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Rejoinder on: Price Discovery in High Resolution

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  • Joel Hasbrouck

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  • Joel Hasbrouck, 2021. "Rejoinder on: Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 465-471.
    • Handle: RePEc:oup:jfinec:v:19:y:2021:i:3:p:465-471.
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    1. Fulvio Corsi & Stefano Peluso & Francesco Audrino, 2015. "Missing in Asynchronicity: A Kalman‐em Approach for Multivariate Realized Covariance Estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(3), pages 377-397, April.
    2. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    3. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    4. Frank De Jong & Peter C. Schotman, 2010. "Price Discovery in Fragmented Markets," Journal of Financial Econometrics, Oxford University Press, vol. 8(1), pages 1-28, Winter.
    5. Menkveld, Albert J. & Koopman, Siem Jan & Lucas, Andre, 2007. "Modeling Around-the-Clock Price Discovery for Cross-Listed Stocks Using State Space Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 213-225, April.
    6. Harvey,Andrew C., 1991. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521405737, September.
    7. Kalok Chan & Y. Peter Chung & Wai-Ming Fong, 2002. "The Informational Role of Stock and Option Volume," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1049-1075.
    8. Fleming, Michael J. & Mizrach, Bruce & Nguyen, Giang, 2018. "The microstructure of a U.S. Treasury ECN: The BrokerTec platform," Journal of Financial Markets, Elsevier, vol. 40(C), pages 2-22.
    9. Gregory Laughlin & Anthony Aguirre & Joseph Grundfest, 2013. "Information Transmission Between Financial Markets in Chicago and New York," Papers 1302.5966, arXiv.org.
    10. Garbade, Kenneth & Lieber, Zvi, 1977. "On the independence of transactions on the New York Stock exchange," Journal of Banking & Finance, Elsevier, vol. 1(2), pages 151-172, October.
    11. Hatheway, Frank & Kwan, Amy & Zheng, Hui, 2017. "An Empirical Analysis of Market Segmentation on U.S. Equity Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(6), pages 2399-2427, December.
    12. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
    13. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 321-340, March.
    14. de Jong, F.C.J.M. & Schotman, P.C., 2010. "Price discovery in fragmented markets," Other publications TiSEM 4650a9e7-c4cf-41cf-a771-e, Tilburg University, School of Economics and Management.
    15. Comerton-Forde, Carole & Putniņš, Tālis J., 2015. "Dark trading and price discovery," Journal of Financial Economics, Elsevier, vol. 118(1), pages 70-92.
    16. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    17. James J. Angel & Lawrence E. Harris & Chester S. Spatt, 2015. "Equity Trading in the 21st Century: An Update," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-39.
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    Cited by:

    1. Sebastiano Michele Zema & Francesco Cordoni, 2023. "A non-Normal framework for price discovery: The independent component based information shares measure," LEM Papers Series 2023/03, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Poutré, Cédric & Dionne, Georges & Yergeau, Gabriel, 2024. "The profitability of lead–lag arbitrage at high frequency," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1002-1021.
    3. 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).
    4. Yan, Tingjin & Chiu, Mei Choi & Wong, Hoi Ying, 2023. "Portfolio liquidation with delayed information," Economic Modelling, Elsevier, vol. 126(C).
    5. Liwei Jin & Xianghui Yuan & Shihao Wang & Peiran Li & Feng Lian, 2022. "Trades or quotes: Which drives price discovery? Evidence from Chinese index futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2235-2247, December.
    6. Dimpfl, Thomas & Schweikert, Karsten, 2023. "Information shares for markets with partially overlapping trading hours," Journal of Banking & Finance, Elsevier, vol. 154(C).
    7. Sagade, Satchit & Scharnowski, Stefan & Theissen, Erik & Westheide, Christian, 2024. "A tale of two cities: Inter-market latency and fast-trader competition," SAFE Working Paper Series 430, Leibniz Institute for Financial Research SAFE.
    8. Zema, Sebastiano Michele, 2022. "Directed acyclic graph based information shares for price discovery," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    9. Peter B. Lerner, 2023. "A New Entropic Measure for the Causality of the Financial Time Series," JRFM, MDPI, vol. 16(7), pages 1-17, July.
    10. F. Campigli & G. Bormetti & F. Lillo, 2022. "Measuring price impact and information content of trades in a time-varying setting," Papers 2212.12687, arXiv.org, revised Dec 2023.

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