If you’re looking to achieve financial independence, you must be fully aware of algorithmic trading and the benefits it offers. There are however some things you’ll need to be aware of quantitative trading too in order to have a full understanding of the trading process.
In this article, we’ll attempt to clarify the differences between these two forms of trading, and ensure that you know why these two types can’t be used in isolation.
Algorithmic trading transforms concepts into strategies through algorithms. The method that has been developed is then tested using historical data to determine whether the results are acceptable in real-world markets.
In contrast, Quantitative trading is the process of using mathematical and statistical models for constructing and executing strategies. It sounds quite similar, right?
A profitable and theoretically sound strategy will remain theoretical if there is no one who can program it.
This is the reason algorithmic and quantitative specialists collaborate closely. This is why their work seems to be similar however, they’re totally different.
Similarities And Differences Between Algorithmic And Quantitative Trading
1. Similarities
As we mentioned above, both kinds of experts usually work closely and their jobs require very similar skills. Both have the ability to write code. Algorithmic traders have to examine their visions.
Although various software applications allow to perform tests, professionals prefer to write their own code to ensure more precise results. Without any formal programming skills, it’s impossible to do this.
The ability of algorithmic traders to code lets both specialists utilize a common language making collaboration and development more simple.
Experts in quantitative trading with some knowledge of algorithmic trading may also have an understanding of markets and ways to implement specific strategies that will result in success.
2. Degrees For Traders And Developers
Both professionals share similar academic backgrounds. However, the most common degrees cover subjects like math, engineering, and physics.
A thorough understanding of these subjects provides an excellent foundation to study the field of software engineering and are widespread among traders who rely on data analysis in order to identify successful strategies.
Computer science degrees provide an excellent way to prepare, but they are not suitable for specialists in algorithmic. Economics and finance are more appropriate for the second kind of student.
Assuming that specialists already have the proper education, they must improve their skills in other areas. Both need to master programming, acquire an understanding of the market, and be familiar with typical strategies.
Algo traders do not need to comprehend a factor regression for instance. In the same way, a quant expert is not expected to master the art of code optimization or GPU programming.
Quantitative trading is a specialized sector of quant finance and professionals invest a substantial amount of time learning the required knowledge needed to develop their strategies.
The job requires a lot of proficiency in programming using languages like MATLAB, Python or R. Algo trading refers to strategies for execution that are employed by managers to purchase the assets or to sell them.
At present, the market is filled with developers who wish to become traders who are systematic. There are, however, very few experts in quantitative trading who are looking to be full-time programmers.
The reason is that only a handful of people are interested in this field because you can perform Algo work by making use of computers and software and manual labor is no longer needed.
If you have the appropriate skills, programming to create algorithms is simple. The design process is a different type of job. This is the reason you need quantitative experts.
