Francis X. Diebold

Last updated
Francis X. Diebold
Born (1959-11-12) November 12, 1959 (age 64)
Philadelphia, PA, US
Academic career
Institution University of Pennsylvania
NBER
Field Econometrics
Financial economics
Macroeconomics
Alma mater University of Pennsylvania (B.S., Ph.D.)
Doctoral
advisor
Marc Nerlove (Chair), Lawrence Klein, Peter Pauly
ContributionsDiebold–Mariano test;
Latent-factor ARCH model;
Realized volatility modeling;
Dynamic Nelson–Siegel yield-curve model;
Network connectedness measurement and visualization;
Aruoba–Diebold–Scotti Index
Awards Guggenheim Fellowship
Sloan Fellowship
Humboldt Fellowship

Francis X. Diebold (born November 12, 1959) is an American economist known for his work in predictive econometric modeling, financial econometrics, and macroeconometrics. He earned both his B.S. and Ph.D. degrees at the University of Pennsylvania, where his doctoral committee included Marc Nerlove, Lawrence Klein, and Peter Pauly. He has spent most of his career at Penn, where he has mentored approximately 75 Ph.D. students. [1] Presently he is Paul F. and Warren S. Miller Professor of Social Sciences and Professor of Economics at Penn’s School of Arts and Sciences, and Professor of Finance and Professor of Statistics at Penn’s Wharton School. He is also a Faculty Research Associate at the National Bureau of Economic Research in Cambridge, Massachusetts, and author of the No Hesitations blog.

Contents

Diebold is an elected Fellow of the Econometric Society, the American Statistical Association, and the International Institute of Forecasters, and the recipient of Sloan, Guggenheim, and Humboldt fellowships. He has served on the editorial boards of Econometrica , Review of Economics and Statistics , and International Economic Review . He has held visiting professorships at Princeton University, University of Chicago, Johns Hopkins University, and New York University. He was President of the Society for Financial Econometrics (2011–2013) [2] and Chairman of the Federal Reserve System's inaugural Model Validation Council (2012–2013). [3]

Scientific contributions

In predictive econometric modeling Diebold is best known for the "Diebold–Mariano test" for assessing point forecast accuracy, [4] methods for assessing density forecast conditional calibration, [5] and for his text, Elements of Forecasting. [6]

In financial econometrics Diebold is best known for his contributions to volatility modeling, including the Diebold-Nerlove "latent-factor ARCH model" [7] and the Andersen-Bollerslev-Diebold extraction of "realized volatility" from high-frequency asset returns; [8] [9]

In macroeconometrics Diebold is best known for his work on the macro-finance interface [10] [11] and his work on real-time macroeconomic monitoring, particularly the Aruoba–Diebold–Scotti ("ADS") Business Conditions Index, now maintained by the Federal Reserve Bank of Philadelphia. [12] [13]

Additional noteworthy contributions include the Diebold–Li "dynamic Nelson-Siegel" yield-curve model and its extensions; [14] [15] [16] and the Diebold–Yilmaz framework for dynamic network connectedness measurement and visualization. [17]

Related Research Articles

<span class="mw-page-title-main">Robert F. Engle</span> American economist and Nobel laureate (born 1942)

Robert Fry Engle III is an American economist and statistician. He won the 2003 Nobel Memorial Prize in Economic Sciences, sharing the award with Clive Granger, "for methods of analyzing economic time series with time-varying volatility (ARCH)".

Econometric models involving data sampled at different frequencies are of general interest. Mixed-data sampling (MIDAS) is an econometric regression developed by Eric Ghysels with several co-authors. There is now a substantial literature on MIDAS regressions and their applications, including Ghysels, Santa-Clara and Valkanov (2006), Ghysels, Sinko and Valkanov, Andreou, Ghysels and Kourtellos (2010) and Andreou, Ghysels and Kourtellos (2013).

Financial econometrics is the application of statistical methods to financial market data. Financial econometrics is a branch of financial economics, in the field of economics. Areas of study include capital markets, financial institutions, corporate finance and corporate governance. Topics often revolve around asset valuation of individual stocks, bonds, derivatives, currencies and other financial instruments.

Christian Gouriéroux is an econometrician who holds a Doctor of Philosophy in mathematics from the University of Rouen. He has the Professor exceptional level title from France. Gouriéroux is now a professor at University of Toronto and CREST, Paris [Center for Research in Economics and Statistics].

Tim Peter Bollerslev is a Danish economist, currently the Juanita and Clifton Kreps Professor of Economics at Duke University. A fellow of the Econometric Society, Bollerslev is known for his ideas for measuring and forecasting financial market volatility and for the GARCH model.

<span class="mw-page-title-main">Volatility (finance)</span> Degree of variation of a trading price series over time

In finance, volatility is the degree of variation of a trading price series over time, usually measured by the standard deviation of logarithmic returns.

