Engle, R. F. (Robert F.)
Most widely held works about
R. F Engle
Most widely held works by
R. F Engle
Longrun economic relationships : readings in cointegration by C. W. J Granger (
Book
)
17
editions published
between
1991
and
2001
in
English and Undetermined
and held by
455
libraries
worldwide
Anticipating correlations : a new paradigm for risk management by R. F Engle (
Book
)
17
editions published
in
2009
in
English
and held by
344
libraries
worldwide
"In Anticipating Correlations, Nobel Prizewinning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. largecap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis  and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included."Jacket
Cointegration, causality, and forecasting : a festschrift in honour of Clive W.J. Granger
(
Book
)
10
editions published
in
1999
in
English
and held by
327
libraries
worldwide
"Clive W.J. Granger is a pioneer in econometrics, perhaps best known for his work on cointegration: this book is a collection of essays dedicated to him and his work. Central themes of Granger's work are reflected in the book with attention given to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, nonlinear and nonparametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work."Jacket
ARCH : selected readings by R. F Engle (
Book
)
17
editions published
between
1995
and
2004
in
English and Undetermined
and held by
324
libraries
worldwide
In the early 1980s, R.F. Engle pioneered the econometric technique of AutoRegressive Conditional Heteroskedasticity (ARCH), which has subsequently generated a very considerable literature. This collection brings together the leading papers which have shaped ARCH research from its inception to the latest developments. Papers present both theory and financial market analysis, and discuss the key issues in the use of ARCH models to study volatility and correlation:  what model to use  what time intervals to employ  how to model multivariate systems  how to apply the models to price and trade options  how to model volatility spillovers across markets and within the day For each of these issues, the selection of a number of papers by different authors allows a variety of viewpoints to emerge. Many applications to financial markets are included, and a new introduction by the editor connects the papers to trace the development of the field. the result is a timely, useful book which will bring graduate students, faculty, and practitioners up to date on this rapidly expanding field of research
Handbook of econometrics by James J Heckman (
Book
)
41
editions published
between
1983
and
2007
in
English
and held by
254
libraries
worldwide
Handbook in econometrics.  v.4
Volatility and time series econometrics : essays in honor of Robert F. Engle
(
Book
)
15
editions published
between
2009
and
2010
in
English
and held by
183
libraries
worldwide
This volume celebrates and develops the work of Nobel Laureate Robert Engle. It includes original contributions from some of the world's leading econometricians that further Engle's work in time series economics
The econometrics of ultrahigh frequency data by R. F Engle (
Book
)
15
editions published
in
1996
in
English
and held by
67
libraries
worldwide
Abstract: Ultrahigh frequency data are complete transactions data which inherently arrive at random times. Marked point processes provide a theoretical framework for analysis of such data sets. The ACD model developed by Engle and Russell (1995) is then applied to IBM transactions data to develop semiparametric hazard estimates and measures of instantaneous conditional variances. The variances are negatively influenced by surprisingly long durations as suggested by some of the market microstructure literature
Option hedging using empirical pricing kernels by Joshua Rosenberg (
Book
)
14
editions published
in
1997
in
English
and held by
67
libraries
worldwide
Abstract: This paper develops a method for option hedging which is consistent with timevarying preferences and probabilities. The preferences are expressed in the form of an empirical pricing kernel (EPK), which measures the state price per unit probability, while probabilities are derived from an estimated stochastic volatility model of the form GARCH components with leverage. State prices are estimated using the flexible riskneutral density method of Rosenberg (1995) and a daily crosssection of option premia. Timevarying preferences over states are linked to a dynamic model of the underlying price to obtain a oneday ahead forecast of derivative price distributions and minimum variance hedge ratios. Empirical results suggest that risk aversion over S & P500 return states is substantially higher than risk aversion implied by BlackScholes state prices and probabilities using long run estimates of S & P500 return moments. It is also found that the daily level of risk aversion is strongly positively autocorrelated, negatively correlated with S & P500 price changes, and positively correlated with the spread between implied and objective volatilities. Hedging results reveal that typical hedging techniques for outofthemoney S & P500 index options, such as BlackScholes or historical minimum variance hedging, are inferior to the EPK hedging method. Thus, timevarying preferences and probabilities appear to be an important factor in the daytoday pricing of S & P500 options
Measuring, forecasting, and explaining time varying liquidity in the stock market by R. F Engle (
Book
)
13
editions published
in
1997
in
English
and held by
66
libraries
worldwide
The paper proposes a new measure, VNET, of market liquidity which directly measures the depth of the market. The measure is constructed from the excess volume of buys or sells during a market event defined by a price movement. As this measure varies over time, it can be forecast and explained. Using TORQ data, it is found that market depth varies positively but less than proportionally with past volume and negatively with the number of transactions. Both findings suggest that over time high volumes are associated with an influx of informed traders and reduce market liquidity. High expected volatility as measured by the ACD model of Engle and Russell (1995) and wide spreads both reduce expected depth. If the asymmetric trades are transacted in shorter than expected times, the costs will be greater giving an estimate of the value of patience
