Financial risk modeling is back in the limelight these days because of its place at the intersection of two hot trends: Fintech and Big Data. Enthusiasm about the intersection of technology and finance is tempered by caution born from past financial risk management failures, such as those witnessed during the Subprime Crisis. In this course, Understanding and Applying Financial Risk Modeling Techniques, you’ll learn the details of three related financial risk modeling techniques: covariance matrices, factor models, and value-at-risk. First, you’ll discover risk, uncertainty, and standard deviation. Next, you’ll explore the role of covariance matrices in modeling risk. Then, you’ll go through building scenario-based stress tests using factor models. Finally, you’ll learn how to implement a robust risk modeling approach using Excel, VBA, R, and Python. By the end of this course, you’ll have a good understanding of how financial risks of all types can be quantified and modeled.
Author Name: Vitthal Srinivasan
Author Description:
Vitthal has spent a lot of his life studying – he holds Masters Degrees in Math and Electrical Engineering from Stanford, an MBA from INSEAD, and a Bachelors Degree in Computer Engineering from Mumbai. He has also spent a lot of his life working – as a derivatives quant at Credit Suisse in New York, then as a quant trader, first with a hedge fund in Greenwich and then on his own, and finally at Google in Singapore and Flipkart in Bangalore. In all these roles, he has written a lot of code, and b… more

Table of Contents

• Course Overview
  1min
• Understanding Financial Risk
  35mins
• Measuring Financial Risk Using Models
  38mins
• Implementing Financial Risk Models in Excel and VBA
  38mins
• Implementing Financial Risk Models in R
  28mins
• Implementing Financial Risk Models in Python
  29mins