Marc Leon Nerlove is an American agricultural economist and econometrician and a distinguished university professor emeritus in agricultural and resource economics at the University of Maryland. He was awarded the John Bates Clark Medal from the American Economic Association (AEA) in 1969 and held appointments at eight different universities from 1958–2016. The Clark Medal is awarded to an economist under the age of 40 who “is judged to have made the most significant contribution to economic thought and knowledge”, and when the AEA appointed him as a distinguished fellow in 2012, they cited his development of widely used econometric methods across a range of subjects, including supply and demand, time series analysis, production functions, panel analysis, and family demography.

Stock market cycles are proposed patterns that proponents argue may exist in stock markets. Many such cycles have been proposed, such as tying stock market changes to political leadership, or fluctuations in commodity prices. Some stock market designs are universally recognized. However, many academics and professional investors are skeptical of any theory claiming to identify or predict stock market cycles precisely. Some sources argue identifying any such patterns as a "cycle" is a misnomer, because of their non-cyclical nature. Economists using efficient-market hypothesis say that asset prices reflect all available information meaning that it is impossible to systematically beat the market by taking advantage of such cycles.

In financial econometrics, the Markov-switching multifractal (MSM) is a model of asset returns developed by Laurent E. Calvet and Adlai J. Fisher that incorporates stochastic volatility components of heterogeneous durations. MSM captures the outliers, log-memory-like volatility persistence and power variation of financial returns. In currency and equity series, MSM compares favorably with standard volatility models such as GARCH(1,1) and FIGARCH both in- and out-of-sample. MSM is used by practitioners in the financial industry to forecast volatility, compute value-at-risk, and price derivatives.

Following the development of Keynesian economics, applied economics began developing forecasting models based on economic data including national income and product accounting data. In contrast with typical textbook models, these large-scale macroeconometric models used large amounts of data and based forecasts on past correlations instead of theoretical relations. These models estimated the relations between different macroeconomic variables using regression analysis on time series data. These models grew to include hundreds or thousands of equations describing the evolution of hundreds or thousands of prices and quantities over time, making computers essential for their solution. While the choice of which variables to include in each equation was partly guided by economic theory, variable inclusion was mostly determined on purely empirical grounds. Large-scale macroeconometric model consists of systems of dynamic equations of the economy with the estimation of parameters using time-series data on a quarterly to yearly basis.

Realized variance or realised variance is the sum of squared returns. For instance the RV can be the sum of squared daily returns for a particular month, which would yield a measure of price variation over this month. More commonly, the realized variance is computed as the sum of squared intraday returns for a particular day.

Nowcasting in economics is the prediction of the very recent past, the present, and the very near future state of an economic indicator. The term is a portmanteau of "now" and "forecasting" and originates in meteorology. Typical measures used to assess the state of an economy, such as gross domestic product (GDP) or inflation, are only determined after a delay and are subject to revision. In these cases, nowcasting such indicators can provide an estimate of the variables before the true data are known. Nowcasting models have been applied most notably in Central Banks, who use the estimates to monitor the state of the economy in real-time as a proxy for official measures.

Anil K. Bera is an Indian-American econometrician. He is Professor of Economics at University of Illinois at Urbana–Champaign's Department of Economics. He is most noted for his work with Carlos Jarque on the Jarque–Bera test.

Kenneth David West is the John D. MacArthur and Ragnar Frisch Professor of Economics in the Department of Economics at the University of Wisconsin. He is currently co-editor of the Journal of Money, Credit and Banking, and has previously served as co-editor of the American Economic Review. He has published widely in the fields of macroeconomics, finance, international economics and econometrics. Among his honors are the John M. Stauffer National Fellowship in Public Policy at the Hoover Institution, Alfred P. Sloan Research Fellowship, Fellow of the Econometric Society, and Abe Fellowship. He has been a research associate at the NBER since 1985.

Monika Piazzesi received her PhD in economics at Stanford University. She was a recipient of the Deutsche Studienstiftung ERP (1997–2000). She has been the Joan Kenney Professor of Economics at Stanford University since 2010. She is also a senior fellow at the Stanford Institute for Economic Policy Research. In 2005, when she was an assistant professor at the University of Chicago Business School, she received the Germán Bernácer Prize. She subsequently won the Elaine Bennett Research Prize. Her research focuses on asset pricing and time series econometrics, especially related to bond markets and the term structure of interest rates. She has published papers related to housing issues, asset prices and quantities, bond markets, interest rate and GDP. In 2023, she was elected to the National Academy of Sciences.

<span class="mw-page-title-main">Laurent-Emmanuel Calvet</span> French economist

Laurent-Emmanuel Calvet is a French economist and a professor of finance. He is Vice President Elect of the European Finance Association.

Barbara Rossi is an ICREA professor of economics at Universitat Pompeu Fabra, a Barcelona GSE Research Professor, a CREI affiliated professor and a CEPR Fellow. She is a founding fellow of the International Association of Applied Econometrics, a fellow of the Econometric Society and a director of the International Association of Applied Econometrics.

<span class="mw-page-title-main">Oded Lowengart</span>

Oded Lowengart is Professor of Marketing at the Ben-Gurion University of the Negev (BGU) in Israel, where he holds the Ernest Scheller Jr. Chair in Innovative Management and is Head of the Department of Business Administration. His two terms as Dean of the Guilford Glazer Faculty of Business and Management (2013–18) saw to opening the International MBA Program, expanded global programs, and increased Journal Citation Reports-ranked research publications.

