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Learn Algorithmic Trading: Steps to Become an Algo Trading Professional

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Compiled by Viraj Bhagat

For beginners who want to venture into algorithmic trading, this article will serve as a guide to all the things that are essential to get you to learn algorithmic trading and to get you trading the algorithmic way.

Acquire knowledge in quantitative analysis, trading, programming and learn all that you would need to know to to learn algorithmic trading and build yourself in the domain with this step by step guide.

Quick look:

With the boom in technological advancements in trading and financial market applications, algorithmic trading and high-frequency trading is being welcomed and accepted by exchanges all over the world.

Within a decade, it is the most common way of trading in the developed markets and is rapidly spreading in the developing economies. It is essential to learn algorithmic trading to trade the markets profitably.

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What you should know about Algorithmic trading

Automated trading does not mean it is free from human intervention. Automated trading has caused the focus of human intervention to shift from the process of trading to a more behind-the-scenes role, which involves devising newer alpha-seeking strategies on a regular basis.

In the past, entry into algorithmic trading firms used to be restricted to PhDs in Physics, Mathematics or Engineering Sciences, who could build sophisticated quant models for trading.

However, in recent years there has been an explosive growth of the online education industry, offering comprehensive algorithmic trading programs to aspiring algorithmic traders. This has made it possible to get into this domain without having to go through the long (8-10 years) academic route.

This has led to a growing demand to learn algorithmic trading.

Here are some helpful sources that will provide a detailed explanation about building your base when you enter the financial markets and the world of trading.

Difference Between Algorithmic Trading, Quantitative Trading, and Automated Trading

There is often a lot of confusion between algorithmic trading, automated trading, and HFT (high-frequency) trading. Let us start by defining algorithmic trading first.

Algorithmic Trading

Algorithmic trading means turning a trading idea into an algorithmic trading strategy via an algorithm. The algorithmic trading strategy thus created can be backtested with historical data to check whether it will give good returns in real markets. The algorithmic trading strategy can be executed either manually or in an automated way.

Quantitative Trading

Quantitative trading involves using advanced mathematical and statistical models for creating and executing an algorithmic trading strategy.

Automated Trading

Automated trading means completely automating the order generation, submission, and the order execution process.

Good reads on who can learn Algorithmic Trading

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Why you should learn Algorithmic Trading

The world is rapidly adapting algorithms and many exchanges have been swiftly executing algorithms since quite a while now.

In 2020, The global market for Algorithmic Trading estimated at US$14.7 Billion, is expected to garner US$31.1 Billion by 2027, growing at a CAGR of 11.3% over the period 2020 to 2027.

Reputed global banks and investment giants are investing in Quants for the future of trading. Back in 2019, Bloomberg reported "JPMorgan Arms Coders With Trading Licenses as Quants Advance".

"2020's high trading volumes meant last year was exceptional for many electronic market makers. Citadel Securities, for example, made revenues of $6.7bn in 2020, and a record $4.1bn in EBITDA." according to this source.

In early 2020, Forbes reported:

  • Citigroup started planning to hire 2,500 programmers for its trading and investment banking units. Citigroups 75% trades were electronic in 2019.
  • While Goldman Sachs started hiring Coders, Data Scientists, and Engineers for their Trading floor,

According to a recent research from New York University Stern School of Business:

Approximately 80% of investments are either quant-based or fully passive, with only one-fifth of trades actively plotted out by sentient lifeforms.

As per latest numbers, the sub-reddit Algo Trading on Reddit has 1.2 Million active users, with thousands joining in daily. The growth indicates the interest of people towards this growing domain.

Banks, investors, financial insitutions are drawn towards this field that is rising quickly and has been adapted globally. This makes it imperative for one to learn algorithmic trading.

Here's an interesting webinar recording that explains the need for Algorithmic Trading: Algorithmic Trading - Why make the move?

Frequencies in Trading

Trading strategies can be categorized as per the holding time of the trades.

  • Low-frequency
  • Medium-frequency
  • High-frequency

High-Frequency Trading (HFT) - High-frequency trading strategies are algorithmic strategies which get executed in an automated way in quick time, usually on a sub-second time scale.

Such strategies hold their trade positions for a very short time and try to make wafer-thin profits per trade, executing millions of trades every day.

If you are a trader or investor in the financial markets, you're probably aware that the investing landscape has undergone a sea change in the last 10-15 years. At the heart of it, is the use of quantitative techniques in making buying and selling decisions in the markets.

