Robert F. Engle III | |
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Born | Syracuse, New York, U.S. | November 10, 1942

Institution | New York University, since 2000 University of California, San Diego, (1975–2003) Massachusetts Institute of Technology, (1969–1975) |

Field | Econometrics |

Alma mater | Cornell University, (Ph.D. 1969) Williams College, (B.S. 1964) |

Doctoral advisor | Ta-Chung Liu ^{ [1] } |

Doctoral students | Mark Watson Tim Bollerslev |

Influences | David Hendry |

Contributions | ARCH Cointegration |

Awards | Nobel Memorial Prize in Economic Sciences (2003) |

Information at IDEAS / RePEc |

**Robert Fry Engle III** (born November 10, 1942) is an American statistician and the winner of 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)".

Engle was born in Syracuse, New York into Quaker family^{ [2] } and went on to graduate from Williams College with a B.S. in physics. He earned an M.S. in physics and a Ph.D. in economics, both from Cornell University in 1966 and 1969 respectively.^{ [3] } After completing his Ph.D., Engle became Professor of Economics at the Massachusetts Institute of Technology from 1969 to 1977.^{ [4] } He joined the faculty of the University of California, San Diego (UCSD) in 1975, wherefrom he retired in 2003. He now holds positions of Professor Emeritus and Research Professor at UCSD. He currently teaches at New York University, Stern School of Business where he is the Michael Armellino professor in Management of Financial Services. At New York University, Engle teaches for the Master of Science in Risk Management Program for Executives,^{ [5] } which is offered in partnership with the Amsterdam Institute of Finance.^{ [6] }

Engle's most important contribution was his path-breaking discovery of a method for analyzing unpredictable movements in financial market prices and interest rates. Accurate characterization and prediction of these volatile movements are essential for quantifying and effectively managing risk. For example, risk measurement plays a key role in pricing options and financial derivatives. Previous researchers had either assumed constant volatility or had used simple devices to approximate it. Engle developed new statistical models of volatility that captured the tendency of stock prices and other financial variables to move between high volatility and low volatility periods ("Autoregressive Conditional Heteroskedasticity: ARCH"). These statistical models have become essential tools of modern arbitrage pricing theory and practice.

Engle was the central founder and director of NYU-Stern's Volatility Institute which publishes weekly date on systemic risk across countries on its V-LAB site.^{ [7] }

More recently, Engle (and Eric Ghysels) co-founded the Society for Financial Econometrics (SoFiE).

- Paternal Grandfather –Robert Fry Engle, Sr. (b. 1879 d. 1946)
- Father –Robert Fry Engle, Jr. (b. 1910 d. 1981, DuPont chemist)
- Mother –Mary Starr Engle ("Murry", French teacher, m. 1939)
- Sister –Patricia Lee Engle ("Patty", twin, UNICEF official)
- Sister – Sally Engle Merry (anthropologist, twin)
- Wife –Marianne Eger Engle (psychologist, m. 10-Aug-1969, two children)
- Daughter –Lindsey Engle Richland (psychologist)
- Son –Jordan Engle (actor, b. May-1980)
- Mother-in-law – Edith Eger (psychologist, b. 29-Sept-1927)

