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README
Apache-2.0

StockAnalysisSystem

This program is designed for Chinese market and Chinese accounting policies (currently). So this document will only provide Chinese version.

Gitee

https://gitee.com/SleepySoft/StockAnalysisSystem

Github

https://github.com/SleepySoft/StockAnalysisSystem

网盘下载:

应网友要求,对于网络访问受限的用户,提供网盘下载(离线数据同样在此下载):
链接: https://pan.baidu.com/s/1Xv3hq09-0-zAgJEk8dd4Gg
提取码: r11g

视频讲解

安装配置:https://www.bilibili.com/video/BV14z411b7AE/
设计与框架:https://www.bilibili.com/video/BV1nK411p7uD/

最近更新内容:

  • 加入分析结果缓存功能,同时analyzer的接口和AnalysisResult也进行了调整

新增数据库SasCache,用以保存计算结果(分析,因子等等)
通过读取缓存,更快得到分析结果

  • 由于图表引入了pyqtgraph,导致pyinstaller打包出现问题,并且尝试py2exe也不成功,故暂停以EXE形式发布Release

  • 更新相应文档

更新计划:

  • 软件已达到最初的目的,为了思考后面怎么做,闭关修炼中,更新减慢

研究类似开源框架
看看阿布的书
学习并尝试引入其它库,例如ta-lib

  • 已有功能持续改进

缓存因子计算结果到数据库,加速因子访问
其它在使用中需要改进的地方
尝试一些量价算法
加入交易方法并提示交易(如网格等)
加入连续运行功能
加入盯盘功能

联系作者

如果有任何意见及建议,或者对此项目感兴趣的,请联系我:
微博:SleepySoft
邮箱:sleepysoft##163.com
QQ群:931499339,进群验证码:SleepySoft
如果遇到BUG,可以给我发邮件,或直接在git上提交issue


股票分析系统(当前规划)

image


本程序的目的:

  1. 自动选择合适的数据抓取模块和数据源下载所需要的数据
  2. 数据抓取模块能够进行有效性检测,并且能够方便地扩充和替换,可以通过适配器接入其它的库
  3. 增加一个数据源以及将其本地化所需的代码应尽可能少
  4. 能进行离线分析
  5. 分析模块(策略模块)应该可以动态扩充和组合
  6. 最终能生成矩阵式excel报告:以证券为行,以分析方法为列,相交点为此分析方法对此证券的评分;最后一列为该证券的总分

使用方法及软件依赖与配置

不想运行,直接看结果

  • 打开analysis_report.xlsx

从网盘下载打包好的程序

  • 需要安装MongoDB,但不需要安装额外的python库
  • 解压后直接运行main.exe
  • 程序第一次启动时,会自动检查配置并弹出配置界面,请按照提示填写即可;如果没有Ts Token,可以胡乱填写
  • 配置界面提供mongodb数据的一键导入功能(数据同样在网盘下载),请分别导入StockAnalysisSystem及StockDaily数据
  • 如果不导入数据,可以通过数据管理界面下载(耗时较长),这种情况下需要正确填写Ts Token)

通过sas库运行程序

  • 安装sas库

pip install StockAnalysisSystem

  • 导入库及运行

import StockAnalysisSystem.api as sas_api
sas_api.main(<your_project_path>)

  • 关于<your_project_path>

# 需要指定一个目录用以存放程序所需的文件,默认为os.getcwd()
<your_project_path>/config.json            # 配置文件
<your_project_path>/Data                     # 数据库目录
<your_project_path>/plugin/Analyze     # 插件目录 - Analyzer
<your_project_path>/plugin/Collector    # 插件目录 - Collector
<your_project_path>/plugin/Extension   # 插件目录 - Extension
<your_project_path>/plugin/Factor        # 插件目录 - Factor

搭建环境并从源码运行

1.1 在当前运行的python环境中安装tushare:pip install tushare
1.2 注册一个tushare的账号:https://tushare.pro/register?reg=271027
1.3 想办法获取500以上的积分(如果没有,无法更新数据,但可以使用离线数据):https://tushare.pro/document/1?doc_id=13
1.4 获取你的token并填入配置界面:https://tushare.pro/document/1?doc_id=39

  • 安装其它依赖库(二种选一)

build.bat -e
pip install -r requirements.txt

  • 运行根目录下的main.py

报告格式说明

报告为表格矩阵,以股票代码为列,以分析算法为行,相交格子为该算法对此股票的评分(0 - 100)

0:VETO
1 -50:FAIL
51 - 75:FLAW
76 - 90:WELL
91 - 100:PASS

结果分为两页,第一页为评分,第二页为分析算法输出的详细信息,以供人工核对及查阅
绿色为PASS,红色为FAIL,灰色为不适用,或因数据缺失导致无法分析
最后一列为总评分,在一行中,只要有一个评分为FAIL,则总评分为FAIL;如果不存在FAIL但存在灰色结果,则总评分为灰色的PASS
当前分析算法还不够完善,结果仅供参考,遇到和自己分析存在偏差的情况,请参阅详细信息并进行人工复核


开发计划:

Analysis

  1. TODO:
  2. 接入更多财务数据

主营业务数据 -> 20200310: Done
限售股解禁: https://tushare.pro/document/2?doc_id=160
回购数据
增减持数据(2000积分暂时没戏): https://tushare.pro/document/2?doc_id=175
2.将因子整合进统一接口进行访问和管理
因子通过query统一获取
因子可以提前计算并缓存
对于未缓存的因子在请求时运行计算过程
以上内容都没想好怎么做,设计上遇到瓶颈,请各位架构大佬赐教OTZ

