The Different Types of Quant

Quants – or quantitative analysts to give them their full title – are big news in the finance, banking and investment industries.

From around the 1970s onwards, there has been rapid promotion and expansion of the ways in which maths and statistics – notably stochastic calculus (yikes!) – can make predictions in markets, price various financial instruments (determine how much assets should be sold for on the financial market due to supply and demand) and improve risk management strategies in the finance industry.

Some quants will lean towards a more mathematical focus in their work, whilst others are more statistically minded and have more strengths in areas like data modelling. Essentially they’re almost different mind sets, so you won’t usually find an ultra-quant who does both.

Who got algorithm?

Programming skills and extensive mathematical and quantitative knowledge and abilities are essential across the board for quants, no matter where they specialise. Skills and attributes that all types of quant tend to have in common include:

• A degree (often a Master’s or even a PhD) in a subject like mathematics, engineering, physics, financial mathematics, financial engineering or quantitative finance.
• Familiarity with computer programming.
• Logical and analytical thinking.
• Ability to interpret highly complex (and copious amounts!) of data.

Different types of quant

It isn’t just about being a mathematically minded quant or having strengths in statistics; there are different types of quant to be found across the financial industry. Here are a few of the main categories:

Risk management quants

The risk management quants belong to the middle office in an investment banks and firms, asset management firms or funds such as a hedge fund. These guys help to keep trader and sales representatives’ feet on the ground with the results of the risk analysis on various different assets and markets. They use various techniques – notably something called ‘value at risk’ (VaR) – to measure the risk of loss on a portfolio of assets.

Quants in risk management will feed back their findings to risk managers in their team. They’ll also perform stress tests, testing out their models.

Algorithmic trading quants

Arguably the most influential type of quant in the industry, it’s seriously a case of ‘knowledge is power’ when it comes to those specialising in algorithmic trading. Algorithmic trading uses highly complex mathematical models to give pre-programmed trading instructions to automated electronic platforms. A system is programmed to automatically buy or sell at a predetermined price and time.

The ever-increasing importance of these systems in the investment industry make these quant specialists top earner within investment firms.

Front office quants (FOQ)

On the front office lines with the salespeople and traders on the trade floor in an investment bank.

These quants develop models to work out the prices of assets on the markets and manage them: what to buy at and what to sell at etc. The calculations they make also help to provide guidance on risk management and support the traders in the development of their risk strategies. They’re also busy on the investment/business development side of things, using their mathematical and statistical techniques to spot potential new investment opportunities.

In terms of salaries amongst the quants, the front office quants are usually amongst the highest paid.

Investment/asset management quants

Asset management firms will also employ quants to assist in their risk management teams. These quants typically aren’t paid as much as front office quants, but the models they develop are of great importance to the mitigation of losses in investments and the integrity of the industry.

Quantitative developer

Quantitative developers or quant engineers are a branch of the technology department in an investment bank or financial services firm. They work on developing and maintaining the quant models used for pricing, risk management and analysis.  Specialist knowledge in coding and computer languages is key to this specialist area.

Decisions, decisions…Where do you think your strengths lie? The competition is tough, so be prepared for some hard work if you choose this career path.