anacaballero / ML-FinanceLinks
Calculate technical indicators from historical stock data Create features and targets out of the historical stock data. Prepare features for linear models, xgboost models, and neural network models. Use linear models, decision trees, random forests, and neural networks to predict the future price of stocks in the US markets. Evaluate performance…
☆33Updated 6 years ago
Alternatives and similar repositories for ML-Finance
Users that are interested in ML-Finance are comparing it to the libraries listed below
Sorting:
- Quantitative analysis of fundamentals in quarterly reports by Machine Learning☆23Updated 5 years ago
- applications for risk management through computational portfolio construction methods☆43Updated 5 years ago
- XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project atte…☆44Updated 6 years ago
- Testing trading signals of commodity futures☆17Updated 5 years ago
- Stock Prediction with XGBoost: A Technical Indicators' approach☆31Updated 6 years ago
- Portfolio Construction Functions under the Basic Mean_Variance Model, the Factor Model and the Black_Litterman Model.☆41Updated 7 years ago
- The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using t…☆61Updated 4 years ago
- keywords - Kmeans Clustering, Tsne, PCA, Indian Stocks, Johansen test☆32Updated 7 years ago
- Built a smart beta portfolio and compared it to a benchmark index by calculating the tracking error. Built a portfolio using quadratic pr…☆68Updated 6 years ago
- This project is to apply Copula Function to pair trading strategy both in American stock market.☆30Updated 7 years ago
- Having effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management…☆52Updated 5 years ago
- ARIMA & GARCH models for stock price prediction☆24Updated 5 years ago
- Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions.☆71Updated 2 years ago
- Design your own Trading Strategy☆38Updated last year
- Deep Reinforcement Learning Framework for Factor Investing☆30Updated 2 years ago
- Pairs trading strategy that includes a research pipeline for identifying and selecting pairs. Tests all possible pairs in a universe for …☆35Updated last year
- factor return calculation, mean-variance / Black&Litterman portfolio optimization, risk decomposition☆31Updated 6 years ago
- The Implied Volatility Smirk of Individual Option in S&P 500 Shows its Underlying Asset’s Return☆38Updated 5 years ago
- Trend Prediction for High Frequency Trading☆42Updated 3 years ago
- In this repository, the goal is to predict the tick direction of a stock based on its current order book and trade data. A LSTM Neural Ne…☆21Updated 4 years ago
- Using Python and Tushare financial database☆29Updated last year
- Financial risk analysis on a stocks portfolio through the VaR (Value at Risk), using Monte Carlo Simulation and Multiple Linear Regressio…☆22Updated 5 years ago
- The NLP News Sentiment Factor Trading Strategy for a Portfolio of S&P 500 Stocks☆12Updated 5 years ago
- Mean-Variance Optimization using DL (pytorch)☆32Updated 3 years ago
- ☆19Updated 8 years ago
- Mean Variance (Markowitz) Portfolio Optimization and Beyond☆64Updated last year
- Quantitative Finance & Algorithmic Trading in Python course of Udemy☆11Updated 8 years ago
- Developing a long/short equity investment portfolio with Machine Learning predictions using data acquired from web-scraping. Flatiron Mod…☆40Updated 4 years ago
- kennedyCzar / STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDAForecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning …☆135Updated 3 years ago
- Optimizing the Pairs-Trading Strategy using Deep Reinforcement Learning with Trading and Stop-loss Boundaries☆13Updated 4 years ago