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Content horizons for conditional variance forecasts

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  • Galbraith, John W.
  • KI[#x1e63]Inbay, Turgut

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 21 (2005)
Issue (Month): 2 ()
Pages: 249-260

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Handle: RePEc:eee:intfor:v:21:y:2005:i:2:p:249-260

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Web page: http://www.elsevier.com/locate/ijforecast

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References

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  1. Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
  2. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  3. Raffaella Giacomini & Halbert White, 2003. "Tests of conditional predictive ability," Boston College Working Papers in Economics 572, Boston College Department of Economics.
  4. Muller, Ulrich A. & Dacorogna, Michel M. & Olsen, Richard B. & Pictet, Olivier V. & Schwarz, Matthias & Morgenegg, Claude, 1990. "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis," Journal of Banking & Finance, Elsevier, vol. 14(6), pages 1189-1208, December.
  5. Ole E. Barndorff-Nielsen & Neil Shephard, 2002. "Estimating quadratic variation using realized variance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 457-477.
  6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
  7. Peter F. Christoffersen & Francis X. Diebold, 1997. "How Relevant is Volatility Forecasting for Financial Risk Management?," Center for Financial Institutions Working Papers 97-45, Wharton School Center for Financial Institutions, University of Pennsylvania.
  8. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  9. Jonathan H. Wright & Tim Bollerslev, 1999. "High frequency data, frequency domain inference and volatility forecasting," International Finance Discussion Papers 649, Board of Governors of the Federal Reserve System (U.S.).
  10. Bollerslev, Tim & Domowitz, Ian, 1993. " Trading Patterns and Prices in the Interbank Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 48(4), pages 1421-43, September.
  11. 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.
  12. Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
  13. 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.
  14. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  15. Dacorogna, Michael M. & Muller, Ulrich A. & Nagler, Robert J. & Olsen, Richard B. & Pictet, Olivier V., 1993. "A geographical model for the daily and weekly seasonal volatility in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 12(4), pages 413-438, August.
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Cited by:
  1. John G. Galbraith & Greg Tkacz, 2006. "How Far Can We Forecast? Forecast Content Horizons For Some Important Macroeconomic Time Series," Departmental Working Papers 2006-13, McGill University, Department of Economics.
  2. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
  3. John W. Galbraith & Greg Tkacz, 2007. "Forecast Content And Content Horizons For Some Important Macroeconomic Time Series," Departmental Working Papers 2007-01, McGill University, Department of Economics.
  4. Jonas Dovern, 2006. "Predicting GDP Components. Do Leading Indicators Increase Predictability?," Kiel Advanced Studies Working Papers 436, Kiel Institute for the World Economy.
  5. Papadimitriou, Theophilos & Gogas, Periklis & Plakandaras, Vasilios, 2013. "Forecasting daily and monthly exchange rates with machine learning techniques," DUTH Research Papers in Economics 3-2013, Democritus University of Thrace, Department of Economics, revised 26 Sep 2013.
  6. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
  7. Georgios Tsiotas, 2009. "On the use of non-linear transformations in Stochastic Volatility models," Statistical Methods and Applications, Springer, vol. 18(4), pages 555-583, November.
  8. Tsiotas, Georgios, 2012. "On generalised asymmetric stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 151-172, January.
  9. Raunig, Burkhard, 2008. "The predictability of exchange rate volatility," Economics Letters, Elsevier, vol. 98(2), pages 220-228, February.
  10. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.

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