Siddhartha Chib is an econometrician and statistician, the Harry C. Hartkopf Professor of Econometrics and Statistics at Washington University in St. Louis. His work is primarily in Bayesian statistics, econometrics, and Markov chain Monte Carlo methods.

The Aruoba-Diebold-Scotti Business Conditions Index is a coincident business cycle indicator used in macroeconomics in the United States. The index measures business activity, which may be correlated with periods of expansion and contraction in the economy. The primary and novel function of the ADS index stems from its use of high-frequency economic data and subsequent high-frequency updating, opposed to the traditionally highly-lagged and infrequently-published macroeconomic data such as GDP.

References

  1. "Francis Diebold Personal Website".
  2. "Past Presidents, Founding Council, and Founding Members". Society for Financial Econometrics.
  3. "FRB: Model Validation Council". Board of Governors of the Federal Reserve System. 2012-04-30. Archived from the original on 2012-09-17.
  4. Diebold, Francis X.; Mariano, Robert S. (2002-01-01). "Comparing Predictive Accuracy". Journal of Business & Economic Statistics. 20 (1): 134–144. CiteSeerX   10.1.1.352.9389 . doi:10.1198/073500102753410444. ISSN   0735-0015. S2CID   12090811.
  5. Diebold, Francis X.; Gunther, Todd A.; Tay, Anthony S. (1998). "Evaluating density forecasts, with Applications to Financial Risk Management" (PDF). International Economic Review. 39 (4): 863–883. doi:10.2307/2527342. JSTOR   2527342. S2CID   38907468.
  6. Diebold, Francis X. (2001). Elements of forecasting. South-Western. ISBN   9780324023930. OCLC   44493316.
  7. Diebold, Francis X.; Nerlove, Marc (1989-01-01). "The dynamics of exchange rate volatility: A multivariate latent factor ARCH model". Journal of Applied Econometrics. 4 (1): 1–21. doi:10.1002/jae.3950040102. ISSN   1099-1255.
  8. Andersen, Torben G.; Bollerslev, Tim; Diebold, Francis X.; Labys, Paul (2003-03-01). "Modeling and Forecasting Realized Volatility". Econometrica. 71 (2): 579–625. CiteSeerX   10.1.1.200.1388 . doi:10.1111/1468-0262.00418. ISSN   1468-0262. S2CID   10045723.
  9. Andersen, Torben G.; Bollerslev, Tim; Diebold, Francis X.; Labys, Paul (2001-03-01). "The Distribution of Realized Exchange Rate Volatility". Journal of the American Statistical Association. 96 (453): 42–55. CiteSeerX   10.1.1.199.9567 . doi:10.1198/016214501750332965. ISSN   0162-1459. S2CID   5756201.
  10. Diebold, Francis X.; Rudebusch, Glenn D.; Borag?an Aruoba, S. (2006-03-01). "The macroeconomy and the yield curve: a dynamic latent factor approach". Journal of Econometrics. 131 (1): 309–338. CiteSeerX   10.1.1.232.9123 . doi:10.1016/j.jeconom.2005.01.011.
  11. Andersen, Torben G; Bollerslev, Tim; Diebold, Francis X; Vega, Clara (2003). "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange". American Economic Review. 93 (1): 38–62. CiteSeerX   10.1.1.201.3408 . doi:10.1257/000282803321455151. ISSN   0002-8282.
  12. "Aruoba-Diebold-Scotti Business Conditions Index".
  13. Aruoba, S. Boragan; Diebold, Francis X.; Scotti, Chiara (2009-10-01). "Real-Time Measurement of Business Conditions". Journal of Business & Economic Statistics. 27 (4): 417–427. CiteSeerX   10.1.1.395.7519 . doi:10.1198/jbes.2009.07205. ISSN   0735-0015. S2CID   219594039.
  14. Christensen, Jens H. E.; Diebold, Francis X.; Rudebusch, Glenn D. (2011-09-01). "The affine arbitrage-free class of Nelson–Siegel term structure models". Journal of Econometrics. Annals Issue on Forecasting. 164 (1): 4–20. CiteSeerX   10.1.1.524.355 . doi:10.1016/j.jeconom.2011.02.011. S2CID   774960.
  15. Diebold, Francis X.; Li, Canlin (2006-02-01). "Forecasting the term structure of government bond yields". Journal of Econometrics. 130 (2): 337–364. CiteSeerX   10.1.1.195.536 . doi:10.1016/j.jeconom.2005.03.005.
  16. Francis X. Diebold; Glenn D. Rudebusch (2013). Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach. Princeton University Press. ISBN   978-0-691-14680-5.
  17. Diebold, Francis X.; Yilmaz, Kamil (2014-09-01). "On the network topology of variance decompositions: Measuring the connectedness of financial firms" (PDF). Journal of Econometrics. Causality, Prediction, and Specification Analysis: Recent Advances and Future Directions. 182 (1): 119–134. doi:10.1016/j.jeconom.2014.04.012. hdl:10419/108574.