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Pairs Trading in CTA trending strategy backtesting, by iterateing parameters on the last 6 months and pick the optimal one, then start trade on the next month
Bayesian regression for latent source model and Bitcoin
TensorFlow code and pre-trained models for BERT
Software in C and data files for the popular GloVe model for distributed word representations, a.k.a. word vectors or embeddings
Python library for processing Chinese text
Replicated Trading Strategy in "Bayesian regression and Bitcoin" by Shah and Zhang (2014)
Bitcoin price prediction algorithm using bayesian regression techniques
A very light matching engine in Python.
Multi-agent Reinforcement Learning for Liquidation Strategy Analysis. ICML 2019 AI in Finance.
FinRL: Financial Reinforcement Learning. 🔥
Performing a trading strategy using deep deterministic policy gradients to know when to buy, hold or sell stocks in a virtual environment that simulates stock prices.
Automated trading agent for an OpenAI Gym enviroment with multiple simultaneous trading of symbols(currency pairs) using separate action and observation timeseries.
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
Source code for paper:Multi-agent reinforcement learning for liquidation strategy analysis
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
The work aims to explore Value based, Deep Reinforcment Learning (Deep Q-Learning and Double Deep Q-Learning) for the problem of Optimal Trade Execution. The problem of Optimal Trade Execution aims…
A parallel framework for population-based multi-agent reinforcement learning.
MichaelKarpe / abides
Forked from abides-sim/abidesABIDES: Agent-Based Interactive Discrete Event Simulation
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Advances in Financial Machine Learning