0 reply: recently launched an open-source project, pyalgotrade of the-share version. Based on the original version, it adds the historical and real-time quotations of A-shares, which can be used for back-test and real-disk simulation. This project will be updated on a regular basis and is testing functions such as the CTP interface and transaction monitoring. With the help of open source, we hope that the advantages of institutional investors in tools can be broken, so that small and medium investors can share procedural dividends.
Https://github.com/Yam-cn/pyalgotrade-cn
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Update the project progress of pyalgotrade-cn:
1. First of all, I have made a series of video tutorials.
[Pyalgotrade-cn Basics]
2. The translation of Chinese documents has been basically completed. Thanks to the eggplant colleagues in the group ~
3. The real-time stock market access has been completed. Now you can perform simulated transactions.
I initiated a vote in the group to learn about the current use of this platform. Later, the video course arrangement and platform update progress will be determined based on the voting result.
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I am very touched by your interest in this project ~~~ Today, we have to spend a few more hours on this project.
Answer some questions in a centralized manner:
1. Can I perform a retest of multiple criteria.
This is acceptable. Both strategy and eventprofiler support multiple stocks.
2. When to open the transaction interface.
The CTP interface is planned to be released in the next version. In addition to some tests and adjustments, it is planned to run stably in the first quarter of this year.
The stock interface should be released. There is no technical problem. Currently, mainstream brokers are compatible, but you know that it is not a good time to open the stock interface ..
3. Is there any document?
Now there are English versions of documents. The Chinese version of the document is being prepared. Recently, this project has spent a lot of time, so the progress of the document is almost the same. I will add new module documents during the Spring Festival holiday, the original document translation work will also be done slowly.
PS: some of my friends reported that github could not be accessed. You can add 300349971 groups and share them with others.
PPS: If you want to take part of the document translation and code testing work, you can directly trust me or M me in the group. It is strongly recommended for data acquisition.
TuShareIt is easy to use and fast, and data can be stored locally by writing only one line of code. It supports csv, excel, hdf5, relational databases, and NoSQL.
TuShare-financial data interface package
Http://Myquant.cn
I think it is good and open enough. I am very optimistic about it. I don't know how many times I applied for it, but I don't know what's going on? Added: tinysoft
Python uses pywin32 to call tiansoft COM. It mainly calls tiansoft data and uses the advantages of tiansoft in data integration to quickly obtain data and has accumulated a large number of financial methods and functions!
Dll-based calls are being enriched. Ricequant-Beta
Ricequant quantitative strategy platform, mibasket technology. Supports compiling and testing policies in Python and Java. With good API design, data purchased from first-line data vendors is provided to users. Currently, there are more than ten years of market data, financial data, and US stock data in the-share market. Ricequant immediately introduced the simulation of real-time push and real-time push policy stock selection function.
Now the quantum community above is also active. Btw, the community is very important! The community is very important! The community is very important! We also ask the scalpers to add more fat water to quantitative enthusiasts.
Tushare, too! It solves the problem of obtaining most market data. Hang Seng Electronics has launched a quantum terminal called quantum winner. I heard that it can be used for quantitative stock selection, procedural transactions, hedging transactions, and so on. In the past, it was a strategy platform of C ++, now it seems to be connected to Python. You can go to their forum to ask for the Python interface.
Quantified winner policy Language Python tutorial
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Update
The quantum winner's PY version has been officially launched, but it only supports trial use by seed users. You can take a look at quantitative traders who use Python development strategies.
Quantified winner strategy development edition User Manual (python)-Hang Seng quantum community
How to become a quantum winner seed user
I have used tushare, and the interface is simple and free of charge. It is suitable for practitioners. Also:
PyAlgoTrade-Algorithmic Trading
I am also developing my own quantitative Platform Based on python. I have been using JoinQuant: jukuan, and everyone is a Kuan Ke.
The Retest is in the policy;
Statistical analysis is under study;
The full online operation has no obvious internal restrictions.
The website seems to have been established soon, so there are some data limitations, mainly in the domestic stock market.
However, the progress is quite fast. You have tried the following:
4. Quantification platform of contact data
It is a Python Environment Research, retesting, and transaction platform. Besides third-party libraries such as pandas, scipy, and numpy mentioned by the subject, you can also use the quantitative analysis library provided by tonglian (which can be seen as the Chinese enhanced version of quantlib) and market data (with data of tonglian itself. If you have purchased third-party data such as Juyuan, can also be used ).
This year, registration should be made available to the outside world.
You have enabled registration.
Https://uqer.io
