IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login

Citations for "Parametric and Nonparametric Volatility Measurement"

by Torben G. Andersen & Tim Bollerslev & Francis X. Diebold

For a complete description of this item, click here. For a RSS feed for citations of this item, click here.
as in new window

  1. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
  2. Torben G. ANDERSEN & Tim BOLLERSLEV & Nour MEDDAHI, 2002. "Correcting The Errors : A Note On Volatility Forecast Evaluation Based On High-Frequency Data And Realized Volatilities," Cahiers de recherche 21-2002, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  3. Linton, Oliver & Ghosh, Anisha, 2009. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," UC3M Working papers. Economics we094928, Universidad Carlos III de Madrid. Departamento de Economía.
  4. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
  5. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
  6. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
  7. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
  8. Hao Zhou & Tim Bollerslev & Michael S. Gibson, 2005. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
  9. Zagaglia, Paolo, 2009. "Money-Market Segmentation in the Euro Area: What has Changed During the Turmoil?," Research Papers in Economics 2009:11, Stockholm University, Department of Economics.
  10. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," NBER Working Papers 15533, National Bureau of Economic Research, Inc.
  11. Brandt, Michael W. & Diebold, Francis X., 2004. "A no-arbitrage approach to range-based estimation of return covariances and correlations," CFS Working Paper Series 2004/07, Center for Financial Studies (CFS).
  12. Tim Bollerslev & Tzuo Hann Law & George Tauchen, 2007. "Risk, Jumps, and Diversification," CREATES Research Papers 2007-19, Department of Economics and Business Economics, Aarhus University.
  13. Fornari, Fabio, 2008. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Working Paper Series 0859, European Central Bank.
  14. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," OFRC Working Papers Series 2005fe05, Oxford Financial Research Centre.
  15. Turgut Kısınbay, 2010. "Predictive ability of asymmetric volatility models at medium-term horizons," Applied Economics, Taylor & Francis Journals, vol. 42(30), pages 3813-3829.
  16. Frowin Schulz & Karl Mosler, 2011. "The effect of infrequent trading on detecting price jumps," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 27-58, March.
  17. Christensen, Kim & Podolskij, Mark, 2006. "Range-Based Estimation of Quadratic Variation," Technical Reports 2006,37, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  18. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank, Research Centre.
  19. Laarni Bulan & Christopher Mayer & C. Tsuriel Somerville, . "Irreversible Investment, Real Options, and Competition: Evidence from Real Estate Development," Zell/Lurie Center Working Papers 391, Wharton School Samuel Zell and Robert Lurie Real Estate Center, University of Pennsylvania.
  20. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
  21. James Chong, 2004. "Options trading profits from correlation forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 14(15), pages 1075-1085.
  22. Tauchen, George & Zhou, Hao, 2011. "Realized jumps on financial markets and predicting credit spreads," Journal of Econometrics, Elsevier, vol. 160(1), pages 102-118, January.
  23. Sean D. Campbell & Francis X. Diebold, 2005. "Weather Forecasting for Weather Derivatives," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 6-16, March.
  24. Sean D. Campbell & Canlin Li, 2004. "Alternative estimates of the presidential premium," Finance and Economics Discussion Series 2004-69, Board of Governors of the Federal Reserve System (U.S.).
  25. Stavros Degiannakis, 2004. "Volatility forecasting: evidence from a fractional integrated asymmetric power ARCH skewed-t model," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1333-1342.
  26. Henker, Thomas & Husodo, Zaäfri A., 2010. "Noise and efficient variance in the Indonesia Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 18(2), pages 199-216, April.
  27. Juan Manuel Julio & Norberto Rodríguez & Hector Zárate, . "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," Borradores de Economia 347, Banco de la Republica de Colombia.
  28. Patton, Andrew J., 2011. "Volatility forecast comparison using imperfect volatility proxies," Journal of Econometrics, Elsevier, vol. 160(1), pages 246-256, January.
  29. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
  30. Fornari, Fabio & Mele, Antonio, 2006. "Approximating volatility diffusions with CEV-ARCH models," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 931-966, June.
  31. René Garcia & Eric Ghysels & Éric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
  32. Haselmann, Rainer & Helmut, Herwartz, 2005. "The Introduction of the Euro and its Effects on Investment Decisions," Economics Working Papers 2005,15, Christian-Albrechts-University of Kiel, Department of Economics.
  33. Ravi Bansal & Varoujan Khatachtrian & Amir Yaron, 2002. "Interpretable Asset Markets?," NBER Working Papers 9383, National Bureau of Economic Research, Inc.
  34. Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
  35. Ceylan, Ozcan, 2012. "Time-Varying Volatility Asymmetry: A Conditioned HAR-RV(CJ) EGARCH-M Model," GIAM Working Papers 12-4, Galatasaray University Economic Research Center.
  36. Chun-Hung Chen & Wei-Choun Yu & Eric Zivot, 2009. "Predicting Stock Volatility Using After-Hours Information," Working Papers UWEC-2009-01, University of Washington, Department of Economics.
  37. Tim Bollerslev & Hao Zhou, 2003. "Volatility puzzles: a unified framework for gauging return-volatility regressions," Finance and Economics Discussion Series 2003-40, Board of Governors of the Federal Reserve System (U.S.).
  38. Brousseau, Vincent & Durré, Alain, 2013. "Interest rate volatility: a consol rate-based measure," Working Paper Series 1505, European Central Bank.
  39. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.