SELECTED TECHNIQUES OF DETECTING STRUCTURAL BREAKS IN FINANCIAL VOLATILITY

Bartosz Stawiarski ()
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Bartosz Stawiarski: Cracow University of Technology

"e-Finanse", 2015, vol. 11, issue 1, 32-43

Abstract: We investigate several promising algorithms, proposed in literature, devised to detect sudden changes (structural breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng’s algorithm is carried out via numerical simulation in the case of simulated T-GARCH models and two real series, namely German and US stock indices. Simulations show that the NPCPM algorithm is superior to ICSS because is not over-sensitive either to heavy tails of market returns or to their serial dependence. Some signals generated by ICSS are falsely classified as structural breaks in volatility, while Cheng’s technique works well only when a single break occurs.

Keywords: volatility; structural breaks; financial time series; logarithmic returns; Threshold-GARCH model Least Squares Method (search for similar items in EconPapers)
JEL-codes: C19 C22 C58 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:rze:efinan:v:11:y:2015:i:1:p:32-43

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