This chapter provides an in-depth overview of an extended set of multi-period risk measures, their mathematical and economic properties, primarily from the perspective of dynamic risk control and portfolio optimization. The analysis is structured in four parts: the first part reviews characterizing proper- ties of multi-period risk measures, it examines their financial foundations, and clarifies cross-relationships. The second part is devoted to three classes of multi- period risk measures, namely: terminal, additive and recursive. Their financial and mathematical properties are considered, leading to the proposal of a unifying representation. Key to the discussion is the treatment of dynamic risk measures taking their relationship with evolving information flows and time evolution into account: after convexity and coherence, time consistency emerges as a key property required by risk measures to effectively control risk exposure within dynamic programs. In the third part, we consider the application of multi-period measures to optimal investment policy selection, clarifying how portfolio selection models adapt to different risk measurement paradigms. In the fourth part we summarize and point out desirable developments and future research directions. Throughout the chapter, attention is paid to the state-of-the-art and methodological and modeling implications.

(2017). Multi-Period Risk Measures and Optimal Investment Policies . Retrieved from https://hdl.handle.net/10446/76057

Multi-Period Risk Measures and Optimal Investment Policies

Chen, Zhiping;Consigli, Giorgio;
2017-01-01

Abstract

This chapter provides an in-depth overview of an extended set of multi-period risk measures, their mathematical and economic properties, primarily from the perspective of dynamic risk control and portfolio optimization. The analysis is structured in four parts: the first part reviews characterizing proper- ties of multi-period risk measures, it examines their financial foundations, and clarifies cross-relationships. The second part is devoted to three classes of multi- period risk measures, namely: terminal, additive and recursive. Their financial and mathematical properties are considered, leading to the proposal of a unifying representation. Key to the discussion is the treatment of dynamic risk measures taking their relationship with evolving information flows and time evolution into account: after convexity and coherence, time consistency emerges as a key property required by risk measures to effectively control risk exposure within dynamic programs. In the third part, we consider the application of multi-period measures to optimal investment policy selection, clarifying how portfolio selection models adapt to different risk measurement paradigms. In the fourth part we summarize and point out desirable developments and future research directions. Throughout the chapter, attention is paid to the state-of-the-art and methodological and modeling implications.
scientifica
Inglese
18-ott-2016
2017
Optimal Financial Decision Making under Uncertainty
Consigli, Giorgio; Kuhn, Daniel; Brandimarte, Paolo;
cartaceo
online
978-3-319-41611-3
245
1
34
Switzerland
Cham
Springer
esperti anonimi
Settore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e Finanziarie
Multi-period risk measures; Time-consistency; Dynamic risk control; Recoursive risk measures; Portfolio optimization; Information processes; Bellman’s principle
info:eu-repo/semantics/bookPart
(2017). Multi-Period Risk Measures and Optimal Investment Policies . Retrieved from https://hdl.handle.net/10446/76057
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1.2 Contributi in volume - Book chapters::1.2.01 Contributi in volume (Capitoli o Saggi) - Book Chapters/Essays
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Chen, Zhiping; Consigli, Giorgio; Jliu, J. Liu; Li, G.; Fu, T.; Hu, Q.
6
268
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