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Citations for "Parametric and Nonparametric Volatility Measurement"

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

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  1. 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.
  2. Christensen, Kim & Podolskij, Mark, 2007. "Realized range-based estimation of integrated variance," Journal of Econometrics, Elsevier, vol. 141(2), pages 323-349, December.
  3. James Chong, 2004. "Options trading profits from correlation forecasts," Applied Financial Economics, Taylor & Francis Journals, vol. 14(15), pages 1075-1085.
  4. Ravi Bansal & Varoujan Khatchatrian & Amir Yaron, 2004. "Interpretable Asset Markets?," 2004 Meeting Papers 136b, Society for Economic Dynamics.
  5. 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.
  6. 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.
  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. Fornari, Fabio, 2010. "Assessing the compensation for volatility risk implicit in interest rate derivatives," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 722-743, September.
  9. ANDERSEN, Torben G. & BOLLERSLEV, Tim & MEDDAHI, Nour, 2002. "Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities," Cahiers de recherche 2002-21, Universite de Montreal, Departement de sciences economiques.
  10. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," OFRC Working Papers Series 2005fe05, Oxford Financial Research Centre.
  11. Laarni Bulan & Christopher Mayer & C. Tsuriel Somerville, "undated". "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.
  12. George Tauchen & Hao Zhou, 2006. "Realized jumps on financial markets and predicting credit spreads," Finance and Economics Discussion Series 2006-35, Board of Governors of the Federal Reserve System (U.S.).
  13. Turgut Kisinbay, 2003. "Predictive Ability of Asymmetric Volatility Models At Medium-Term Horizons," IMF Working Papers 03/131, International Monetary Fund.
  14. 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.
  15. 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.
  16. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," CREATES Research Papers 2009-52, Department of Economics and Business Economics, Aarhus University.
  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. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model For Volatility Using Intra-Daily Data," Econometrics Working Papers Archive wp2003_07, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  19. 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.
  20. 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.).
  21. Michael W. Brandt & Francis X. Diebold, 2006. "A No-Arbitrage Approach to Range-Based Estimation of Return Covariances and Correlations," The Journal of Business, University of Chicago Press, vol. 79(1), pages 61-74, January.
  22. Tim Bollerslev & Michael S. Gibson & Hao Zhou, 2004. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Finance and Economics Discussion Series 2004-56, Board of Governors of the Federal Reserve System (U.S.).
  23. 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.
  24. 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.
  25. Peter Christoffersen & Francis X. Diebold, 2002. "Financial Asset Returns, Market Timing, and Volatility Dynamics," CIRANO Working Papers 2002s-02, CIRANO.
  26. 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.
  27. Sean D. Campbell & Francis X. Diebold, 2003. "Weather Forecasting for Weather Derivatives," NBER Working Papers 10141, National Bureau of Economic Research, Inc.
  28. 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.
  29. Hellström, Jörgen & Lönnbark, Carl, 2011. "Identi�cation of jumps in �financial price series," MPRA Paper 30977, University Library of Munich, Germany.
  30. 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.
  31. 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.
  32. Brousseau, Vincent & Durré, Alain, 2013. "Interest rate volatility: a consol rate-based measure," Working Paper Series 1505, European Central Bank.
  33. 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.).
  34. Juan Manuel Julio & Norberto Rodríguez & Héctor Manuel Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," BORRADORES DE ECONOMIA 002605, BANCO DE LA REPÚBLICA.
  35. Elena Andreou & Eric Ghysels, 2004. "Monitoring for Disruptions in Financial Markets," CIRANO Working Papers 2004s-26, CIRANO.
  36. 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.
  37. Andrew Patton, 2006. "Volatility Forecast Comparison using Imperfect Volatility Proxies," Research Paper Series 175, Quantitative Finance Research Centre, University of Technology, Sydney.
  38. René Garcia & Eric Ghysels & Éric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO.
  39. 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.
This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.