Mathematical Methods for Quantitative Finance (using R)

Colleagues, in the “Mathematical Methods for Quantitative Finance (using R)” program you will learn the mathematical foundations essential for financial engineering and quantitative finance: linear algebra, optimization, probability, stochastic processes, statistics, and applied computational techniques in R. This course will help anyone seeking to confidently model risky or uncertain outcomes. Its topics are essential knowledge for applying the theory of modern finance to real-world settings. Quants, traders, risk managers, investment managers, investment advisors, developers, and engineers will all be able to apply these tools and techniques. Learn Probability distributions in finance, Time-series models: random walks, ARMA, and GARCH, Continuous-time stochastic processes, Optimization, Linear algebra of asset pricing, Statistical and econometric analysis, Monte Carlo simulation, and Applied computational techniques. Skill-based training modules include: 1) Probability, 2) Statistics, 3) Time-series Models, 4) Continuous time stochastic processes, 5) Linear Algebra, 6) Optimization, and 7) Numerical Methods - Monte Carlo techniques; quadratic programming.

Enroll today at (teams & execs welcome): https://fxo.co/HFFq  

Download your free Finance, Accounting & Banking - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Financial Certification Academy (share with your team)