Mean-Risk portfolio optimization method proposes an efficient frontier that consists of portfolios not dominated by any portfolio. Consequently, this method reduces the choice set by excluding inefficient portfolios. Different risk measures offer different efficient frontiers, which can be interpreted as different optimal choice sets. The question is whether these different risk measures lead to significantly different efficient frontiers for the investors, and which risk measure should be used. My purpose is to present a method to assess the effect of the choice set reduction from different Return-Risk models and to answer the question presented earlier. The most important contribution of the paper is the creation of a two-dimensional space “Risk- Aversion – Certainty Equivalence (CE)” as a platform for comparisons. The curves, representing different risk-averse investors and different models, on this space are called “Certainty Equivalence Curves (CEC)”. The empirical analysis shows that the Mean-Variance method is very effective in ranking portfolios for exponential utility investors. Therefore, it is not recommended to use more complicated methods such as Mean-CVaR.
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Hien Vu obtained PhD in Finance at University of Lugano in Switzerland. He also obtained Master in Finance at Lund University in Sweden and Bachelor in Finance at Australian National University in Australia.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mean-Risk portfolio optimization method proposes an efficient frontier that consists of portfolios not dominated by any portfolio. Consequently, this method reduces the choice set by excluding inefficient portfolios. Different risk measures offer different efficient frontiers, which can be interpreted as different optimal choice sets. The question is whether these different risk measures lead to significantly different efficient frontiers for the investors, and which risk measure should be used. My purpose is to present a method to assess the effect of the choice set reduction from different Return-Risk models and to answer the question presented earlier. The most important contribution of the paper is the creation of a two-dimensional space 'Risk- Aversion - Certainty Equivalence (CE)' as a platform for comparisons. The curves, representing different risk-averse investors and different models, on this space are called 'Certainty Equivalence Curves (CEC)'. The empirical analysis shows that the Mean-Variance method is very effective in ranking portfolios for exponential utility investors. Therefore, it is not recommended to use more complicated methods such as Mean-CVaR. 52 pp. Englisch. Seller Inventory # 9783659758393
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vu HienHien Vu obtained PhD in Finance at University of Lugano in Switzerland. He also obtained Master in Finance at Lund University in Sweden and Bachelor in Finance at Australian National University in Australia.Mean-Risk portf. Seller Inventory # 159144668
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mean-Risk portfolio optimization method proposes an efficient frontier that consists of portfolios not dominated by any portfolio. Consequently, this method reduces the choice set by excluding inefficient portfolios. Different risk measures offer different efficient frontiers, which can be interpreted as different optimal choice sets. The question is whether these different risk measures lead to significantly different efficient frontiers for the investors, and which risk measure should be used. My purpose is to present a method to assess the effect of the choice set reduction from different Return-Risk models and to answer the question presented earlier. The most important contribution of the paper is the creation of a two-dimensional space ¿Risk- Aversion ¿ Certainty Equivalence (CE)¿ as a platform for comparisons. The curves, representing different risk-averse investors and different models, on this space are called ¿Certainty Equivalence Curves (CEC)¿. The empirical analysis shows that the Mean-Variance method is very effective in ranking portfolios for exponential utility investors. Therefore, it is not recommended to use more complicated methods such as Mean-CVaR.Books on Demand GmbH, Überseering 33, 22297 Hamburg 52 pp. Englisch. Seller Inventory # 9783659758393
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mean-Risk portfolio optimization method proposes an efficient frontier that consists of portfolios not dominated by any portfolio. Consequently, this method reduces the choice set by excluding inefficient portfolios. Different risk measures offer different efficient frontiers, which can be interpreted as different optimal choice sets. The question is whether these different risk measures lead to significantly different efficient frontiers for the investors, and which risk measure should be used. My purpose is to present a method to assess the effect of the choice set reduction from different Return-Risk models and to answer the question presented earlier. The most important contribution of the paper is the creation of a two-dimensional space 'Risk- Aversion - Certainty Equivalence (CE)' as a platform for comparisons. The curves, representing different risk-averse investors and different models, on this space are called 'Certainty Equivalence Curves (CEC)'. The empirical analysis shows that the Mean-Variance method is very effective in ranking portfolios for exponential utility investors. Therefore, it is not recommended to use more complicated methods such as Mean-CVaR. Seller Inventory # 9783659758393
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Taschenbuch. Condition: Neu. Return-Risk vs. Direct Utility Maximization | Hien Vu | Taschenbuch | 52 S. | Englisch | 2015 | LAP Lambert Academic Publishing | EAN 9783659758393 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 104267730