A Quantile Spillover-Driven Markov Switching Model for Volatility Forecasting: Evidence from the Cryptocurrency Market

A Quantile Spillover-Driven Markov Switching Model for Volatility Forecasting: Evidence from the Cryptocurrency Market

This paper develops a novel modeling framework that integrates time-varying quantile-based spillover effects into a regime-switching realized volatility model. A dynamic spillover factor is constructed by identifying the most influential contributors to Bitcoin’s realized volatility across different...

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Bibliographic Details
Main Authors: Fangfang Zhu, Sicheng Fu, Xiangdong Liu
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Mathematics
Subjects:
quantile spillover
dynamic quantile-driven factor
cryptocurrency market
realized volatility
Online Access:https://www.mdpi.com/2227-7390/13/15/2382
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