George E. Tauchen
  • George E. Tauchen

  • William Henry Glasson Professor of Economics
  • Economics
  • 221 Social Sciences, Durham, NC 27708
  • Campus Box 90097
  • Phone: (919) 660-1812
  • Fax: (919) 684-8974
  • Homepage
  • Curriculum Vitae
  • Overview

    George Tauchen is the William Henry Glasson Professor of Economics and professor of finance at the Fuqua School of Business. He joined the Duke faculty in 1977 after receiving his Ph.D. from the University of Minnesota. He did his undergraduate work at the University of Wisconsin. Professor Tauchen is a fellow of the Econometric Society, the American Statistical Association, the Journal of Econometrics, and the Society for Financial Econometrics (SoFie). He is also the 2003 Duke University Scholar/Teacher of the Year. Professor Tauchen is an internationally known time series econometrician. He has developed several important new techniques for making statistical inference from financial time series data and for testing models of financial markets.  He has given invited lectures at many places around the world, including London, Paris, Beijing, Taipei, Hong Kong, and Sydney. His current research (with Professor Li of Duke) examines the impact of large jump-like moves in stock market returns on the returns of various portfolios and individual securities.  He is a former editor of the Journal of Business and Economic Statistics (JBES) and former associate editor of Econometrica, Econometric Theory, The Journal of the American Statistical Association (JASA), and JBES.   He is currently Co-Editor of the Journal of Financial Econometrics.
  • Bio

    George Tauchen is the William Henry Glasson Professor of Economics and Professor of Finance, Fuqua School of Business. He joined the Duke faculty in 1977 after receiving his Ph.D. from the University of Minnesota. He did his undergraduate work at the University of Wisconsin. Tauchen is a fellow of the Econometric Society, a fellow of the American Statistical Association, and a Fellow of the Journal of Econometrics. He is also the 2003 Duke University Scholar/Teacher of the Year.

    Tauchen is an internationally known time series econometrician. He has developed several important new techniques for making statistical inference from time series data and for testing models of financial markets.

    Professor Tauchen regularly gives research seminars at major U.S. research universities and at international meetings, conferences, and research institutes. He was Visiting Fellow at the Australian National University, and he gave one of the major invited addresses at the Seventh World Congress of the Econometric Society in Tokyo, Japan. He has lectured in such diverse places as Buenos Aires, Taipei, Helsinki, Sydney, Paris, Madrid, Vienna, Tokyo, Chile, and London. He regularly gives research seminars at major research universities and institutions world-wide.

    He is former Editor of the Journal of Business and Economic Statistics (JBES) and former associate editor of Econometrica, Econometric Theory, The Journal of the American Statistical Association, and JBES.
  • Specialties

    • Econometrics
    • Financial Economics
    • Mathematical and Quantitative Methods
  • Working Papers

    • V Todorov and G Tauchen.
    • (2012).
    • Realized laplace transforms for pure-jump semimartingales.
    • Annals of Statistics
    • ,
    • 40
    • (2)
    • ,
    • 1233-1262.
    • [web]
    Publication Description

    We consider specification and inference for the stochastic scale of discretely-observed pure-jump semimartingales with locally stable Lévy densities in the setting where both the time span of the data set increases, and the mesh of the observation grid decreases. The estimation is based on constructing a nonparametric estimate for the empirical Laplace transform of the stochastic scale over a given interval of time by aggregating high-frequency increments of the observed process on that time interval into a statistic we call realized Laplace transform. The realized Laplace transform depends on the activity of the driving pure-jump martingale, and we consider both cases when the latter is known or has to be inferred from the data. © Institute of Mathematical Statistics, 2012.

    • V Todorov and G Tauchen.
    • (2012).
    • Inverse realized laplace transforms for nonparametric volatility density estimation in jump-diffusions.
    • Journal of the American Statistical Association
    • ,
    • 107
    • (498)
    • ,
    • 622-635.
    • [web]
    Publication Description

    This article develops a nonparametric estimator of the stochastic volatility density of a discretely observed Itô semimartingale in the setting of an increasing time span and finer mesh of the observation grid. There are two basic steps involved. The first step is aggregating the high-frequency increments into the realized Laplace transform, which is a robust nonparametric estimate of the underlying volatility Laplace transform. The second step is using a regularized kernel to invert the realized Laplace transform. These two steps are relatively quick and easy to compute, so the nonparametric estimator is practicable. The article also derives bounds for the mean squared error of the estimator. The regularity conditions are sufficiently general to cover empirically important cases such as level jumps and possible dependencies between volatility moves and either diffusive or jump moves in the semimartingale. TheMonte Carlo analysis in this study indicates that the nonparametric estimator is reliable and reasonably accurate in realistic estimation contexts. An empirical application to 5-min data for three large-cap stocks, 1997-2010, reveals the importance of big short-term volatility spikes in generating high levels of stock price variability over and above those induced by price jumps. The application also shows how to trace out the dynamic response of the volatility density to both positive and negative jumps in the stock price. © 2012 American Statistical Association.

