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An Approach to Modeling on Financial Time Series Data with Regime Shifts

Author

Listed:
  • Yokouchi, Daisuke
  • 横内, 大介
  • Kato, Takeshi
  • Aoki, Yoshimitsu

Abstract

This paper proposes a newmethod to analyze time series data with regime shifts and makes the following three contributions: (1) it suggests an exponential weighted estimation algorithm for autoregressive model with time varying coefficients, (2) it gives a visualization technique of structural change points and an outlier measure based on the Mahalanobis distance and (3) it illustrates that our method works for hedge fund return data and high frequency FX data.

Suggested Citation

  • Yokouchi, Daisuke & 横内, 大介 & Kato, Takeshi & Aoki, Yoshimitsu, 2020. "An Approach to Modeling on Financial Time Series Data with Regime Shifts," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 53(1), pages 21-30, February.
    • Handle: RePEc:hit:hitjcm:v:53:y:2020:i:1:p:21-30
    DOI: 10.15057/30973
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    References listed on IDEAS

    as
    1. Getmansky, Mila & Lo, Andrew W. & Makarov, Igor, 2004. "An econometric model of serial correlation and illiquidity in hedge fund returns," Journal of Financial Economics, Elsevier, vol. 74(3), pages 529-609, December.
    2. Ryozo Miura & Yoshimitsu Aoki & Daisuke Yokouchi, 2009. "A note on statistical models for individual hedge fund returns," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(3), pages 553-577, July.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
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