Stock price forecasting stuff with BERT

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 Network is used as an example of potential solution for such problem.

A Django app to predict realtime stock market prices for NSE India and NYSE using LSTM.

Implementação de uma LSTM para prever fechamento de ações na B3. Scripts para análise e predição de valores.

Forecasting stock prices with Long Short Term Memory (LSTM) architecture

Analyzing and predicting Google's stock prices through detailed data exploration and advanced LSTM models. This project involves data preprocessing, creating time-series sequences, constructing and training LSTM networks, and evaluating their performance to forecast future stock prices utilizing Python and Machine Learning libraries.

Easy to follow stock price analysis on Indian stock data

A personal end-to-end machine learning project that seeks to predict stock prices from economical indicators for a variety of USA-based companies.

Google's New TimesFM 2.5 time-series forecasting engine with automated financial market reports via Ollama, Gemma, and interactive Streamlit UI.

Backtesting software for intraday and daily timeframe SARIMAX forecasting model. Capable of forecasting on any asset class with backtesting capability across various parameter sets customizable by the user.

This repository contains code for implementing both Large Language Models (LLM) and Long Short-Term Memory (LSTM) models in AWS SageMaker Studio Lab. It includes notebooks for LLM-based applications and LSTM models for stock price prediction.

Implementation of Time Series

Deep learning project for forecasting Google stock prices using LSTM. Includes EDA, SMA insights, LSTM tuning, and model performance comparison.

A time series forecasting project using ARIMA, Prophet, and Stacked BiLSTM models to predict Apple stock prices. Includes technical indicators, Fourier transforms, and residual modeling for improved accuracy.

Stock Forecasting

AI-driven multi-agent pharmacy system for autonomous medication ordering, real-time safety validation, stock forecasting, and procurement.

Datasets for the OAMLS paper: Objective-Aware Meta-Learning System for Financial Time Series Forecasting.

Stock Price Forecasting using Python, yfinance and Facebook Prophet — pulled 753 days of live Apple (AAPL) stock data, calculated moving averages and volatility, predicted 30-day price direction with confidence intervals. Built with pandas, matplotlib and Prophet.

Stock prediction model

Multi-model ML dashboard for short-horizon stock price forecasting with technical analysis and news sentiment.