{"repo":"uberdeveloper/fastbt","free":true,"listed":false,"github":"https://github.com/uberdeveloper/fastbt","clone":"git clone https://github.com/uberdeveloper/fastbt.git","description":"A simple framework for quick and dirty backtesting","language":"Python","stars":27,"topics":["finance","python3","backtesting"],"license":"MIT","category":"trading","readme_excerpt":"Introduction fastbt is a simple and dirty way to do backtests based on end of day data, especially for day trading. The main purpose is to provide a simple framework to weed out bad strategies so that you could test and improve your better strategies further. It is based on the assumption that you enter into a position based on some pre-defined rules for a defined period and exit either at the end of the period or when stop loss is triggered. See the rationale for this approach and the built-in assumptions. fastbt is rule-based and not event-based. If your strategy gets you good results, then check them with a full featured backtesting framework such as zipline or backtrader to verify your results. If your strategy fails, then it would most probably fail in other environments. This is alpha Most of the modules are stand alone and you could use them as a single file. See embedding for more details Features - Create your strategies in Microsoft Excel - Backtest as functions so you can parallelize - Try different simulations - Run from your own datasource or a database connection. - Run backtest based on rules - Add any column you want to your datasource as formulas Installation fastbt requires python =3.6 and can be installed via pip Quickstart Fastbt assumes your data have the following columns (rename them in case of other names) - timestamp - symbol - open - high - low - close - volume would return a dataframe with all the trades. And if you want to see some metrics You now ","default_branch":null,"files":null,"tree":[],"storefront":"/r/uberdeveloper","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/uberdeveloper/fastbt/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}