In the U.S., generally, quant professionals are offered salaries of around $130,000 (according to Indeed). Although, the experience of the quant, the job role and the expertise matter in determining the exact salary, a quant usually earns well. This blog will give you a deeper insight into the salary of a quant in general as well as where the quants are employed.
To give you an example of the impact of quant trading, Man Group's AHL Dimension programme is a $5.1 billion dollar hedge fund with the help of quants.
Let us find out more about the quantitative analyst and the salary aspect of the same with this blog that covers:
- Who is a quant?
- All about the quant salary
- Skills for becoming a quant trader
- The job responsibility of a quant
- Where do quants get employed?
- Future of quants
- A candid conversation with an algorithmic trader
Who is a quant?
Simply speaking, a quant or a quantitative analyst holds knowledge of the three fields, namely:
- Programming language (Python, C++ etc.)
Hence, a quant applies the knowledge of mathematical and statistical methods (such as numerical or quantitative techniques), to financial and risk management problems. A quant applies the knowledge of above mentioned fields to fulfil any trade related requirement.
For instance, in order to identify and evade the risk of trading a particular stock, the quant will calculate the probability of risk occurrence as well as the possibility of the amount of risk involved. The quant will then create a computer algorithm of the solution to execute the solution in an automated manner.
All about the quant salary
Let us now find out the average salary of a quant or a quantitative analyst in different regions/countries.
Average Base Salary/year
Please note that this is the average base salary computed from leading portals such as Indeed, LinkedIn, Payscale and Glassdoor.
Also, it is important to mention here that, since a majority start as freshers, they get the benefits of a joining bonus and profit-sharing which are not included in the base salary. Hence, the actual salaries are higher.
Also, the better and more relevant your skill sets are, the more are chances that a prospective company will hire you. Becoming a quant requires effort from your end, but the results are much more rewarding from a career point of view.
Hence, even as amateur traders, you can surely climb the ladder up to become a professional quant someday!
Note: The salary figures may vary across companies, roles, experiences and other factors.
Skills for becoming a quant trader
We just mentioned the relevant skill sets for increasing your chances of being hired by a firm as a quantitative analyst. But, what are those relevant skills?
Let us take a look at each skill briefly here:
- Programming - For becoming a quant, you must have a good hold of programming skills. Python being the most favoured computer language is used the most by quants.
- Probability and statistics - A key part of trading is a good knowledge of probability and statistics. Basic statistics, time series, multivariate analysis etc. are used for formulating strategies, and risk-management.
- Markets and the economy - Good knowledge of how markets and the economy work helps the quant sustain in the industry.
- Analytical thinking - A big role is played by an individual’s analytical thinking and the capability to work out the problem with strong reasoning.
Hence, these were some of the most integral skills for becoming a quant. According to the job responsibility of each role in the quant domain, the skills come into use.
The job responsibility of a quant
As a fresher, a quant will be working in a team with other quants for creating trade related models or strategies.
Usually, the job responsibility of a quant requires the individual to perform the following tasks:
- Trading a vast portfolio.
- Analysing hundreds of gigabytes of data to ascertain micro behavioural patterns (at the microsecond time frame) to trade at such signals.
- Simultaneously, while trading, analysing information across time and assets to build macro signals.
- Creating automated trading signals with the help of algorithms.
- Performing risk management while trading.
- Discovering and imitating the logic and, thereby, automating the process of setting the hundreds of parameters or conditions of trading that traders do on a daily basis.
But as you move up the ladder, you will be able to handle much more. Take a look at the various job roles of a quant, which are as follows:
- Junior analyst
- Quant analyst
- Quantitative research analyst
- Senior quantitative analyst
Note: The job responsibilities may vary across companies, roles, experiences and other factors.
Where do quants get employed?
The simple answer to this question is, Quant Funds!
Before we begin with what a quant fund is, it is a must to mention that aspiring individuals need to crack the quant interview in order to get started as a quant.
At first glance, you might think - What is the big deal about a quant fund?
It must be just another one in the plethora of options we have today, like index funds, mutual funds etc. But drill down and you will find that quant funds are slowly but surely getting a foothold in the industry.
If you look at the US market, the two big names are Renaissance Technologies and Two Sigma. While Renaissance Technologies has AUM of US $130 billion ⁽¹⁾ (April 2021), Two Sigma is reportedly managing $58 billion ⁽²⁾ (January 2020) of AUM.
In the era of diversification, quant funds have, thus, created demand from investors who are seeking a relatively structured fund. This has also spiked up the demand for quants who are already fewer in number.
While most of the fund houses would definitely have profit-sharing as a part of the compensation package, there are countless examples of quants who have set up their own algorithmic trading desks.
Future of quants
There is a reason Quants have become sought after in the world of finance, especially trading.
Back in the day, manual traders used to apply technical analysis tools as well as fundamental analysis to gauge whether the stock is worth investing in or not. Over time, complex mathematical models were built to assess the profitability of a trade.
In the quest to develop a sound trading strategy which avoided human emotions, these models became increasingly complex and difficult to put into practice. Here is where the role of programmers came in, who developed the algorithms for the models.
Over time, it was realised that we didn’t need three different people to perform the task when one trained professional could easily perform them alone.
Going forward, in the next five years, it has been predicted that the demand for quants will grow significantly.
A candid conversation with an algorithmic trader
Let us see the interesting and useful information that we got from a candid conversation with a successful algorithmic trader. The questions and the answers by the trader himself are as follows:
How do you set up an algo desk?
