Jump driven risk model performance in cryptocurrency market

Artikel

This paper aims at identifying a validated risk model for the cryptocurrency market. We propose a stochastic volatility model with co-jumps in return and volatility (SVCJ) to highlight the role of jumps in returns and volatility in affecting Value-at-Risk (VaR) and Expected Shortfall (ES) in cryptocurrency market. Validation results based on backtesting show that SVCJ model is superior in terms of statistical accuracy of VaR and ES estimates, compared to alternative models such as TGARCH (Threshold GARCH) volatility and RiskMetrics models. The results imply that for the cryptocurrency market, the best performing model is a stochastic process that accounts for both jumps in returns and volatility.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: International Journal of Financial Studies ; ISSN: 2227-7072 ; Volume: 8 ; Year: 2020 ; Issue: 2 ; Pages: 1-18 ; Basel: MDPI

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Portfolio Choice; Investment Decisions ; Asset Pricing; Trading Volume; Bond Interest Rates
• Thema: cryptocurrency market ; RiskMetrics ; stochastic volatility with co-jumps ; threshold GARCH ; validation

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Nekhili, Ramzi ; Sultan, Jahangir
• Ereignis: Veröffentlichung
• (wer): MDPI
• (wo): Basel
• (wann): 2020

Weitere Informationen

• DOI: doi:10.3390/ijfs8020019
• Handle: http://hdl.handle.net/10419/257686
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