Quantitative Analyst - Mathematical and Statistical Approaches

Mathematical and Statistical Approaches

Because of their backgrounds, quantitative analysts draw from three forms of mathematics: statistics and probability, calculus centered around partial differential equations, and econometrics. The majority of quantitative analysts have received little formal education in mainstream economics, and often apply a mindset drawn from the physical sciences. Physicists tend to have significantly less experience of statistical techniques, and thus lean on approaches based upon partial differential equations, and solutions to these based upon numerical analysis.

The most commonly used numerical methods are:

  • Finite difference method – used to solve partial differential equations;
  • Monte Carlo method – Also used to solve partial differential equations, but Monte Carlo simulation is also common in risk management.

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