A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
- trading
- trading-bot
- trading-systems
- cryptocurrency
47,133 repositories indexed
25–40 of 40 · Most stars
A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine
Open Source Algorithmic Trading Engine
Predicting price trends in cryptomarkets using an lstm-RNN for the use of a trading bot
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Trading environnement for RL agents, backtesting and training.
Building a population of models that trade crypto and mutate iteratively
AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
Parameter Optimization for Lean Algorithms
AI crypto trading bot with deep neural network (84.9% accuracy, 25 coins). BiLSTM + Attention trained on GPU. Bybit, Binance, OKX, Gate.io. Free cloud or self-hosted.
My algorithmic trading strategies with the Gekko cryptocurrency trading bot.
AI-Powered Quantitative Trading Engine — Evolve strategies with genetic algorithms
Stock price prediction using a deterministic algorithm inspired by LSTM, focusing on pattern recognition in historical data.
Wisp CLI — Interactive trading platform for backtesting and live trading across spot, perpetual futures, options, and prediction markets
Open BTC 5-minute prediction market sandbox for AI agents — register with one API call, get 1,000 test credits, and place a live order
Simple, modern ETH backtesting project using Pandas/Numpy: data prep, MA signals, portfolio simulation, and result visualization.
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.