Academic Backgrounds That Are Fit For Algorithmic Trading

5 min read

By Chainika Thakar

Algorithmic trading is one of the ways of trading in which the trade orders are executed with the help of algorithms carrying pre-defined instructions. Now, a very common question is:

What academic background should I belong to for doing algorithmic trading?

The answer is simple!

There are some undergraduate and postgraduate degrees which consist of the subjects that help to gain essential basic skills required for algorithmic trading. Possessing one of the degrees can help you with learning and understanding the concepts required for algorithmic trading in detail.

Also, this article consists of answers to the frequently asked questions from the professionals/students who aim at starting algorithmic trading from scratch.

This article includes:


Which are the undergraduate and postgraduate degrees with subjects that can help in pursuing algorithmic trading?

In this section, I have created a list of degrees that are helpful for an aspiring algorithmic trader. Since algorithmic trading includes different job roles such as that of a quantitative analyst, quantitative developer, risk analyst etc., on the basis of the skill set you possess, you can decide to specialise in a particular role.

But, you need to have a know-how of all the other roles simultaneously. As a quantitative developer, even though you specialise in programming, you need to have the knowledge of mathematics to avoid any basic errors in codes.

For instance, while showing the maximum drawdown for a stock, the meaning of maximum drawdown needs to be well understood so that you are able to code the right conditional statements.

Take a look at the undergraduate and postgraduate degrees which are helpful for algorithmic trading, the skill set gained in each degree (for making a base for learning algorithmic trading) and the skill set missed out in each:

Undergraduate degrees:

Degrees

Will be helpful to gain the following skills which can make a base for learning algorithmic trading

Artificial Intelligence & Machine Learning

  • Machine learning
  • Programming

Computer Science

  • Programming

Mathematics/Statistics

  • Statistics & Probability
  • Monte Carlo

Finance

  • Fundamental analysis
  • Trading/Finance (Basics of markets)
  • Risk management

Postgraduate degrees:

Degrees

Will be helpful to gain the following skills which can make a base for learning algorithmic trading

Artificial Intelligence & Machine Learning

  • Machine learning 
  • Programming

Computer Science

  • Programming
  • Networks and systems

Mathematics/Statistics

  • Statistics and Probability theory
  • Stochastic calculus
  • Advanced calculus

Financial engineering

  • Machine learning
  • Statistics and Probability theory
  • Stochastic calculus
  • Risk management
  • Programming
  • Quantitative analysis

Finance

  • Risk management
  • Quantitative analysis
  • Trading/Finance (Basics of markets)

Credits for the tabular information: Gaurav Singh

And, if you already possess an above mentioned degree, then you can focus on the missing skills and learn from the resources available.


Resources for learning Algorithmic Trading

Whether you are looking to learn missed out skills or to gain an in-depth know how on existing skills, these learning tracks and courses will serve the purpose:

Learning tracks

Learning Track: Machine Learning and Deep Learning in Financial Markets for learning:

  • Introduction to machine learning
  • Basic concepts of machine learning such as neural networks and decision trees

Learning Track: Algorithmic Trading for Everyone for learning:

  • Python programming
  • Trading with machine learning and mathematical concepts
  • Trading strategies: quantitative trading strategies, day trading, options trading (Basics of markets)

Courses

Executive Programme in Algorithmic Trading (EPAT) - A 6-month long comprehensive algo trading course that builds your knowledge and expertise in:

  • Quantitative analysis
  • Statistics
  • Trading

Quantitative Portfolio Management for learning:

  • Risk management

Blog

How to Backtest a Trading Strategy for learning:

  • Backtesting

Next, there is a set of interesting frequently asked questions revolving around the academic background for algorithmic trading.


Frequently asked questions about education required for Algo Trading

Can someone with no prior technical knowledge do algorithmic trading?

Yes, it is okay to not have an existing technical knowledge initially. But for doing algorithmic trading you can learn the technicalities with ease. Such technicalities are programming, creating machine learning algorithms and application of quantitative trading strategies. We discussed in the blog above about the learning resources that can help you equip these relevant skills or technicalities.

See this inspiring story of Zahra, who began her trading journey from age 17. Later, she could manage the transition from a manual trader to an algorithmic trader with the help of EPAT. If Zahra can do it, so can you!

Would it make more sense to do a MFE or any quantitative analytics course before getting enrolled in an algorithmic trading course?

It is always good to be carrying some knowledge from MFE or other graduate courses. That is why we have mentioned the graduate and postgraduate degrees that help to gain basic knowledge required for algorithmic trading. A quantitative analytics course can help with making it easier to grasp the fundamental concepts of algorithmic trading.

For instance, the knowledge of advanced mathematics (probability theory, stochastic calculus, partial differential equations, numerical analysis, statistics, econometrics) and/or the ability to programme using a programming language like Python.

On the other hand, you can opt for a course like EPAT that provides you with the entire know-how of algorithmic trading right from the scratch. For enrolling in such a course, you do not need a prior course. The stories of Narciso Perez  and Shubhrabaran provide a deeper insight into the helpfulness of such a programme.

We only see PhDs, math scholars, hard core programmers and IITians in the domain. Is that true for the majority?

While many think that only the PhD holder, a C++ programmer or an IITian get into algorithmic trading domain, it is not completely true. The truth is that, for doing algorithmic trading, you need the knowledge of fundamental concepts such as programming, machine learning, trading etc.

But, being from a different discipline is not an obstacle. If you remain dedicated towards algorithmic trading domain, you can get enrolled in a course which will equip you with the required knowledge.

Apart from the IITians, PhDs, math scholars and hard core programers, there are others who enrol in an algorithmic trading course for learning the fundamental concepts from scratch.

This chart shows the percentage of enrolled students in our EPAT programme who belong to other professions/disciplines:

algo trading professional background

The pie chart shows that the percentage of EPAT students who come from other backgrounds is 25.7%. This reveals that the percentage of students coming from different fields is much higher than the percentage of students who have a background in trading, data analyst roles and programming.


Conclusion

As a student, a degree which helps you gain the required skills for algorithmic trading is surely a plus. The missed out skills can be gained with a professional course and the knowledge you gained from your academic background will help you acquire the foundational base for learning algorithmic trading.

Also, being in any other field for years can not be an obstacle if you have passion for algorithmic trading. With the right guidance and training, you can gain the knowledge required for algorithmic trading and take the right steps further.

Start your quest to upgrade your knowledge of Algorithmic Trading with the Executive Programme in Algorithmic Trading (EPAT) - a comprehensive course covering topics ranging from Statistics & Econometrics to Financial Computing & Technology including Machine Learning and more. Check it out here.

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