Regime Switching Models and the Mental Accounting Framework

Автор: Felix Andresen

Език:

Корици: С меки корици

Издател: Grin Publishing

Наличност: Външен склад

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Master's Thesis from the year 2014 in the subject Economics - Finance, grade: 1,0, Frankfurt School...

Информация за книгата

Автор

Felix Andresen

Език

Английски език

Корици

Книга - С меки корици

Издадена

2017

страници

108

EAN

9783668486546

ISBN

3668486549

Enbook ID

16804195

Издател

Grin Publishing

Теглоt

167

Размери

148 x 210 x 7

Пълно описание

Master's Thesis from the year 2014 in the subject Economics - Finance, grade: 1,0, Frankfurt School of Finance & Management, language: English, abstract: The main goal of this thesis is to combine all of these concepts into a unified framework, evaluate its feasibility and performance, and to perform an analysis of the most common pitfalls and practical considerations. This unified framework uses both the MVPT and MA approach for asset allocation, but at the same time allows for dynamic and fat-tailed distributions of asset returns. It is implemented in approximately 1200 lines of efficient MATLAB code, which is publicly available at The application is programmed in a way that it is readily expandable to a larger number of assets and other investment approaches. The framework is also independent on the choice of assets, which is why the choice of assets for the illustration of the thesis findings was based on the availability of data. The thesis is structured as follows. Chapter 2 reviews the current literature and theoretical concepts. More specifically, Chapter 2.1 introduces the Mental Accounting framework and the connections and differences to Markowitz's Mean Variance Portfolio Theory. In Chapter 2.2 the most important concepts of dynamic investment management and stochastic programming are introduced. Chapter 2.3 discusses the regime switching models used to generate scenarios for the stochastic programming approach and the important topic of model selection. Chapter 2.4 gives an overview of Gaussian Mixture Models which present a tool to create the expected distribution used to optimize the asset allocation. In Chapter 3 all the pieces from the theoretical parts are brought together to formulate the dynamic programming models and the hypotheses to be tested in the thesis. The market data used to carry out the analysis is discussed in Chapter 4, as well as some necessary methodology on how to calculate, aggregate and interpret asset returns. Chapter 5 presents exemplary and illustrative results, and discusses the strengths and weaknesses of the MVPT and MA investment approaches. The thesis closes with a summary and conclusion in Chapter 6.

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Regime Switching Models and the Mental Accounting Framework

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