This repository contains programs to help backtest Dollar Cost Averaging (DCA)
You can use ticker_history.py to collect ticker history for a single ticker for a given historical time range. The returned payload is TSV data which is written into the ticker_data (created if not exists) path.
The program can be invoked from the command line to simply print the results (along with other messages) to stdout, in addition to creating a flat file under ticker_data.
To understand the arguments do this (Make sure your requirements are properly installed ahead of time): python3 ticker_history.py --help
It can also be used as a module that you could import into another program. The same payload (a string of .tsv data) is returned by the program in this case that can be consumed by the caller.
Note: There's a check on if a file with the matching data already exists under ticker_data, with the pattern {ticker.upper()}_{start_date_string}_to_{end_date_string}.tsv. If such a file exists, it is read and a trip to the Yahoo Finance API (via the yfinance module) is suppressed. If for some reason you want to force the re-creation of a file, simply delete it and call ticker_history.py accordingly.
sim_dca.py is used to simulate Dollar Cost Averaging (DCA) strategies. Its author is a middle class fellow (i.e. NOT RICH), so take that knowledge and do what you will with it.
For now (at the time of this writing, 2023-04-21), I haven't bothered to parameterize this program. It simply reads a file that would have been created by the ticker_history.py program. It also exepcts that it will exist ahead of time. All the parameters that influence the sim are towards the top of main() to make them easy to play with
It can be made more fancy at a later date, or never. Pull requests are welcome