Foundations of Quant: Behind the Math and Models 

You’ve likely heard the word “Quant” before, especially if you look at financial data or work in the industry. What is its history and can just anyone jump into the Quant pool? Ishan Shah, AVP of Research & Content at QuantInsti joins Cassidy Clement, Senior Manager of SEO and Content at Interactive Brokers to discuss the basics of Quant.

Summary – Cents of Security Podcasts Ep. 24

The following is a summary of a live audio recording and may contain errors in spelling or grammar. Although IBKR has edited for clarity no material changes have been made.

Cassidy Clement

Welcome back to the Cents of Security podcast. I’m Cassidy Clement, senior manager of SEO and Content at Interactive Brokers. Today, I’m your host for our podcast. Our guest is Ishan Shah, the Assistant Vice President of Research and Content at QuantInsti. We’re going to discuss the basics of quant. You’ve likely heard that word before if you look at financial data or work in the industry. So what’s its history? And can anyone just jump into the quant pool? Welcome to the program, everyone. So, Ishan, thanks for joining us on Cents of Security.

Ishan Shah

Yeah. Thanks for having me, Cassidy.

Cassidy Clement

Sure, of course. So what’s your background in the quant industry?

Ishan Shah

Yeah. Thanks for asking. So currently I’m working in Quantra by Quantinsti on the research and content team. And my primary job is to create content around algo and quant trading courses and prior to that I work with Barclays in their capital markets division. And before that, I’ve worked with Bank of America, Merrill Lynch, their OTC products division and I’ve also written a book on machine learning for trading. So that’s my background.

Cassidy Clement

What is the background of quant? Like a brief history of quant. A lot of people have heard that word, but if you were to explain some of that to our listeners..

Ishan Shah

Yeah, sure. So quant basically describes the profile of people who use mathematical or statistical models to base their trading decisions. So the history is actually quite old. Like you can say that even before the advent of such high-speed computers, people were using some kind of mathematics to base their trading decision. They were in a way “quant”, but they become more prevalent. The invention or with the bringing of option pricing models in during 1960s and 70s. That’s where I will say that the real birth of quant started. And during 80s and 90s, we had these famous hedge funds like Renaissance Technology and Long Term Capital Management, which made it quite prevalent during those times and later on from 2000 with the advent of high speed computers and other stuff, there was a lot of room and the quant actually grew quite fast. Like you’ll see that high-frequency trading firms, machine learning data analysis and what not actually became quite prevalent from there on.

Cassidy Clement

Would you explain quantitative finance kind of in the finance space? I mean you mentioned investment banks, hedge funds, sometimes there’s large amounts of models involved. Where would an investor or a reader of financial journalism normally see reference to quant? I know financial engineering gets mentioned a lot in the same breath. Where would they normally see that?

Ishan Shah

So quants are prevalent in lot of spaces in finance. So you rightly mentioned they will be there in asset management firms and typically they will help to build their portfolios using quantitative techniques. So they will use some kind of a machine learning algorithm to determine which assets should be combined together and create a holistic performance which can give better risk adjusted returns. Or they can be there in high frequency trading firms where they’ll be very smart. Some smart strategies where they are buying and selling at a millisecond or even nanoseconds and making trading profits for the firm. Or they might be sitting in a risk management division. They would be assessing how much risk should be given per trader or per company.

They can also assess credit risk of a company through these quant models. So you can think they are present in a lot of divisions across finance. During the 2008 financial crisis, there was even much more need for using this quant so that you have a better risk management solution in your team.

Cassidy Clement

So you had mentioned that you can see these quants or this field of study or this line of work in many different departments within the financial space. But are quants more prevalent at a large scale at some of these companies? Or does it depend on the type of business that they’re involved with? Because usually if you’re talking about math in general- finance, engineering, it’s filled with math, but are some businesses more likely to have a higher amount of quants in part of their workforce than others?

Ishan Shah

It depends on what kind of business it is. You’re right. So with the traditional asset management company, which is primarily doing equity research to base their decisions, they will most likely not hire so many quants. They will have, let’s say one or two quants. And on the other hand, if it’s a like a hedge fund like I mentioned, Renaissance Technology or such a large hedge fund, they will have quite a large number of quants who are working across their divisions, trading divisions and helping the firm in achieving their objective.

As you rightly mentioned, this is a very skillful job in the sense you should be aware of three skills. One is in programming, you should be fluent with. Second is you should be aware of these mathematical and statistical models. And 3rd is you should also be aware of some trading nuances. These three skills are very difficult to get in a single individual. Therefore they are concentrated more on the hedge fund and prop trading firms and lesser on the traditional asset management firms.

Cassidy Clement

So you had mentioned models programming and then some deep mathematical understanding. So what are some common topics that are usually covered within the quant space outside looking in? I’m not a quant. But I know that there are some key topics that I will see when it comes to high level discussions about quant, whether it’s white paper or discussions about the space in general, whether it’s programming languages, the pricing knowledge, volume, large amounts of data or different types of mathematical theory. So what are those common topics that you would say people who are new to this space should try to brush up on that they’re going to come across pretty often?

Ishan Shah

Yeah, that’s actually very relevant question. And we also get asked this question quite a lot by newbies in this space. So one of the most important topics or the knowledge required is let’s break it down into three domains. So first is in terms of mathematical and statistical knowledge, you should be aware of basics of mathematics like what is correlation, what is cointegration and also how to perform various kind of hypothesis testing and able to interpret the distribution curves and able to identify the patterns in it and so on. So this is about mathematics.

