Algorithmic Trading With Python - Scalping Strategy With CandleStick Pattern Backtest In Python

This is a scalping Trading Strategy optimization using CandleStick Wick length pattern to confirm price momentum along with 3 moving exponential averages to estimate if the price trend is up or down. The backtest is carried out in Python using an algorithmic trading approach to compare the results. Accordingly we will decide to take long or short positions based on moving average slopes and the candlestick wick length depending if the trend is down or up. The algorithm is written in python language and previous related videos along with the code are available following these links: strategy description https://youtu.be/NoNucP_IVB0 strategy optimization https://youtu.be/ybmep_u5MeU 🍓 If you want to follow structured courses with more details and practice exercises check my "About" page for Discount Coupons on my Udemy courses covering: Python basics, Object Oriented Programming and Data Analysis with NumPy and Pandas, ... more courses are on the way drop me a message if you have a particular interesting topic! Good luck! download of the jupyter notebook: https://drive.google.com/file/d/1Kb_XTnuElVmg7jjDRLK13aL--DV3xfVq/view?usp=sharing Price action trading is not hard we are simply trying to discover the ideal entry level for day trading or scalping. Guessing if a strategy is a winner in day trading was hard until I discovered that all can be backtested in python. So all in all we are trying to find the best price action trading strategy that would change the way we trade without going through endless trading course. Backtesting a strategy is the way to go using algorithmic trading features. Python libraries can provide a powerful tool for algorithmic trading and strategies backtesting. Good luck! 00:00 Moving Average Introduction 00:40 Candles Price Action Entry Positions 01:45 Key Price Action Idea 03:00 Python Code For Backtesting 09:00 New Candle Wick Limit 10:20 New Backtesting Results