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This presentation is based on a part of an academic course on Enterprise Risk Management (ERM) titled ‘Extreme Events and Extreme Value Theory (EVT)’ and covers topics such as: what do we mean by extreme events and why are they relevant in a financial context, Extreme Value Theory (EVT) and a case study on wind storm losses using EVT

Slides

1	Session 8: Extreme Events and Extreme Value Theory (EVT)
2	Session 8: Extreme Events and Extreme Value Theory (EVT)
3	Extreme events
4	Analysing fat-tailed behaviour
5	Anchoring versus experience
6	Example QQ-plot (versus Normal)
7	Many (most?) investment return series are ‘fat-tailed’
8	More periods give more scope for extreme events
9	Skew(ness), kurtosis and Cornish-Fisher
10	Flaws in Cornish Fisher (and hence skew/kurtosis)
11	Joint fat-tailed behaviour
12	What causes fat-tailed behaviour?
13	Time-varying volatility
14	Explains some market index fat tails, esp. on upside
15	A longer term phenomenon too
16	Crowded trades and selection effects
17	Session 8: Extreme Events and Extreme Value Theory (EVT)
18	Extreme Value Theory (EVT)
19	In case study we will focus on
20	Extreme value theory (EVT) results
21	Block maxima results
22	Generalised extreme value (GEV) distribution
23	Limiting behaviour
24	Main result for threshold exceedances
25	Potential weaknesses
26	Using EVT to Estimate VaRs
27	Maximum likelihood (ML) estimation of tails
28	Estimate the quantile that starts the tail
29	Combined estimate
30	Choosing the threshold
31	Judging the start of the tail
32	Session 8: Extreme Events and Extreme Value Theory (EVT)
33	Estimated loss quantiles in SEK m
34	Other analyses included in case study
35	Application to ERM
36	Important Information

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