DeepMarket is a framework for performing Limit Order Book simulation with Deep Learning. This is also the official repository for the paper 'TRADES: Generating Realistic Market Simulations with Diffusion Models'.
Rust Market Simulation Library with a Python API
End-to-end RL trading framework with PPO agent, self-attention neural network, custom Gym environment, and advanced backtesting.
A back-tester for testing stock trading strategies on historical data
MarketGPT: Developing a Pre-trained transformer (GPT) for Modeling Financial Time Series
Contingency Random Number Generator — numbers with controllable fat tails, volatility clustering, and scale convergence
{Frontend/Backend} Simulate stock trading and investment strategies with real-time data and portfolio management features.
SHS: Signal Herding Strength ABM for studying prediction-market signals and trader herding
SHS: Signal Herding Strength ABM for studying prediction-market signals and trader herding
Agent-based market adoption simulator with Bass diffusion model and JTBD analysis
Code for paper "Gradient-assisted calibration for financial agent-based models"
A simple GUI for bristol stock exchange a minimal simulation of a limit order book financial exchange
Interactive crypto market simulator that demonstrates how news, panic, and investor psychology can affect price movements.
AHMAPPO_LLM is an AI trading system using ML and RL to predict stocks. It processes data via ingestion, cleaning, and feature engineering. The reproducible pipeline enables end-to-end trading strategy development. Important files - model trainer, builder, AHMAPPO AI agent building, etc. are in private repo to preserve originality.
Deterministic, event-driven Core, with explicit risk management, order state machines, queue semantics, and research orchestration.
bid/ask market engine
Financial market simulations combining stochastic models (GBM, Heston) with agent-based modeling. Explores price dynamics through different trader behaviors - fundamentalists, chartists, noise traders, contrarians, and institutional players. Built with Python for anyone interested in quantitative finance and computational economics.
A hardened version of ABIDES-JPMC, with reworked API, configuration, and performance
Energy market backtesting framework for European power trading. Purpose-built for DA auctions and intraday continuous markets with 15-minute MTU support. Write once, run in backtest, paper, and live modes without code changes.
A functional reactive trading simulator built in OCaml.
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