Metadata-Version: 1.1
Name: hft
Version: 1.0.4
Summary: High Frequency Portfolio Analytics by PortfolioEffect
Home-page: https://github.com/PortfolioEffect/PortfolioEffectHFT-Python
Author: Aleksey Zemnitskiy, Stephanie Toper, Andrey Kostin
Author-email: aleksey.zemnitskiy@portfolioeffect.com, stephanie.toper@portfolioeffect.com, andrey.kostin@portfolioeffect.com
License: GPL
Download-URL: https://github.com/PortfolioEffect/PortfolioEffectHFT-Python/tarball/1.0.4
Description: # Portfolioeffect hft Package for Python 
        
        Python API to PortfolioEffect cloud service for backtesting high frequency trading (HFT) strategies, 
        intraday portfolio analysis and optimization. Includes auto-calibrating model pipeline for market
        microstructure noise, risk factors, price jumps/outliers, tail risk (high-order moments) and price 
        fractality (long memory). Constructed portfolios could use client-side market data or access HF 
        intraday price history for all major US Equities.
        
        ## Package Installation
        
        	python setup.py install
        
        ## License
        
        This package is released under the GPLv3 license. See the file LICENSE.
        
        Usage of this package with PortfolioEffect services shall be subject to the [Terms of Service][PortfolioEffect Terms].
        
        ## Copyright
        
        Copyright &copy; 2015 PortfolioEffect
        
        [PortfolioEffect Terms]: https://www.portfolioeffect.com/docs/terms
        
        
Keywords: hft,trading,backtest,risk,microstructure
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Office/Business :: Financial :: Investment
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
