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Advances in Portfolio Selection: Ref...

Strub, Moris Simon.

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Advances in Portfolio Selection: Reference Points, Conditional Value-at-Risk, Mean-Variance Induced Utility Functions and Predictable Forward Processes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advances in Portfolio Selection: Reference Points, Conditional Value-at-Risk, Mean-Variance Induced Utility Functions and Predictable Forward Processes./
作者:	Strub, Moris Simon.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	222 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-06, Section: B.
Contained By:	Dissertations Abstracts International80-06B.
標題:	Applied Mathematics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=11012164
ISBN:	9780438658660

Advances in Portfolio Selection: Reference Points, Conditional Value-at-Risk, Mean-Variance Induced Utility Functions and Predictable Forward Processes.
Strub, Moris Simon.

Advances in Portfolio Selection: Reference Points, Conditional Value-at-Risk, Mean-Variance Induced Utility Functions and Predictable Forward Processes. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 222 p.

Source: Dissertations Abstracts International, Volume: 80-06, Section: B.

Thesis (Ph.D.)--The Chinese University of Hong Kong (Hong Kong), 2018.

This item must not be sold to any third party vendors.

This thesis seeks to make several advances in portfolio selection under preference measures going beyond the neoclassical expected utility maximization framework. In Chapter 2, we ask whether updating the reference point leads to time-inconsistent investment in a discrete-time model with reference dependence and loss-aversion and answer this question in the affirmative. We additionally shed some light on how reference points are updated in a dynamic setting and contribute to a reconciliation between prospect theory and the disposition effect. In Chapter 3, we consider three models for portfolio selection under loss-aversion with a mentally adjusted reference point: a model of mental reference point updating, a model of a partially endogenous reference point and a model of a mentally optimal reference point. We find that optimal trading behavior is remarkably robust with respect to mental reference point formation and converges to the neoclassical prediction with increasing experience and sophistication of the investor. We solve a discrete-time mean-CVaR portfolio selection problem in Chapter 4. Embedding this time-inconsistent problem into a family of expected utility maximization problems with a piecewise linear utility function allows us to derive the optimal trading strategy explicitly. We further determine how mean-CVaR preferences need to be updated such that the pre-committed optimal strategy remains optimal at any point in time by solving an inverse investment problem. In Chapter 5, we introduce a family of mean-variance induced, non-standard utility functions and two measures of risk and potential. We establish a semi-analytical solution for the optimal trading strategy and provide numerical examples showing that lowering the potential-aversion leads to better investment performance from different perspective. We investigate how preferences evolve under the framework of discrete-time predictable performance processes by studying the behavior of the Arrow-Pratt measure of risk-tolerance under the joint evolution of wealth and time in Chapter 6. We are able to completely characterize initial utility functions leading to a preservation of preferences and relate the curvature of the initial utility function to the future dynamics of the measure of risk-tolerance.

ISBN: 9780438658660Subjects--Topical Terms:

1669109
Applied Mathematics.

Advances in Portfolio Selection: Reference Points, Conditional Value-at-Risk, Mean-Variance Induced Utility Functions and Predictable Forward Processes.
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