Quantitative trading, popularly known as 'quant trading', is a sophisticated method of trading using quantitative analysis of historic and back-tested data, market conditions and trade volume to devise profitable investment strategies. The popularity of quant trading or algorithmic trading has risen rapidly with the advancement in technology which eliminates human or emotional factors that can negatively impact investment strategies. Instead, quant traders and coders use complex financial and pricing models to devise their trading strategies or modify existing ones with their programming expertise in C/C++, Python, MATLAB and/or R. This makes decision making less susceptible to biases and increases their chances of turning profitable.
To get through an investment bank, a hedge fund or any other financial institution as a quant trader, candidates need to pass a very difficult and rigorous interview process. The interview questions encompass intensive math, statistics and probability questions, along with computer science fundamentals. They also include complex puzzles to determine the analytical and logical understanding of the candidate. The talent that finds a role at the end of the process usually comes from either a top tier academic institute or has a proven track record and experience in the industry. The market or region where the individual has gained his/her expertise plays a vital role, as some markets are more matured than the others, presenting more challenging scenarios which can expose the professionals from that region to a wealth of experience.
Below, we look at the desired skill sets required to enter in the quantitative trading space as a "Quant". We will also discuss the possibilities of movement of talent from non-financial sectors and their chances of succeeding in quantitative trading.
From what we've seen at Aquis Search, finance or engineering graduates from top tier institutes have been very successful in getting through the recruitment process. An additional specialised degree or diploma in financial engineering, statistics, analytics or data science is also an advantage. The challenge for employers is the availability of talent and so having an academic specialisation in the areas mentioned above increases any candidate's chances of standing out at top tier firms. This especially holds true in the case of graduates who have little to no professional experience to back them.
Knowledge of financial markets and trading strategies
The value of a quant trader is determined by the kind of financial market knowledge they possess along with the trading strategies they have worked on or developed in the past. A proven track record puts a trader in a commanding position as they are revenue generating from day one of joining a business. However, in order to develop their portfolio, the trader must be constantly aware of the pulse of the market. They should be proficient in analysing the micro and macro-economic landscape of the world and leveraging their ability to analyse data to execute profitable trades.
Technology and programming skills
Programming is an integral part of quantitative trading. The information and insights derived from large data sets allow for the execution of more accurate trades through the use of precise coding. The interview process for a quant professional will focus on assessing a candidate's ability to code productively. While the role might require just 30% of an individual's time coding, employers consider it essential to have detailed knowledge. As a result of this, candidates often will be evaluated as a full-fledged coder.
Quant traders are required to know programming languages like C++ or Python to create and execute programmable scripts on the infrastructure created by the tech teams in a business.
Research and analytical skills
The strategies developed and executed can only be as strong as the research on the historical and market data conducted in the backend. Researchers and analysts are usually profiles that are taken up by graduates entrusted with the sole responsibility of gathering pertinent market information that can assist in formulating successful trading strategies.
A trader's mindset
In addition to being thorough with finance fundamentals and advanced theories, successful traders have to be ingenious and inventive about their trading strategies. They might also have to think 'out of the box' and be unorthodox in their approach. This requires them to be calm under pressure and persistent. When it comes to financial strategies they need to be comfortable with unchartered territories and have a risk-taking appetite that can yield results.
Hiring from outside of the industry vs existing experience hires
The bar set for academic and professional excellence is considerably high when it comes to quantitative trading. The skills, knowledge and expertise required are proportionately compensated as this sector has one of the highest paying bonuses and fixed compensations. This makes it a sought-after job and attracts individuals who are outsiders to the world of quant trading. The question is: Can individuals from outside of the industry build a successful career in quant trading? The answer is a 'yes' but with conditions applied. Most of the skills required are transferrable and hence gives a chance to the non-financial professionals to develop a career in quant trading.
Strong mathematical, statistical and programming skills with an eye for detail when it comes to numerical analysis. Although these are seen as 'must haves', there are many more qualities and traits that candidates from outside the financial industry should possess to succeed in their job search. These aren't finance-specific skills and are mostly linked to personality.
a. Attention to detail
With the volume of data, an individual needs to work with, overlooking the detail can be the difference between a successful and failed strategy. In many cases, senior management relies on this data to base their financial working, which means missing out of crucial details can compound the error and can cost the firm millions.
b. Ability to work under pressure in a competitive setting
In the high-octane environment where decisions are made on the current market scenarios, delay in analysis can mean a considerable loss due to market volatility. This subsequently impacts the trade execution strategies leading to a missed opportunity.
c. Logical thinking and analytical mentality
Most problems on their face value would seem unsolvable. However, a professional with a logical approach towards these problems with the ability to break them down into smaller questions and approach them in a step-by-step manner would be the apt candidate for these roles. Again, in such scenarios, individuals should possess incredible attention to detail to ensure they don't skip important pieces of information.
Be prepared for a steep learning curve
Quant trading is essentially a technology backed timely execution of trades. Decision-making and success are based on the analysis of market data, trends, historical information and consumption patterns that transform an educated guess into a statistically probable outcome favouring the trader. This implies, with the advancement of technology and its ability to retrieve data on demand, the key to success lies in the ability of the quant trader to comprehend and capitalise on the gathered data turning them into insights. This is possible only when the incumbent has the know-how and acumen to understand and reason financial situations. This combination of theoretical knowledge and the ability to skillfully manipulate financial data is what separates the best candidates.
Although it is essential for professionals to have a strong academic background in engineering or an MBA from top-tier universities, they need to demonstrate a strong propensity to understand financial nuances. The financial industry inherently is known for its requirement of excellent mathematical and analytical skills amongst other requirements. Most of the skills are transferrable. However, what makes the job a challenge is a fact that there is a combination of skills that professionals are expected to exhibit making it a demanding profession. A professional from a finance background would have garnered these traits over the span of his/her career. However, a non-finance professional would be required to bring themselves up to speed in a much shorter period. This is what is probably the biggest learning curve of professionals from outside the industry.
Quant relies heavily on the accurate analysis of patterns. What may seem as 'data noise' can reveal crucial repeating patterns which can be pivotal in devising sustainable and profitable strategies. The ability to undertake these activities with the capability of translating them into fluent lines of code might take some time to master, but once successful, individuals are sought after by the top quant firms globally. Quant trading is technology intensive as it is and is still undergoing a rapid evolution with the advent of new technologies. The breakthroughs in the field of cloud computing, artificial intelligence and machine learning have made quant trading more sophisticated and have given rise to some exciting start-ups that are providing specialised services.
Daniel Vaz, the Managing Consultant with Aquis Search, has over six years of specialised experience in recruiting high-frequency quantitative trading professionals in APAC and Europe. Contact him on email@example.com