Lucrative salaries, hefty bonuses and creativity on the job have resulted in quantitative trading becoming an attractive career option. Quantitative traders, or quants for short, use mathematical models to identify trading opportunities and buy and sell securities. The influx of candidates from academia, software development and engineering have made the field quite competitive. In this article, we’ll look at what quants do and the skills and education needed.
What Do Quantitative Traders Really Do?
The word “quant” is derived from quantitative, which essentially means working with numbers. The advancement of computer-aided algorithmic trading and high-frequency trading means there is a huge amount of data to be analyzed. Quants mine and research the available price and quotes data, identify profitable trading opportunities, develop relevant trading strategies and capitalize on opportunities with lightning-fast speed using self-developed computer programs. In essence, a quant trader needs a balanced mix of in-depth mathematics knowledge, practical trading exposure and computer skills. Quant traders can work for investment firms and banks, or they can be proprietary traders, using their own money for investment.
An aspiring quant should have, at minimum, a background in finance, mathematics and computer programming. In addition, quants should have the following skills and background:
- Numbers, numbers and numbers: Quant traders must be exceptionally good with mathematics and
quantitative analysis. For example, if terms like conditional probability, skewness, kurtosis and VaR don’t sound familiar, then you’re probably not ready to be a quant. In-depth knowledge of math is a must for researching data, testing the results, and implementing identified trade strategies. Identified trade strategies, implemented algorithms and trade execution methods should be as fool-proof as possible. In the present day lightning-fast trading world, complex number-crunching trading algorithms occupy a majority of the market share. Even a small mistake in the underlying concept on the part of the quant trader can result in a huge trading loss.
- Education and training: It is usually difficult for new college graduates to score a job as a quant trader. A more typical career path is starting out as a data research analyst and becoming a quant after a few years. Education like a masters in financial engineering, a diploma in quantitative financial modeling or electives in quantitative streams during the regular MBA may give candidates a head start. These courses cover the theoretical concepts and practical introduction to tools required for quant trading.
- Trading concepts: Quants are expected to discover and design their own unique trading strategies and models from scratch as well as customize established models. A quant trading candidate should have a detailed knowledge of popular trading strategies as well as each one’s respective advantages and disadvantages.
- Programming skills: Quant traders must be familiar with data mining, research, analysis and automated trading systems. They are often involved in high-frequency trading or algorithmic trading. A good understanding of at least one programming language is a must, and the more programs the candidate knows, the better. C++, Java, Python and Perl are few commonly used programming languages. Familiarity with tools like MATLAB and spreadsheets, and concepts like big data and data structuring, is a plus.
- Computer usage: Quants implement their own algorithms on real-time data containing price and quotes. They need to be familiar with any associated systems, like a Bloomberg terminal, which provides data feeds and content. They should also be comfortable with charting and analysis software applications and spreadsheets and be able to use broker trading platforms to place orders.
Beyond the above-mentioned technical skills, quant traders also need soft skills. Those employed at investment banks or hedge funds may occasionally need to present their developed concepts to fund managers and higher ups for approval. Quants do not typically interact with clients and they often work with a specialized team, so average communication skills may suffice. In addition, a quant trader should have the following soft skills:
- A trader’s temperament: Not everyone can think and act like a trader. Successful traders are always looking for innovative trading ideas, are able to adapt to changing market conditions, thrive under stress and accept long working hours. Employers thoroughly assess candidates for these traits. Some even give psychometric tests.
- Risk-taking abilities: The present day trading world is not for the faint-hearted. Courtesy of margin and
leveraged trading with dependency on computers, losses can reach to amounts higher than a trader’s available capital. Aspiring quants must understand
risk management and risk mitigation techniques. A successful quant may make 10 trades, face losses on the first eight, and profit only with the last two trades.
- Comfortable with failure: A quant keeps looking for innovative trading ideas. Even if an idea seems foolproof, dynamic market conditions may render it a bust. Many aspiring quant traders fail because they get stuck on an idea and keep trying to make it work despite hostile market conditions. They may find it difficult to accept failure and are thus unwilling to let go of their concept. On the other hand, successful quants follow a dynamic detachment approach and quickly move on to other models and concepts as soon as they find challenges in existing ones.
- Innovative mindset: The trading world is highly dynamic, and no concept can make money for long. With algorithms pitted against algorithms and each trying to out perform the others, only the one with better and unique strategies can survive. A quant needs to keep looking for new innovative trading ideas to seize profitable opportunities that may vanish in quickly. It is a never-ending cycle.
The Bottom Line
Quant trading requires advanced-level skills in finance, mathematics and computer programming. Big salaries and sky-rocketing bonuses attract many candidates, so getting that first job can be a challenge. Beyond that, continued success requires constant innovation, comfort with risk and long working hours.