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Evaluating the performance of futures hedging using multivariate realized volatility

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  • Ubukata, Masato
  • Watanabe, Toshiaki

Abstract

This paper investigates the performance of a conditional hedging model using the realized covariance measure (RCM) with noisy high-frequency data. We employ a bivariate realized exponential GARCH (BREG) model with some RCMs to estimate conditional optimal hedge ratios in the Japanese stock and futures markets. The bivariate Student’s t-distribution as well as the bivariate normal distribution are used for the return distribution. The out-of-sample results show that the BREG model outperforms the DCC-EGARCH model and the OLS approach using daily returns for a short hedge in the period without unpredictably large fluctuations in returns such as the Lehman aftermath and the economic impact of the Great East Japan Earthquake. The BREG model with a Student’s t-distribution is likely to be superior to that with a normal distribution. The use of RCMs with methods reducing bias induced by microstructure noise and non-synchronous trading improves the performance. We also find that the joint model of returns and RCM such as the BREG model yields better performance for a short hedge than a model in which RCM is included as an exogenous variable.

Suggested Citation

  • Ubukata, Masato & Watanabe, Toshiaki, 2015. "Evaluating the performance of futures hedging using multivariate realized volatility," Journal of the Japanese and International Economies, Elsevier, vol. 38(C), pages 148-171.
  • Handle: RePEc:eee:jjieco:v:38:y:2015:i:c:p:148-171
    DOI: 10.1016/j.jjie.2015.07.001
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    Cited by:

    1. Bruce Budd, 2017. "Canaries in the coal mine. The tale of two signals: the VIX and the MOVE Indexes," Proceedings of Economics and Finance Conferences 4807778, International Institute of Social and Economic Sciences.

    More about this item

    Keywords

    Realized covariance matrix; Optimal hedge ratio; Conditional hedging model; High-frequency data;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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