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Quantile information share

Author

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  • Donald Lien
  • Zijun Wang

Abstract

This paper presents a new method to estimate Hasbrouck‐type market information share in price discovery. The prevailing market information share is calculated on the basis of conditional mean. We propose a conditional quantile regression approach to obtain a new market information share measure, quantile information share, which varies across the combinations of different price quantiles. The method is illustrated with two data sets, one on the spot and futures markets in pricing S&P 500 equity index, and the other on price discovery for a cross‐listed stock.

Suggested Citation

  • Donald Lien & Zijun Wang, 2019. "Quantile information share," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(1), pages 38-55, January.
    • Handle: RePEc:wly:jfutmk:v:39:y:2019:i:1:p:38-55
    DOI: 10.1002/fut.21940
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    3. Donald Lien & Ziling Wang & Xiaojian Yu, 2021. "Quantile information share under Markov regime‐switching," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(4), pages 493-513, April.
    4. Kuck, Konstantin & Schweikert, Karsten, 2023. "Price discovery in equity markets: A state-dependent analysis of spot and futures markets," Journal of Banking & Finance, Elsevier, vol. 149(C).
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    6. Wu, Liang & Liu, Hengzhi & Liu, Chang & Long, Yunshen, 2020. "Determining the information share of liquidity and order flows in extreme price movements," Economic Modelling, Elsevier, vol. 93(C), pages 559-575.
    7. Dan Zhang & Arash Farnoosh & Frédéric Lantz, 2022. "Does something change in the oil market with the COVID-19 crisis?," International Economics, CEPII research center, issue 169, pages 252-268.

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