How to Optimize Trading Strategies in Python (Step-by-Step)

In this video I use the backtesting.py Python library to show you how to optimize a simple EMA crossover strategy on SPY (S&P 500) data over the last 4 years. This video follows on from the previous video where I show you how to do just the backtesting. This can be found here: • How to Backtest Tradin...
All of the code + data can be found here on GitHub:
Code: github.com/Alp...
Data: github.com/Alp...
Python libraries used in this video:
Backtesting.py: github.com/ker...
Pandas: github.com/pan...
This video is for educational purposes only and is not financial or investment advice. Trading involves significant risk, and you should carefully consider your objectives and risk tolerance before engaging in any trading activity. Past performance is not indicative of future results. Always do your own research and consult a licensed financial advisor before making financial decisions. I am not responsible for any losses incurred. Trade at your own risk.
#trading #backtesttradingstrategy #tradingsystem #stockmarket #emacrossoverstrategy #investing #technicalanalysis

[@animeshbarai5272]

prepare a video on how to analyze the market data to build a strategy or a project that find possible best fit conditions for building a trading strategy

[@alphabeacon1]

Thank you for the suggestion!