Quick Comparison: Options Strategies to Backtest With AI
1. Covered Calls
Covered calls are one of the cleanest strategies to test because the structure is simple: own shares, sell calls, collect premium, and accept capped upside. AI can help test different call deltas, expirations, rolling rules, and market regimes. For example, a trader may compare weekly covered calls versus 30- to 45-day expirations, or test whether selling calls after sharp rallies improves results. The key variables are:- Call delta or moneyness
- Days to expiration
- Roll or close rules
- Underlying selection
- Dividend and earnings filters
2. Cash-Secured Puts
Cash-secured puts are often described as a way to get paid while waiting to buy a stock. That description is incomplete. The strategy is still long downside risk. Backtesting helps traders see whether the put premium compensates for that risk. AI can compare selling puts at different deltas, avoiding earnings weeks, requiring valuation filters, or only selling after volatility spikes. Important questions include:- How often would assignment occur?
- What happens during market selloffs?
- Does implied volatility justify the premium?
- Is the strategy better than simply buying the stock?
3. Long Calls
Long calls are simple to understand but difficult to trade well. The direction can be right while the option still loses money because timing, implied volatility, or strike selection was poor. AI can help test when long calls have historically worked best: breakouts, post-earnings momentum, analyst upgrades, high relative strength, or broad market risk-on conditions. Backtest variations should include:- In-the-money versus out-of-the-money calls
- Short-dated versus longer-dated expirations
- Profit-taking and stop-loss rules
- Filters for spread width and liquidity
- Avoiding periods of elevated implied volatility
4. Long Puts
Long puts can be used for bearish trades or portfolio protection. In both cases, backtesting matters because puts are often expensive when fear is already visible. AI can test whether puts work better after volatility compression, trend breakdowns, weak breadth, earnings risk, or macro stress signals. It can also compare outright puts with put spreads to see whether defined upside is worth the lower premium. Useful metrics include hit rate, average loss, payoff skew, drawdown protection, and cost of carry. A good backtest should also show how often the hedge expired worthless. For hedging, the question is not whether every put makes money. The question is whether the strategy reduces unacceptable portfolio risk at a reasonable cost.5. Vertical Spreads
Vertical spreads are useful because they define risk and reward in advance. Traders can test bull call spreads, bear put spreads, bear call spreads, and bull put spreads using different strikes and expirations. AI can help compare spread width, entry timing, delta selection, and exits based on profit targets or time remaining. This is where options backtesting software becomes valuable: small changes in strike choice can materially change expectancy. Backtest these assumptions:- Debit versus credit structure
- Short-leg delta
- Days to expiration
- Exit at 50%, 75%, or expiration
- Liquidity and bid-ask spread filters
6. Iron Condors
Iron condors are designed for range-bound markets. They collect premium by selling an out-of-the-money call spread and put spread, but they can suffer when volatility expands or price trends aggressively. AI can test which environments are most favorable: falling realized volatility, post-event volatility crush, low trend strength, or mean-reverting index behavior. Key variables include wing width, short-delta selection, days to expiration, stop-loss rules, and whether to close early after collecting a set percentage of max profit. Backtesting should focus less on win rate and more on loss size. Many condor strategies look attractive until a few large losses erase months of premium.7. Long Straddles and Strangles
Long straddles and strangles are volatility trades. The trader is not just betting on direction; they are betting that realized movement will exceed the premium paid. AI can test these strategies around earnings, product announcements, macro releases, litigation events, or unusually compressed volatility. It can also compare at-the-money straddles with wider strangles. The most important backtest questions are:- Was implied volatility already too high?
- How large was the realized move?
- Did the move happen quickly enough?
- Were spreads wide around the event?
- Did exits improve results versus holding to expiration?
8. Calendar Spreads
Calendar spreads use options with different expirations, usually to express a view on time decay and volatility term structure. They are more nuanced than simple directional trades. AI can test whether calendars work better before earnings, after volatility spikes, during quiet index periods, or when short-term implied volatility differs meaningfully from longer-term implied volatility. The backtest should include changes in implied volatility, not just price movement. Calendar spreads can behave unexpectedly when both the underlying and volatility surface move at the same time. For advanced traders, this is where an AI options trading platform should provide transparency around Greeks, term structure, and exit assumptions.9. Earnings Options Strategies
Earnings are ideal for AI-assisted testing because the event timing is clear and the option market often prices in a large move. Traders can test long premium, short premium, spreads, or post-earnings continuation trades. Backtesting should compare implied move versus realized move, pre-event IV behavior, post-event IV crush, gap direction, liquidity, and whether waiting until after the report improves risk-adjusted results. Potential tests include:- Buying straddles before earnings
- Selling iron condors after IV spikes
- Trading post-earnings drift with calls or puts
- Using spreads instead of outright options
- Avoiding names with poor liquidity
How to Evaluate Options Backtesting Software
Options backtests are only as good as their assumptions. Before trusting results, confirm that the tool handles real contracts rather than synthetic shortcuts. Look for:- Historical option chains
- Bid, ask, and mid-price handling
- Implied volatility and Greeks
- Expiration and strike selection rules
- Liquidity and open interest filters
- Earnings and event calendars
- Transaction cost assumptions
- Assignment and exercise logic where relevant
- Clear logs of every simulated trade