Diagonal Spread

A diagonal spread is an options strategy that combines a vertical spread and a calendar spread. It uses different strikes and different expirations.

Structure

Buy a longer dated option at one strike
Sell a shorter dated option at a different strike

Payoff Profile

The position benefits from time decay of the short option while retaining directional exposure through the long option. The payoff is asymmetric and depends on the relationship between strikes and expiration dates.

Greeks

Diagonal spreads are often net long vega and positive theta in the near term. Delta exposure depends on the strike placement and underlying price.

Use Cases

Diagonal spreads are used when a trader expects a gradual move in the underlying and wants to take advantage of time decay. They can also be used to express a volatility view.

Risks

The strategy is sensitive to implied volatility and requires monitoring of the short option as it approaches expiration. Large moves can reduce the value of the long option relative to the short.

Adjustment Ideas

Common adjustments include rolling the short leg forward or up and down to capture additional premium. Adjustments should be planned before entry.

Practical Notes

Model the payoff across a range of prices and dates. This helps identify where the strategy performs best and where it carries the highest risk.

Operational Notes

Definitions and conventions should be consistent across datasets and venues. A small difference in data fields or session boundaries can change outcomes, especially for short term strategies. Document inputs and assumptions so results can be reproduced.

If the concept depends on exchange rules or broker behavior, confirm those rules for the specific venue. Operational details often explain why a trade behaved differently than expected.

Stress Scenarios

During volatility spikes, liquidity can evaporate and price gaps can appear. Under these conditions, indicators can lag, order types can misfire, and spreads can widen sharply.

Stress testing the concept against fast markets, thin liquidity, and sudden news helps reveal hidden risks. If a strategy only works in calm conditions, size and timing should reflect that.

Documentation Tips

Keep a short checklist of the rules, parameters, and decision points. Record how the concept is used in live trading and compare it to backtest assumptions. This makes future refinement easier and reduces drift in execution.

Common Questions

Traders often ask how sensitive results are to parameter choices, how the concept behaves in different regimes, and whether it scales with size. Answering these questions early improves reliability and prevents overfitting.

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime

Checklist

Define the exact rule in plain language
Validate data quality and timing
Quantify execution costs
Set risk limits and stop logic
Review performance by regime