wzy2009520

wzy2009520's Stars

• binary-husky/gpt_academic

  为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。

  Language:Python66.7k8.2k

• OpenRL-Lab/openrl

  Unified Reinforcement Learning Framework

  Language:Python66263

• kieranjwood/trading-momentum-transformer

  This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

  Language:Python491206

• Wenxuan-Zhou/PLAS

  Code for Latent Action Space for Offline Reinforcement Learning [CoRL 2020]

  Language:Python5114

• takuseno/d3rlpy

  An offline deep reinforcement learning library

  Language:Python1.4k244

• hijkzzz/reinforcement-learning-trading-robot

  Trading Robot based on LSTM-PPO

  Language:Python245

• AntoineTheb/RNN-RL

  Experiments with reinforcement learning and recurrent neural networks

  Language:Python11316

• Pandede/FDRNN

  Deep direct reinforcement learning for financial signal representation and trading

  Language:Python2613

• locuslab/TCN

  Sequence modeling benchmarks and temporal convolutional networks

  Language:Python4.2k884

• sfujim/TD3_BC

  Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

  Language:Python33947

• opendilab/DI-engine

  OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

  Language:Python3.2k381

• im1235/ISAC

  Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning

  Language:Python13856

• mmargenot/machine-learning-market-maker

  Implementation of a Bayesian-style market maker in the vein of 'Intelligent Market-Making in Artificial Financial Markets' by Sanmay Das

  Language:Python10253

• fedecaccia/avellaneda-stoikov

  Avellaneda-Stoikov HFT market making algorithm implementation

  Language:Python455139

• comeh/LOB_AlgoTrading

  Some codes used for the numerical examples proposed in https://hal.archives-ouvertes.fr/hal-01514987v2 and https://arxiv.org/abs/1705.01446

  Language:C++2111

• Ryan-Ray-Martin/Market-Maker

  Language:Python83

• bakalex/autohedger

  Paper: https://arxiv.org/pdf/2008.12275.pdf

  Language:Python2610

• ZhengyaoJiang/PGPortfolio

  PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).

  Language:Python1.8k754

• AshengLin/FDRNN

  Deep Direct Reinforcement Learning for Financial Signal Representation and Trading(http://cslt.riit.tsinghua.edu.cn/mediawiki/images/a/aa/07407387.pdf)

  Language:Python2918

• sfujim/BCQ

  Author's PyTorch implementation of BCQ for continuous and discrete actions

  Language:Python602140

• jsg71/Deep-Hedging

  14943

• gavincyi/LightMatchingEngine

  A very light matching engine in Python.

  Language:Python32889

• nkaz001/algotrading-example

  algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex, binance futures, market making)

  Language:Jupyter Notebook28896

• lineojcd/Order-Imbalance-Strategy

  for 18HS MFOEC198 Introduction to systematic risk premia strategies traded at hedge funds (L+E)

  Language:Python134

• algosenses/Order_Imbalance_HFT

  非平衡订单流高频交易模型

  Language:Python10440

• Draichi/T-1000

  :zap: :zap: 𝘋𝘦𝘦𝘱 𝘙𝘓 𝘈𝘭𝘨𝘰𝘵𝘳𝘢𝘥𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘙𝘢𝘺 𝘈𝘗𝘐

  Language:Python17443

• meltjl/RL-Trading

  Language:Python5021

• Kostis-S-Z/trading-rl

  Deep Reinforcement Learning for Financial Trading using Price Trailing @ ICASSP 2019

  Language:Python21845

• sadighian/crypto-rl

  Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent

  Language:Python866237

• rorysroes/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.

  Language:Jupyter Notebook2k673