Crypto Trading Strategy Backtester

Easy-to-use cryptocurrency trading strategy simulator

Features

• You can run it fast, and it is easy to use.
• There are no complexities and no database usage in this project. Even dependencies are a few.
• It is easy to modify and customize.
• It generates many different statistical parameters in a complete report.
• This project saves the downloaded data for offline usage, so no unnecessary downloads are required.
• This project generates practical datasets for data scientists.
• After backtesting, you can see the opened and closed positions on an interactive chart.
• You can read the code for educational purposes.

Run

1. Clone the repository.
2. Run pip3 install -r requirements.txt.
3. Run python3 main.py.

This will backtest an example strategy for trading Bitcoin.

Config

To define the strategy, you can:

• Change config.py constants.
• Define new indicators in indicators.py.
• Change _is_it_time_to_open_long_position and _is_it_time_to_open_short_position methods.
• Change _check_conditions_to_close_long_position and _check_conditions_to_close_short_position methods.

Config.py Description

• COINS_SYMBOL: The trading pair
• START_DEPOSIT: How much money do we have to start trading with?
• LEVERAGE: Futures trading leverage
• OPEN_POSITION_FEE_PERCENT and CLOSE_POSITION_FEE_PERCENT: Exchange fees
• USE_LONG_POSITIONS and USE_SHORT_POSITIONS: Are we trading in the futures market?
• TAKE_PROFIT_PERCENTS_LIST and STOP_LOSS_PERCENTS_LIST: Set multiple take profit and stop losses for your positions
• MOVING_AVERAGE_SIZE andINDICATORS_TIMEFRAME: If use some indicators, you can set them up here.
• START_YEAR, START_MONTH, START_DAY, START_HOUR, START_MINUTE , and START_SECOND: Starting time for trading
• END_YEAR, END_MONTH, END_DAY, END_HOUR, END_MINUTE , and END_SECOND: Starting time for trading
• TIMEFRAME: The main time frame used for iterating candles and checking the take profits and stop losses
• IMPORTANT_RECENT_CANDLES_TIMEFRAME: Generated output dataset candles timeframe
• IMPORTANT_RECENT_CANDLES_COUNT: Number of candles in the generated output dataset
• OPEN_POSITION_TIMEFRAME: We want to open the position at some exact rounded times
• REPORT_PERCENTILES_COUNT: Number of percentiles used in the statistical analysis report
• TEST_SET_SIZE_RATIO: How big is the final generated test set of our dataset?
• MINIMUM_NUMBER_OF_CANDLES_TO_START_TRADING: Do not start trading soon!

Output

• A plot in plot.png, for example:

• Another plot to see the opened and closed positions on an interactive chart
• A complete report on candle statistics (as the program text output)
• A complete report on opened and closed positions (as the program text output)
• A complete report on the strategy (in deposit_changes.csv)
• A spreadsheet containing opened and closed positions (in positions.csv)
• Two datasets for data science and machine learning purposes (test.csv and train.csv)

To Do

• Use 5m, 15m, 1h, etc. instead of m5, m15, h1, etc.
• Use Python private methods in some cases

See Also

• Binance Futures Trading Bot
• Binance Spot Trading Bot

Credits

Erfan Alimohammadi and Amir Reza Shahmiri