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Things to know while learning Algorithmic Trading

Steps To Becoming An Algo Trading Professional

In the sections below, we outline the core areas that any aspiring algorithmic trader ought to focus on to learn algorithmic trading. We also present a comprehensive picture of the different ways and means through which these essential skill sets can be acquired.

Step 1: Being thorough with the core areas of Algorithmic Trading

Algorithmic trading is a multi-disciplinary field which requires knowledge in three domains, namely,

  • Quantitative Analysis or Quantitative Modeling
  • Trading knowledge ie. Financial Markets Knowledge
  • Programming Skills

Quantitative Analysis or Quantitative Modeling

If you are a trader who is used to trade using fundamental analysis and technical analysis, you would need to shift gears to start thinking quantitatively. Problem-solving skills are highly valued by recruiters across trading firms.

Trading knowledge ie. Financial Markets Knowledge

This knowledge will be crucial when you interact with the quants and will help in creating robust programs. A professional Coder/Developer in a trading firm is expected to have a good fundamental knowledge of financial markets.

This knowledge should be about:

  • types of trading instruments (stocks, options, currencies etc.),
  • types of strategies (Trend Following, Mean Reversal etc.),
  • arbitrage opportunities,
  • options pricing models, and
  • risk management.

Programming Skills

The strategies created by the quants are implemented in the live markets by the Programmers.

If you want to excel in the technology-driven domain of automated trading, you should be willing to learn new skills and you shouldn’t be disinclined to any field. So if you have never printed “hello world” by compiling your own coding program, it’s time to download the compiler of your interest - C++/Java/Python/Ruby and start doing it!

The best way to learn to program is to practice, practice and practice. Sound knowledge of programming languages like Python/C++/Java/R is a pre-requisite for a Quant Developer job in trading firms. It is also interesting to learn that Python is the preferred choice among traders.

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You can also check out some of the most popular Python trading platforms for Algorithmic Trading

If you want a brief introduction to Python and the key components of its data science stack, or want a quick refresher on using Python for data analysis, check out this book: Python Basics Handbook - Download For FREE!

Step 2: How to become an Algo Trading Professional?

If you've been looking to build a career into the quantitative and algorithmic trading domain, there is a high probability that you would have heard about the EPAT programme.

But is EPAT something that can help you in achieving your career & learning objectives in this domain? This informative session on how EPAT can help you addresses this question while covering various practical aspects of the EPAT programme.

With this session on How to create a trading algorithm from scratch, learn to create a trading algorithm from scratch and test on real market data. Learn about all the fundamental components of creating a trading algorithm. This session explains various trading strategy paradigms like momentum trading and mean reversion with examples.

Books to learn Algorithmic Trading

You will find many good books written on different algorithmic trading topics by some well-known authors, that can help you learn algorithmic trading. Here are some useful books that can help:

Free resources to learn Algorithmic Trading

In addition to the books mentioned above, beginners can refer to the following free resources to learn algorithmic trading.

Although these free resources are a good starting point to learn algorithmic trading, one should note that some of these have their own shortcomings.

  • Algorithmic trading books do not give you hands-on experience in trading.
  • Free courses to learn algorithmic trading on online portals can be subject-specific and may offer very limited knowledge to serious learners.
  • Another important point to note is the lack of interaction with experienced market practitioners when you opt for some of these free courses.

Learn Algorithmic Trading from Professionals, Trading Experts or Market Practitioners

The building blocks in learning Algorithmic trading are Statistics, Derivatives, Matlab/R, and Programming languages like Python. It becomes necessary to learn algorithmic trading from the experiences of market practitioners, which you can do only by implementing strategies practically alongside them.

Training to learn Algorithmic Trading

You can join any organization as a trainee or intern to get familiarized with their work ethics and market best practices and to learn algorithmic trading. If it’s not possible for you to join any such organization then you can opt for classroom courses/workshops or paid online courses. Most of the classroom courses/workshops are delivered in the form of 2 days to 2 weeks long workshops or as a part of Financial Engineering degree programs.

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Self-learning about Algorithmic Trading online

On the online front, there are online learning portals such as QuantInsti, Coursera, Udemy, Udacity, edX, & Open Intro, that have expert faculty from mathematics and computer science backgrounds who share their experiences and strategy ideas/tactics with you during the course.

Algorithmic Trading essentials to learn Algorithmic Trading

6 month comprehensive course on Algorithmic Trading with certification

Keeping in mind the need for an online certification programme for working professionals in the domain of Algorithmic and Quantitative Trading, QuantInsti offers a comprehensive hands-on course called the Executive Programme in Algorithmic Trading (EPAT).

