Understanding and Applying Financial Risk Modeling Techniques

Financial risk modeling is at the intersection of two hot trends: Fintech and Big Data. This course covers three financial risk modeling techniques: covariance matrices, factor models, and value-at-risk.
Course info
Rating
(16)
Level
Intermediate
Updated
Apr 17, 2017
Duration
2h 51m
Table of contents
Description
Course info
Rating
(16)
Level
Intermediate
Updated
Apr 17, 2017
Duration
2h 51m
Description

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.

About the author
About the author

An engineer and tinkerer, Vitthal has worked at Google, Credit Suisse, and Flipkart and studied at Stanford and INSEAD. He has worn many hats, each of which has involved writing code and building models. He is passionately devoted to his hobby of laughing at his own jokes.

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