StudyQuant股票量化交易系统

sq-stockquant is an algorithmic trading library for stock assets written in Python. It allows trading strategies to be easily expressed and backtested against historical data (with daily and minute resolution), providing analytics and insights regarding a particular strategy's performance. sq_stockquant also supportslive-trading of stoc -assets starting with many exchanges (tonghuashun) with more being added over time.

Sq-StockQuant 是一套基于Python的量化交易框架，帮助个人/机构量化人员进行股票量化交易。框架具有回测/实盘交易功能。 StudyQuant股票量化系统支持多个数据源的渠道的下载, 量化策略回测，选股+择时策略，并有本地化的自动交易解决方案，目前暂时未开源，主要供股票量化训练营及定制用户学习使用，购买Python与股票量化投资的课程。

Features

环境准备

• 支持的系统版本：Windows 7以上/Windows Server 2008以上/Ubuntu 18.04 LTS
• 支持的Python版本：Python 3.6 64位/ 3.7+

Installation

Windows 使用要安装Python，激活环境，进入studyquant/install目录下的运行install.bat 安装依赖库 安装dependencies 中的依赖库

Quickstart

数据下载

from studyquant import *
sqd = SqData()
alldata = sqd.get_all_market(False)
print(alldata)
print(alldata['000002'])

策略回测

from studyquant import *
ak = AkData()
symbol= "000001"
start_date = '20000101'
end_date = '20220301'
smabt = SMAVectorBacktester(symbol, 42, 252,start_date, end_date)

print(smabt.run_strategy())
# 设置参数
smabt.set_parameters(SMA1=20, SMA2=100)
# 运行策略
print(smabt.run_strategy())
# 优化参数
smabt.optimize_parameters((5, 56, 4), (20, 300, 4))

实盘交易

api = SqStockApi(path, broker)
sqdata = SqData()
strategy = MultFactorStrategy(api,sqdata)
strategy.run()

股票量化课程介绍

1、Python量化投资与股票投资

2、量化投资实战训练营 （Stock/Crypto）

量化训练营介绍

课程提供 社群答疑、文档查询、样例代码、 视频，直播

网校链接：网校链接

各课程试听课链接：课程试听课

有机会来支持一下哈。

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