https://github.com/westonplatter/ta_scanner
Scanner that finds patterns in stocks/options/futures and discerns future risk/reward. Ie, money ball engine.
https://github.com/westonplatter/ta_scanner
futures interactive-brokers options quantitative-finance statistical-analysis stocks technical-analysis trading
Last synced: 23 days ago
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Scanner that finds patterns in stocks/options/futures and discerns future risk/reward. Ie, money ball engine.
- Host: GitHub
- URL: https://github.com/westonplatter/ta_scanner
- Owner: westonplatter
- License: bsd-3-clause
- Created: 2020-06-13T05:10:59.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2021-08-06T05:21:59.000Z (about 4 years ago)
- Last Synced: 2025-05-12T08:36:46.082Z (5 months ago)
- Topics: futures, interactive-brokers, options, quantitative-finance, statistical-analysis, stocks, technical-analysis, trading
- Language: Jupyter Notebook
- Homepage:
- Size: 175 KB
- Stars: 24
- Watchers: 4
- Forks: 4
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Technical Analaysis Scanner
## Goals
This software attempts to provide a framework that does a combination of
(1) scanning and, (2) backtesting to ask and answer such questions as,
- which instruments have responded well to the 4 hr MACD(26, 9, 12) in the
last quarter?
- which stocks are getting close to their 20/50 Moving Average Crossover, and
of those stocks, which have responded more than +/- 2.5% in the past?
- which instruments in the last 2 weeks after trended out of their opening
ranges? What is the 1 and 2 std dev band for each isntrument at 30 minute
intervals?
## Features
- [x] Pull data from IB
- [ ] Apply various indicators against single or multiple instruments
- [ ] Simple Moving Average Crossover
- [ ] MACD Crossover
### Digging a little deeper
Technical analysis sometimes works, and sometimes doesn't. The goal of this
codebase is to provide means/methods for measuring a universe of instruments
and determine which ones are behaving in line with various TA patterns
It's intended to work differently than a traditional backtester (eg, a
Quantopian and QuantConnect). From what I undestand about backtesting, the
goal is to provide predetermined entry and exit rules, and measure the
results for a single or multiple instruments. This software is didferent
it that it intends to experiment with the entry and exit rules and see how
those adjustments impact results.
## Structure
Core Framework lives in this repo, and your secret sauce parameter/configs,
research findings live in another one.
This repo will feel like a mono repo to many, and focuses on
- downloading market data (currently using IB API Gateway)
- exposing market data
- running multi-variate simulations
- reporting results
## Releasing
Pypi release commands,
```
python setup.py sdist bdist_wheel
twine upload dist/*
```