gym-continuousDoubleAuction VS QuantitaveFinanceExamplesPy

Compare gym-continuousDoubleAuction vs QuantitaveFinanceExamplesPy and see what are their differences.

gym-continuousDoubleAuction

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. (by ChuaCheowHuan)
multi-agent-reinforcement-learning gym-environment limit-order-book high-frequency-trading Ray rllib market-microstructure financial-engineering self-play double-auction Ppo zero-sum-games zero-sum quantitative-finance quantitative-trading marl n-player Lstm
Source Code
chuacheowhuan.github.io
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QuantitaveFinanceExamplesPy

Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir). (by mrtkp9993)
quantitative-finance Python Quant quantitative-trading stock-market stock-analysis portfolio-optimization market-data
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gym-continuousDoubleAuction QuantitaveFinanceExamplesPy
5 1
136 38
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0.0 0.0
over 1 year ago over 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License GNU General Public License v3.0 only
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gym-continuousDoubleAuction

Posts with mentions or reviews of gym-continuousDoubleAuction. We have used some of these posts to build our list of alternatives and similar projects.

QuantitaveFinanceExamplesPy

Posts with mentions or reviews of QuantitaveFinanceExamplesPy. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing gym-continuousDoubleAuction and QuantitaveFinanceExamplesPy you can also consider the following projects:

recurrent-ppo-truncated-bptt - Baseline implementation of recurrent PPO using truncated BPTT

quantstats - Portfolio analytics for quants, written in Python

alpha-zero-general - A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Finding-Alpha-with-AI - A 3 part series of Jupyter notebooks to help one find alpha in the stock market with AI

FinanceExamplesPy - Financial analysis, algorithmic trading, portfolio optimization examples with Python (DISCLAIMER - No Investment Advice Provided, YASAL UYARI - Yatırım tavsiyesi değildir). [Moved to: https://github.com/mrtkp9993/QuantitaveFinanceExamplesPy]

thesis-computational-artificial-market - Artificial stock market (ASM) with Julia language.

SGX-Full-OrderBook-Tick-Data-Trading-Strategy - Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Empyrial - AI and data-driven quantitative portfolio management library for portfolio risk and performance analysis 投资组合管理

gym-continuousDoubleAuction vs recurrent-ppo-truncated-bptt QuantitaveFinanceExamplesPy vs quantstats gym-continuousDoubleAuction vs alpha-zero-general QuantitaveFinanceExamplesPy vs qlib gym-continuousDoubleAuction vs Finding-Alpha-with-AI QuantitaveFinanceExamplesPy vs FinanceExamplesPy gym-continuousDoubleAuction vs FinanceExamplesPy QuantitaveFinanceExamplesPy vs thesis-computational-artificial-market gym-continuousDoubleAuction vs SGX-Full-OrderBook-Tick-Data-Trading-Strategy QuantitaveFinanceExamplesPy vs Empyrial QuantitaveFinanceExamplesPy vs Finding-Alpha-with-AI