Algorithmic Trading is a process of using a set of instructions to place an order of buying or selling scripts with volumes and speed impossible for a human being. The set of instructions is based on various market metrics like price, time, volume and any other user preference.
The good part about algo trading is that it eliminates human intervention thereby making trading sans emotions and intuition.
A typical Algorithmic system’s architecture entails three primary components
- Market Data Handler
- Strategy Module
- Order Router
The market data handler, as the name suggests, receives the market data and stores it. Strategies for trading, in a mathematical model, are fed to the strategy module. It also serves as an interface between the market and a trader.
Order Router or manager sends the order back to the exchange for buy/sell.
To set up an algo desk, as a broker you need to identify your co-location to place the servers in close proximity to the exchange, feed in your strategies to your system after having it backtested and authenticated, have a good internet connection, and I think you are good to go!
What are the steps would you suggest to venture into the field?
Well, the first and most important step is to build a solid base. Learn some programming skills and get a grip on the markets. Being good with numbers always helps.
Begin by exploring core subjects like statistics and econometrics. Some books like Quantitative Trading by Ernest Chan or Trading & Exchanges by Larry Harris can elaborate on setting up a “proper” Algorithmic trading system.
When you are through with the above-mentioned steps, get your hands dirty in strategy building, modelling techniques, and statistical tools.
Get a hang of various trading strategy paradigms, like statistical arbitrage, execution strategies, bid-ask spread. There are a few free courses available online on Quantra, Udemy and Udacity which are quite good to test the waters. There are other paid and advanced courses available for serious learners.
Which are the commonly used programming languages employed by traders?
C++ remains the most preferred language as far as High-Frequency Trading (HFT) goes. The reason being that memory leaks and related errors are far less in C++ as compared to other languages.
Python has come up in a major way for coding strategies as well as backtesting, because it is easier to master, and is backed by good scientific libraries like Numpy and Pandas.
A number of forums today discuss investing and trading strategies coded on Python programmes.
How is retail participation in Algorithmic trading?
The setting up cost is definitely on the higher side, than a traditional trading terminal. Obtaining a co-location can be an expensive affair.
According to recent statistics, nearly 70-80% of trades on Wall Street are executed using Algos, chiefly by large institutional investors and hedge funds.
However, the scene for retail participants is evolving with the offering of web-based platforms. For someone who is not too concerned regarding latency, it works like a charm. Other than that, firms like Interactive Brokers provide retail clients with API and packages so that traders can code their strategies and trade.
Once you get a hang of it, it is like a simple Gmail account. You log in to your account, test your strategy, perform backtesting, and after optimisation, trade in the live markets.
Paper trading or testing on a simulator is also highly recommended.
How is the ecosystem for Algorithmic Trading in India? Are companies readily opting for Algorithmic trading given its niche category and involvement of highly skilled practitioners?
Algorithmic trading was allowed in India by SEBI in 2008. In a span of 8 years, nearly 50% of the trade by volume or maybe even more than that is Algo-based. That speaks for its popularity.
Indian bourses have adapted to the change very well, with a steady increase in active participants. Both FIIs and domestic funds use the Algo route to place orders.
What does the future of trading look like?
The future of trading seems promising actually. It is clear that automation is the future that is driving the world. Be it in any field, automation is making a tectonic shift from a traditional path, and the same applies to stock markets. In US markets, 70-80% of the exchange volumes are happening through automated systems.
Emerging markets like India are witnessing exponential growth in the domain. Of course, the markets are maturing every day, so trading costs would decrease after a certain point.
Case in point: Automobile Industry, where after the introduction of robots, it was initially thought that the industry would be unsustainable due to high capital cost.
What are a few things that a beginner should keep in mind when venturing into this field?
The most important one is that it is just not enough to have a good trading strategy, but also to have a competitive edge.
It can range from having innovative ideas which disrupt, to having a low brokerage or the kind of markets you have access to, but you have to have a killer proposition if you plan to be successful. Treat this like any regular business, where you have to develop a strategy to outwit the competition.
It is important for someone starting new to have the nuances of the trade figured out.
What should be my next step if I want to understand more about this field?
The best way is to find experts and domain authorities to talk to and discuss your doubts. Try out freely available tools and resources on the internet. Be prepared to embrace new knowledge and develop new skill sets!
These were but a few questions answered by the trader themselves. What do you think, do you have any questions regarding how to be a quant or set up your own desk? You can always drop in a comment below and we would answer them as soon as possible.
Becoming a quantitative analyst is not only highly rewarding but is quite interesting as well since a quant works for a highly professional firm with several perks.
No doubt a quant’s journey to success requires a lot of hard work and dedication. But, once you enter a quant fund or an investment bank as a quant, the career scope is huge!
In case you want to find out more about quant, you must learn algorithmic trading with our algo trading course. You will be able to acquire the necessary skills required to become a successful quantitative trader such as programming, statistics, data analysis and modelling etc.
Also, EPAT is an in-depth learning experience since it is a full fledged programme and hence, will help you learn the required concepts in detail.
We wish you all the best for your successful quant journey!
Note: The original post has been revamped on 14th November 2022 for accuracy, and recentness.
Disclaimer: All investments and trading in the stock market involve risk. Any decision to place trades in the financial markets, including trading in stock or options or other financial instruments is a personal decision that should only be made after thorough research, including a personal risk and financial assessment and the engagement of professional assistance to the extent you believe necessary. The trading strategies or related information mentioned in this article is for informational purposes only.