Automated Backtester Research Plan (Appendix B)

From Jan 2019, this should be the final entry of the current blog mini-series (see Appendix A introductory remarks).

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More relevant to the WF approach, could we shorten the period to X months and look at the average and extremes of the distribution of daily price changes? We would be stopped out going into a big change. When placing trades in the new market environment placing trades, we should get compensated by higher option premiums. This gives us a fighting chance and if we can somehow decrease position size in accordance with ATR, then maybe we can keep the average PnL changes somewhat constant across anything from calm to volatile market environments. Stuff to think about.

I don’t believe this holds any relevance with regard to the daily/serial trades categorization (see Part 5 paragraphs 2-3). This may be something to study with regard to allocation or it may be something to monitor before trade entry. A study of ATR versus future MAE may help to determine what relationship (if any) exists between the two.

If the market goes up more than it goes down, then why not trade bullish butterflies rather than naked puts? Position sizing aside, the risk is much lower for the butterflies.

My initial thought on this was to study MAE and MFE of the underlying over the next ~30 days. Mild MAE numbers and better MFE would signify a market moving gradually higher. The key for butterfly profitability is when the market gets inside the expiration tent, which would not be indicated by this study. If we target something like 10%/-20% PT/max loss, though, then any movement up will likely get close to the PT unless the market skyrockets.

We could also study these max excursion distributions over different time intervals (e.g. 5-20 days by increment of 5). The butterfly would be indicated if MAE remains constant at some point while MFE continues to grow. Another indication would be a high percentage of cases showing MAE to be contained while MFE is large. Another indication would be MFE limited and positive within a certain time range. A final indication would be tip of bell curve corresponding to a set range. We could study butterflies that are centered X% above the money to X% below the money and calculate differences in profit.

We could also look at the asymmetrical butterfly (butterfly + PCS), but spread width would have to be specified, etc.

As backdrop from the easier scenario against which to compare all recent discussion (this blog mini-series), consider an all-equity portfolio where backtesting can easily be done with fixed position size throughout as defined by:

      Number of shares traded = (initial number shares * initial stock price) / current stock price

Normalized drawdown can then be calculated at any point as a percentage of the initial account value.