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Housewives of Tokyo versus the gnomes of Zurich: Measuring price discovery in sequential markets

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  • Wang, Jianxin
  • Yang, Minxian

Abstract

This paper presents two methods to measure market-specific contributions to price discovery in non-overlapping sequential markets: one is a non-parametric approach using high-frequency data and the other is a structural VAR model based on open-to-close returns. The methods complement the existing methodologies for comparing price discovery in parallel markets. Using these methods, we estimate the information shares of four sequential markets for the trading of AUD, JPY, EUR, and GBP against USD over an eight-year period. We find that price discovery in the foreign exchange markets are still dominated by Europe and the United States, particularly the London-New York overlapping trading hours. Asia is losing information shares to Europe in the trading of AUD and JPY. The significance of the "housewives of Tokyo" in currency trading may have been overstated.

Suggested Citation

  • Wang, Jianxin & Yang, Minxian, 2011. "Housewives of Tokyo versus the gnomes of Zurich: Measuring price discovery in sequential markets," Journal of Financial Markets, Elsevier, vol. 14(1), pages 82-108, February.
  • Handle: RePEc:eee:finmar:v:14:y:2011:i:1:p:82-108
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    Cited by:

    1. Otsubo, Yoichi, 2014. "International cross-listing and price discovery under trading concentration in the domestic market: Evidence from Japanese shares," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 36-51.
    2. Jin, Muzhao & Li, Youwei & Wang, Jianxin & Yang, Yung Chiang, 2016. "Price Discovery in the Chinese Gold Market," MPRA Paper 71135, University Library of Munich, Germany.
    3. Wang, Jianxin, 2014. "Overnight price discovery and the internationalization of a currency: The case of the Korean won," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 86-95.
    4. Zhang, Yongjie & An, Yahui & Feng, Xu & Jin, Xi, 2017. "Celebrities and ordinaries in social networks: Who knows more information?," Finance Research Letters, Elsevier, vol. 20(C), pages 153-161.
    5. Wang, Jianxin & Yang, Minxian, 2015. "How well does the weighted price contribution measure price discovery?," Journal of Economic Dynamics and Control, Elsevier, vol. 55(C), pages 113-129.
    6. Hou, Yang & Li, Steven, 2017. "Time-Varying Price Discovery and Autoregressive Loading Factors: Evidence from S&P 500 Cash and E-Mini Futures Markets," MPRA Paper 81999, University Library of Munich, Germany.
    7. Chai, Edwina F.L. & Lee, Adrian D. & Wang, Jianxin, 2015. "Global information distribution in the gold OTC markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 206-217.
    8. Moshirian, Fariborz & Nguyen, Huong Giang (Lily) & Pham, Peter Kien, 2012. "Overnight public information, order placement, and price discovery during the pre-opening period," Journal of Banking & Finance, Elsevier, vol. 36(10), pages 2837-2851.
    9. repec:eee:pacfin:v:48:y:2018:i:c:p:35-55 is not listed on IDEAS
    10. repec:eee:jimfin:v:79:y:2017:i:c:p:232-254 is not listed on IDEAS
    11. Kao, Chung-Wei & Wan, Jer-Yuh, 2012. "Price discount, inventories and the distortion of WTI benchmark," Energy Economics, Elsevier, vol. 34(1), pages 117-124.

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