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

Kód výsledku v 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>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

<a href="/cs/project/GA20-16764S" target="_blank" >GA20-16764S: Zobecněný přístup ke stochastické dominanci: teorie a finanční aplikace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

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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Počet stran výsledku

11

Strana od-do

63-73

Název nakladatele

Silesian University in Opava, School of Business Administration in Karviná

Místo vydání

Karviná

Místo konání akce

Horní Lomná

Datum konání akce

2. 11. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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