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This project is a Stock Trader trained to trade stocks from the S&P 500. It was made using a Deep Q-Learning model and libraries such as TensorFlow, Keras, and OpenAI Gym. It was trained on data from 2006-2016, cross validated on data from 2016-2018, and tested on data from 2018-2021

Learning Quant Trading and Financial Repository

Q Learning automated bitcoin trader on Bitmex

QuantTraderDL combines quantitative finance and AI, using TFT models to forecast major indices (S&P 500, Nasdaq, IBEX 35, Dow Jones, EURO STOXX 50) and optimize portfolios. A DRL trading bot adapts to market changes to maximize returns and manage risk with prediction confidence and trend detection.

Trading Bitcoin with Deep Reinforcement Learning

Stock Backtester and Analysis application for EOD (End-of-day) data.

Binance Quantitative Trader is an advanced low latency trading engine designed to automate and optimize trading strategies on the Binance exchange.

Stock investment can be one of the ways to manage one’s asset. Technical analysis is sometimes used in financial markets to assist traders make buying and selling decisions [1]. Many technical analysis trading rules are deterministic trading policies. [2] uses genetic algorithm to find technical ... Read more

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tabular q learning for trading