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The impact of jumps and thin trading on realized hedge ratios

The use of intradaily data to produce daily variance measures has resulted in increased forecast accuracy and better hedging for many markets. However, this paper shows that improved hedging ratios can depend on the behavior of price disruptions in the assets. When spot and future prices for the same asset do not jump simultaneously inferior hedging outcomes can be observed. This problem dominates potential bias from thin trading. Using US Treasury data we demonstrate how the extent of non-synchronized jumping leads to the ?nding that optimal hedging ratios are not improved with intradaily data in this market.

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File URL: http://eprints.utas.edu.au/16318/1/2013-02_DHH_Mardi.pdf
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Paper provided by University of Tasmania, Tasmanian School of Business and Economics in its series Working Papers with number 2013-02.

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Length: 27 pages
Date of creation: 28 Mar 2013
Date of revision: 28 Mar 2013
Publication status: Published by the University of Tasmania. Discussion paper 2013-02
Handle: RePEc:tas:wpaper:16318
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  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Jin (Ginger) Wu, 2005. "A Framework for Exploring the Macroeconomic Determinants of Systematic Risk," NBER Working Papers 11134, National Bureau of Economic Research, Inc.
  2. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
  3. Stephen G. Cecchetti & Robert E. Cumby & Stephen Figlewski, 1986. "Estimation of the optimal futures hedge," Research Working Paper 86-10, Federal Reserve Bank of Kansas City.
  4. Bruce Mizrach & Christopher J. Neely, 2007. "Information shares in the U.S. treasury market," Working Papers 2005-070, Federal Reserve Bank of St. Louis.
  5. 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.
  6. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(04), pages 535-551, December.
  7. Almut Veraart, 2008. "Inference for the jump part of quadratic variation of Itô semimartingales," CREATES Research Papers 2008-17, Department of Economics and Business Economics, Aarhus University.
  8. LAHAYE, Jérôme & LAURENT, Sébastien & NEELY, Christopher J., . "Jumps, cojumps and macro announcements," CORE Discussion Papers RP 2413, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, Elsevier.
  10. de Goeij, Peter & Marquering, Wessel, 2006. "Macroeconomic announcements and asymmetric volatility in bond returns," Journal of Banking & Finance, Elsevier, vol. 30(10), pages 2659-2680, October.
  11. Tae H. Park & Lorne N. Switzer, 1995. "Bivariate GARCH estimation of the optimal hedge ratios for stock index futures: A note," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(1), pages 61-67, 02.
  12. Todorov, Viktor & Tauchen, George, 2011. "Volatility Jumps," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 356-371.
  13. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(04), pages 523-543, December.
  14. Dungey, Mardi & McKenzie, Michael & Smith, L. Vanessa, 2009. "Empirical evidence on jumps in the term structure of the US Treasury Market," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 430-445, June.
  15. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  16. Evans, Kevin P., 2011. "Intraday jumps and US macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2511-2527, October.
  17. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-70, March.
  18. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 319-342.
  19. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
  20. Michael Johannes, 2004. "The Statistical and Economic Role of Jumps in Continuous-Time Interest Rate Models," Journal of Finance, American Finance Association, vol. 59(1), pages 227-260, 02.
  21. Dark, Jonathan, 2007. "Basis Convergence and Long Memory in Volatility When Dynamic Hedging with Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(04), pages 1021-1040, December.
  22. Dungey, Mardi & Hvozdyk, Lyudmyla, 2012. "Cojumping: Evidence from the US Treasury bond and futures markets," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1563-1575.
  23. Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 456-499.
  24. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-24, April-Jun.
  25. Jiang, George & Yan, Shu, 2009. "Linear-quadratic term structure models - Toward the understanding of jumps in interest rates," Journal of Banking & Finance, Elsevier, vol. 33(3), pages 473-485, March.
  26. Michael J. Fleming, 2001. "Measuring treasury market liquidity," Staff Reports 133, Federal Reserve Bank of New York.
  27. Kim Christensen & Roel Oomen & Mark Podolskij, 2011. "Fact or friction: Jumps at ultra high frequency," CREATES Research Papers 2011-19, Department of Economics and Business Economics, Aarhus University.
  28. H. N. E. BystrOm, 2003. "The hedging performance of electricity futures on the Nordic power exchange," Applied Economics, Taylor & Francis Journals, vol. 35(1), pages 1-11.
  29. de Goeij, P. C. & Marquering, W., 2006. "Macroeconomic announcements and asymmetric volatility in bond returns," Other publications TiSEM bc4389f3-bad2-4e5b-b996-3, Tilburg University, School of Economics and Management.
  30. Richard D. F. Harris & Jian Shen & Evarist Stoja, 2010. "The Limits to Minimum-Variance Hedging," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(5-6), pages 737-761.
  31. Jiang, George J. & Lo, Ingrid & Verdelhan, Adrien, 2011. "Information Shocks, Liquidity Shocks, Jumps, and Price Discovery: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(02), pages 527-551, April.
  32. Blair, Bevan J. & Poon, Ser-Huang & Taylor, Stephen J., 2001. "Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 5-26, November.
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