The objective of EPAT is to make you market-ready for the world of algorithmic trading upon successful completion of the coursework. Hundreds of course participants from over 70+ countries working across different sectors such as financial markets, technology, and quantitative finance have benefited from the programme in various ways.

Features of EPAT

The salient features of the EPAT algorithmic trading course are listed in the table below.

Course Features

Executive Programme in Algorithmic Trading (EPAT)

Industry recognition

Yes

Delivery

Online

Course curriculum

100+ hours of Live Lectures

200 study hours

Course duration

6 months via weekend lectures

Course modules

14 modules

Faculty members

15+

Part-time

Yes

Live Lectures

Yes

Practical hands-on exposure

Yes

Certification

Yes

Specialization available

Yes. Asset/Strategy Type.

Platform

Various

Programming language

Python

Algo Trading Strategy Paradigms

Yes

Networking and latency

Yes

Project

Yes. Hands-on project work under industry practitioners.

Algo Trading desk setup guidance

Yes

Dedicated placement services

Yes. Lifetime placement assistance for all EPATians.

Dedicated student support team

Yes. Plus a dedicated support manager for your 6 months at EPAT.

Course content access

Lifelong updated course content access via the Alumni Portal.

Alumni community

Yes

Industry benefits

Yes. Access to exclusive offers from top brokers, vendors, global events, cutting-edge tools, etc.

Guest lectures

Yes. Exclusive Guest lectures from industry stalwarts.

Convocation

Yes. Online Convocation ceremony on completion of EPAT.

Scholarship

Yes

Financial aid

Yes

Verified certification

Yes

Exam centre

With proctored exam centres in 80+ countries, the participants have a choice to pick between the Online and In-center Proctor exam as per their preference.

Resolving queries and doubts

Yes. Direct online interaction with the faculty.

Lecture recording availability

Yes. Via the Student Portal.

Backtesting and Live Trading

Access to Blueshift

Counselling session

Yes

Learning Material

Yes

Read about entrepreneurs, traders, developers, analysts from around the globe, who changed their lives by gaining the must-have skills set in algorithmic trading. in these Success Stories about Algorithmic Trading.

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Strengthening the basics: Preparatory lectures on Python and statistics are conducted to ensure that you establish a strong base.

Concept clarity: Midterm exams help participants gain clarity of the concepts covered before the course progresses to advanced topics.

Pre-requisites for joining EPAT: EPAT participants are equipped with high intellectual curiosity, possess a strong interest in finance and have analytical skills.

Although there is no specific degree requirement, most participants joining the programme come from various quantitative disciplines such as mathematics, statistics, physical sciences, engineering, operational research, computer science, finance or economics.

Participants from other disciplines should be familiar with basic financial markets understanding, spreadsheets and computational problem solving if they wish to pursue EPAT.

To know more about EPAT, visit here, or directly connect with us.

Step 3: Get placed, learn more and implement on the job

It is often seen that students who would like to get placed in high-frequency trading firms or in quantitative roles, go for MFE programs.

  • Most of the MFE programs give a very good overview of mathematical concepts including Calculus, PDE and Pricing Models.
  • For learning quantitative trading, what is also required is the implementation of these skills/theories on actual market data under a simulated environment.
  • It is always better to get trained by practitioners and traders themselves if the aim is to go out there and make some money!
  • If you would like to pursue research in these fields, then taking a more academic path is recommended.

Once you get placed in an algorithmic trading firm, you are expected to apply and implement your algorithmic trading knowledge in real markets for your firm. As a new recruit, you are also expected to have knowledge of other processes as well, which are part of your workflow chain.

As an example, firms which trade low latency strategies will usually have their platform built on C++, whereas in trading firms where latency is not a critical parameter, trading platforms can be based on a programming language like Python. Thus, it becomes essential for aspiring and new Quant Developers to have an understanding of both the worlds.

New recruits working on specific projects may be given a brief training to get a good grasp on the subject. Trading firms usually make their new recruits spend time on different desks (e.g. Quant Desk, Programming, Risk Management Desk) which give them a fair understanding of the work process followed in the organization.

To put it in subtle words,

Learning in the algorithmic world never stops!!

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Career opportunities that you can take up after learning Algorithmic Trading

Frequently Asked Questions about Algorithmic Trading

Here are some of the most commonly asked questions which we came across during our Ask Me Anything session on Algorithmic Trading.

