Systemic Risk Prediction Using Entropy Rule in Double Portfolio Selection Strategy: Evidence on US Stock Market.

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F22%3A10251541" target="_blank" >RIV/61989100:27510/22:10251541 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Systemic Risk Prediction Using Entropy Rule in Double Portfolio Selection Strategy: Evidence on US Stock Market.
Original language description
Recently, uncertainty in the financial markets makes the investment environment uncomfortable for investors and analysts. Therefore, we should try to predict the presence of systemic risk in the market. In this paper, we analyze whether applying the defined entropy measure rule employing considered as an alarm allows us to predict a systemic risk and thus outperform the simple portfolio selection strategy. In particular, Shannon and Tsallis entropy measures are used. To determine the optimal weights of a portfolio, we apply a multifactor model with OLS regression and a newly proposed double optimization approach while considering proportional transaction costs. More detailed, we assume a reward-risk maximization model in the first step, and then selected risk indicators (VaR, CoVaR) are minimized while at least the expected return from the first step is achieved. Finally, ex-post results in empirical analysis with US stock data confirm the beneficial properties of this portfolio strategy.
Czech name
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Czech description
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Project
<a href="/en/project/GA20-16764S" target="_blank" >GA20-16764S: A generalized approach to stochastic dominance: theory and financial applications</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 13th International Scientific Conference Karviná Ph.D. Conference on Business and Economics : November 2-3, 2022, Horní Lomná, Czech Republic
ISBN
978-80-7510-529-5
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
63-73
Publisher name
Silesian University in Opava, School of Business Administration in Karviná
Place of publication
Karviná
Event location
Horní Lomná
Event date
Nov 2, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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