Steps to become a quantitative trader

Lucrative salaries, sizeable bonuses, and creativity on the job have made quantitative trading an attractive career option. Quantitative traders, or quants for short, use mathematical models to identify trade opportunities and buy and sell securities. The influx of candidates from academia, software development, and engineering has made the field quite competitive. In this article, we’ll see what quanta do and the necessary skills and education.

Key takeaways

  • Quantitative traders use strategies based on quantitative analysis (mathematical calculations and numerical calculation) to find trading possibilities that can involve hundreds of thousands of securities.
  • An aspiring quantitative trader must be exceptionally skilled and interested in all mathematical questions; If you don’t live, breathe, and sleep numbers, this is not the field for you.
  • A bachelor’s degree in mathematics, a master’s degree in financial engineering or quantitative financial modeling, or an MBA are all helpful in getting a job; some analysts will also have a doctorate. in these or similar fields.
  • In the absence of an advanced degree, a candidate must have at least on-the-job training and experience as a data analyst; Experience with data mining, research, analytics, and automated trading systems is a must.
  • Traders also need soft skills, such as the ability to thrive under pressure, stay focused despite long hours, endure an intense and aggressive environment, and stomach setbacks and failures in the pursuit of success.

What do quant traders really do?

The word “quantitative” is derived from quantitative, which essentially means working with numbers. The advancement of computer-aided algorithmic trading and high-frequency trading means that there is a large amount of data to analyze. Quants extracts and investigates available prices and listing data, identifies profitable business opportunities, develops relevant business strategies, and capitalizes on opportunities at lightning speed using self-developed software. In essence, a quantitative trader needs a balanced combination of in-depth math knowledge, practical trading exposure, and computer skills.

Quantitative traders can work for investment firms, hedge funds, and banks, or they can be proprietary traders using their own money to invest.

Technical skills

An aspiring quant must have, at a minimum, experience in finance, mathematics, and computer programming. Additionally, quants must have the following skills and backgrounds:

  • Numbers, numbers and numbers: Quantitative traders must be exceptionally good with math and quantitative analysis. For example, if terms like conditional probability, skewness, kurtosis, and VaR don’t sound familiar, you’re probably not ready to be quantitative. In-depth knowledge of mathematics is imperative to research data, test results, and implement identified business strategies. The identified trading strategies, the implemented algorithms and the trading execution methods must be as foolproof as possible. In today’s world of ultra-fast trading, complex number processing trading algorithms occupy the majority of the market share. Even a small error in the underlying concept on the part of the quant trader can result in a large trading loss.
  • Education and training: It is usually difficult for recent college graduates to get a job as a quantitative trader. A more typical career path is to start as a data research analyst and become a quant after a few years. Education such as a master’s degree in financial engineering, a diploma in quantitative financial modeling, or electives in quantitative flows during the regular MBA can give candidates an edge. These courses cover theoretical concepts and practical introduction to the tools necessary for quantitative trading.
  • Business concepts: The Quants are expected to discover and design their own unique business models and strategies from the ground up, as well as customize established models. A quantitative trading candidate should have a detailed understanding of popular trading strategies, as well as the respective advantages and disadvantages of each.
  • Programming skills: Quantitative traders should 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 essential, and the more programs the candidate knows, the better. C ++, Java, Python, and Perl are some commonly used programming languages. Familiarity with tools like MATLAB and spreadsheets, and concepts like big data and data structuring, is a bonus.
  • Use of the computer: Quants implements its own algorithms on real-time data containing prices and quotes. They should be familiar with any associated system, such as a Bloomberg terminal, that provides data and content feed. They should also be comfortable with charting and analysis software applications and spreadsheets, and should be able to use broker trading platforms to place orders.

$ 125,000 – $ 500,000 +

The pay range for quantitative traders (with added bonuses), based on recent statistics, with the high level reserved for seasoned traders with advanced titles (who likely work in a hedge fund).

Soft skills

Beyond the technical skills mentioned above, quant traders also need soft skills. Those employed in investment banks or hedge funds may occasionally need to present their developed concepts to fund managers and above for approval. Quants don’t typically interact with customers and often work with a specialized team, so average communication skills may suffice. Additionally, a quantitative trader must have the following soft skills:

  • The temperament of a merchant: Not everyone can think and act like a trader. Successful traders are always looking for innovative business ideas, can adapt to changing market conditions, thrive under stress, and accept long hours of work. Employers thoroughly screen candidates for these traits. Some even conduct psychometric tests.
  • Risk-taking skills: Today’s business world is not for the faint-hearted. Courtesy of margin and computer-dependent leveraged trading, losses can reach greater amounts than a trader’s available capital. Aspiring quanta must understand risk management and risk mitigation techniques. A successful quant can make 10 trades, face losses on the first eight, and make a profit on just the last two trades.
  • Comfortable with failure: A quant continues to search for innovative business ideas. Even if an idea seems foolproof, dynamic market conditions can make it a failure. 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 therefore are unwilling to give up their concept. On the other hand, successful quanta follow a dynamic detachment approach and move quickly to other models and concepts as soon as they encounter challenges in existing ones.
  • Innovative mindset: The business world is very dynamic and no concept can make money for long. With algorithms pitted against algorithms and each trying to outperform the others, only the one with the best and unique strategies can survive. A quant needs to keep looking for new innovative business ideas to take advantage of profitable opportunities that can quickly disappear. It is an endless cycle.

The bottom line

Quantitative trading requires advanced-level skills in finance, math, and computer programming. Big salaries and sky-high bonuses attract a lot of candidates, so landing that first job can be challenging. Beyond that, continued success requires constant innovation, comfort with risk, and long hours of work.

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About the author

Mark Holland

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