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How to use Python to make a quantitative trading tool! I believe that many inexperienced people are at a loss about this, so this article summarizes the causes and solutions of the problem. I hope you can solve this problem through this article.

Quantitative transaction refers to the way of investment transaction by using computer technology with the help of modern statistics and mathematical methods.

For people who have never been exposed to quantification, if they want to understand what quantification is, it is crucial to master four parts: basic knowledge of Python, financial knowledge, technical indicators, and quantitative trading framework.

Basic knowledge of Python: the fastest way to master a programming language is to write more code and do more exercises on the basis of understanding the basic syntax, data types, operations, process control, and function design of Python. Now Niuke.com, leetcode and many other platforms provide online practice functions, these platforms can help you quickly improve your programming ability.

Financial knowledge: it is not too difficult to master financial knowledge at the entry stage. We need to understand the operating rules of the underlying market in which we invest. Take A shares and US stocks as an example: a shares and US stocks are different in terms of trading time, minimum trading unit, rise and fall limit, settlement method, circuit breaker mechanism, and so on. Investors can quantify them only by mastering the operating rules such as the underlying market, and realize programmed trading.

Technical indicators: technical indicators are through charts to study the response of market behavior, in order to speculate the trend of price changes. There are many common technical indicators, and the classification is not the same. Beginners only need to master some commonly used technical indicators, understand their meaning, how to calculate and how to use them.

Quantitative trading framework: there are many online platforms that provide quantitative strategy writing functions and integrate many convenient tools. Developers focus on strategy development and are very easy to use. Such as: big quant, excellent mine, rice basket. Of course, there are many open source quantitative trading frameworks, developers can carry out secondary development according to their own needs, such as vnpy, easyquant and other frameworks. Quantitative developers should choose a tool that suits them to implement the quantitative strategy.

After reading the above, you know how to use Python to make a quantitative trading tool! Is there a way to do it? If you want to learn more skills or want to know more about it, you are welcome to follow the industry information channel, thank you for reading!

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