Automated Backtester Research Plan (Part 3)

Finishing up the discussion on filters, some can probably be tested on the underlying alone without the automated backtester. By looking just at underlying price we can plot trade distribution (looking for consistent vs. lumpy). Maximum adverse excursion can also be studied to see whether this improves with filter application. This type of analysis may lend itself more to spreadsheet work and macros. I have numerous research questions that would fit in this category.

Back to the automated backtester, I would like to study rolling as a trade management tool. We can roll naked puts [down and] out to the next month when a short strike is tested or when the trade is down 2-5x initial credit. We can also roll naked puts down to same original delta in the same or next month if strike gets tested.

Some thought may need to be given to calculate days in trade (DIT) for rolling adjustments. If rolling out doubles DIT, for example, then annualized ROI is halved. This may not be the best result. If I’m not looking to calculate [annualized] ROI then this may be a moot point, but we should be aware that for breakeven or normal profit, rolling will significantly increase DIT.

As an overlay, another adjustment I am interested in testing is the addition of an ATM short call to manage NPD.

Parts 1 and 2 of this research plan primarily addressed naked puts. The plan is similar for naked calls.

The first phase of naked call backtesting involves overlapping trades. We can study trades entered every day between 7-42 DTE. We can choose the first strike under 0.10 to 0.50 delta by increments of 0.10. We can hold to expiration or manage winners at 25% (ATM options only?) or 50%. We can manage losers at 2x, 3x, 4x, and 5x initial credit. I’d like to track and plot maximum adverse (favorable) excursion (no management) for the winners (losers) along with final PnL and total number of trades. I want to monitor winning percentage, average win, average loss, largest loss, profit factor, average trade (PnL), PnL per day, standard deviation of winning trades, standard deviation of losing trades, average DIT, average DIT for winning trades, and average DIT for losing trades.

My gut leans away from studying longer-term naked calls because of vertical index skew. With the market generally drifting higher and naked calls being cheaper than put counterparts (thereby implying NTM call sales for equivalent premium to farther OTM puts), my bias is toward shorter-term holdings. On the other hand, a 30-64 DTE backtest would allow for an apples-to-apples naked put comparison. This is subject for debate.

I will continue next time.