Automated Backtester Research Plan (Part 6)

In the last three posts, I detailed portfolio margin (PM) considerations with the automated backtester. After backtesting naked puts and naked calls separately, the next thing I want to do is add a naked call overlay to the naked puts.

This is not the previously-mentioned ATM call adjustment but rather study of 0.10-0.40- (by increments of 0.10) delta strangles. Strangles can be left to expiration, managed at 50%, or closed for loss at 2-5x initial credit. I want to track total number of trades, winning percentage, average PnL, average loss, largest loss, standard deviation of returns, days in trade, PnL per day, PF, RAR, and maximum adverse excursion. Strangles should be normalized for notional risk and with implementation of PM logic, notional risk can be replaced by theoretical loss from walking the chain up 15% (or up 12% plus a 10% vega adjustment). With this done, return on capital can then be calculated as return on PM (perhaps calculated as return on the largest PM ever seen in the trade since PMR varies from one day to the next). Maximum subsequent:initial PM ratio should be tracked. We can also study the effect of time stops.

If deemed useful then maximum favorable excursion (MFE) can also be studied for unmanaged trades. This could be studied and plotted in histogram format before looking at ranges of management levels (not mentioned in previous paragraph). With MFE and MAE, some thought may need to be given about whether to analyze in terms of dollars or percentages. If notional risk is somehow kept constant, though, then either may be acceptable.

Incorporating naked calls with filters can also be studied. Naked calls may or may not be part of the overall position at any given time. I am interested to study MAE by looking at underlying price change of different future periods given specified filter criteria. Any stable edges we identify could be higher probability entries for a naked call overlay. I approach this with some skepticism since it does imply market timing. As discussed in Part 3, this type of analylsis lends itself more to spreadsheet research than to the automated backtester, which would run simulated trades. We would primarily be studying histograms and running statistical analysis on distributions.

Backtesting of undefined risk strategies will conclude with naked straddles. Like strangles, straddles can be left to expiration, managed at 10-50% by increments of 5%, or closed for loss at 2-5x initial credit. I would want to monitor total number of trades, winning percentage, average PnL, average loss, largest loss, standard deviation of returns, days in trade, PnL per day, PF, RAR, and MAE (MFE?). The same comments given above for straddles regarding PM logic, return on PM, and PM ratios also apply here. We can also study the effect of time stops (managing early from 7-21 DTE by increments of seven).

As discussed with naked puts and calls, I would like to study rolling as a trade management tool. We can reposition strangles in the same (subject to a minimum DTE, perhaps) or following month back to the original delta values when a short strike gets tested or when down 2x-5x initial credit. We can do the same for straddles when an expiration breakeven (easily calculated) is tested as well as rolling just the profitable side to ATM.

Aside from studying straddles and strangles as daily trades, serial [non-overlapping] backtesting can be done in order to general equity curves and study relevant system metrics as discussed previously with regard to naked puts and naked calls.