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Liquidity and volatility in the U.S. treasury market

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Abstract

We model the joint dynamics of intraday liquidity, volume, and volatility in the U.S. Treasury market, especially through the 2007-09 financial crisis and around important economic announcements. Using various specifications based on Bauwens and Giot?s (2000) Log- ACD(1,1) model, we find that liquidity, volume, and volatility are highly persistent, with volatility having a lower short-term persistence than the other two. Market liquidity and volume are important to explaining volatility dynamics but not vice versa. In addition, market dynamics change during the financial crisis, with all variables exhibiting increased responsiveness to their most recent realizations. Our models also reveal different market dynamics around announcements. Finally, we introduce new measures of liquidity risk that are useful for continually monitoring liquidity conditions and the risk of liquidity stress in the market.

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  • Robert Engle & Michael J. Fleming & Eric Ghysels & Giang Nguyen, 2012. "Liquidity and volatility in the U.S. treasury market," Staff Reports 590, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:590
    Note: Previous title: "Liquidity, Volatility and Flights to Safety in the U.S. Treasury Market: Evidence From A New Class of Dynamic Order Book Models"
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    Cited by:

    1. Markus Engler & Vahidin Jeleskovic, 2016. "Intraday volatility, trading volume and trading intensity in the interbank market e-MID," MAGKS Papers on Economics 201648, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Darrell Duffie & Michael J. Fleming & Frank M. Keane & Claire Nelson & Or Shachar & Peter Van Tassel, 2023. "Dealer Capacity and U.S. Treasury Market Functionality," Staff Reports 1070, Federal Reserve Bank of New York.
    3. Kinkyo, Takuji, 2020. "Volatility interdependence on foreign exchange markets: The contribution of cross-rates," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    4. Lieven Baele & Geert Bekaert & Koen Inghelbrecht & Min Wei, 2020. "Flights to Safety," The Review of Financial Studies, Society for Financial Studies, vol. 33(2), pages 689-746.
    5. Ben Omrane, Walid & Tao, Yusi & Welch, Robert, 2017. "Scheduled macro-news effects on a Euro/US dollar limit order book around the 2008 financial crisis," Research in International Business and Finance, Elsevier, vol. 42(C), pages 9-30.
    6. Broto, Carmen & Lamas, Matías, 2020. "Is market liquidity less resilient after the financial crisis? Evidence for US Treasuries," Economic Modelling, Elsevier, vol. 93(C), pages 217-229.
    7. Stefania D’Amico & N Aaron Pancost, 2022. "Special Repo Rates and the Cross-Section of Bond Prices: The Role of the Special Collateral Risk Premium [Pr icing the term structure with linear regressions]," Review of Finance, European Finance Association, vol. 26(1), pages 117-162.
    8. Han, Seung-Oh & Huh, Sahn-Wook & Park, Jeayoung, 2023. "Detecting jumps amidst prevalent zero returns: Evidence from the U.S. Treasury securities," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 276-307.
    9. Lin, Hai & Lo, Ingrid & Qiao, Rui, 2021. "Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market," Journal of Banking & Finance, Elsevier, vol. 133(C).
    10. Schneider, Michael & Lillo, Fabrizio & Pelizzon, Loriana, 2016. "How has sovereign bond market liquidity changed? An illiquidity spillover analysis," SAFE Working Paper Series 151, Leibniz Institute for Financial Research SAFE.
    11. Mariano González-Sánchez & Eva M. Ibáñez Jiménez & Ana I. Segovia San Juan, 2021. "Market and Liquidity Risks Using Transaction-by-Transaction Information," Mathematics, MDPI, vol. 9(14), pages 1-14, July.
    12. Geromichalos, Athanasios & Herrenbrueck, Lucas M. & Salyer, Kevin D., 2016. "A search-theoretic model of the term premium," Theoretical Economics, Econometric Society, vol. 11(3), September.
    13. Siikanen, Milla & Kanniainen, Juho & Valli, Jaakko, 2017. "Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic," Finance Research Letters, Elsevier, vol. 21(C), pages 264-271.
    14. Clements, Adam & Liao, Yin, 2017. "Forecasting the variance of stock index returns using jumps and cojumps," International Journal of Forecasting, Elsevier, vol. 33(3), pages 729-742.
    15. Song, Zhaogang & Zhu, Haoxiang, 2018. "Quantitative easing auctions of Treasury bonds," Journal of Financial Economics, Elsevier, vol. 128(1), pages 103-124.
    16. Andrew C. Meldrum & Oleg Sokolinskiy, 2023. "The Effects of Volatility on Liquidity in the Treasury Market," Finance and Economics Discussion Series 2023-028, Board of Governors of the Federal Reserve System (U.S.).
    17. Carol Alexander & Daniel Heck & Andreas Kaeck, 2021. "The Role of Binance in Bitcoin Volatility Transmission," Papers 2107.00298, arXiv.org, revised Aug 2021.
    18. Krishnan, R. & Mishra, Vinod, 2013. "Intraday liquidity patterns in Indian stock market," Journal of Asian Economics, Elsevier, vol. 28(C), pages 99-114.
    19. Benos, Evangelos & Žikeš, Filip, 2018. "Funding constraints and liquidity in two-tiered OTC markets," Journal of Financial Markets, Elsevier, vol. 39(C), pages 24-43.

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    More about this item

    Keywords

    limit order book; volatility; liquidity; Treasury market; announcements; financial crisis;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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