Financial Risk Modeling Techniques

Colleagues, the Financial Risk Modeling Techniques program 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. 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. Training modules equip you to: 1) Understand Financial Risk - Risk and Uncertainty,  Idiosyncratic and Systemic Risk, Case Studies in Risk Management, Mean and Variance, Covariance Matrices, 2) Measuring Financial Risk Using Models - An Approach to Risk Management  Portfolios as Sums of Random Variables, Covariance Matrices in Measuring Portfolio Variance, The Intuition Behind Factor Models,  The Math Behind Factor Models, The Intuition Behind Value-at-risk, The Math Behind Value-at-risk, and the Advantages and Disadvantages of VaR, 3) Implementing Financial Risk Models in Excel and VBA - Assembling a Portfolio, Estimating Historical Risk,  Building Factor Models, Idiosyncratic and Systemic Risk, Scenario-based Stress Testing, Quantifying the Worst Case with VaR, 4) Implementing Financial Risk Models in R - Assembling a Portfolio, Estimating Historical Risk, Building Factor Models, Idiosyncratic and Systemic Risk, Scenario-based Stress Testing, Quantifying the Worst Case with VaR, and 5) Implementing Financial Risk Models in Python - Assembling a Portfolio, Estimating Historical Risk, Building Factor Models, Idiosyncratic and Systemic Risk, Scenario-based Stress Testing and Quantifying the Worst Case with VaR.

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