search
HomeBackend DevelopmentPython Tutorial中国的 Python 量化交易工具链有哪些?

回复内容:

最近发起了一个开源项目,A股版的pyalgotrade,在原版的基础上,增加了A股的历史行情和实时行情,可以用来做回测和实盘模拟。这个项目会定期更新,正在测试CTP接口和交易监控等功能。希望借助开源的力量,能打破机构投资者在工具上的优势,让中小投资者也能分享程序化的红利。
github.com/Yam-cn/pyalg


------------------------------------------------2016.03.17----------------------------------------------------
更新一下pyalgotrade-cn的项目进度:
1. 首先,大家反映学习资料比较少的,问题,我现在已经做一个系列的视频教程。
[pyalgotrade-cn基础]

2. 中文文档翻译已经基本完成,感谢群里的茄子同学~

3. 股票实时行情接入已经完成了,现在可以进行模拟交易。

我在群里发起了一个投票,了解一下现在这个平台的使用情况。之后会根据这个投票结果来决定视频课程的安排,和平台的更新进度。

------------------------------------------------2016.01.28----------------------------------------------------
看到大家对这个项目的兴趣,十分感动~~~今天一定要多熬几个小时在这个项目上

集中回答一下一些问题:
1. 是否可以进行多标的的回测。
这个是可以的,strategy和eventprofiler都是支持多股票的。

2. 什么时候开放交易接口。
CTP接口计划在下一个版本放出,再加上一些测试和调整,计划在今年一季度可以跑稳CTP。
股票接口这个择机放出吧,技术上问题不大,现在主流的券商都可以兼容,不过你懂得,现在开放股票接口并不是一个好时候。。

3. 是否有文档
现在有英文版的文档,中文版的文档正在制作中,最近在这个项目上花的时间比较多,所以文档进度就差一点,我会在春节假期补上新增模块的文档,原版的文档翻译工作,也会慢慢做起来。

PS: 有些朋友反映github访问不了,可以加群300349971,群共享里面也有。
PPS: 如果有希望承担一部分文档翻译,代码测试工作的朋友,可以直接私信我,或者在群里M我。 在数据获取方面强烈推荐使用TuShare,简单易用,速度很快,而且只写一行代码就能将数据存储在本地了,支持csv、excel、hdf5和关系型数据库和NoSQL。
TuShare -财经数据接口包 Myquant.cn我觉得不错,足够开放性,我个人非常看好。申请了几次也不给审批,不知道是怎么回事? 补充一个:tinysoft
Python通过pywin32调用天软COM,主要是调用天软的数据,利用天软在数据整合上面的优势快速获得数据,并且有大量积累的金融方法函数!
dll方式的调用正在丰富中。 Ricequant - Beta Ricequant量化策略平台,米筐科技。支持Python和Java编写和测试策略。有良好的API设计,从一线数据商采购的数据提供给用户使用,现在有A股市场逾十年的市场数据和财务数据,美股数据等。Ricequant 马上推出的模拟实盘和实时微信推送策略选股择时的功能。

现在上面的量化社区也比较活跃了。 btw,社区很重要!社区很重要!社区很重要!还请大牛们多给量化爱好者们灌些肥水。

Tushare 我也要给大大的赞! 解决了大部分市场数据的获取的问题。 恒生电子新推出了一个叫量化赢家的量化终端,听说可以做量化选股、程序化交易还有对冲交易之类的,以前是C++的策略平台,现在好像对接Python了,可以去他们的论坛找他们要Python接口。
量化赢家策略语言Python教程
-----------------------------------------------------
2015.7.10更新
量化赢家的PY版本已经正式推出了,不过暂时只支持种子用户试用,对使用Python开发策略的量化交易者可以关注一下。
量化赢家策略开发版使用手册(python)-恒生量化社区
如何成为量化赢家种子用户 个人用过tushare,接口简单,而且免费,适合拿来练练手。 还有这个:
PyAlgoTrade - Algorithmic Trading
我自己也在基于python开发自用的量化平台 我一直用的是JoinQuant:聚宽,人人皆为宽客
回测在策略里;
统计分析在研究里;
全程在线操作,比好的是没有明显的内的限制。
网站好像还成立不久,所以数据方面有些局限,在上面主要还是做国内股票。
不过进步还挺快的。 试用过下面这个:
4. 通联数据的量化平台
是一个Python环境的研究,回测,交易平台,除了可以使用题主提到的pandas,scipy,numpy等第三方库之外,还可以使用通联提供的量化分析库(可以看做是quantlib的中国加强版),以及行情数据(有通联自己的数据,如果购买了聚源等第三方的数据,也可使用)。

今年年中应该会对外开放注册了。

已经开放注册了.
uqer.io
Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How to Use Python to Find the Zipf Distribution of a Text FileHow to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Mathematical Modules in Python: StatisticsMathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and Deserialization of Python Objects: Part 1Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

What are some popular Python libraries and their uses?What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationScraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

How to Create Command-Line Interfaces (CLIs) with Python?How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

Hot Tools

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SAP NetWeaver Server Adapter for Eclipse

SAP NetWeaver Server Adapter for Eclipse

Integrate Eclipse with SAP NetWeaver application server.

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use