Probabilistic Scenario Optimisation
Foreword
Introduction
Beyond Modern Portfolio Theory
A Modern Risk Management Perspective
The Probability Measure
Real Securities and Reinvestment Strategies: Fixed-Income and Inflation-Linked Securities and Structured Products
Derivation and Modelling of Risk–Return Time Profiles
À la Markowitz: A Tale of Simple Worlds
The Black–Litterman Approach: A Tale of Subjective Views
Probabilistic Scenario Optimisation
Case Studies: Mean–Variance and Black–Litterman
Case Studies: Probabilistic Scenario Optimisation
Creating a new theory is not like destroying an old barn and erecting a skyscraper in its place. It is rather like climbing a mountain, gaining new and wider views, discovering unexpected connections between our starting points and its rich environment. But the point from which we started out still exists and can be seen, although it appears smaller and forms a tiny part of our broad view gained by the mastery of the obstacles on our adventurous way up.
Albert Einstein (1879–1955)
PSO is an exhaustive enumeration technique for designing goal-based and long-term optimal investing. In this chapter we present a step-by-step process from potential to admissible portfolios, and discuss low-discrepancy sequences and lexicographical representations, risk-adequate portfolios and the goal-based objective function.
INTRODUCTION
Markowitz has shaped the landscape of portfolio optimisation since the introduction of the mean–variance approach in the 1950s, and subsequent academic advances have further refined his original ideas, particularly regarding the risk measure definition (eg, semi-variance and expected shortfall). The change in perspective introduced by Black and Litterman
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