Enhanced Risk Management: Integrating Fuzzy Logic and EWMA Model for Market Volatility
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F25%3A00141919" target="_blank" >RIV/00216224:14560/25:00141919 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-97992-7_84" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-97992-7_84</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-97992-7_84" target="_blank" >10.1007/978-3-031-97992-7_84</a>
Alternative languages
Result language
angličtina
Original language name
Enhanced Risk Management: Integrating Fuzzy Logic and EWMA Model for Market Volatility
Original language description
In the financial markets, volatility is vital for hedging, assets risk management, and the derivatives pricing. Consequently, it is essential to forecast markets volatility accurately. The standard exponential weighted moving average (EWMA) model tracks market shift in conditional variance of returns by prioritizing the recent observations and decreasing weights exponentially to the past returns. We propose a new fuzzy based FEWMA model that integrates fuzzy logic systems, k-means clustering and EWMA model to forecast market volatility more accurately by assigning weights to returns on the basis of fuzzy logical relationships and rules. The proposed model’s performance is compared to that of the classic GARCH, EWMA, and different modified versions of EWMA models in terms of statistical accuracy measures. This research aims to introduce fuzzy theory in RiskMetrics modeling scheme which adopts nonlinear structure to assign suitable weights to past returns. Furthermore, proposed FEWMA model’s structure combines an effective fuzzy logical control system and pattern learning in k-means clustering environment to forecast volatility with higher accuracy.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
50200 - Economics and Business
Result continuities
Project
<a href="/en/project/EH22_010%2F0007541" target="_blank" >EH22_010/0007541: MSCAfellow6_MUNI</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Intelligent and Fuzzy Systems
ISBN
9783031979910
ISSN
2367-3370
e-ISSN
—
Number of pages
10
Pages from-to
781-790
Publisher name
Springer Cham
Place of publication
Cham
Event location
Türkiye
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001587447700084