Hedging options in a GARCH environment : testing the term structure of stochastic volatility models by R. F Engle (
Book
)
15
editions published
in
1994
in
English and Undetermined
and held by
64
libraries
worldwide
This paper develops a methodology for testing the term structure of volatility forecasts derived from stochastic volatility models, and implements it to analyze models of S & P 500 index volatility. Volatility models are compared by their ability to hedge options positions sensitive to the term structure of volatility. Overall, the most effective hedge is a BlackScholes (BS) deltagamma hedge, while the BS deltavega hedge is the least effective. The most successful volatility hedge is GARCH components deltagamma, suggesting that the GARCH components estimate of the term structure of volatility is most accurate. The success of the BS deltagamma hedge may be due to mispricing in the options market over the sample period
Forecasting transaction rates : the autoregressive conditional duration model by R. F Engle (
Book
)
15
editions published
between
1994
and
1995
in
English and Undetermined
and held by
63
libraries
worldwide
This paper will propose a new statistical model for the analysis of data that does not arrive in equal time intervals such as financial transactions data, telephone calls, or sales data on commodities that are tracked electronically. In contrast to fixed interval analysis, the model treats the time between observation arrivals as a stochastic time varying process and therefore is in the spirit of the models of time deformation initially proposed by Tauchen and Pitts (1983), Clark (1973) and more recently discussed by Stock (1988), Lamoureux and Lastrapes (1992), Muller et al. (1990) and Ghysels and Jasiak (1994) but does not require auxiliary data or assumptions on the causes of time flow. Strong evidence is provided for duration clustering beyond a deterministic component for the financial transactions data analyzed. We will show that a very simple version of the model can successfully account for the significant autocorrelations in the observed durations between trades of IBM stock on the consolidated market. A simple transformation of the duration data allows us to include volume in the model
GARCH gamma by R. F Engle (
Book
)
11
editions published
in
1995
in
English
and held by
60
libraries
worldwide
Abstract: This paper addresses the issue of hedging option positions when the underlying asset exhibits stochastic volatility. By parameterizing the volatility process as GARCH, and utilizing risk neutral valuation, we estimate hedging parameters (delta and gamma) using MonteCarlo simulation. We estimate hedging parameters for options on the Standard and Poor's 500 index, a bond futures index, a weighted foreign exchange rate index, and an oil futures index. We find that BlackScholes and GARCH deltas are similar for all the options considered, while GARCH gammas are significantly higher than BS gammas for all options. For near the money options, GARCH gamma hedge ratios are higher than BS hedge ratios when hedging a long term option with a short term option. Away from the money, GARCH gamma hedge ratios are lower than BS
Modeling the impacts of market activity on bidask spreads in the option market by Cho YoungHye (
Book
)
14
editions published
between
1998
and
1999
in
English
and held by
59
libraries
worldwide
Abstract: In this paper, we examine the impact of market activity on the percentage bidask spreads of S & P 100 index options using transactions data. We propose a new market microstructure theory which we call derivative hedge theory, in which option market percentage spreads will be inversely related to the option market maker's ability to hedge his positions in the underlying market, as measured by the liquidity of the latter market. In a perfect hedge world, spreads arise from the illiquidity of the underlying market, rather than from inventory risk or informed trading in the option market itself. We find option market volume is not a significant determinant of option market spreads. This finding leads us to question the use of volume as a measure of liquidity and supports the derivative hedge theory. Option market spreads are positively related to spreads in the underlying market, again supporting our theory. However, option market duration does affect option market spreads, with very slow and very fast option markets both leading to bigger spreads. The fast market result would be predicted by the asymmetric information theory. Inventory model predicts big spreads in slow markets. Neither result would be observed if the underlying securities market provided a perfect hedge. We interpret these mixed results as meaning that the option market maker is able to only imperfectly hedge his positions in the underlying securities market. Our result of insignificant options volume casts doubt on the price discovery argument between stock and option market (Easley, O'Hara, and Srinivas (1998)). Asymmetric information costs in either market are naturally passed to the other market maker's hedgeing and therefore it is unimportant where the informed traders trade
Timevarying betas and asymmetric effects of news : empirical analysis of blue chip stocks by YoungHye Cho (
Book
)
10
editions published
in
1999
in
English
and held by
54
libraries
worldwide
Theoretical and empirical properties of Dynamic Conditional Correlation Multivariate GARCH by R. F Engle (
Book
)
14
editions published
in
2001
in
English
and held by
52
libraries
worldwide
