vectorbt is the new Python Backtesting framework I’m using these days. I really like it so I decided to share an example of the simplest strategy built in the vecotrbt from scratch, so you can understand why I like it. This library is developed mostly in Pandas and Numpy so it should be really fast Running simple and fast backtests in Python with vectorbt Read More →
Portfolio calculation and optimizations are very basic tasks in Quantitative Finance. But people who are just started programming might have issues with them. Empyrial library in Python might be a solution for simple portfolio tasks. It encloses data downloading and all computations behind a super simple interface. You can literally code optimization in 1-2 lines Empyrial – The Easiest Way to Optimize Portfolios in Python Read More →
Portfolio calculation and optimizations are very basic tasks in Quantitative Finance. But people who are just started programming might have issues with them. Empyrial library in Python might be a solution for simple portfolio tasks. It encloses data downloading and all computations behind a super simple interface. You can literally code optimization in 1-2 lines Empyrial – The Easiest Way to Optimize Portfolios in Python Read More →
If you’re even slightly interested in trading or investing you probably heard about WallStreetBets. I’s a huge community of retail traders on Reddit with 9.5M followers. This community can influence the market quite significantly these days. Here is a chart of Gamestop, the most famous stock in the community. As you can see community triggered Paring WallStreetBets in Python in Few Lines of Code (Reddit API) Read More →
Pretty often it can be interesting to backtest a strategy across several timeframes. In the simple case you want to have a signal on one timeframe and just want a confirmation for another higher timeframe. In this video, I will show you how easy it is to use multiple timeframes in Backtrader backtests in Python. Calculating Multi-Timeframe Backtests in Python with Backtrader Read More →
Pretty often you want to backtest your strategy on multiple instruments and you’re interested in how it will work together. In this article, I will show you how easy it is to do that in Python using Backtrader. To load multiple data sources to Backtrader you can use the following code: The idea is pretty Running Backtesting for Universe of Stocks in Python with Backtrader Read More →
ByBit is of the most popular crypto exchanges on the market, and many people trade on it. It’s important to use historical data to backtest trading strategies. So I decided to create an article showing you how you can download historical bars from ByBit with Python. Libraries used: Function to get bars from Bybit: Example Getting Historical Bars from ByBit API with Python Read More →
Quite often, when you work on advanced strategies only prie is not enough for you. You might want to use correlations between stocks, sentiment data, fundamentals, and so on. In this article, I will show you how you can use multiple data sources in Backtrader Strategies. So let’s assume I want to add additional conditions Using Multiple Datasets in Backtrader’s Strategies Read More →
Pretty often strategies you backtest have quite a lot of parameters and it’s pretty hard to find out which parameters work the best. Of course, you can change parameters manually and run backtest multiple times. But there are better ways to do that. In this article, I will show you how you run multiple backtests Optimizing Strategy Backtesting in Python with Backtrader Read More →
Python is a very powerful language for backtesting and quantitative analysis. You’re free to use any data sources you want, you can use millions of raws in your backtesting easily. In this article, I show an example of running backtesting over 1 million 1 minute bars from Binance. Including libraries: Function to get data from Running a Massive Backtest on 1M Bars in Python with Backtrader Read More →
