/

This presentation is based on a part of an academic course on Enterprise Risk Management (ERM) titled ‘Market Risk’ and covers topics such as: the definition of ‘market’ risk, statistical techniques for estimating VaR (Value-at-Risk) and TE (tracking error) including parametric, non-parametric and market-implied approaches and interaction with matrix algebra including application of principal components analysis

Slides

1	Session 4: Market Risk
2	Session 4: Market Risk
3	What is market risk?
4	Typical approaches (1)
5	Axioms
6	Typical approaches (2)
7	Session 4: Market Risk
8	Statistical techniques for estimating risk measures
9	Session 4: Market Risk
10	Parametric Approach
11	Issues
12	Incomplete or out-of-date data
13	Non-linear exposures
14	Call option price
15	Heteroscedasticity
16	GARCH models
17	Properties of GARCH models
18	RiskMetrics approach
19	RiskMetrics specification
20	Session 4: Market Risk
21	Non-parametric approach: order statistics
22	Standard errors in non-parametric approach
23	Maximum Likelihood Estimation
24	Log likelihood
25	Desirable properties of ML estimator
26	Likelihood ratio tests
27	Binomial back testing
28	Introducing a restriction
29	Goldman Sachs VaR model
30	New directions for market risk: IRC
31	New directions for market risk: Stress VaR
32	Session 4: Market Risk
33	Market-implied risk statistics
34	Session 4: Market Risk
35	Interaction with matrix algebra: principal components
36	Principal components - explanation or noise?
37	Smaller eigenvalues/principal components
38	Important Information

---

NAVIGATION LINKS
Contents | Next | ERM Lecture Series

---