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Volatility and Time Series Econometrics: Essays in Honor of Robert Engle

Editor

Listed:
  • Bollerslev, Tim
    (Professor of Economics and Finance, Duke University)

  • Russell, Jeffrey
    (Professor of Econometrics and Statistics, University of Chicago Booth School of Economics)

  • Watson, Mark
    (Professor of Economics and Public Affairs, Princeton University)

Abstract

Robert Engle received the Nobel Prize for Economics in 2003 for his work in time series econometrics. This book contains 16 original research contributions by some the leading academic researchers in the fields of time series econometrics, forecasting, volatility modelling, financial econometrics and urban economics, along with historical perspectives related to field of time series econometrics more generally. Engle's Nobel Prize citation focuses on his path-breaking work on autoregressive conditional heteroskedasticity (ARCH) and the profound effect that this work has had on the field of financial econometrics. Several of the chapters focus on conditional heteroskedasticity, and develop the ideas of Engle's Nobel Prize winning work. Engle's work has had its most profound effect on the modelling of financial variables and several of the chapters use newly developed time series methods to study the behavior of financial variables. Each of the 16 chapters may be read in isolation, but they all importantly build on and relate to the seminal work by Nobel Laureate Robert F. Engle. Contributors to this volume - Mark W. Watson, Princeton University Tim Bollerslev, Duke University Jeffrey Russell, University of Chicago Ole E. Barndorff-Nielsen, University of Aarhus Solja Kinnebrock, University of Oxford Neil Shephard, University of Oxford Gianna Boero, University of Warwick Jeremy Smith, University of Warwick Kenneth F. Wallis, University of Warwick Jacob Boudoukh, Arison School of Business, IDC Christopher Downing, Barclays Global Investors Matthew Richardson, New York University Richard Stanton, University of California, Berkeley Robert F. Whitelaw, New York University Luis Catao, IADB and IMF Allan Timmerman, University of California, San Diego N. Edward Coulson, Pennsylvania State University Francis X. Diebold, University of Pennsylvania Kamil Yilmaz, Koc University Stephen Figlewski, New York University Gloria Gonzalez-Rivera, University of California, Riverside Emre Yoldas, University of California, Riverside Clive W.J. Granger, University of California, San Diego James D. Hamilton, University of California, San Diego David F. Hendry, University of Oxford Carlos Santos, Portuguese Catholic University James H. Stock, Harvard University Andrew J. Patton, University of Oxford Halbert White, University of California, San Diego Tae-Hwan Kim, Yonsei University Simone Manganelli, European Central Bank

Suggested Citation

  • Bollerslev, Tim & Russell, Jeffrey & Watson, Mark (ed.), 2010. "Volatility and Time Series Econometrics: Essays in Honor of Robert Engle," OUP Catalogue, Oxford University Press, number 9780199549498.
  • Handle: RePEc:oxp:obooks:9780199549498
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    Citations

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    Cited by:

    1. Diebold, Francis X. & Yilmaz, Kamil, 2015. "Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring," OUP Catalogue, Oxford University Press, number 9780199338306.
    2. Lorenzo-Valdes, Arturo & Ruiz-Porras, Antonio, 2011. "Modelación de los rendimientos bursátiles mexicanos mediante los modelos TGARCH y EGARCH: Un estudio econométrico para 30 acciones y el Índice de Precios y Cotizaciones
      [Modeling Mexican stock retu
      ," MPRA Paper 36872, University Library of Munich, Germany.
    3. Kerry Patterson & Michael A. Thornton, 2013. "A review of econometric concepts and methods for empirical macroeconomics," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 2, pages 4-42, Edward Elgar Publishing.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    5. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    6. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org.
    7. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 10(4), pages 637-668, September.
    8. Narayan, Seema & Smyth, Russell, 2015. "The financial econometrics of price discovery and predictability," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 380-393.
    9. LAURENT, Sébastien & VIOLANTE, Francesco, 2012. "Volatility forecasts evaluation and comparison," CORE Discussion Papers RP 2414, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Dimitrios P. Louzis & Spyros Xanthopoulos‐Sisinis & Apostolos P. Refenes, 2013. "The Role of High‐Frequency Intra‐daily Data, Daily Range and Implied Volatility in Multi‐period Value‐at‐Risk Forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(6), pages 561-576, September.
    11. Andrew S. Duncan & Alain Kabundi, 2014. "Global Financial Crises and Time-Varying Volatility Comovement in World Equity Markets," South African Journal of Economics, Economic Society of South Africa, vol. 82(4), pages 531-550, December.

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