What is quantitative trading? A Beginner's Guide to Quantitative Trading for Newbies

This article is organized and released by the public [Lezai Quantification]

While the topic of artificial intelligence continues to be mythologized, quantification has become an increasingly distant field for most people. But in recent years, quantitative investment has attracted more and more attention from investors, and quantitative products have also created better returns for investors. Many people have the most intuitive and simple understanding of quantitative trading: it can make money, and a lot of money.

But how does quantitative trading work? There are several steps from novice to entry, and many people actually fall at the entry level.

In this article, I will give you a quantitative primer from the following aspects

What is quantitative trading? (1) Quantitative trading in the eyes of ordinary people (2) Real quantitative trading

What is quantitative trading? (1) Quantitative trading in the eyes of ordinary people When I talk to many finance students, I find that the first reaction of most people when they talk about quantification is: it is difficult. There is always diversity in discussions in a field. Before helping you answer these questions, we need to talk about the essence of quantitative trading: what is quantitative trading?

(2) Real quantitative trading

People usually interpret q-Quant and P-Quant, or divide quantitative transactions from a sell-side/buy-side quantitative perspective. There are many similar topics on Zhihu. Today, I want to talk about this topic from the definition of quantification itself.

1. Definition of Quantitative

Quantification is the use of mathematical models (rather than the human brain) to determine the type, volume, direction and timing of trades. It is easy to understand that the core of quantification is to replace the human brain with mathematical models, to replace human emotional and rational models, to convert our investment logic into mathematical language, to strictly implement the models formulated by trading rules, and to determine the trading elements (variety, quantity, etc.). , direction and timing).

The so-called hero does not ask the source, so is the quantitative strategy of real-time forced hero production.

The quantitative strategy of quality is to observe whether it is suitable for the current market, the current asset condition and the current era background of the battle record its real market, rather than a complex model to judge, its bottom is supported by the investment logic. This means that when people talk about quantization, they don't have to equate high frequency, deep learning, AI, etc. A good strategy can be simple or complex, and ultimately it is a consideration of the underlying investment logic.

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2. Quantitative trading is at the door

In fact, there is a simple and easy-to-use quantitative trading model around us - when you open the fund software, select a fund, specify 500 yuan every Friday, and click the confirm button, you have realized the simplest quantitative strategy.

You might laugh, but don't underestimate this quantitative strategy that can be implemented in Excel. In many cases, fixed investment strategies are easier to obtain stable returns than our follow-through transactions for the following reasons: a. Regular fund investment has characteristics similar to long-term savings, which can be accumulated in small amounts and the investment cost is evenly distributed. Therefore, regular fixed investments can smooth out the peaks and troughs of the fund's net worth and remove market volatility. Due to its quantitative nature (the timing of buying and selling is determined by the rules), regular investment can avoid the impact of investors' subjective judgment on the timing of entry, greatly reducing the huge losses caused by subjective judgment errors (buying at market peaks and selling at market lows) ). Therefore, the fixed investment strategy can well reduce the volatility of fixed investment objectives, as well as investors' misjudgment of investment points caused by personal emotions and information factors. It can also be seen that the fixed investment strategy is a very suitable long-term investment strategy, and the only thing investors need to do is to choose a long-term optimistic goal, and then they can carry out fixed investment operations.

How to Be a Quantitative Trader From the above statement, it's not hard to see that it's "quantitative" which is not as far-fetched as most people think. Does this mean that if we want to become a quantitative trader, it's not as hard as we think?

As discussed in "Definition of Quantification", most people tend to focus on the term "mathematical model" and ignore another core element of quantification - trading. In the construction process of the whole quantitative strategy, it is first necessary to convert the transaction logic into a mathematical language, and then realize the conversion from the mathematical language to the program through tools such as programming languages.

At the bottom of this three-step, two-step transformation process, it is backed by solid transaction logic. The cultivation of trading literacy takes time to accumulate, which is also a major advantage of traditional financial practitioners when they turn to quantitative work.

However, most quant teams have yet to achieve "fully automated trading". Due to the limitations of mathematical models, as well as the impact of black swans and cycles, most quantitative teams still maintain an artificial+intelligence approach to quantitative investing, which further improves quantitative researchers’ understanding of trading.

After realizing what underpinned the underlying logic of quantization, I stopped worrying about rumors about quants favoring programmers and started doing what I was doing.

In fact, with the development of AI intelligence in recent years, the fundamental of quantitative trading has also undergone a qualitative leap and progress. Use Yingshou Quantification to see the future development trend. The world's first "AI stock trading robot automatic trading platform" that can be used by everyone without programming is designed using innovative technologies such as big data, neural networks, blockchain, special algorithms, and deep self-learning functions.

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It has three core operating functions:

(1) Any user does not need to write programming and only needs to click the mouse to combine a trading strategy with a super annualized rate of return, or directly add the number of ️ to easily design his best stock trading profit model on this platform as Fully automatic programmed trading strategy, fully automated by AI robots;

(2) It is also possible to directly add multiple underlying securities for automatic T+0 trading;

(3) You can also write your own program and add the platform's original risk factor for de-marketing, so that the annualized rate of return will be about 50% higher than the original strategy. It can meet the operational needs of all investors. The AI ​​automatic stock trading robot trading platform that can completely replace the traditional and backward manual trading software is a landmark and epoch-making securities trading upgrade product! It will bring revolutionary changes to the development of China's stock exchange market! Not only can it free the majority of investors from the busy work of speculating in stocks, and let the AI ​​​​bot operate fully automatically, but also achieve a more ideal return than human brain analysis of manual transactions! Because of its powerful functions and excellent performance quality, it will play a huge role in promoting China's securities market and economic and social development.

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In my spare time at work and learning programming, I read some classic investment biographies, and recorded and organized a lot of reading notes, trying to grow fast on the shoulders of giants.

This article is organized and released by the public [Lezai Quantification]