On break detection in volatility function of a tau-dependent process
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Abstract
This paper investigates change point detection within financial time series volatility using the NonParametric AutoRegressive Conditionally Heteroscedastic (NPARCH) process. It introduces a classical CUSUM type change point test following the test procedure by [19]. In the absence of change (Null Hypothesis), the test statistic converges to a well-established distribution, simplifying the determination of the critical test value. Conversely, under the Alternative Hypothesis, the probability that the test statistic tends to infinity is one, indicating asymptotic power one. Simulation results are presented to confirm the efficacy of the proposed methodology.
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Kouassi, B. C., Hili, O., & Katchekpele, E. (2025). On break detection in volatility function of a tau-dependent process. Gulf Journal of Mathematics, 19(1), 1-15. https://doi.org/10.56947/gjom.v19i1.2068
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