Stock Prediction Models — AI Agent Review & Live Stats

Live GitHub stats, community sentiment, and trend data for Stock Prediction Models. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Apr 16, 2023 • Sentiment updated: Mar 17, 2026

GitHub Statistics

• GitHub Stars: 9,280
• Forks: 3,020
• Open Issues: 47
• Primary Language: Jupyter Notebook
• License: Apache-2.0
• Weekly Star Velocity: +11 stars/week

Community Sentiment

Community Buzz: The community is actively engaged with the project, with many contributors and frequent updates. The project's focus on deep learning and stock market prediction has sparked interesting discussions.

Why Stock Prediction Models Stands Out

Stock-Prediction-Models is different from other stock forecasting tools because it provides a wide range of pre-built deep learning models and agent models that can be used for trading and portfolio optimization. The project's focus on deep learning and agent-based modeling sets it apart from other projects that rely on traditional machine learning approaches. Additionally, the project's use of Monte Carlo simulations and data exploration tools provides a comprehensive framework for analyzing and predicting stock market trends.

Built With

Build a stock forecasting model that predicts prices with high accuracy — Stock-Prediction-Models provides pre-built deep learning models for stock forecasting, Build a trading bot that automates buy and sell decisions — Stock-Prediction-Models includes various agent models for trading, such as the Turtle-trading agent and Moving-average agent, Build a portfolio optimization tool that maximizes returns — Stock-Prediction-Models includes a portfolio optimization simulation that can be used to optimize investment portfolios, Build a risk analysis tool that simulates different market scenarios — Stock-Prediction-Models includes Monte Carlo simulations that can be used to analyze risk and predict potential outcomes, Build a market trend analysis tool that identifies patterns in stock prices — Stock-Prediction-Models includes data exploration tools that can be used to analyze and visualize stock market data

Getting Started

1. Install the required libraries by running `pip install -r requirements.txt`
2. Clone the repository by running `git clone https://github.com/huseinzol05/Stock-Prediction-Models.git`
3. Navigate to the `deep-learning` directory and run `python lstm.ipynb` to train an LSTM model
4. Configure the agent models by modifying the `agent` directory and running `python turtle-agent.ipynb` to train a Turtle-trading agent
5. Try running `python monte-carlo-drift.ipynb` to verify that the Monte Carlo simulation works

About

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

Category & Tags

Category: trading

Tags: deep-learning, deep-learning-stock, evolution-strategies, learning-agents, lstm, lstm-sequence, monte-carlo, monte-carlo-markov-chain, seq2seq, stock-market, stock-prediction-models, stock-price-forecasting, stock-price-prediction, strategy-agent, trading-bot

Market Context

This project is relevant to the growing field of AI-powered stock market analysis and prediction.