Python Trader Backtest

Python Trader Backtest is an app for backtesting simple trading strategies based on historical trading data from the yfinance python package. The application enables variations of portfolio periodic balancing with a weighted averaged portfolio value for a variety of selling strategies like, FIFO (First In First Out), LIFO (First In Lirst Out) or TAX_OPT that picks which stock to sell next by minimizing the amount of tax payed in the transaction.

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Requirements

#	package	version
1	pandas	1.2.2
2	numpy	1.19.5
3	matplotlib	3.2.0
4	yfinance	0.1.67
5	PySimpleGUI	4.55.1

Notebook

#	file	Subject	Colab	Nbviewer
1	backtesting_simulator.ipynb	Runing the full simulator in Jupyter notebook

Command Line API

You should run the main.py file in the src folder with the following arguments:

Argument	Description
-tickers	The tickers to trade in, type=str, required=True, nargs='+'
-periods	Periods to test balancing periods, type=int, required=True, nargs='+'
-ratios	The balancing process is happens according to the ratios, type=float, required=True, nargs='+'
-start_date	Initial date of trading , type=int, required=True, nargs='+'
-end_date	Final date of trading , type=int, required=True, nargs='+'
-deposit	The amount to deposit in a periodic fasion, type=float, default=0.0
-deposit_period	The period of deposit, type=int, default=30
-buy_fee	Transaction buying fee in percents, type=float, default=0.08
-min_buy_fee	Transaction minimal buying fee, type=float, default=2.
-sell_fee	Transaction selling fee in percents, type=float, default=0.08
-min_sell_fee	Transaction minimal selling fee, type=float, default=2.
-tax	The amount of tax on profits in percents, type=float, default=25.
-liquid	The trader's initial liquid, type=float, required=True
-verbose	Print to terminal the balancing process (slowers the simulation), type=bool, default=True
-plots_normalize	Normalizing the market plots to unity, type=bool, default=True
-sell_strategy	The selling strategy for which the trader will follow, type=str, default='FIFO', choices='FIFO', 'LIFO', 'TAX_OPT'

For example:

python3 main.py -liquid=100000 -tickers 'AAPL' 'GOOG' 'SPY' 'ORCL' -periods 2 10 20  -ratios 0.25 0.25 0.25 0.25 -deposit 1000 -deposit_period 10 -verbose False -start_date 2019 1 1 -end_date 2021 1 1

The App

This repository also contains a simple (and a bit ugly) python app with the same functionality of the original API. The app got three windows:

• Input window which contain the input parameters to the market, broker and trader classes

• Output window for textual progress display

• Plots window for ploting the simulation results

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Enjoy ...