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Poor Man's Covered Call Pro

Read Me First — PMCC Pro

The Poor Man's Covered Call is a diagonal spread: a long-dated call provides leveraged equity exposure while repeated short calls generate premium and cap part of the upside. PMCC Pro evaluates both legs together instead of treating the short-call income as if it were independent.

Start with the research question: Does repeatedly selling short calls against a long-dated stock-replacement call improve the total diagonal position after time decay, volatility exposure, leverage, rolling, and transaction costs?

What this lab is designed to do

The Poor Man's Covered Call is a diagonal spread: a long-dated call provides leveraged equity exposure while repeated short calls generate premium and cap part of the upside. PMCC Pro evaluates both legs together instead of treating the short-call income as if it were independent.

Key controls and inputs

What the outputs mean

A good first experiment

  1. Use the default high-delta long call and a moderate-delta short call.
  2. Run a Typical market path and record the combined return of both option legs and cash.
  3. Repeat the identical settings in Strong bull. Watch whether repeated short calls dominate the result through forgone upside.
  4. Repeat in Choppy and Bear environments to see how premium interacts with the long-call drawdown.
  5. Run the long-call leg without short calls, if the lab allows, or compare with the closest available long-call benchmark.
  6. Change only the short-call delta and then only the long-call roll threshold. This reveals which leg is driving the result.

How to interpret the result

Do not judge the strategy from one path, one seed, or one favorable market environment. Read return, drawdown, exposure, trade frequency, and benchmark-relative performance together. A result is more credible when it persists across reasonable parameter changes and when the comparison benchmark has similar economic exposure.

Important assumptions and limitations

How this complements backtesting

Historical PMCC backtests can be difficult because they require consistent long- and short-option chain data over long periods. Simulation fills that gap by controlling the volatility surface and path assumptions. Use historical tests where data quality permits and use simulation to test sensitivity to assumptions that history samples only a few times.

Research use only. These labs are tools for controlled simulation and model-based research. They do not forecast the market, guarantee future performance, or provide individualized investment advice.