Role of a Quantitative Modeler

A quantitative modeler is someone who works in finance and uses numerical and quantitative techniques to build complex quantitative models. They are commonly known as quants or quantitative analysts.

The typical industries that hire quantitative modelers include investment banking, risk management, portfolio optimization, and derivatives pricing and hedging. Broadly speaking, quantitative modelers apply mathematics in finance.

A quantitative modeller is expected to have multitude of skills including advanced knowledge of mathematics, finance, statistical modelling, data mining and the ability to create computer programs using languages such as C++ or Java.

Let’s take a few examples of what quantitative modelers do.

  • The quants are employed in the trading and sales divisions of investment banks where they help in pricing innovative financial products, manage risk in these products, and help identify profit making opportunities using algorithms.
  • Many portfolio managers and asset manager also heavily depend on quantitative techniques for their trading strategies for which they require quants.
  • The quantitative models also find their place in risk management department where they assess and hedge the risks associated with the bank’s portfolios. The commonly used techniques include value-at-risk, stress testing, and direct analysis of risky trades.
  • Quants are also employed by insurance firms for various roles such as product pricing, building models for fraud detection, liability quantitative modelling, and validating and testing various statistical models.
  • Then we have quantitative developers who are more like computer specialists and build and maintain quant models.

If you have a flair for finance, mathematics and computer program, then quantitative modelling is a lucrative career option for you that pays very well.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.