Popular GitHub Repositories for Stock Market

? A curated list of awesome LLMs & deep learning strategies & tools in financial market.

:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

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

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

Programs for stock prediction and evaluation

playing idealized trading games with deep reinforcement learning

股市情感分析

在A股(股票)市场上训练强化学习交易智能体

Examples of python neural net and ML stock prediction methods with sample stock data.

Trading Environment(OpenAI Gym) + PPO(TensorForce)

A Deep Reinforcement Learning Framework for Stock Market Trading

Reinforcement Learning for Stock Market Prediction

Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading." In Findings of ACL2021

Stock price prediction using a Temporal Fusion Transformer

Scrape, analyze & visualize stock market data for the S&P500 using Python. Build a basic trading strategy using machine learning to assess company performance and determine buy, sell, hold. Read me & instructions available in Spanish. This is a working repo, with plans to expand the project from technical analysis to fundamental analysis.

GANs for Time series analysis (Synthetic data generation, anomaly detection and interpolation), Hypertuning using Optuna, MLFlow and Databricks

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement learning algorithm. We implement a sentiment analysis model using a recurrent convolutional neural network to predict the stock trend from the financial news. The objective of this paper is not to build a better trading bot, but to prove that reinforcement learning is capable of learning the tricks of stock trading.

Stock Market Prediction & Trading Bot using AI