Introduction to Backtrader – Creating your First Trading Strategy – Python Trading Tutorial

Backtrader is an open-source python framework for backtesting, optimizing, and deploying live algorithmic trading strategies.

Using Backtrader one can create their own indicators, trading strategies with Buy or Sell indications(observers), get trading statistics (analyzers) and even building stock screeners.

Used Python Version – Python 3.8.5

How to Install Backtrader?

open your command line and use the following command. Ensure that pip is already installed.

pip install backtrader
pip install nsepy

Backtrader library is used for backtesting purpose and nsepy python library to get the End of the day data from NSE

Understanding Cerebro

Cerebro is a powerful trading engine and it serves as a central part for connecting the data feeds, running trading strategies, providing trade metrics, execute the backtesting, live trading, and plotting the results.

Creating your First Strategy involves the following steps in Backtrader

1)Download/Prepare the Data
2)Create the Datafeed from the Dataset
3)Create Buy/Sell Signal Observers (Optional)
4)Create Trading Strategy
5)Enable Logging in your Trading Strategy (Optional)
6)Create Cerebro Engine
7)Add Datafeed to Cerebro Engine
8)Set Initial Capital and Trading Commissions
9)Add Trading Strategy to Cerebro Engine
10)Add Observers to Plot Buy/Sell Indications
11)Run Cerebro Engine
12)Plot the Charts with Buy/Sell Signals
13)Get the Portfolio Results and Trade Metrics

Python Code to Implement a Simple Ema Crossover Strategy with Buy/Sell Signals Plot.

Backtrader comes with active community support for the traders who are enthusiastic about creating their own trading system and automating their trades.