Malcolm Kemp – Extreme Events. Robust Portfolio Construction in the Presence of Fat Tails

Description

Taking due account of excessive occasions when developing portfolios of belongings or liabilities is a key self-discipline for market professionals. Extreme occasions are a truth of life in how markets function.

In Extreme Events: Robust Portfolio Construction in the Presence of Fat Tails, main professional Malcolm Kemp exhibits readers tips on how to analyse market information to uncover fat-tailed behaviour, tips on how to incorporate professional judgement in the dealing with of such data, and tips on how to refine portfolio building methodologies to make portfolios much less weak to excessive occasions or to learn extra from them.

This is the solely textual content that mixes a complete remedy of fashionable threat budgeting and portfolio building strategies with the particular refinements wanted for them to deal with excessive occasions. It explains in a logical sequence what constitutes fat-tailed behaviour and why it arises, how we are able to analyse such behaviour, at combination, sector or instrument stage, and the way we are able to then take benefit of this evaluation.

Along the approach, it supplies a rigorous, complete and clear improvement of conventional portfolio building methodologies relevant if fat-tails are absent. It then explains tips on how to refine these methodologies to accommodate actual world behaviour.

Throughout, the guide highlights the significance of professional opinion, displaying that even the most data-centric portfolio building approaches in the end depend upon practitioner assumptions about how the world may behave.

The guide contains:

• Key ideas and strategies concerned in analysing excessive occasions
• A complete remedy of mean-variance investing, Bayesian strategies, market constant approaches, threat budgeting, and their software to supervisor and instrument choice
• A scientific improvement of the refinements wanted to conventional portfolio building methodologies to cater for fat-tailed behaviour
• Latest developments in stress testing and again testing methodologies
• A robust deal with the sensible implementation challenges that may come up at every step in the course of and on tips on how to overcome these challenges

“Understanding how to model and analyse the risk of extreme events is a crucial part of the risk management process. This book provides a set of techniques that allow practitioners to do this comprehensively.”
Paul Sweeting, Professor of Actuarial Science, University of Kent

“How can the likeliness of crises affect the construction of portfolios? This question is highly topical in times where we still have to digest the last financial collapse. Malcolm Kemp gives the answer. His book is highly recommended to experts as well as to students in the financial field.”
Christoph Krischanitz, President Actuarial Association of Austria, Chairman WG “Market Consistency” of Groupe Consultatif

 

Table of Contents

Preface.

Acknowledgements.

Abbreviations.

Notation.

