Backtest: Buy XOM at the close when it gaps down more than 1% at the open but closes ab...
Thirteen trades, a positive return, and a 73.56-point shortfall to the S&P 500. That is the shape of this test: buying XOM when it gaps down more than 1% at the open yet closes above that open — the rejected gap-down, the seller-exhaustion pattern — made money overall, but it finished far behind simply holding the benchmark over the same window. The thesis was that a supermajor’s equity would re-couple with oil after crude-shock selling. The numbers say the signal fired rarely, and when it did, the edge was thin.
The full study below walks through the methodology, the trade-by-trade results, and the charts that show where the 46.2% win rate and the exit rules did and didn’t do their job. With only 13 closed trades, the conclusions are suggestive, not settled — but the evidence is in the analysis that follows.
Buy XOM at the close when it gaps down more than 1% at the open but closes above its open; exit after 3 trading days, at +2%, or at -2%, whichever comes first. A rejected gap-down in a supermajor after crude-shock selling marks seller exhaustion and tends to be bought back as the equity re-couples with oil.
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 XOM at the close when it gaps down more than 1% at the open but closes above its open; exit after 3 trading days, at +2%, or at -2%, whichever comes first. A rejected gap-down in a supermajor after crude-shock selling marks seller exhaustion and tends to be bought back as the equity re-couples with oil.
The key numbers
The charts
The takeaway
The strategy returned +2.78% on $100,000 starting capital across 13 closed trades with a 46% win rate. Over the same window SPY buy-and-hold returned +76.34%, so the strategy finished trailing the benchmark by 73.56 points. Best single trade +3.39%, worst -2.25%.
The fine print
- Simulated results on historical data — fills, slippage and costs are idealized.
- Past performance does not predict future results.