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Real-Time Monitoring Test for Realized Volatility

Author

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  • Shin-Huei Wang Cindy

    (CORE, Universite Catholique de Louvain and CEREFIM, FUNDP, Belgium; Department of Quantitative Finance, National Tsing Hua University, Taiwan)

  • Hsiao Cheng

    (Department of Economics, University of Southern California, CA, United States; Hong Kong University of Science and Technology, Hong Kong; WISE, Xiamen University, China)

Abstract

This paper proposes a monitoring cumulative sum of squares (CUSQ)-type test for structural breaks in real time via an autoregressive (AR) approximation framework where data generating process (DGP) is a long memory process. The limiting distribution of the monitoring test follows a Brownian bridge and is free of long memory parameters under the null hypothesis of no break. The test is easy to implement and avoids the issue of spurious breaks found for some retrospective tests for long memory process. Neither does it need to use the bootstrap procedure to find the critical values. Monte Carlo simulations appear to confirm that there exists negligible size distortion and satisfactory power performances in finite samples. The procedure is then applied to monitor the real-time pattern of realized volatilities of dollar–Deutschmark and dollar–Japanese Yen.

Suggested Citation

  • Shin-Huei Wang Cindy & Hsiao Cheng, 2013. "Real-Time Monitoring Test for Realized Volatility," Journal of Time Series Econometrics, De Gruyter, vol. 5(1), pages 1-24, January.
    • Handle: RePEc:bpj:jtsmet:v:5:y:2013:i:1:p:1-24:n:2
    DOI: 10.1515/jtse-2012-0014
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    References listed on IDEAS

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    1. Choi, Kyongwook & Yu, Wei-Choun & Zivot, Eric, 2010. "Long memory versus structural breaks in modeling and forecasting realized volatility," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 857-875, September.
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
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