Explore the Interconnection of Investing and Quantitative Analysis
Next start date:
September 26, 2018
Computational finance brings together the power of computing and statistical analysis with the principles of finance and investment management. This four-course certificate program examines the mathematical, statistical and econometric principles that underlie the quantitative management of financial investments. You’ll study the mechanisms of investment science, investigate portfolio optimization and asset management, and build models of risk and return. You’ll also receive an in-depth introduction to using the R statistical programming language for financial modeling and analysis.
Experienced professionals looking to advance their career in computational finance, those who have completed the Quantitative Fundamentals of Computational Finance certificate program, or those with a degree in a related field preparing to pursue graduate study.
For more information, visit the Computational Finance Certificate website.
“The program was great because there were other people who were in career transition, like I was, and really pivoting into a brand new world. So it was a great way for me to network with other people.”
If you’re thinking about heading back to school, you’re probably also wondering how you’ll pay for it. To help you figure that out, we’ve put together a list of ways to help fund your education.
Learn how to apply cutting-edge tools and techniques to extract meaning from data sets ranging in size from gigabytes to petabytes.
Explore the key mathematical, statistical and econometric foundations of modern computational finance. Study the major concepts and theories of portfolio optimization and risk management.
Study the fundamentals of R programming. Learn the structure and organization of the R environment and practice accessing and running R packages.
Learn methods of applying mathematics to different fields in this top-ranked interdisciplinary program. Gain skills that complement your area of expertise.
Gain valuable knowledge and skills relating to portfolio optimization, financial data science, quantitative risk management, simulation, machine learning and R programming.