Legacy Main Page
From Quant Fund Software Wiki
Contents |
Legacy
This page is old. You probably want to be here QuantSoftware_ToolKit
The QuantSoftware ToolKit
QSToolKit (QSTK) is a Python-based open source software framework designed to support portfolio construction and management. We are building the QSToolKit primarily for finance students, computing students, and quantitative analysts with programming experience. You should not expect to use it as a desktop app trading platform. Instead, think of it as a software infrastructure to support a workflow of modeling, testing and trading. Our initial implementation targets:
- Daily trading (versus intra-day high frequency trading);
- Publicly traded equities for which historical data are available;
- US market calendars (e.g. NYSE open/close).
Having said that, the tool kit can easily be adapted for other trading regimes. You might want to scan our Work Flow Guide to see how we intend QSToolKit to be used. That should help you decide whether it would be useful for you.
Documentation
This page is the root page for QSTK documentation. Here are links to information about important modules and APIs:
- QSToolKit Installation Guide for downloads and details on getting up and running.
- pseries module documentation
- QuickSim documentation
- production windows setup here's how we configure our production windows machine
Contributing & Coding Conventions
Contact Tucker Balch to get write access to the SVN repository (the repository is already open for public reading).
Please follow coding conventions described here: http://www.python.org/dev/peps/pep-0008/ . Pay attention to naming conventions please.
We follow pydoc conventions.
Use the text 2FIX as a comment indicating a potential bug. As in:
# 2FIX we may inadvertently divide by zero below x = y / u
Contributors
QSToolKit development began to support CS 8803-FIN: Machine Learning for Trading, a course at Georgia Tech. To date, the main contributors are at Georgia Tech, but we certainly welcome others!
- Architecture/Design: Prof Tucker Balch (GT), Prof Maria Hybinette (UGA).
- Data Import and Conversion: Harikrishna Narayanan (GT, now Yahoo Finance), Shreyas Joshi (GT)
- QuickSim: Drew Bratcher
- Back Tester: Micah X (GT), Melody X (GT), Peter X (GT), Shreyas Joshi (GT)
Courses
- CS 8803-FIN/4803-FIN ML4Trading will be taught Fall 2011 at Georgia Tech
- CS 8803-FIN, 2010SPR8803 was taught Spring and Fall 2010 at Georgia Tech
Resources, Relevant News & Links
- Resources: Additional relevant resources.
- Tucker Balch's blog augmentedtrader.wordpress.com
- WSJ article about AI for trading.
Getting Started with Wikimedia
- User's Guide for information on using the wiki software.
- Configuration settings list
- MediaWiki FAQ
- MediaWiki release mailing list
Links
Older documents [Fund Tools]
