financial-forecasting

A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物

Simulate anything, for $1 & less than 10 min - Universal Swarm Intelligence Engine

MiroShark: Build Swarm Intelligence Apps in Under 10 Minutes for $1 (2026)

PyTorch implementation of FactorVAE

Hidden Markov Models in stock price forecasting.

FISY is a completely free financial provisional plan template, designed to provide entrepreneurs with a simple and flexible model allowing them to focus on the essentials: building the business model, defining the business strategy and developing the financial plan to better prepare their business plan .

Hybrid Expert Advisor for Forex HFT using EMA/ADX signals and AI forecasts (XGBoost, RF, LSTM). Supports real-time trading and backtesting in MetaTrader 5.

A learning tool to demonstrate the process of financial forecasting, budgeting, and analysis.

Analyze financial news sentiment and its correlation with stock market movements. Use NLP, sentiment analysis, and financial analytics to uncover insights for enhanced financial forecasting and innovative investment strategies.

Simple Finance Forecasting Ai. This Ai Model uses historical price data to forecast future prices. The model is trained on data downloaded from Yahoo Finance using the yfinance library, and predictions are made using a linear regression Ai model from sklearn. The model supports all the symbols supported by Yahoo Finance.

This is the GitHub repository complementing the paper "Forecasting Cryptocurrency Prices Using Deep Learning: Integrating Financial, Blockchain, and Text Data"

A Simple and Universal Swarm Intelligence Engine, Predicting Anything. A Go system built on top of MiroFish

End-to-End Python implementation of "FedSight AI" multi-agent system for Federal Funds Target Rate prediction (NeurIPS 2025 Workshop). Simulates FOMC deliberations using LLMs with Chain-of-Draft reasoning and In-Context Learning. Integrates structured macro indicators with unstructured narratives (Beige Book, Dot Plots).

An comparative investigation into WGAN-GP, CTGAN, TimeGAN and DoppelGANger usage for generating synthetic time series finance data for use in forecasting model

Personal finance agent that decides whether an expense is safe — pay in full, split, use installments, or wait — from a 90-day balance forecast over real transaction history, with a deterministic decision core and a narrow multimodal evidence layer for receipts and messages.

Reproducible Python time-series forecasting benchmark with walk-forward validation, leakage-safe backtesting, classical models, lag-based machine learning, tests, and CI.

Complex modelling and forecast various scenarios against your cloud application

Quickly predict the future prices of financial instruments with a customizable LSTM Recurrent Neural Network

Multi-Container application to dashboard expected returns for global equity markets. Isolate Streamlit frontend, FastAPI backend, and SQLModel database with Docker. Orchestrate with Docker-Compose.

Short-term stock price prediction system using machine learning and time-series models to forecast near-future market movements based on historical financial data.