Then let’s move on to the programming side. As a quant, you will be working with large amounts of data. Here in high frequency space will be working with huge data. So you should be pretty much fluent in working with various data sets like how to retrieve this data, where to store this data, etc.

And once you retrieve the data, how do you play around with this data and identify the patterns? So let’s say if you go to Python programming, you should be familiar with all that stuff. And 3rd is in terms of trading. So since you’ll be trading or actually placing the orders in the market, there will be an impact whenever you hit the market. So you should be aware of various basics like market microstructure. Like what is an order book? What is a data spread and how to trade in market, so on and so forth.

So this is the basic stuff. So on top of this you can build your expertise in programming. So for example, if you’re interested in machine learning, once you’re through with the basics of maths you can then get into machine learning where you can start with basics like regression and classification models and later on move to neural networks and reinforcement learning kind of models. And similarly in trading, once you’re familiar with basics of market microstructure, then you can move on to more complex and advanced strategies like, let’s say, statistical arbitrage strategy, momentum trading, and even you can use new sentiment or use natural language processing to abstract new sentiment and trade using that.

Cassidy Clement

With some of these topics that you mentioned, are some quants in a specialized field, meaning they only specialize in certain products? Because you can apply a lot of these languages or models to things like stocks, bonds, commodities. But do quants usually specialize?

Ishan Shah

So generally quant is a transferable skill. So for example you’ve developed model for stocks. Let’s say you developed a momentum trading strategy for stocks. You can easily transfer that strategy to commodities market. So some of the strategies and some of the skills that even like machine learning are easily transferable across the asset. All that you have to learn is the nuances which that particular asset class belongs in.

For example, you should understand what are the specific nuances in only the currency market and not in stock market. For example, they are not very volatile. You can leverage much more than what is available in stocks. So if you have the basics clear, you can easily transfer your strategy from one market to another. People usually specialize on the strategy part, so they would be like someone would specialize on machine learning side, someone would specialize on high frequency trading side. And readily apply across the spectrum.

Cassidy Clement

What are some ways that someone can learn about quant if they are not at a firm that practices quant?

Ishan Shah

That’s a good question. So they can basically learn from multiple sources. So the old way of learning is through books and I have also written a book on machine learning for trading. So you can start with that and it’s actually free for everyone. And 2nd is you can also read a book by Ernie Chen. The name of the book is Algorithmic Trading: Winning Strategies and Their Rationale .

And similarly you will find books by Marcus Lopez de Prado on Advances in Financial Machine Learning Based on your area of interest you will find these books. If you want to start from very basic you can also start with an options book by John C Hull (Options, Futures and Other Derivatives). So that is one way.

Another is if you are just very young and you’re not used to this old ways of learning, then you can also start with online courses so you can start with Quantra where I’m currently working. It has courses on algo and quant trading or you will find these courses at other places also. So based on your inclination and where you find the right objectives where your objectives are met, you can start with that. The 2nd is online courses and 3rd is you can also join some events, seminars, even podcasts like one which we are doing to increase your knowledge about this space.

Cassidy Clement

So, are there some soft skills that quants may need to make sure they’re prepared for? Like maybe long hours or tedious tasks since you’re looking at large data sets? Anything like that that you can recall?

Ishan Shah

Typically at entry level the requirement of soft skills is less. It’s more about you as the individual contributor. You’re given a task, you’re delivering on those tasks and you just need patience to deal with long hours. But as you grow in your role, you become a team leader. That’s where your soft skills become even more important. You have to manage a team. You have to understand their requirements and deal with it. And similarly, if you start growing even much more then there will be a client side to it where you have to talk to clients, explain what kind of trading strategies you are deploying and the requirement of soft skills will be much more higher when you move to the client side of the room.

Cassidy Clement

So some people say that going into the quant field or to become a quant that you have to love numbers, like eat, breathe and sleep numbers. Do you agree with that or do you think that somebody can come in from maybe more of a standard issue finance side and jump in?

Ishan Shah

Yeah. So I don’t have any particular bias. I feel anyone who has zeal for learning and inclination to excel in this field will eventually make it in this field and do well. But someone who is very good with numbers, who loves this field very passionate about this is definitely more likely to succeed in this field. Because every now and then you are dealing with some model, analyzing back testing results, you’re looking at various parameters like sharp ratio or analyzing what are the P&L distributions.

So if you love numbers, it’s very easy to pick up these skills and it will come naturally also, right? You can easily spot if there is some anomaly or some something is wrong. So that gives an edge. But I’ve seen a lot of people who are not from mathematics background, like very different non-mathematics background that come to us and learned from us and eventually they made it big in this field.

Cassidy Clement

So normally within the quant space- from an education perspective are people usually just bachelor’s degree, a mix between that and masters and phD? What do you normally see within the space?

Ishan Shah

So what we currently see is across the dimensions people are getting into this field. Like we even had someone who was 70 years old after retirement, was so much passionate for quant trading. We see also a lot of young guys who get into this after their Bachelors or even after their Masters. They want to start their own trading desk or they want to make a career in this field. That’s their primary objective of getting into this field. But I’ll say the majority of them would be around their 30s who typically want to use quant in their own trading sector. And the younger crowd is mostly looking to make a career in this field where they’ll be joining some or the other.

Cassidy Clement

Interesting. Those are some interesting points. So thanks for joining us, Ishan.

Ishan Shah

Thanks Cassidy. I hope this was helpful.

Cassidy Clement

Yeah, thank you. So as always, listeners can learn more about an array of financial topics for free at ibkrcampus.com; follow us on your favorite podcast network and feel free to leave us a rating or review. Thanks for listening everyone.