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Liquidity and volatility in the U.S. Treasury market

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  • Nguyen, Giang
  • Engle, Robert
  • Fleming, Michael
  • Ghysels, Eric

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 (2000)’s 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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  • Nguyen, Giang & Engle, Robert & Fleming, Michael & Ghysels, Eric, 2020. "Liquidity and volatility in the U.S. Treasury market," Journal of Econometrics, Elsevier, vol. 217(2), pages 207-229.
    • Handle: RePEc:eee:econom:v:217:y:2020:i:2:p:207-229
    DOI: 10.1016/j.jeconom.2019.12.002
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    7. 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.
    8. Carol Alexander & Daniel F. Heck & Andreas Kaeck, 2022. "The Role of Binance in Bitcoin Volatility Transmission," Applied Mathematical Finance, Taylor & Francis Journals, vol. 29(1), pages 1-32, January.
    9. 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.
    10. 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).
    11. 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).
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. Song, Zhaogang & Zhu, Haoxiang, 2018. "Quantitative easing auctions of Treasury bonds," Journal of Financial Economics, Elsevier, vol. 128(1), pages 103-124.
    18. 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.).
    19. Krishnan, R. & Mishra, Vinod, 2013. "Intraday liquidity patterns in Indian stock market," Journal of Asian Economics, Elsevier, vol. 28(C), pages 99-114.

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    More about this item

    Keywords

    Treasury market; Liquidity; Volatility; Log-ACD models; Liquidity-at-risk;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G01 - Financial Economics - - General - - - Financial Crises
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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