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This presentation is based on a part of an academic course on Further Enterprise Risk Management (Further ERM) titled ‘Creating portfolio risk and return models’ and covers topics such as: different types of risk (and return) models (including fundamental, econometric and statistical factor models), seeking ‘meaningfulness’, the model timescale, economic scenario generators, modelling different instrument types, incorporating return views and applying models to portfolio construction

Slides

1	Session 2: Creating portfolio risk and return models
2	Session 2: Creating portfolio risk and return models
3	Different types of risk (and return) models
4	Models
5	Designing models
6	Session 2: Creating portfolio risk and return models
7	Factor models (1)
8	Factor models (2)
9	Factor models (3)
10	Factor models (4)
11	In practice often produce similar results
12	Session 2: Creating portfolio risk and return models
13	Seeking ‘meaningfulness’
14	Independent components analysis
15	E.g. Non-Normality and Projection pursuit
16	Projection pursuit algorithm (1)
17	Projection pursuit algorithm (2)
18	Independent components analysis (ICA)
19	Blending together PCA and ICA
20	Identifying Principal Components one at a time
21	Blending PCA with ICA
22	Extreme events appear to be very important!
23	Session 2: Creating portfolio risk and return models
24	The model timescale
25	Time periods that are not infinitesimal
26	Session 2: Creating portfolio risk and return models
27	Economic scenario generators (1)
28	Economic scenario generators (2)
29	Economic scenario generators (3)
30	Advanced techniques
31	Session 2: Creating portfolio risk and return models
32	Modelling different instrument types
33	Call option price
34	Caveats with valuation engines
35	Session 2: Creating portfolio risk and return models
36	Incorporating return views
37	Going beyond traditional time series analysis (1)
38	Return views (1)
39	Return views (2)
40	Return views (3)
41	Session 2: Creating portfolio risk and return models
42	Applying models to portfolio construction
43	Traditional (quantitative) portfolio construction
44	Refinements
45	Robust mean-variance portfolio construction
46	Time-varying risk and return
47	Expected utility theory
48	Regime-switching
49	Appendix: Model validation
50	Model risk and back-testing
51	Model assessment
52	Link with calibration
53	Ideally model should also fit well ‘period by period’
54	Look-back bias and in-sample testing
55	Look-back bias and out-of-sample testing
56	Market consistent risk measurement
57	Back testing in other regulatory frameworks
58	Important Information

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