1 Introduction.

1.1 Extreme occasions.

1.2 The portfolio building downside.

1.3 Coping with actually excessive occasions.

1.4 Risk budgeting.

1.5 Elements designed to maximise profit to readers.

1.6 Book construction.

2 Fat Tails – In Single (i.e., Univariate) Return Series.

2.1 Introduction.

2.2 A fats tail relative to what?

2.3 Empirical examples of fat-tailed behaviour in return sequence.

2.4 Characterising fat-tailed distributions by their moments.

2.5 What causes fats tails?

2.6 Lack of diversification.

2.7 A time-varying world.

2.8 Stable distributions.

2.9 Extreme worth idea (EVT).

2.10 Parsimony.

2.11 Combining completely different attainable supply mechanisms.

2.12 The practitioner perspective.

2.13 Implementation challenges.

3 Fat Tails – In Joint (i.e., Multivariate) Return Series.

3.1 Introduction.

3.2 Visualisation of fats tails in a number of return sequence.

3.3 Copulas and marginals – Sklar’s theorem.

3.4 Example analytical copulas.

3.5 Empirical estimation of fats tails in joint return sequence.

3.6 Causal dependency fashions.

3.7 The practitioner perspective.

3.8 Implementation challenges.

4 Identifying Factors That Significantly Influence Markets.

4.1 Introduction.

4.2 Portfolio threat fashions.

4.3 Signal extraction and principal elements evaluation.

4.4 Independent elements evaluation.

4.5 Blending collectively principal elements evaluation and unbiased elements evaluation.

4.6 The potential significance of choice results.

4.7 Market dynamics.

4.8 Distributional mixtures.

4.9 The practitioner perspective.

4.10 Implementation challenges.

5 Traditional Portfolio Construction Techniques.

5.1 Introduction.

5.2 Quantitative versus qualitative approaches?

5.3 Risk-return optimisation.

5.4 More basic options of mean-variance optimisation.

5.5 Manager choice.

5.6 Dynamic optimisation.

5.7 Portfolio building in the presence of transaction prices.

5.8 Risk budgeting.

5.9 Backtesting portfolio building strategies.

5.10 Reverse optimisation and implied view evaluation.

5.11 Portfolio optimisation with choices.

5.12 The practitioner perspective.

5.13 Implementation challenges.

6 Robust Mean-Variance Portfolio Construction.

6.1 Introduction.

6.2 Sensitivity to the enter assumptions.

6.3 Certainty equivalence, credibility weighting and Bayesian statistics.

6.4 Traditional strong portfolio building approaches.

6.5 Shrinkage.

6.6 Bayesian approaches utilized to place sizes.

6.7 The ‘universality’ of Bayesian approaches.

6.8 Market constant portfolio building.

6.9 Resampled mean-variance portfolio optimisation.

6.10 The practitioner perspective.

6.11 Implementation challenges.

7 Regime Switching and Time-Varying Risk and Return Parameters.

7.1 Introduction.

7.2 Regime switching.

7.3 Investor utilities.

7.4 Optimal portfolio allocations for regime switching fashions.

7.5 Links with spinoff pricing idea.

7.6 Transaction prices.

7.7 Incorporating extra complicated autoregressive behaviour.

7.8 Incorporating extra intrinsically fat-tailed behaviour.

7.9 More heuristic methods of dealing with fats tails.

7.10 The practitioner perspective.

7.11 Implementation challenges.

8 Stress Testing.

8.1 Introduction.

8.2 Limitations of present stress testing methodologies.

8.3 Traditional stress testing approaches.

8.4 Reverse stress testing.

8.5 Taking due account of stress checks in portfolio building.

8.6 Designing stress checks statistically.

8.7 The practitioner perspective.

8.8 Implementation challenges.

9 Really Extreme Events.

9.1 Introduction.

9.2 Thinking outdoors the field.

9.3 Portfolio function.

9.4 Uncertainty as a truth of life.

9.5 Market implied information.

9.6 The significance of good governance and operational administration.

9.7 The practitioner perspective.

9.8 Implementation challenges.

10 The Final Word.

10.1 Conclusions.

10.2 Portfolio building ideas in the presence of fats tails.

Appendix: Exercises.

A.1 Introduction.

A.2 Fat tails – In single (i.e., univariate) return sequence.

A.3 Fat tails – In joint (i.e., multivariate) return sequence.

A.4 Identifying components that considerably affect markets.

A.5 Traditional portfolio building strategies.

A.6 Robust mean-variance portfolio building.

A.7 Regime switching and time-varying threat and return parameters.

A.8 Stress testing.

A.9 Really excessive occasions.

References.

Index.

 

Author Information

Malcolm Kemp (London, UK) is Founder and Managing director of Nematrian Ltd, a consulting agency delivering companies to the quantitative finance and actuarial communities. Previously, he was Director and Head of the Quantitative Research Team at Threadneedle Asset Management, answerable for the spinoff desk and its portfolio threat measurement and administration actions. He is a number one professional on derivatives, efficiency measurement, threat measurement, legal responsibility pushed funding and different quantitative funding strategies. Prior to this, Malcolm was a companion at Bacon & Woodrow in their funding consultancy apply. He holds a first-class diploma in Mathematics from Cambridge University and can also be a Fellow of the Institute of Actuaries. He is a daily on the convention circuit, together with Risk Europe and GARP occasions the place he speaks on a spread of portfolio administration and derivatives subjects.