Who is it for?

ARPM is for you, likely: the only requirement to benefit from ARPM is a solid quantitative background from an undergraduate program in the hard sciences.
No finance or coding background is necessary, as both skills are built up during your ARPM experience.

Professional and Academic Backgrounds

ARPM is designed for professionals working or planning to move into one of the following areas: Risk Management, Portfolio Management, Fund Management, Asset Management, Derivatives, Actuary, Hedge Funds, Structuring, Insurance, Quantitative Trading, Trading, Quantitative Analysis, Analytics, Valuation, Model Validation, Quantitative Research, Data Science, Information Technology, Consulting...

The following categories represent the ideal audience for the ARPM experience:

  • Portfolio managers and risk managers with quantitative proficiency (see below), who wish to learn the principles behind the recipes that they implement every day, and wish to access a comprehensive reference for the most advanced techniques in their field.
  • Computer/data scientists, who need to learn quickly how to deploy their statistical knowledge in the complex world of finance.
  • Derivative quants and quantitative actuaries, who wish to quickly switch from quantitative pricing to modern applications of finance, utilizing the same tools they have learned so far.
  • Students (advanced undergraduates and master level) with quantitative proficiency (see below), who wish to learn how disparate topics in quantitative finance fit together.
  • Academics in quantitative disciplines, who wish to do research and teach finance, learning it in the concise, rigorous language to which they are accustomed.

Quantitative Proficiency Expectations

Individuals extract the most value from the ARPM experience if they have any of:

  • an undergraduate degree in the hard sciences/STEM: mathematics, physics, electrical engineering, computer science, or similar disciplines
  • a master's level degree in mathematical/quantitative finance or mathematical/quantitative economics
  • extensive working knowledge of the concepts below:
    • Linear algebra: matrix/vector notation and manipulations, trace, determinant, eigenvectors, eigenvalues.
    • Multivariate calculus: derivatives, integrals, and Taylor expansions.
    • Statistics: basic concepts of distributions, probability density function, and cumulative distribution function.

If you are interested in brushing up your math with a focus on applications, a mathematics refresher is available.

Programming Proficiency Expectations

No coding experience is needed to fully benefit from the ARPM experience. What is important is your quantitative background.
However, if you are interested in learning to code or brushing up your skills, coding refreshers are available.

Read what our alumni say about ARPM.

See who are our Clients and Partners.

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