- Engle, Robert F. (1982). "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation".
*Econometrica*.**50**(4): 987–1008. doi:10.2307/1912773. JSTOR 1912773. - Engle, Robert F.; Hendry, David F.; Richard, Jean-Francois (1983). (with David F. Hendry and Jean-Francois Richard). "Exogeneity".
*Econometrica*.**51**(2): 277–304. doi:10.2307/1911990. JSTOR 1911990. - . (with C. Granger, J. Rice and A. Weiss). "Semi-parametric Estimates of the Relation between Weather and Electricity Demand".
*J. Amer. Statist. Assoc.***81**(394): 310–320. 1986. doi:10.1080/01621459.1986.10478274.CS1 maint: others (link) - Engle, Robert F.; Granger, C. W. J. (1987). (with Clive Granger). "Co-Integration and Error Correction: Representation, Estimation, and Testing" (PDF).
*Econometrica*.**55**(2): 251–276. doi:10.2307/1913236. JSTOR 1913236. - Engle, Robert F.; Lilien, David M.; Robins, Russell P. (1987). (with David Lilien and Russell Robins). "Estimation of Time Varying Risk Premia in the Term Structure: the ARCH-M Model".
*Econometrica*.**55**(2): 391–407. doi:10.2307/1913242. JSTOR 1913242. - . (with V. Ng, and M. Rothschild). "Asset Pricing with a Factor ARCH Covariance Structure: Empirical Estimates for Treasury Bills" (PDF).
*Journal of Econometrics*.**45**(1–2): 213–237. 1990. doi:10.1016/0304-4076(90)90099-F. hdl: 2027.42/28496 . S2CID 55667632.CS1 maint: others (link) - Engle, Robert F.; Russell, Jeffrey R. (1998). (with J.R. Russell). "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data".
*Econometrica*.**66**(5): 1127–1162. doi:10.2307/2999632. JSTOR 2999632. - "Dynamic Conditional Correlation – A Simple Class of Multivariate GARCH Models".
*Journal of Business and Economic Statistics*.**20**(3): 339–350. 2002. doi:10.1198/073500102288618487. S2CID 14784060. - Easley, D.; Engle, R. F.; O'Hara, M.; Wu, L. (2008). (with Maureen O'Hara, David Easley and L. Wu). "Time-Varying Arrival Rates of Informed and Uninformed Traders".
*Journal of Financial Econometrics*.**6**(2): 171–207. doi: 10.1093/jjfinec/nbn003 .

* Econometrica* is a peer-reviewed academic journal of economics, publishing articles in many areas of economics, especially econometrics. It is published by Wiley-Blackwell on behalf of the Econometric Society. The current editor-in-chief is Guido Imbens.

**Sir Clive William John Granger** was a British econometrician known for his contributions to nonlinear time series analysis. He taught in Britain, at the University of Nottingham and in the United States, at the University of California, San Diego. Granger was awarded the Nobel Memorial Prize in Economic Sciences in 2003 in recognition of the contributions that he and his co-winner, Robert F. Engle, had made to the analysis of time series data. This work fundamentally changed the way in which economists analyse financial and macroeconomic data.

In econometrics, the **autoregressive conditional heteroscedasticity** (**ARCH**) model is a statistical model for time series data that describes the variance of the current error term or innovation as a function of the actual sizes of the previous time periods' error terms; often the variance is related to the squares of the previous innovations. The ARCH model is appropriate when the error variance in a time series follows an autoregressive (AR) model; if an autoregressive moving average (ARMA) model is assumed for the error variance, the model is a **generalized autoregressive conditional heteroskedasticity** (**GARCH**) model.

In statistics, a vector of random variables is **heteroscedastic** if the variability of the random disturbance is different across elements of the vector. Here, variability could be quantified by the variance or any other measure of statistical dispersion. Thus heteroscedasticity is the absence of homoscedasticity. A typical example is the set of observations of income in different cities.

In finance, **volatility clustering** refers to the observation, first noted by Mandelbrot (1963), that "large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes." A quantitative manifestation of this fact is that, while returns themselves are uncorrelated, absolute returns or their squares display a positive, significant and slowly decaying autocorrelation function: corr(|r_{t}|, |r_{t+τ} |) > 0 for τ ranging from a few minutes to several weeks. This empirical property has been documented in the 90's by Granger and Ding (1993) and Ding and Granger (1996) among others; see also. Some studies point further to long-range dependence in volatility time series, see Ding, Granger and Engle (1993) and Barndorff-Nielsen and Shephard.

**Thomas John Sargent** is an American economist and the W.R. Berkley Professor of Economics and Business at New York University. He specializes in the fields of macroeconomics, monetary economics, and time series econometrics. As of 2020, he ranks as the 29th most cited economist in the world. He was awarded the Nobel Memorial Prize in Economics in 2011 together with Christopher A. Sims for their "empirical research on cause and effect in the macroeconomy".

**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.

**Cointegration** is a statistical property of a collection (*X*_{1}, *X*_{2}, ..., *X*_{k}) of time series variables. First, all of the series must be integrated of order *d*. Next, if a linear combination of this collection is integrated of order less than d, then the collection is said to be co-integrated. Formally, if (*X*,*Y*,*Z*) are each integrated of order *d*, and there exist coefficients *a*,*b*,*c* such that *aX* + *bY* + *cZ* is integrated of order less than d, then *X*, *Y*, and *Z* are cointegrated. Cointegration has become an important property in contemporary time series analysis. Time series often have trends—either deterministic or stochastic. In an influential paper, Charles Nelson and Charles Plosser (1982) provided statistical evidence that many US macroeconomic time series have stochastic trends.

