Rqalpha bitcoin
Publish: 2021-04-30 10:59:33
1. Python quantitative investment framework: back testing + simulation + firm offer
Python quantitative investment simulation trading platform 1. Stock Quantitative Investment Framework 1.1 before back testing firm offer trading, quantitative trading strategy must be back tested and simulated to determine whether the strategy is effective, and improve and optimize. As an ordinary person, you can think of, generally someone has done. So is the back testing framework. At present, Xiao mainly sees the following five backtesting frameworks: zipline: event driven framework, which is very popular abroad. The defect is that it is not suitable for the domestic market. Pyalgotrade: event driven framework, the latest update date is August 17, 2016. It supports the domestic market and uses Python 2.7 to develop. The biggest bug is that it does not support the version 3.5 and the powerful panda. Pybacktest: back test is concted by processing vector data. The latest update date is 2 months ago, and the update is unstable. Tradingwithpython: Refactoring based on pybacktest. There are few references. Ultra Finance: the project of GitHub stopped updating two years ago. The latest project is on Google platform, but can't open the website. If you are interested, please check it by yourself. Rqalpha: event driven framework, suitable for A-share market, with daily data. It's an open source framework for backtesting of rice basket. Relatively speaking, I prefer this platform. 2. Simulation trading is also an important step before real trading. In order to prevent similar to the current incident of a securities company, the loss of hundreds of millions within half an hour has had a bad impact on the whole stock market. Simulation transaction, the key consideration is whether the transaction logic of the program is reliable, whether all kinds of data transmission conditions are taken into account. At present, the open source platform I like to use is snowball simulation trading, followed by the simulation trading interface provided by wind. For example, those provided by youkuang, mizuan and jukuan can only be tested on the online platform, so they are not very free and don't feel much. Snowball simulation trading: in the follow-up trading mole, we will focus on the introction, and the main application is an open source easytrader series. Wind simulation transaction: if there is no institutional version, the student free version can be considered. Please refer to the following links for specific simulation transaction interfaces: http://www.dajiangzhang.com/document 3. Firm offer is undoubtedly our ultimate goal. Stock program trading has been restricted. But for all of us, there is always a solution. At present, the most important thing is to crack the trading interface of the website version of securities companies, or to use crawlers to operate. For me, I prefer the open source platform of easytrader series. For institutional users, e to the large amount of funds, it is not recommended for security and reliability. At present, easytrader series mainly consists of three parts: easytrader: providing funds for securities companies Huatai / lijinbao / Yinhe / Guangfa / xueqiu, and automatic programmed trading of stocks, Quantitative trading component easyquotation: real time access to Sina / leverfun's free stocks and level 2's ten quotations / classified fund quotations with ideas. Easyhistory: used to obtain and maintain the historical data of stocks. Easyquant: stock quantitative framework, which supports quotation acquisition and trading. 2, I'm not familiar with futures, but I'm familiar with stocks. Let's make a brief summary according to what we know. 2.1 back testing back testing, it seems that there is no very popular open source framework. There are two possible reasons: compared with stocks, futures have higher threshold, more institutional trading and less open source; So far last year, the futures regulatory control is relatively strict, so far it has not been liberalized, so we can only do some CTA strategies, and many other people are in great interest. In terms of personal understanding, maybe wind is a relatively appropriate choice. 2.2 simulation + real vn.py is the most popular open source platform in China. The independent trading system, which originated from domestic private placement, was just a python encapsulation of the trading API interface when it was launched in early 2015. With the increasing attention of the instry and the continuous contribution of the community, it has graally grown into a comprehensive trading program development framework. As the official website said, the framework focuses on the transaction mole, which is not supported by the back testing mole. The ability is limited. If you are interested in the related framework, please refer to the related links. My personal expectation is to build a backtest framework based on rqalpha, a simulation framework based on snowball or wind, and trade with easy series.
Python quantitative investment simulation trading platform 1. Stock Quantitative Investment Framework 1.1 before back testing firm offer trading, quantitative trading strategy must be back tested and simulated to determine whether the strategy is effective, and improve and optimize. As an ordinary person, you can think of, generally someone has done. So is the back testing framework. At present, Xiao mainly sees the following five backtesting frameworks: zipline: event driven framework, which is very popular abroad. The defect is that it is not suitable for the domestic market. Pyalgotrade: event driven framework, the latest update date is August 17, 2016. It supports the domestic market and uses Python 2.7 to develop. The biggest bug is that it does not support the version 3.5 and the powerful panda. Pybacktest: back test is concted by processing vector data. The latest update date is 2 months ago, and the update is unstable. Tradingwithpython: Refactoring based on pybacktest. There are few references. Ultra Finance: the project of GitHub stopped updating two years ago. The latest project is on Google platform, but can't open the website. If you are interested, please check it by yourself. Rqalpha: event driven framework, suitable for A-share market, with daily data. It's an open source framework for backtesting of rice basket. Relatively speaking, I prefer this platform. 2. Simulation trading is also an important step before real trading. In order to prevent similar to the current incident of a securities company, the loss of hundreds of millions within half an hour has had a bad impact on the whole stock market. Simulation transaction, the key consideration is whether the transaction logic of the program is reliable, whether all kinds of data transmission conditions are taken into account. At present, the open source platform I like to use is snowball simulation trading, followed by the simulation trading interface provided by wind. For example, those provided by youkuang, mizuan and jukuan can only be tested on the online platform, so they are not very free and don't feel much. Snowball simulation trading: in the follow-up trading mole, we will focus on the introction, and the main application is an open source easytrader series. Wind simulation transaction: if there is no institutional version, the student free version can be considered. Please refer to the following links for specific simulation transaction interfaces: http://www.dajiangzhang.com/document 3. Firm offer is undoubtedly our ultimate goal. Stock program trading has been restricted. But for all of us, there is always a solution. At present, the most important thing is to crack the trading interface of the website version of securities companies, or to use crawlers to operate. For me, I prefer the open source platform of easytrader series. For institutional users, e to the large amount of funds, it is not recommended for security and reliability. At present, easytrader series mainly consists of three parts: easytrader: providing funds for securities companies Huatai / lijinbao / Yinhe / Guangfa / xueqiu, and automatic programmed trading of stocks, Quantitative trading component easyquotation: real time access to Sina / leverfun's free stocks and level 2's ten quotations / classified fund quotations with ideas. Easyhistory: used to obtain and maintain the historical data of stocks. Easyquant: stock quantitative framework, which supports quotation acquisition and trading. 2, I'm not familiar with futures, but I'm familiar with stocks. Let's make a brief summary according to what we know. 2.1 back testing back testing, it seems that there is no very popular open source framework. There are two possible reasons: compared with stocks, futures have higher threshold, more institutional trading and less open source; So far last year, the futures regulatory control is relatively strict, so far it has not been liberalized, so we can only do some CTA strategies, and many other people are in great interest. In terms of personal understanding, maybe wind is a relatively appropriate choice. 2.2 simulation + real vn.py is the most popular open source platform in China. The independent trading system, which originated from domestic private placement, was just a python encapsulation of the trading API interface when it was launched in early 2015. With the increasing attention of the instry and the continuous contribution of the community, it has graally grown into a comprehensive trading program development framework. As the official website said, the framework focuses on the transaction mole, which is not supported by the back testing mole. The ability is limited. If you are interested in the related framework, please refer to the related links. My personal expectation is to build a backtest framework based on rqalpha, a simulation framework based on snowball or wind, and trade with easy series.
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