    • G. Tauchen , T. Bolerslev, N. Sizova, and D. Osterrieder.
    • (2011).
    • Risk and Return: Long-Run Relationships, Fractional Cointegration, and Return Predictability.
    • (submitted)
    • .
    • G. Tauchen.
    • (Summer, 2005).
    • Stochastic Volatility in General Equilibrium.
    • .
    • G. Tauchen with A. R. Gallant.
    • (Summer, 2004).
    • SNP: A Program for Nonparametric Time Series Analysis.
    • .
    • [web]
    • G. Tauchen.
    • (Summer, 2004).
    • Recent Developments in Stochastic Volatility: Statistical Modelling and General Equilibrium Analysis.
    • .
    • G. Tauchen, M. Chernov, A. R. Gallant, and E. Ghysels.
    • (1999).
    • A New Class of Stochastic Volatility Models with Jumps: Theory and Estimation.
    • .
    • (under revision)
  • Research Summary

    Econometrics, Financial Economics
  • Areas of Interest

    Econometrics
    Financial Economics
  • Education

      • Ph.D.,
      • Economics,
      • University of Minnesota, Twin Cities,
      • 1978
      • B.A.,
      • Economics,
      • University of Wisconsin at Madison,
      • 1971
  • Awards, Honors and Distinctions

      • Fellow,
      • Society for Financial Econometrics,
      • January 2012
      • Founding member of the Society for Financial Econometrics,
      • September, 2007
      • Founding Member,
      • Society for Financial Econometrics,
      • January 2007
      • Fellow,
      • Journal of Econometrics,
      • January 2004
      • Fellow of the Journal of Econometrics, 2004,
      • 0 2004
      • Scholar/Teacher of the Year,
      • Duke University,
      • January 2003
      • Duke University Scholar/Teacher of the Year, 2003,
      • Duke University,
      • 0 2003
      • William Henry Glasson Professor of Economics,
      • Duke University,
      • 1997
      • Fellow,
      • Econometric Society,
      • January 1994
      • Fellow of the Econometric Society, 1994,
      • 0 1994
      • ASA Fellows,
      • American Statistical Association,
      • January 1993
      • Fellow of the American Statisticial Association, 1993,
      • 0 1993
  • Recent Publications

      • GE Tauchen.
      • (2016).
      • Robust Jump Regressions.
      • Journal of the American Statistical Association
      • .
      • [web]
      • TG Andersen, O Bondarenko, V Todorov and G Tauchen.
      • (2015).
      • The fine structure of equity-index option dynamics.
      • Journal of Econometrics
      • ,
      • 187
      • (2)
      • ,
      • 532-546.
      • [web]
      • M Reiß, V Todorov and G Tauchen.
      • (2015).
      • Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data.
      • Stochastic Processes and their Applications
      • ,
      • 125
      • (8)
      • ,
      • 2955-2988.
      • [web]
      • V Todorov and G Tauchen.
      • (2014).
      • Limit theorems for the empirical distribution function of scaled increments of Itô semimartingales at high frequencies.
      • The Annals of Applied Probability
      • ,
      • 24
      • (5)
      • ,
      • 1850-1888.
      • [web]
      • V Todorov, G Tauchen and I Grynkiv.
      • (2014).
      • Volatility activity: Specification and estimation.
      • Journal of Econometrics
      • ,
      • 178
      • (PART 1)
      • ,
      • 180-193.
      • [web]
      Publication Description

      The paper examines volatility activity and its asymmetry and undertakes further specification analysis of volatility models based on it. We develop new nonparametric statistics using high-frequency option-based VIX data to test for asymmetry in volatility jumps. We also develop methods for estimating and evaluating, using price data alone, a general encompassing model for volatility dynamics where volatility activity is unrestricted. The nonparametric application to VIX data, along with model estimation for S&P index returns, suggests that volatility moves are best captured by an infinite variation pure-jump martingale with a symmetric jump compensator around zero. The latter provides a parsimonious generalization of the jump-diffusions commonly used for volatility modeling.

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  • Teaching

    • ECON 883.07
      • TOPICS IN ECONOMETRICS
      • Social Sciences 111
      • Tu 06:30 PM-08:30 PM
    • ECON 957S.01
      • RSRCH SEM: FINANL ECONOMETRICS
      • Social Sciences 111
      • M 11:45 AM-01:00 PM
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