Question: How to go step-by-step to algorithmic trading from 0 to 90?

Reply: So if you are starting from 0 the key things to note here is that algorithmic trading typically would have 3 major pillars which the whole algo at quant trading stands on.

  • Statistics & Econometrics
  • Financial Computing
  • Quantitative Trading Strategies

If your knowledge in all these three domains is 0 then the first thing will be to learn about it. There are a lot of resources available out there. Even on QuantInsti’s website, there are a lot of resources that are freely available to start with and then progress towards automating.

  • In case you are new to trading strategies then learn about them.
  • If you are already a trader but are looking at automation then you can use some broker API and start automating your strategy.
  • But if you are already doing that, in that case, you can move ahead and get a medium frequency trading strategy and code it on a vendor platform.
  • If you are an expert programmer yourself or you have a team of expert programmers then you can build your own API as well and build your own trading platform as well.
  • You can code your strategy on that platform and if everything is well set then as an institution or a prop house you can venture out in the high-frequency domain.

That’s typically 0 to 90.

Question: I’m a trader but I don’t know how to programme. How should I get started with Algorithmic Trading?

Reply: The good part is for most of the tasks that you would need to do in algorithmic trading, you don’t need hardcore programming expertise in the languages like C++ or C, but if you have that, that’s great but even if you don’t have that or have a decent understanding of languages like Python, that also works.

Python in the last 5 years has come up like anything. So if you know a bit of Python but not C++ or Java that also works but you do need to know a bit or you will be handicapped.

Another good part is we have seen so many people who do not have a programming background but have been able to pick up programming languages like Python with much more ease in comparison to the difficulty they use to face with C++ or Java. Though, it will need a lot of effort, time and commitment on your side if you have never done programming in your life before.

Question: Can EPAT help me to develop all the three skills (Statistics & Econometrics, Financial Computing and Quantitative Trading Strategies) to become an algorithmic trader?

Reply: Yes! It definitely can.

Question: How comprehensive is the EPAT programme? Would I get profitable strategies from EPAT?

Reply: I think it’s quite comprehensive. The interesting part about EPAT is that we start right from the basics for each of these pillars of quantitative and algorithmic trading which we have discussed few times in the earlier questions. But it goes up pretty fast and does touch upon a decent number of advanced topics and more in depths topic on the statistical way of trading.

Another interesting part is that most of the EPAT faculty members are practitioners, which means you learn things more from practical orientation point of view, the theory at times is required and has to be covered but there is a certain level of practical touch we try to maintain.

We don’t claim to give profitable strategies to our students. It’s not that we give you 10-20 strategies and you trade with them while making a lot of money, that’s definitely not the idea of the programme.

The thing is if there is a strategy that works for you, it might not work for me. I might have a different infra, different setup, different risk tolerance, different system, there are too many variables that are out there.

So it’s not about profitable strategies but how to model those strategies, coming up with strategy ideas and testing them out, optimizing them, implementing them and the complete flow.

The idea is that by the end of the course you should be able to create hundreds of your own trading strategies and then it’s up to you, what you implement and what you don’t. So it’s more about the power of knowledge than the power of strategies.

Executive Programme in Algorithmic Trading

Lifetime Placement Assistance

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Question: Do you provide professional alumni social network?

Reply: We are in the process of building a community right now which is exclusive for all the EPAT participants and the alumni. So there are two things, one which is exclusive for them that comes with a lot of things with it and one which is already open for all but we are improving it a bit for an enhanced experience, which will be coming this year itself.

Suggested reads:

We have curated a list of some of our most demanded blogs on Algorithmic Trading written by experts!

Conclusion

This article gives an overview of algorithmic trading, the core areas to focus on, and the resources that serious aspiring algorithmic traders can explore to learn algorithmic trading.

Do let us know your thoughts on it and feel free to share any suggestions in the comments below.

In case you are also interested in developing lifelong skills that will always assist you in improving your trading strategies. In this algo trading course, you will be trained in statistics & econometrics, programming, machine learning and quantitative trading methods, so you are proficient in every skill necessary to excel in quantitative & algorithmic trading. Know more about the EPAT course now!

Disclaimer: All data and information provided in this article are for informational purposes only. QuantInsti® makes no representations as to accuracy, completeness, currentness, suitability, or validity of any information in this article and will not be liable for any errors, omissions, or delays in this information or any losses, injuries, or damages arising from its display or use. All information is provided on an as-is basis.

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