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Bullish Iron Butterflies (Part 6)

So far I have done several things with the BIBF analysis: considered the impact of transaction fees (TF), looked at width-adjusted ROI, identified a relationship between spread width and underlying price, and looked at performance stratified by implied volatility. Today I want to talk about maximum adverse excursion (MAE).

I have two issues to address before looking at MAE distribution: TF and width normalization. I like to remain as plain vanilla as possible in my analysis to minimize chances of curve-fitting. This means not implementing one condition then overlaying another on top of that then a third on top of the first two, etc. Adhering to the “plain vanilla” guideline could mean leaving the $26/contract TF and not normalizing for spread width.

I would be more willing to conduct the analysis this way if it didn’t differentially affect trades. At $26/contract, the total TF is $208/trade. Given $735 as the average cost for a 20-point butterfly, starting down $208 means the minimum MAE is -28.2% (and -52% for the cheapest trade of $400!). The wider butterflies are affected less due to the larger denominator.

Aside from this TF-induced-apples-to-oranges MAE comparison, the whole concept of being in loss at trade inception seems questionable. Yes, slippage is a reality of trading and this is a logical way of accounting for it. Intuitively, though, I feel MAE should be zero when the trade is placed.

Reducing TF to $6/contract would cost me $48/trade, which is a 77% reduction. For the average 20-point butterfly this is -6.5% (-12% for the cheapest 20-point butterfly). This feels small enough to be tolerable while still acknowledging the reality of slippage. Unfortunately this still affects narrow butterflies more than wider ones. In the true spirit of MAE, I think I must normalize for TF by adding back the $208 for each trade.

The discussion is similar with regard to spread width. Narrow-butterfly PnL seems to be skewed toward the loss side while normalizing for spread width mitigates this effect. To some degree this is a position sizing issue (how many contracts per $10,000?), which I would prefer to leave out of the system development process altogether. Because of the large effect, though, I think I have no choice but to normalize.

Next time I will study the distribution of width-adjusted MAE without transaction fees.

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