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What drives volatility persistence in the foreign exchange market?

  • David W. Berger
  • Alain P. Chaboud
  • Erik Hjalmarsson
  • Edward Howorka

We analyze the factors driving the widely-noted persistence in asset return volatility using a unique dataset on global euro-dollar exchange rate trading. We propose a new simple empirical specification of volatility, based on the Kyle-model, which links volatility to the information flow, measured as the order flow in the market, and the price sensitivity to that information. Through the use of high-frequency data, we are able to estimate the time-varying market sensitivity to information, and movements in volatility can therefore be directly related to movements in two observable variables, the order flow and the market sensitivity. The empirical results are very strong and show that the model is able to explain almost all of the long-run variation in volatility. Our results also show that the variation over time of the market's sensitivity to information plays at least as important a role in explaining the persistence of volatility as does the rate of information arrival itself. The econometric analysis is conducted using novel estimation techniques which explicitly take into account the persistent nature of the variables and allow us to properly test for long-run relationships in the data.

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Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 862.

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Date of creation: 2006
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Handle: RePEc:fip:fedgif:862
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  1. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
  2. Shimotsu, Katsumi & Phillips, Peter C B, 2002. "Exact Local Whittle Estimation of Fractional Integration," Economics Discussion Papers 8838, University of Essex, Department of Economics.
  3. Mitchell, Mark L & Mulherin, J Harold, 1994. " The Impact of Public Information on the Stock Market," Journal of Finance, American Finance Association, vol. 49(3), pages 923-50, July.
  4. Clifford M. Hurvich & Bonnie K. Ray, 2003. "The Local Whittle Estimator of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 1(3), pages 445-470.
  5. Martin D. D. Evans & Richard K. Lyons, 2007. "Exchange Rate Fundamentals and Order Flow," NBER Working Papers 13151, National Bureau of Economic Research, Inc.
  6. Andersen, Torben G, 1996. " Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
  7. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Vega, Clara, 2002. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," Working Papers 02-1, University of Pennsylvania, Wharton School, Weiss Center.
  8. Federico Bandi & Benoit Perron, 2003. "Long memory and the relation between implied and realized volatility," Econometrics 0305004, EconWPA.
  9. Nicolae B. Garleanu & Lasse H. Pedersen, 2007. "Liquidity and Risk Management," NBER Working Papers 12887, National Bureau of Economic Research, Inc.
  10. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January.
  11. David W. Berger & Alain P. Chaboud & Sergey V. Chernenko & Edward Howorka & Jonathan H. Wright, 2006. "Order flow and exchange rate dynamics in electronic brokerage system data," International Finance Discussion Papers 830, Board of Governors of the Federal Reserve System (U.S.).
  12. Killeen, William P. & Lyons, Richard K. & Moore, Michael J., 2006. "Fixed versus flexible: Lessons from EMS order flow," Journal of International Money and Finance, Elsevier, vol. 25(4), pages 551-579, June.
  13. R. F. Engle, 1972. "Band Spectrum Regressions," Working papers 96, Massachusetts Institute of Technology (MIT), Department of Economics.
  14. Bollerslev, Tim & Wright, Jonathan H., 2000. "Semiparametric estimation of long-memory volatility dependencies: The role of high-frequency data," Journal of Econometrics, Elsevier, vol. 98(1), pages 81-106, September.
  15. Payne, Richard, 2003. "Informed trade in spot foreign exchange markets: an empirical investigation," Journal of International Economics, Elsevier, vol. 61(2), pages 307-329, December.
  16. Graham Elliott & Ulrich K. Muller, 2006. "Efficient Tests for General Persistent Time Variation in Regression Coefficients," Review of Economic Studies, Oxford University Press, vol. 73(4), pages 907-940.
  17. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
  18. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
  19. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
  20. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
  21. Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
  22. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
  23. Clifford Hurvich & Eric Moulines & Philippe Soulier, 2004. "Estimating Long Memory in Volatility," Econometrics 0412006, EconWPA.
  24. Alain P. Chaboud & Sergey V. Chernenko & Edward Howorka & Raj S. Krishnasami Iyer & David Liu & Jonathan H. Wright, 2004. "The high-frequency effects of U.S. macroeconomic data releases on prices and trading activity in the global interdealer foreign exchange market," International Finance Discussion Papers 823, Board of Governors of the Federal Reserve System (U.S.).
  25. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Wu, Jin, 2004. "Realized beta: Persistence and predictability," CFS Working Paper Series 2004/16, Center for Financial Studies (CFS).
  26. Martin D. D. Evans and Richard K. Lyons., 1999. "Order Flow and Exchange Rate Dynamics," Research Program in Finance Working Papers RPF-288, University of California at Berkeley.
  27. Christensen, Bent Jesper & Nielsen, Morten Orregaard, 2006. "Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting," Journal of Econometrics, Elsevier, vol. 133(1), pages 343-371, July.
  28. Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-76, March.
  29. Isabelle Huault & V. Perret & S. Charreire-Petit, 2007. "Management," Post-Print halshs-00337676, HAL.
  30. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
  31. Hasbrouck, Joel, 1991. " Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
  32. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
  33. Grant McQueen, 2004. "Whence GARCH? A Preference-Based Explanation for Conditional Volatility," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 915-949.
  34. Peter C.B. Phillips, 1985. "Understanding Spurious Regressions in Econometrics," Cowles Foundation Discussion Papers 757, Cowles Foundation for Research in Economics, Yale University.
  35. Lamoureux, Christopher G & Lastrapes, William D, 1994. "Endogenous Trading Volume and Momentum in Stock-Return Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 253-60, April.
  36. Berry, Thomas D & Howe, Keith M, 1994. " Public Information Arrival," Journal of Finance, American Finance Association, vol. 49(4), pages 1331-46, September.
  37. Liesenfeld, Roman, 2001. "A generalized bivariate mixture model for stock price volatility and trading volume," Journal of Econometrics, Elsevier, vol. 104(1), pages 141-178, August.
  38. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-29, March.
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