Technical_Analysis_and_Feature_Engineering
Financial analysis project
Analyzing and applying machine learning techniques to financial markets using feature engineering and technical indicators.
Feature Engineering and Feature Importance in Machine Learning for Financial Markets
122 stars
3 watching
34 forks
Language: Jupyter Notebook
last commit: 9 months ago
Linked from 1 awesome list
algorithmic-tradingfeature-engineering
Related projects:
Repository | Description | Stars |
---|---|---|
jmrichardson/tuneta | Automates optimization of technical indicators for machine learning models in finance | 413 |
sdcoffey/techan | A Go library for analyzing financial data and building trading strategies using technical indicators | 839 |
lastancientone/stock_analysis_for_quant | A comprehensive project providing various tools and techniques for analyzing financial data and developing trading strategies | 1,686 |
juliaquant/markettechnicals.jl | Tools and algorithms for analyzing financial market data | 127 |
giuseppec/featureimportance | A tool to assess feature importance in machine learning models | 33 |
jrmeier/fast-trade | A Python library for building and backtesting trading strategies using technical analysis indicators. | 377 |
dysonance/indicators.jl | A Julia package offering efficient implementations of many technical analysis indicators and algorithms. | 216 |
lastancientone/deep_learning_machine_learning_stock | An in-depth analysis and experimentation of stock market prediction using machine learning and deep learning techniques. | 1,254 |
vivekpa/aialpha | This project trains machine learning models to predict stock returns using various algorithms and techniques. | 1,734 |
greyblake/ta-rs | A Rust library providing technical analysis indicators for financial data | 694 |
malhartakle/mastersdissertation | An experimental project comparing different machine learning algorithms and ensemble methods for predicting stock market trends. | 1 |
firmai/machine-learning-asset-management | A collection of machine learning models and techniques for portfolio optimization and trading strategy development in asset management. | 1,686 |
amv-dev/yata | A Rust-based technical analysis library providing indicators and methods for trading and financial analysis | 330 |
lacava/few | Automates feature engineering by using genetic programming to select the most useful features for machine learning models. | 51 |
iamjinlei/go-tart | Provides efficient streaming updates of technical indicators for financial analysis | 58 |