How I Maximize Market Returns to a Win Rate of 65% with Volatility-Bollinger Bands

Implementing and backtesting techniques can be a useful tool for traders to evaluate the viability of their trading ideas in the realm of stock trading. The Volatility using Bollinger Bands method is one of them. We will go into detail about this strategy in this article and show you how to put it to the test using Python.   Let’s quickly review the data preparation procedure before moving on to the strategy itself. In a previous article titled “Backtesting Stock Trading Strategies Using Python (Data Preparation),” we discussed how to get online OIH stock data and create files with data in several timeframes, including 1-minute, 5-minute, 15-minute, 1-hour, and 1-day intervals. <h2> </h2> These files will serve as the input for testing our Volatility with Bollinger Bands strategy. We also prepared an environment to test any strategy generating buy and sell signals which we are going to use to generate this backtest. <a href="https://medium.com/@diegodegese/unlocking-market-profits-achieving-a-65-win-rate-with-the-volatility-bollinger-bands-strategy-c53cdadce99b">Visit Now</a>