Understanding the determinants of volatility clustering in terms of stationary Markovian processes

DOI10.1016/J.PHYSA.2016.06.081zbMath1400.91687OpenAlexW2422365087MaRDI QIDQ1619870

Salvatore Miccichè

Publication date: 13 November 2018

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2016.06.081

zbMATH Keywords

stochastic processesfirst passage timevolatilityeconophysicslong-range correlation

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Applications of statistical and quantum mechanics to economics (econophysics) (91B80) Financial applications of other theories (91G80)

Uses Software

• longmemo
• plfit

Cites Work

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• Econophysics and Physical Economics
• Multiple time scales and the exponential Ornstein–Uhlenbeck stochastic volatility model
• Power-Law Distributions in Empirical Data
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices
• Stochastic Process with Ultraslow Convergence to a Gaussian: The Truncated Lévy Flight
• Stochastic volatility as a simple generator of apparent financial power laws and long memory
• A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
• Introduction to Econophysics

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