Financial technical analysis in python [closed]
Here are a few thoughts... I have only used Numpy, Scipy, and Matplotlib for financial calculations.
- py-fi - very basic financial functions
- fin2py - financial tools
- Numpy/Scipy - covers all of the statistics basics
- Matplotlib - plotting financial functions
- RPy - a Python interface to R allowing use of R libraries
- ystockquote - Python API for Yahoo! Stock Data
- QuantLib - Open source library (supposedly has Python Bindings)
- PyFinancial - Docs in Spanish
- PyMacLab - "Series of classes useful for conducting research in dynamic macroeconomics"
- TSDB - for storing large volumes of time series data
- PyVol - volatility estimation of financial time series
There is also a Computational Finnance Course on Coursera.org.
They use a Python Open Source Library called QSTK (QuantSoftware ToolKit).They have a bunch of tutorials on the wiki page and you can always take the courseif you want to learn more.
For convenience I copied the description from the wiki page below:
QSToolKit (QSTK) is a Python-based open source software frameworkdesigned to support portfolio construction and management. We arebuilding the QSToolKit primarily for finance students, computingstudents, and quantitative analysts with programming experience. Youshould not expect to use it as a desktop app trading platform.Instead, think of it as a software infrastructure to support aworkflow of modeling, testing and trading.
Scroll through the Gallery to see the sorts of things you can do easily with QSTK.If you are in a hurry, you can skip to the QSToolKit_Installation_Guide.Key components of QSTK are:
- Data: A data access package that enables fast reading of historical data (qstkutil.DataAccess).- Processing tools: Uses pandas, a Python package designed for time series evaluation of equity data.- Portfolio optimization: Using the CVXOPT library.- Event studies: An efficient event analyzer, Event_Profiler.- Simulation: A simple backtester, quicksim, that includes transaction cost modeling.