Financial Risk Management in Python, R and Excel
4.6 (6 ratings)
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Financial Risk Management in Python, R and Excel

Value-at-Risk and factor-based models in Python, R and Excel/VBA
New
4.6 (6 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
124 students enrolled
Created by Loony Corn
Last updated 8/2017
English
Price: $50
30-Day Money-Back Guarantee
Includes:
  • 4 hours on-demand video
  • 1 Article
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Design robust risk models using covariance matrices, Value-at-Risk and factor analysis
  • Implement these robust factor-based models in Excel, Python and R
  • Create realistic scenarios for stress-testing risk
  • Contrast covariance-matrices, scenario-based and factor-based risk models
  • Understand the strengths and weaknesses of value-at-risk
View Curriculum
Requirements
  • Basic familiarity with finance. No programming experience required, but some familiarity with Excel, Python or R would be helpful
Description

A financial portfolio is almost always modeled as the sum of correlated random variables. Measuring the risk of this portfolio accurately is important for all kinds of applications: the financial crisis of 2007, the failure of the famous hedge fund LTCM and many other mishaps are attributable to poor risk modeling.

In this course, we cover the theory and practice of robust risk modeling:

  • Model risk using covariance matrices and historical returns
  • Refine this approach using factor models for dimensionality reduction and robustness
  • Generate realistic stress-test scenarios using these factor model
  • Calculate Value-at-Risk and understand the implications, strengths and weaknesses of this approach
  • Implement all of this in Python, Excel and R


Who is the target audience?
  • Finance or technical professionals seeking to implement risk models in Excel, Python and R
Compare to Other Financial Management Courses
Curriculum For This Course
28 Lectures
04:04:09
+
Introduction
1 Lecture 01:40
+
Introducing Risk management
6 Lectures 01:00:30
Risk Management - Slides and Source Code
00:02


Factor Risk Models
10:24

Case Studies
12:50

Mean Variance
11:50

Correlations
12:56
+
Outlining an Approach to Risk Management
6 Lectures 01:03:52
Overall Approach
12:51

Portfolio Mean Variance
09:21

Factor Models
09:15

Factor Variance Calc
10:27

VaR
11:32

VaR - Pros and Cons
10:26
+
RIsk Modeling in Excel/VBA
7 Lectures 01:01:03
Yahoo Finance
10:33

Returns
10:38

VBA Cov
07:36

Factor Regressions
10:11

Factor Model Risk
05:56

Scenario Risk
09:23

Va R Calc
06:46
+
Risk Modeling in R
5 Lectures 31:33
Data Frames
05:24

Covariance Matrices based on Historical Return
08:32

Factor Modeling
08:31

Scenario-based Stress Tests
04:33

VaR
04:33
+
Risk Modeling in Python
3 Lectures 25:31
Covariance Matrices based on Historical Return
09:30

Factor Modeling
07:26

Scenario-based Stress Tests and VaR
08:35
About the Instructor
Loony Corn
4.3 Average rating
5,491 Reviews
42,738 Students
75 Courses
An ex-Google, Stanford and Flipkart team

Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabad and have spent years  working in tech, in the Bay Area, New York, Singapore and Bangalore.

Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft

Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too

We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!

We hope you will try our offerings, and think you'll like them :-)