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What Is The Difference Between Algorithmic And Quantitative Trading?

Algorithmic And Quantitative Trading

Published on September 3rd, 2019

If your goal is to become financially independent, then you are already well aware of algorithmic trading and its benefits. However, there are a few things you need to know about quantitative trading as well, for a better understanding of the processes.

In this article, we will try to explain the difference between these two types of trading and make sure you understand why both types cannot go without one another.

Algorithmic trading turns ideas into strategies via algorithms. The approach thus created is then backtested with historical data to check whether or not the returns will be good in real markets. On the other hand, quantitative trading involves using statistical and advanced mathematical models for creating and executing strategies. It sounds quite similar, right?

Both trading roles are essential jobs. Without the algorithm designer, the quant specialist who creates the software will leave you without work. A theoretically profitable strategy will remain theoretical without a person to program it. This reason is why quantitative and algorithmic specialists work closely together. Due to this, their jobs seem quite similar, but in fact, they are entirely different.

1. Similarities

As we said, both types of specialists usually work so closely together that their roles get very similar skill sets. Both can code. Algorithmic traders need to test their visions. Although different software packages enable to perform tests, specialists prefer to code themselves to get more accurate results. And without formal programming, this is impossible.

The fact that algorithmic traders can code allows both specialists to use a common language, which makes their communication and joint development much easier. Quantitative trading experts who have some experience in the algorithmic trading will also have a better idea on markets and how to implement certain ideas that lead to success.

2. Degrees For Traders And Developers

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Both professionals have similar educational backgrounds. However, generic quantitative degrees are subjects like math, physics, and engineering. Mastery of these subjects offer excellent preparation for software engineering and are very common among traders that rely on data analysis to find winning strategies.

Computer science degrees are an excellent preparation but are unhelpful for algorithmic specialists. Studying finance and economics is more suitable for the second type.

Assuming specialists already have the right degree, then they need to work on their other skills. They both need to learn to program, get an understanding of the markets, and learn typical strategies.

Algo traders are not expected to know how to interpret the results of a factor regression, for example. Similarly, a quant specialist should not learn the arts of code optimization or GPU programming.

Quantitative trading is a sophisticated area of quant finance, and specialists spend a significant amount of time to gain the necessary knowledge to build their strategies. The job requires extensive programming expertise in languages such as MATLAB, Python, or R. Algo trading refers to execution strategies that are used by managers to buy or sell assets.

Right now, it is full of programmers who would like to become systematic traders. However, there are very few quantitative trading experts who would like to become full-time coders.

Only a few people embrace this profession is because you can do Algo work with the help of programs and computers and manual work is no longer necessary.

If you can acquire the right skills, coding up algorithms can be quite easy. Designing them is another type of work. That is why you need quant experts.