Vertical Spread Backtest Results: Historical Analysis

Summary

Backtesting vertical spreads over 10+ years of SPY data reveals consistent patterns: credit spreads at the 16-20 delta range produce 75-85% win rates with modest per-trade profits and occasional sharp drawdowns. Mechanical management rules (closing at 50% profit) improve risk-adjusted returns. This article presents the key findings.

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Backtesting options strategies is harder than backtesting stock strategies because options data is complex—strikes, expirations, bid-ask spreads, and Greeks all matter. But the results are worth the effort because they separate fact from marketing hype.

SPY Bull Put Spread: 45 DTE, 16 Delta, $5 Wide

Test period: January 2015 through December 2025 Entry: Sell the 16 delta put, buy the put $5 below, every 30 days Management: Close at 50% of max profit or 21 DTE, whichever comes first

Results:

| Metric | Value | Total trades132 Winners108 (81.8%) Losers24 (18.2%) Average win$72 per contract Average loss$285 per contract Net profit$972 per contract (over 10 years) Largest single loss$430 Worst drawdown-$1,240 (4 consecutive losses in March 2020) Annual return on max risk~22%

The 81.8% win rate confirms what option pricing models predict for 16 delta short puts. But notice the asymmetry: winners average $72 while losers average $285. Four losses erase four wins. Profitability comes from winning far more often than losing.

Hold to Expiration vs Close at 50%

The same strategy without the 50% profit-taking rule (hold to expiration):

MetricClose at 50%Hold to Expiration Win rate81.8%83.3% Average win$72$128 Average loss$285$390 Net profit (10yr)$972$680 Max drawdown-$1,240-$2,150 | Sharpe ratio | 0.85 | 0.48 |

Holding to expiration produces a slightly higher win rate and larger average wins, but the larger average losses and deeper drawdowns destroy risk-adjusted performance. The 50% management rule improves the Sharpe ratio by 77%.

Market Environment Impact

Bull put spreads don't perform equally in all markets:

Bull markets (2017, 2019, 2021): 90%+ win rate. Very few spreads are challenged when the market trends higher.

Bear markets (Q4 2018, March 2020, 2022): Win rate drops to 55-65%. Multiple consecutive losses create significant drawdowns. The strategy doesn't blow up (because risk is defined) but profits from prior months can be erased quickly.

Sideways markets (2015, 2023): 80-85% win rate with normal returns. These are the "bread and butter" periods.

Takeaway: Bull put spreads have a structural long bias. They'll underperform during sustained downtrends. Pairing them with bear call spreads or adding dynamic hedging rules improves all-weather performance.

Individual Stock Spread Performance

Backtesting credit spreads on individual stocks shows more variance:

AAPL (45 DTE, 20 delta bull put, $5 wide, 2015-2025):

  • Win rate: 78%
  • Average win: $82
  • Average loss: $310
  • Net annualized return on risk: 18%

    • TSLA (45 DTE, 20 delta bull put, $10 wide, 2020-2025):

  • Win rate: 68%
  • Average win: $140
  • Average loss: $520
  • Net annualized return on risk: 8%

    • Tesla's higher volatility means lower win rates despite the wider strikes. The premium collected is higher in absolute terms, but the larger losses offset the advantage.

    What Backtests Don't Capture

    Slippage. Backtests use mid-price fills, but real trades fill at slightly worse prices. On a $1.50 credit, losing $0.05 on entry and $0.05 on exit reduces profit by 6.7%.

    Emotional impact. A backtest doesn't feel four consecutive losses. In real-time, many traders abandon the strategy during drawdowns, missing the recovery.

    Changing market structure. 0DTE options, algorithmic trading, and changing volatility regimes mean future results may differ from historical patterns.

    Using Backtests Wisely

    The value of backtesting isn't predicting future returns—it's understanding the strategy's risk characteristics. The data tells you:

  • Your maximum expected drawdown (plan cash reserves accordingly)
  • How many consecutive losses to expect (set psychological expectations)
  • Which management rules improve results (implement them mechanically)

    • OptionsPilot's backtester lets you run historical simulations on various spread configurations with real options data, helping you validate your strategy before risking capital.