Hello everyone!
From the beginning I needed to backtest with tick data collected from my own broker that has variable spread. However I wasn't able to find how to do that. It took me several days but I think that I got it right finally. I will write the steps I took so it can serve as a tutorial for other people attempting to do something similar. I also hope that this will eventually help to discover bugs as I don't have much experience in C programming.
1. Obtaining dataFor this demonstration I will use
Dukascopy tick data downloaded using
StrategyQuant Tick Downloader. First I downloaded the data for each currency pair and then I exported them to .csv files, each line in this format: YYYY-MM-DD hh:mm:ss.fff,bid,ask,bidVol,askVol
2. Splitting dataT1 conversion is more complicated than M1 conversion because there is no maximum size of the data set and the physical memory may not be sufficient to read the input file at once. Because I didn't want to end up wit too complicated Zorro conversion script I decided to split the data and reverse the line order using Python script and Linux shell command 'tac' (reversed 'cat'
). The script can be found here:
split.py. To use it in Windows you will need something like
Cygwin.
3. ConversionI had to modify the Zorro/Strategy/Convert.c script to accomodate for T1 structs (
ConvertT1.c ). You need to set 'base_path', 'smbl', 'start' and 'end' variables to use it. The input files should be in aforementioned CSV format (produced by split.py) and stored in base_path folder. Their names should be in this form: [SYMBOL]_[YEAR].csv. The important part is that if the SPREAD is defined using #define directive in the ConvertT1.c script, another .t1 file (besides the one with ask prices) is exported. Its name contains 's' at the end of symbol's name and it contains spread values for each tick.
4. Checking the converted dataTo make sure that the conversion has been done properly you can use this modified export script:
ExportT1.c 5. Simulating variable spreadThe final step is using both .t1 files during backtest to simulate variable spread. One of the ways to do so is to include both SYMBOL and SYMBOLs in the backtest. SYMBOLs is an artificial asset used only to get the spread value for the actual asset. When the program loops through SYMBOLs, save the spread value from T1 struct to a global variable. When the program loops through the actual SYMBOL, assign the spread from the global variable to Zorro's Spread variable. And that's it
