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aggregate-framework

Aggregate Framework是为方便开发人员运用DDD和CQRS**来构建复杂的、可扩展的Java企业应用系统而提供的Java技术框架。该框架提供了Aggregate、Repository、Domain Event等构建块的实现；使用DomainEvent，借助于内建的Disruptor组件，AggregateFramework可使开发人员方便的实现高性能SEDA架构。此外，该框架支持与Spring集成，提供使用 annotation的方式让开发人员方便地为Domain Event定义一个或多个事件处理, 同时可指定事件处理是同步还是异步触发，并支持分布式事务事件; 使用Spring事务管理器管理事务时，支持Unit Of Work数据访问模式以及内建一级缓存以提高访问性能，另也支持可配置的2级缓存。

agriculture_knowledgegraph

农业知识图谱(KG)：农业领域的信息检索，命名实体识别，关系抽取，分类树构建，数据挖掘

algotrading

Algorithmic trading platform for multiple assets

alphagen

Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.

alphaware

tools for alpha research

anomaliesinoptions

In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.

anyquant

A Financial Investment Web Application based on J2EE

asio_benchmark

automatic_factors

autotrade

C++实现，通过不同交易所交易对的差价，进行对冲搬砖。

backtestengine

backtrader-doc-zh

backtrader_bokeh

Use bokeh as the backend, you will get richer plot effects for backtrader

backtrader_ib_insync

Async integration between backtrader and Interactive brokers.

backtrader_strategy

backtradercpp

A High Performance Live Trading and backtesting platform written in C++.

btgym

Scalable, event-driven, deep-learning-friendly backtesting library

cktrader

用于程序化交易的框架

coolercppidiom

cooler c++ patterns like async, event delegate, json auto serialization

cpptrader

High performance components for building Trading Platform such as ultra fast matching engine, order book processor

cppvnpy

data_integration_celery

通过celery定期执行更相关任务，将万得wind，同花顺ifind，东方财富choice、Tushrae、JQDataSDK、pytdx、CMC等数据终端的数据进行整合，清洗，一致化，供其他系统数据分析使用

dataapi

datacore

devilyuan

DevilYuan可视化股票量化系统，支持选股，历史数据自动下载，策略回测及参数优化，实盘交易和常用的统计功能

dl_forfinance

This git repository is based on the work of J.Heaton, N.Polson and J.Witte and their articleDeep Learning for Finance: Deep Portfolios. This paper let us explore the use of deeplearning models for problems in financial prediction and classification. Our goal isto show how applying deep learning methods to these problems can produce betteroutcomes than standard methods in finance or in Machine Learning

doctor

基于知识图谱的分布式智能医疗诊断系统（提供医生机器人的实现方案）（获山东省大学生软件大赛一等奖、山东省大学生移动互联创新创业大赛二等奖、山东省新动能软件创新创业大赛三等奖）

doubanrecommend

基于豆瓣图书的推荐、知识图谱与知识引擎简单构建neo4j

elitequant_cpp

C/C++ 11 High frequency quantitative trading platform. It follows modern design patterns such as event-driven, server/client architect, dependency injection and loosely-coupled robust distributed system. It is self-contained and can be used out of box. At the same time, it serves as server side for other EliteQuant projects.

elitequant_python

Python quantitative trading and investment platform; Python3 based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.