Metadata-Version: 2.1
Name: crypto_empyrical
Version: 1.0.4
Summary: crypto_empyrical is a fork of Quantopian's Empyrical package modified to work for 24/7 markets of cryptocurrency
Home-page: https://github.com/jesse-ai/crypto-empyrical
Maintainer: Jesse.Trade
Maintainer-email: info@jesse.trade
License: Apache License, Version 2.0
Description: [![PyPI](https://img.shields.io/pypi/v/crypto_empyrical?color=%234ec726&style=flat-square)](https://pypi.org/project/crypto_empyrical/)
        
        # crypto_empyrical
        
        crypto_empyrical is a fork of Quantopian's Empyrical package modified by [Jesse](https://jesse.trade) to work for 24/7 markets of cryptocurrency. 
        
        ## Table of Contents
        
        - [Installation](#installation)
        - [Usage](#usage)
        - [Support](#support)
        - [Contributing](#contributing)
        - [Testing](#testing)
        
        ## Installation
        ```
        pip install crypto_empyrical
        ```
        
        ## Usage
        
        Simple Statistics
        ```python
        import numpy as np
        from crypto_empyrical import max_drawdown, alpha_beta
        
        returns = np.array([.01, .02, .03, -.4, -.06, -.02])
        benchmark_returns = np.array([.02, .02, .03, -.35, -.05, -.01])
        
        # calculate the max drawdown
        max_drawdown(returns)
        
        # calculate alpha and beta
        alpha, beta = alpha_beta(returns, benchmark_returns)
        
        ```
        
        Rolling Measures
        ```python
        import numpy as np
        from crypto_empyrical import roll_max_drawdown
        
        returns = np.array([.01, .02, .03, -.4, -.06, -.02])
        
        # calculate the rolling max drawdown
        roll_max_drawdown(returns, window=3)
        
        ```
        
        Pandas Support
        ```python
        import pandas as pd
        from crypto_empyrical import roll_up_capture, capture
        
        returns = pd.Series([.01, .02, .03, -.4, -.06, -.02])
        
        # calculate a capture ratio
        capture(returns)
        
        # calculate capture for up markets on a rolling 60 day basis
        roll_up_capture(returns, window=60)
        ```
        
        ## Testing
        - install requirements
          - "nose>=1.3.7",
          - "parameterized>=0.6.1"
        
        ```
        ./runtests.py
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Provides-Extra: dev
