Quant Trading / Quant Research

Hi WSO - hoping someone can shed some light on these two areas of finance. I've found bits and pieces of information, but no detailed breakdown of the two. Understand that there's also some variability in what the titles mean at different firms. 

Particularly interested in learning:

  • What do these jobs actually constitute - machine learning/AI? Coding/infrastructure development? Pen-and-paper math/statistics?
  • What does the day-to-day work look like?
  • How do these two career paths compare in terms of compensation, relative to each other and to traditional discretionary trading?
  • What does career longevity look like?
  • Are Masters/PhD programs in stats/math/comp sci/physics still the best way to land these roles? 
  • Is being at a "target school" as important for recruiting as it is at the undergraduate level?

Any info would be greatly appreciated. Thanks!

 
Most Helpful

Quant finance masters / sell side risk quant here. 

Quant Research

Typically refers to sell side that work on or near the trading floor. Most of the day is spent coding up pricing models for derivative products depending on the desk (e.g. equity, FX, rates, commodities, credit, structured products, etc.). Typically pricing models are implemented in C++. A lot of time is also spent building trading tools or analysis for the traders in a quick scripting language like Python. Another part of the job is monitoring the models or updating the ones that the desk uses to trade. Time is spent with different areas of the bank: S&T, model validation, IT, market risk, etc.). Overall, they are a support function for the traders, who might ask them to fix problems or understand a complex trade or how to risk manage the book. Longevity is OK as long as you like the role as it is stimulating but can also get tiring working as a support function.

Quant Trading

Typically refers to prop trading firms. Quant traders can be ETF market makers, equity options traders, or any other exchange traded derivatives trading. Typically these traders tend to look for signals in the market. For market making, market microstructure is heavily used (think high frequency trading, limit order book, bid ask spread, tick sizes, hidden orders, etc.). For equity options traders on the prop side, they'll look at volatility surfaces of individual names and have a view ("surface trading") by identifying areas on the surface that look mispriced (strategies include time spreads, verticals, etc.). Volatility traders typically stay delta neutral by hedging out their exposure to the underlying stock. Great longevity if you want to stay in trading and are good as you can make a lot of money.

Educational Comparison

Both areas require significant understanding of math, finance, statistics, and programming. Masters programs include financial engineering / quant finance / financial math / etc. and PhDs can be anything quantitative but mostly physics or math. QR requires stochastic calculus for pricing, numerical methods for implementation, and option pricing theory for fundamental understanding of derivatives. QT relies more on quick mental math and a practical understanding of risk management of the option greeks, a holistic understanding of portfolio theory, and what is going on with the markets. QT can hire out of the best bachelors (think top 10 US) and also masters students (typically not PhD unless its for a HF). QR will almost exclusively hire masters or PhDs from the top 20, never heard of a bachelor's quant. 

Compensation Comparison

QT typically starts off with a lower base than QR but eventually will be much more lucrative as bonus comp is discretionary depending on how the prop trading firm performs. Salaries in 2021 for QR are around 130k-160k base (capped at VP level probably around 225k) with bonus comp probably around 40%. QT starts off around 80k-120k and bonus in first year due to training can be lousy but the more experience you get managing a book and making money the base can start to raise in the 150k area and bonuses can range anywhere from 80k-400k and even up to 1MM+ for the most senior traders.

Not much ML / AI right now on the sell side. Mostly on buy side, specifically for high frequency trading. Could be used for longer term strategies too on the HF side using time series data. 

Hope this was helpful. Best of luck!

 

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