Informatics and Applications
2019, Volume 13, Issue 3, pp 72-81
PERFORMANCE ESTIMATIONS FOR OPTIMAL-ON-CC-VaR PORTFOLIOS IN OPTION MARKETS
Abstract
The paper continues investigations of the author about using continuous VaR-criterion (CC-VaR) in financial markets. The problem ofprojecting ideas and methods elaborated for investments in the ideal theoretical one-period market and its discrete scenario analog onto a discrete-in-strikes option market is considered. The main focus is on the methods of calculating distribution function of income and return relative, and also their mean for option portfolios optimal on CC-VaR and their randomized versions, both full and partial. A discrete optimization algorithm as the result of projecting the theoretical algorithm based on the Newman-Pearson procedure onto scenario market is suggested. The optimal vector of weights derived from this algorithm is applied to the basis of normalized simplest butterflies. If randomizing portfolios are admissible, then special algorithms based on the ideas of the Monte-Carlo method that determine distribution functions of income and return relative are suggested.
The exposition is illustrated by examples with beta-distributed underlier's prices and investor's probability forecast, which deal with the problems of volatility selling and buying. The respective diagrams are adduced.
[+] References (5)
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[+] About this article
Title
PERFORMANCE ESTIMATIONS FOR OPTIMAL-ON-CC-VaR PORTFOLIOS IN OPTION MARKETS
Journal
Informatics and Applications
2019, Volume 13, Issue 3, pp 72-81
Cover Date
2019-09-30
DOI
10.14357/19922264190311
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
continuous VaR-criterion (CC-VaR); investor's risk-preferences function (r.p.f.); Newman-Pearson procedure; scenarios; options; indicators; butterflies; full and partial randomizing; optimal portfolio; income; yield
Authors
G. A. Agasandyan
Author Affiliations
A. A. Dorodnicyn Computing Center, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 40 Vavilov Str., Moscow 119333, Russian Federation
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