Who is ARPM for?

To get maximum benefit from ARPM it is recommended you have a quantitative background, typical backgrounds include Mathematics, Physics, Quantitative Finance, Probability and Statistics or other hard sciences.

Finance or coding experience is welcome but not necessary; both skills are developed during your ARPM experience.

Professional and Academic Backgrounds

ARPM is designed for professionals working or planning to work in 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 and others.

The ARPM experience will enhance your current role and effectiveness:

• Portfolio managers and risk managers will learn the core principles behind the techniques that they implement every day, in addition they will gain access, knowledge and understanding of other techniques and approaches employed throughout the industry.
• Computer/data scientists, who want the ability to deploy their statistical knowledge in the complex world of finance.
• Derivative quants and quantitative actuaries, who want to evolve current quantitative pricing techniques to include the most current groundbreaking applications of finance.
• Students pursuing quantitative disciplines who want to learn the dynamic method and approaches in quantitative finance.
• Academics who wish to do research and teach finance, learning it in the concise way using the rigor to which they are accustomed.

Mathematical Proficiency Expectations

The ARPM experience will be enhanced with the following recommended prerequisites:

• A degree in one of the following: mathematics, physics, electrical engineering, computer science, or other similar disciplines
• A degree in mathematical/quantitative finance or mathematical/quantitative economics
• Working knowledge in the following concepts:
• 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.

Coding Proficiency Expectations

No coding experience is needed to fully benefit from the ARPM experience. What is important is your willingness to embrace the challenge.
For those interested in learning to code or brushing up current skills, coding primers are available.