  1. 接入股东数据

实际控制人数据(巨潮): http://webapi.cninfo.com.cn/#/dataBrowse?id=266

  1. 加入更多分析算法

无实际控制人
去年及未来一年有减持计划

  1. 整合测试入口,执行一个文件即可运行所有测试
  2. 将数据迁移到MongoDB

XList Table

  1. 加入实时数据
  2. 策略参数可配置可保存

Stock Memo(股票笔记)

表格形式
标签:为股票选择标签(黑/白/灰名单,短线/长线,以及自定义各种标签),以便区分操作策略
基准:将当天或某个价格作为基准,显示基于此价格的涨跌幅
笔记:和History功能配合,将笔记显示在时间轴上
历史:打开该股票的历史(或者与笔记一起,混合显示)
搜索:名字/部分名字,代码/部分代码,行业,产品
仪表盘:打开仪表盘,其中有直达各种第三方工具的链接
更新:仅更新此股票数据
分析:调用分析器针对这一只股票进行分析并立即展现结果

Discovery(股票发现)

依赖以下信息:
股票基本信息(曾用名)
行业数据
股票概念及分类数据
公司产品数据
当用户输入关键字时,依次搜索和匹配以下内容:
股票代码
股票名称
自定义标签
产品
概念
行业
经验系统
联想推理(经验系统):
用户可以通过输入关联信息添加经验数据,例如:
疫情->口罩->无纺布
新基建->数据中心->UPS, 电力设施
继而发现[产品]或[概念]相关的公司


任务回收站

  • 从vnpy移植K线图表,重做Stock Memo功能

History(股市史)

  1. 为History加入Horizon轴支持 -> Done
  2. 增加显示折线图的Track -> Done
  3. 集成到StockAnalysisSytem -> Done
  4. 股票历史的录入
  5. Stock Memo在时间轴上的显示
  • 重新组织程序文件结构,使其能够打包成库

现在本程序可以通过pip install StockAnalysisSystem获取
详情请见下方说明

将数据描述(Prob)从UniversalDataTable中提取出来,使数据加入,更新和检查更加自动化

将分析过程用到的参数抽取为因子 -> 20200507: Done

5.加入扩展(Extension)功能 -> 20200323:Done

History -> 效果不佳,考虑使用vnpy的K线图库
Chart Lab -> 20200331: Partly Done 因子图表 -> Done

History:

入口:上方菜单 Extension -> History
在时间轴下方显示笔记,上方显示对应日期的的K线
设计目标:
1.按时间节点记录事件及研究笔记
2.今后的回测功能可以在时间轴上显示关键点,以供参考
缺陷:
1.尽管进行过优化,然而对于大量数据的显示(比如上证指数,约9000+交易日)效率依然不佳
2.界面效果没达到预期,后期边用边改进吧

年报下载:

入口:上方菜单 Extension -> 年报下载
用以从巨潮上下载指定股票对应报告期间的年报
主要代码来自:https://github.com/gaodechen/cninfo_process
暂时仅支持年报下载
请谨慎进行大批量下载

4.加入《手把手教你读财报》的分析方法 -> 20200406: Done

现金流画像 -> 20200328:Done
货币资金分析 -> 20200328:Done
应收预付分析 -> 20200329:Done
资产构成分析 -> 20200405: Done
利润表分析 -> 20200406: Done

股东人数和十大股东 -> 20200305: Done

  1. 生成EXCEL格式的报告 -> 20200129: Done
  2. 编写数据更新的管理界面 -> 20200130: Done

硬编码过多,待重构数据结构解决 -> 20200201: Partly done
data_update_ui: 将线程任务打包,并正确显示各个项目的进度 -> 20200212: Done

  1. 编写策略选择界面 -> 20200131: Done
  2. 策略运行进度显示 -> 20200131: Done
  3. 界面集成 -> 20200201: Done
  4. 完善设计文档 -> 2020.2.2: Partly done
  5. 加入配置界面,而非写入config.py,使程序便于打包成EXE -> 20200203: Done
  6. 加入配置检查功能 -> 20200203: Done
  7. 加入打包功能,使程序能打包成EXE直接执行 -> 20200204: Done
  8. 改善mongodb读写性能和内存使用 ->20200214: Done

加入connection计数与限制,超过后关闭client以释放连接及内存 ->20200214: Done
为nosql数据库加入索引,提升查询和upsert速度 ->20200214: Done
使用bulk减少IO操作 -> 20200222: Done
使用多线程同时下载数据和写入数据库 -> 20200305: Done

  1. 接入更多财务数据

股权质押数据 -> 20200212: Done

  1. 接入股东数据

股权质押数据 -> 20200221: Done
股东人数和十大股东: 20200227: Done

  1. 接入交易数据 -> 20200221: Done
  2. 加入更多分析算法

存贷双高 -> 20200206: Done
股权质押过高 -> 20200223: Done
商誉过高 -> 2200223: Done

  1. 将数据迁移到MongoDB

UpdateTable -> 20200209: Done

  1. 废弃旧仓库,重新建立仓库以减少空间占用,并同时迁移数据到gitee(今后代码会同时提交到两个仓库) -> 20200218: Done
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上市公司财报分析系统 展开 收起
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