Metadata-Version: 2.1
Name: fastbt
Version: 0.1.0
Summary: A simple framework for fast and dirty backtesting
Home-page: https://github.com/uberdeveloper/fastbt
Author: UM
Author-email: uberdeveloper001@gmail.com
License: MIT license
Keywords: fastbt,backtesting,algo trading
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Utilities
Description-Content-Type: text/markdown
Requires-Dist: pandas (>=0.23.0)
Requires-Dist: sqlalchemy (>=1.1.18)

# 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 itinassumptions.

If your strategy gets you good results, then check them with a full featured backtesting framework such as [zipline](http://www.zipline.io/) or [backtrader](https://www.backtrader.com/) to verify your results.
If your strategy fails, then it would most probably fail in other environments.

This is very much **alpha**

# Quickstart

```python
import pandas as pd
from datasource import DataSource
```

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History
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0.1.0 (2018-10-13)
------------------

* First release on PyPI.