**Sanford** "**Sandy**" **Jay Grossman** is an American economist and hedge fund manager specializing in quantitative finance. Grossman’s research has spanned the analysis of information in securities markets, corporate structure, property rights, and optimal dynamic risk management. He has published widely in leading economic and business journals, including *American Economic Review*, *Journal of Econometrics*, *Econometrica*, and *Journal of Finance*. His research in macroeconomics, finance, and risk management has earned numerous awards. Grossman is currently Chairman and CEO of QFS Asset Management, an affiliate of which he founded in 1988. QFS Asset Management shut down its sole remaining hedge fund in January 2014.

**Takeshi Amemiya** is an economist specializing in econometrics and the economy of ancient Greece.

**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 spends six months from every year teaching at the University of Toronto, and the other half of his year teaching at the Center for Research in Economics and Statistics (CREST) in France, at the University of Paris and the "Paris Graduate School of Economics, Statistics and Finance".

**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. He is editor of the *Journal of Applied Econometrics.*

**Sir David Forbes Hendry**, FBA CStat is a British econometrician, currently a professor of economics and from 2001 to 2007 was head of the Economics Department at the University of Oxford. He is also a professorial fellow at Nuffield College, Oxford.

In financial econometrics, an **autoregressive conditional duration** model considers irregularly spaced and autocorrelated intertrade durations. ACD is analogous to GARCH. Indeed, in a continuous double auction waiting times between two consecutive trades vary at random.

**Anil K. Bera** is an Indian 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.

The **LSE approach to econometrics**, named for the London School of Economics, involves viewing econometric models as *reductions* from some unknown data generation process (DGP). A complex DGP is typically modelled as the starting point and this complexity allows information in the data from the real world but absent in the theory to be drawn upon. The complexity is then reduced by the econometrician by a series of restrictions which are tested.

**William H. Greene** is an American economist. He is the Robert Stansky Professor of Economics and Statistics at Stern School of Business at New York University.

**Stefan Mittnik** is a German economist, currently holds the Chair of Financial Econometrics at the Ludwig Maximilian University of Munich. He is a fellow of the Center for Financial Studies and known for his work on financial market and financial risk modeling as well as macroeconometrics. He is also a co-founder of the German-British robo-advisor Scalable Capital.

**Francis X. Diebold** 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. 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.

**High frequency data** refers to time-series data collected at an extremely fine scale. As a result of advanced computational power in recent decades, high frequency data can be accurately collected at an efficient rate for analysis. Largely used in financial analysis and in high frequency trading, high frequency data provides intraday observations that can be used to understand market behaviors, dynamics, and micro-structures.

- ↑ Engle, Robert F.; Liu, Ta-Chung (1972), "Effects of Aggregation Over Time on Dynamic Characteristics of An Econometric Model", in Hickman, Bert G. (ed.),
*Econometric Models of Cyclical Behavior*(PDF), Conference on Research in Income and Wealth. Studies in income and wealth,**2**, NBER, p. 673. - ↑ Robert F. Engle III on Nobelprize.org , accessed 2 May 2020
- ↑ Homepage at New York University
- ↑ MIT Nobel laureates
- ↑ "NYU Stern School of Business" . Retrieved 10 March 2017.
- ↑ "Amsterdam Institute of Finance - Financial Training" . Retrieved 10 March 2017.
- ↑ The Volatility Institute at NYU-Stern School of Business site

- V-Lab: real time financial volatility and correlation measurements, modeling and forecasting
- The Society for Financial Econometrics (SoFiE)
- "Robert F. Engle (1942– )".
*The Concise Encyclopedia of Economics*. Library of Economics and Liberty (2nd ed.). Liberty Fund. 2008. - Robert F. Engle at the Mathematics Genealogy Project
- Appearances on C-SPAN

Awards | ||
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Preceded by Daniel Kahneman Vernon L. Smith | Laureate of the Nobel Memorial Prize in Economics 2003 Served alongside: Clive W.J. Granger | Succeeded by Finn E. Kydland Edward C. Prescott |

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