Learn Python To Develop High Performing Trading Strategies
Spend 45 minutes with Larry Connors where he discusses how backtesting and researching in Python can make you a better trader.
Week One – You’ll gain the foundation in order to do your backtesting, research and signal generation.
This foundation will lay the groundwork for you to scale into the upcoming weeks.
Your homework will include learning how to do technical analysis calculations in Python including moving averages, RSI, and the other major technical indicators used by professionals.
Week Two – You’re going to be backtesting in Python!
You’ll be writing code in Python and testing strategies and signals to find market edges. For example, you’ll be writing code using a 2, 3, or 4 period RSI on various levels, such as RSI below 30, RSI below 20, etc.
By the end of Week 2, you’ll be able to test various market conditions (for example overbought and oversold conditions) and calculate the historical edges that exist in those conditions.
Week Three – You’ll be writing full-fledged trading strategies. This includes allocating capital to trades, adding risk management tools, and analyzing portfolio returns.
At the end of Week 3, you will be able to run more advanced backtests of your trading ideas and strategies.
Week Four – In Week 4 you’ll be analyzing your backtests. This includes analyzing your cumulative returns, analyzing your risk (drawdowns, volatility, etc.), analyzing correlations through time, and a deep dive into analyzing individual signals in order for you to see when and how to best optimize your trading strategies.
Week Five – In Week 5 you’ll be writing more advanced backtests. This includes creating signal list generation and managing a portfolio of multiple securities. You’ll also learn advanced concepts on position sizing in order for you to optimize the edges you are finding in your strategies.
By the end of this course, you will have the ability to find your own market edges, build your backtest, and do a deep analysis of the test results.
Classes begin Tuesday, March 12, 2019, at 4:30 pm ET.