Pinned Repositories
-chanlun
缠论量化，包含严格笔，线段作为最低级别，中枢的构成，级别的扩展，第一二三类买卖点，同级别分解的，背驰的判断，区间套
Adv_Fin_ML_Exercises
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
alphagen
Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.
AlphaNet-v1
alphasickle
多因子指数增强策略/多因子全流程实现
AmericanOptionPINN
chatgpt
CorrLoss
CTA_summary
Testing trading signals of commodity futures
deep_learning_alchemy
深度学习炼丹笔记，包含深度学习数学基础知识、神经网络基础部件详解、构建 CNN 网络总结，深度学习炼丹策略，以及如何实现深度学习推理框架实战。
wzy1019288's Repositories
wzy1019288/AmericanOptionPINN
wzy1019288/chatgpt
wzy1019288/deep_learning_alchemy
深度学习炼丹笔记，包含深度学习数学基础知识、神经网络基础部件详解、构建 CNN 网络总结，深度学习炼丹策略，以及如何实现深度学习推理框架实战。
wzy1019288/Adv_Fin_ML_Exercises
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
wzy1019288/alphagen
Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.
wzy1019288/AlphaNet-v1
wzy1019288/CorrLoss
wzy1019288/deephedging
Implementation of the vanilla Deep Hedging engine
wzy1019288/DynamicSocialNetworkFraudDetection
“DynamicSocialNetworkFraudDetection”（动态社交网络反欺诈检测）是一个专注于动态社交网络中金融欺诈检测的图神经网络项目。该项目利用来自企业不同业务时间段的数据集，构建了一个代表用户复杂关系的全连通有向动态图。本项目的目标是通过利用图神经网络模型，包括但不限于GAT、GraphSAGE以及新型的GEARSage，分析用户间的复杂互联关系并预测欺诈活动。我们的工作通过深入理解社交网络的演化性质并应用最前沿的机器学习技术，增强了金融欺诈检测的能力。
wzy1019288/EarnHFT
wzy1019288/FactorVAE
Reproduce AAAI22-FactorVAE
wzy1019288/Finite-Difference-in-Option-Pricing
Use the Finite Difference method to price European, American and Bermudan options.
wzy1019288/FinRL
A Deep Reinforcement Learning Framework for Automated Trading in Quantitative Finance. NeurIPS 2020. 🔥
wzy1019288/GPlearn_finiance_stock_futures_extension
This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market.
wzy1019288/leedl-tutorial
《李宏毅深度学习教程》，PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases
wzy1019288/Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
wzy1019288/MachineSmiling
wzy1019288/MarketGAN
Implementing a Generative Adversarial Network on the Stock Market
wzy1019288/PairsTrading
A low frequency statistical arbitrage strategy
wzy1019288/pfhedge
PyTorch-based framework for Deep Hedging
wzy1019288/PortfolioManagement
wzy1019288/pysabr
SABR model Python implementation
wzy1019288/QUANTAXIS
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
wzy1019288/quantstats
Portfolio analytics for quants, written in Python
wzy1019288/reinforcement-learning-trading-commodity-futures
Streamline data processing, agent training and testing implementation for futurers contracts.
wzy1019288/streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io
wzy1019288/Time-Series-Library
A Library for Advanced Deep Time Series Models.
wzy1019288/toolbox
This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms.
wzy1019288/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).
wzy1019288/vnpy_rebalancetrader