Backtester Development (Part 8)

Today I will continue (see end of Part 7) with backtester logic for maximum excursion (ME).

I will begin talking about the output files. Two dataframes are created with pd.DataFrame(): btstats for intratrade monitoring and summary_results for end-of-trade reporting. These are ultimately converted to .csv files with pd.to_csv().

Rows are added sequentially to the dataframes upon completion. For btstats, add_btstats is created where each list element corresponds to a dataframe column. Minimal calculation in this list statement (e.g. L_iv_orig x 100) could have been done with variable assignment if I renamed the variables to reflect it. Index of the last record is then used to add list to the bottom:

     > btstats.loc [ len ( btstats . index ) ] = add_btstats

In contrast to adding rows as lists, I build summary_results by adding rows as one dictionary per trade:

     > summary_results = summary_results . append ( { ‘Trade Num’ : len (trade_list) }, ignore_index = True)

This is a long line with a key-value pair for every column (only one of which is shown here). The final argument is needed when appending a dictionary to avoid a TypeError.

Pandas documentation says DataFrame.append() has been deprecated in favor of .concat(). I do not get any such warning. A closer look suggests the deprecation pertains to adding one dataframe to another. I am adding a dictionary.

Now that I have described the structures in which ME will be reported, let’s talk about ME itself. By definition, MFE (favorable) is the farthest a trade goes in my favor before ending up a loser and MAE (adverse) is the farthest a trade goes against me before ending up a winner. Strictly speaking, a losing (winning) trade has no MAE (MFE).

However, a useful application might involve running trades from start to finish without profit targets or max losses to record largest intratrade loss and gain. Plotting the two against each other can then give an idea whether a particular stop level might lock in more winners to the exclusion of losers or avoid locking in more losers to the exclusion of winners. All this is contingent on knowing whether intratrade gain or loss comes first. I have the _dte variables to tell me that.

To allow for such application, I define MFE (MAE) to be maximum intratrade gain (loss) without regard to trade outcome. My tweak is to recognize MFE (MAE) for winning (losing) trades as the previous day’s MFE (MAE) before stop level is hit.

Needing to differentially apply current or previous ME when stop levels are checked after ME is updated makes the program logic more complicated. For trade_status ‘IN_TRADE,’ I report MAE and MFE. For ‘WINNER’ (‘LOSER’), I report MAE and MFE_prev (MAE_prev and MFE). All this leaves me with three different add_btstats lines that need to be properly fit into an if-elif-else block. The same goes for summary_results.

I will continue next time.