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Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets

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  • Alain Chaboud
  • Benjamin Chiquoine
  • Erik Hjalmarsson
  • Mico Loretan

Abstract

Using two newly available ultrahigh-frequency datasets, we investigate empirically how frequently one can sample certain foreign exchange and U.S. Treasury security returns without contaminating estimates of their integrated volatility with market microstructure noise. We find that one can sample FX returns as frequently as once every 15 to 20 seconds without contaminating volatility estimates; bond returns may be sampled as frequently as once every 2 to 3 minutes on days without U.S. macroeconomic announcements, and as frequently as once every 40 seconds on announcement days. With a simple realized kernel estimator, the sampling frequencies can be increased to once every 2 to 5 seconds for FX returns and to about once every 30 to 40 seconds for bond returns. These sampling frequencies, especially in the case of FX returns, are much higher than those often recommended in the empirical literature on realized volatility in equity markets. The higher sampling frequencies for FX and bond returns likely reflects the superior depth and liquidity of these markets.

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  • Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Mico Loretan, 2008. "Frequency of observation and the estimation of integrated volatility in deep and liquid financial markets," BIS Working Papers 249, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:249
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    Cited by:

    1. Andersen, Torben G. & Dobrev, Dobrislav & Schaumburg, Ernst, 2012. "Jump-robust volatility estimation using nearest neighbor truncation," Journal of Econometrics, Elsevier, vol. 169(1), pages 75-93.
    2. Takatoshi Ito & Kenta Yamada & Misako Takayasu & Hideki Takayasu, 2020. "Execution Risk and Arbitrage Opportunities in the Foreign Exchange Markets," NBER Working Papers 26706, National Bureau of Economic Research, Inc.
    3. Opschoor, Anne & Taylor, Nick & van der Wel, Michel & van Dijk, Dick, 2014. "Order flow and volatility: An empirical investigation," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 185-201.
    4. Bubák, Vít & Kocenda, Evzen & Zikes, Filip, 2011. "Volatility transmission in emerging European foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2829-2841, November.
    5. Schmidt, Anatoly B., 2009. "Detrending the realized volatility in the global FX market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(9), pages 1887-1892.
    6. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    7. Caporale, Guglielmo Maria & You, Kefei & Chen, Lei, 2019. "Global and regional stock market integration in Asia: A panel convergence approach," International Review of Financial Analysis, Elsevier, vol. 65(C).
    8. Taesuk Lee & Mico Loretan & Werner Ploberger, 2013. "Rate-optimal tests for jumps in diffusion processes," Statistical Papers, Springer, vol. 54(4), pages 1009-1041, November.
    9. Marina Theodosiou, 2010. "Calendar Time Sampling of High Frequency Financial Asset Price and the Verdict on Jumps," Working Papers 2010-7, Central Bank of Cyprus.
    10. Yu‐Sheng Lai, 2022. "High‐frequency data and stock–bond investing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1623-1638, December.
    11. Apergis, Nicholas, 2023. "Realized higher-order moments spillovers across cryptocurrencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    12. Chen, Yu-Lun & Tsai, Wei-Che, 2017. "Determinants of price discovery in the VIX futures market," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 59-73.
    13. Mohammad Jahan-Parvar & Filip Zikes, 2019. "When do low-frequency measures really measure transaction costs?," Finance and Economics Discussion Series 2019-051, Board of Governors of the Federal Reserve System (U.S.).
    14. Onur, Esen & Roberts, John S. & Tuzun, Tugkan, 2023. "Trader positions and aggregate portfolio demand," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    15. Degiannakis, Stavros & Filis, George, 2022. "Oil price volatility forecasts: What do investors need to know?," Journal of International Money and Finance, Elsevier, vol. 123(C).
    16. Roland Füss & Ferdinand Mager & Michael Stein & Lu Zhao, 2018. "Financial crises, price discovery, and information transmission: a high-frequency perspective," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 333-365, November.
    17. Tseng, Tseng-Chan & Lee, Chien-Chiang & Chen, Mei-Ping, 2015. "Volatility forecast of country ETF: The sequential information arrival hypothesis," Economic Modelling, Elsevier, vol. 47(C), pages 228-234.

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    Keywords

    realized volatility; sampling frequency; market microstructure; bond markets; foreign exchange markets; liquidity;
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