day simple moving average; exit when XLE closes above its 5-day simple moving average or after 5 trading days, whichever comes first. A sector dip in a low-oil-vol regime is positioning rather than a repricing of supply risk, so XLE tends to snap back once the forced selling clears.
How this was measured
This is a simulated backtest generated from the plain-English strategy below, executed bar-by-bar on historical market data using the price + news data mode with $100,000 starting capital. Strategy: Buy XLE at the close when Brent crude's 20-day realized volatility is in the bottom quintile of its prior 252 sessions and XLE closes below its 20-day simple moving average; exit when XLE closes above its 5-day simple moving average or after 5 trading days, whichever comes first. A sector dip in a low-oil-vol regime is positioning rather than a repricing of supply risk, so XLE tends to snap back once the forced selling clears.
The key numbers
The charts
The takeaway
The strategy returned +1.71% on $100,000 starting capital across 16 closed trades with a 56% win rate. Over the same window SPY buy-and-hold returned +76.34%, so the strategy finished trailing the benchmark by 74.63 points. Best single trade +2.23%, worst -2.96%.
The fine print
- Simulated results on historical data — fills, slippage and costs are idealized.
- Past performance does not predict future results.