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Erschienen in: Decisions in Economics and Finance 1/2019

02.03.2019

Possibilistic mean–variance portfolios versus probabilistic ones: the winner is...

verfasst von: Marco Corazza, Carla Nardelli

Erschienen in: Decisions in Economics and Finance | Ausgabe 1/2019

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Abstract

In this paper, we compare the mean–variance portfolio modeling based on the possibilistic representation of the future stock returns to the one based on the classical probabilistic modelization of the same returns. There exist several different definitions of possibilistic mean, possibilistic variance and possibilistic covariance. In this paper, we consider definitions recently proposed in the literature for modeling portfolio selection problems: the possibilistic mean and variance à la Carlsson–Fullér–Majlender, the lower possibilistic mean and variance, and the upper possibilistic mean and variance. In particular, we mean to answer to the following research questions: first, to check whether, from a methodological and theoretical standpoint, it is possible to detect elements of superiority of one of the two approaches with respect to the other one; then, to check whether, from an operational point of view, one of the two approaches is more effective than the other one in terms of virtual-future performances. We disclosed that, on the basis of the results we obtained, the winner is the probabilistic approach.
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Fußnoten
1
A brief recall on the trapezoidal fuzzy numbers is provided in Appendix A.
 
2
From here on, when not differently specified, with the term “variance” we imply also the term “covariance.”
 
3
The definitions of all these possibilistic quantities will be given in Sect. 2.
 
4
For instance, with reference to only the lower possibilistic framework, the riskless asset \(A_1 = (c_1, c_1, 0, 0)\) and the risky asset \(A_2 = (a_2, b_2, 0, \beta _2)\), with \(\beta _2 >0\), both have the lower possibilistic variance, \(\mathrm{Var}_*(A_1)\) and \(\mathrm{Var}_*(A_2)\), respectively, equal to zero. An equivalent example can be given with reference to the upper possibilistic framework.
 
5
Note that we can perform this test on the basis of the Central Limit Theorem. In fact, given the sample mean and the standard deviation of the above average percentage of times, \(m_\mathrm{apt}\) and \(s_\mathrm{apt}\), respectively, from basic statistics one has that \( \left( m_\mathrm{apt} - 50\% \right) /\left( s_\mathrm{apt} \sqrt{M-1} \right) \rightarrow {\mathcal {N}} (0,1)\) as \(M \rightarrow +\infty \), where M is the total number of comparisons.
 
6
Notice that only in the case “\(a=b \wedge {\gamma }=1\),” one has the absence of variability of A since \([A]^1 = [a,a] = [b,b]\).
 
7
See the previous footnote.
 
8
Of course, the proof can be performed also in terms of rows.
 
9
See the previous footnote.
 
10
See footnote 8.
 
11
See footnote 8.
 
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Metadaten
Titel
Possibilistic mean–variance portfolios versus probabilistic ones: the winner is...
verfasst von
Marco Corazza
Carla Nardelli
Publikationsdatum
02.03.2019
Verlag
Springer International Publishing
Erschienen in
Decisions in Economics and Finance / Ausgabe 1/2019
Print ISSN: 1593-8883
Elektronische ISSN: 1129-6569
DOI
https://doi.org/10.1007/s10203-019-00234-1

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