Watch 李贞/Deep-Convolution-Stock-Technical-Analysis

Uses Deep Convolutional Neural Networks (CNNs) to model the stock market using technical analysis. Predicts the future trend of stock selections.

Watch 李贞/stock_selection

some strategy for stock selection, include machine learning, data mining and etc.

Watch 李贞/weighted_stock_selection

Stock Portfolio Performance by Weighted Stock Selection - The project quantitatively predicts the factors that must be given the most and least weights to obtain obtain the highest returns, risk and win-rates while developing a S&P500 portfolio

Watch 李贞/Deep-Learning-Applications-on-multifactor-stocks-selection

Watch 李贞/stockscore

A python project to fetch stock financials/statistics and perform preliminary screens to aid in the stock selection process

Watch 李贞/QTC2019

This program focused on the core concepts and practice of quantitative investment (multi-factor combination analysis, technical analysis CTA strategy, real-time stock selection and timing strategy, etc.).

Watch 李贞/Multi-factor-Stock-Selection

select stock automatically, trade manually

Watch 李贞/Multi-factor-stock-selection-model

A multi-factor stock selection model based on random forest with an average annualized yield of 33.74% from March 2014 to June 2017 when the market index yield was 12.32%.

Watch 李贞/stock_picker

A stock selection and prediction tool for the next day using a variety of stacked LSTM neural networks

Watch 李贞/alphalens

Performance analysis of predictive (alpha) stock factors