In this paper, we develop the theoretical and empirical properties of a new class of multivariate GARCH models capable of estimating large timevarying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need be modified. We use the model to estimate the conditional covariance of up to 100 assets using S&P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator
Indexoption pricing with stochastic volatility and the value of accurate variance forecasts by R. F Engle (
Book
)
13
editions published
in
1993
in
English
and held by
51
libraries
worldwide
In pricing primarymarket options and in making secondary markets, financial intermediaries depend on the quality of forecasts of the variance of the underlying assets. Hence, the gain from improved pricing of options would be a measure of the value of a forecast of underlying asset returns. NYSE index returns over the period of 19681991 are used to suggest that pricing index options of up to 90days maturity would be more accurate when: (1) using ARCH specifications in place of a moving average of squared returns; (2) using Hull and White's (1987) adjustment for stochastic variance in Black and Scholes's (1973) formula; (3) accounting explicitly for weekends and the slowdown of variance whenever the market is closed
CAViaR : conditional value at risk by quantile regression by R. F Engle (
Book
)
11
editions published
in
1999
in
English
and held by
50
libraries
worldwide
Value at Risk has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes. Despite its conceptual simplicity, its measurement is a very challenging statistical problem and none of the methodologies developed so far give satisfactory solutions. Interpreting Value at Risk as a quantile of future portfolio values conditional on current information, we propose a new approach to quantile estimation which does not require any of the extreme assumptions invoked by existing methodologies (such as normality or i.i.d. returns). The Conditional Value at Risk or CAViaR model moves the focus of attention from the distribution of returns directly to the behavior of the quantile. We postulate a variety of dynamic processes for updating the quantile and use regression quantile estimation to determine the parameters of the updating process. Tests of model adequacy utilize the criterion that each period the probability of exceeding the VaR must be independent of all the past information. We use a differential evolutionary genetic algorithm to optimize an objective function which is nondifferentiable and hence cannot be optimized using traditional algorithms. Applications to simulated and real data provide empirical support to our methodology and illustrate the ability of these algorithms to adapt to new risk environments
Empirical asset pricing : the cross section of stock returns by Turan G Bali (
Book
)
9
editions published
between
2013
and
2016
in
English and German
and held by
44
libraries
worldwide
"Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional." Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences "The empirical analysis of the crosssection of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray's clear and careful guide to these issues provides a firm foundation for future discoveries." John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University "Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing." Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College "This exciting new book presents a thorough review of what we know about the crosssection of stock returns. Given its comprehensive nature, systematic approach, and easytounderstand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing." Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with indepth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: Discussions on the driving forces behind the patterns observed in the stock market An extensive set of results that serve as a reference for practitioners and academics alike Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduatelevel courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and cofounding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize
A multiple indicators model for volatility using intradaily data by R. F Engle (
Book
)
11
editions published
in
2003
in
English
and held by
42
libraries
worldwide
Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases, the quality of forecasts should improve. Yet, there is no consensus about a true' or best' measure of volatility. In this paper we propose to jointly consider absolute daily returns, daily highlow range and daily realized volatility to develop a forecasting model based on their conditional dynamics. As all are nonnegative series, we develop a multiplicative error model that is consistent and asymptotically normal under a wide range of specifications for the error density function. The estimation results show significant interactions between the indicators. We also show that onemonthahead forecasts match well (both in and out of sample) the marketbased volatility measure provided by an average of implied volatilities of index options as measured by VIX
Technical capabilities necessary for regulation of systemic financial risk summary of a workshop by Workshop on Technical Capabilities Necessary for Regulation of Systemic Financial Risk (
Book
)
6
editions published
in
2010
in
English
and held by
5
libraries
worldwide
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Alternative Names
Engle, R. F. Engle, R. F. 1942 Engle, Rob 1942 Engle, Robert. Engle, Robert 1942 Engle, Robert F. Engle, Robert F. III Engle, Robert Fry III Robert Engle Amerikaans econoom Robert Engle amerykański ekonomista, ekonometryk, noblista Robert Engle economista e statistico statunitense Robert F. Engle American economist Robert F. Engle amerikansk ekonom Robert F. Engle amerikansk økonom Robert F. Engle économiste américain Robert F. Engle USamerikanischer Wirtschaftswissenschaftler Robert Fry Engle Robert İnql Ρόμπερτ Ενγκλ Роберт Енгл американски економист Роберт Фрай Енґл Роберт Энгл Роберт Інгл Робърт Енгъл Робэрт Інгл Ռոբերտ Ինգլ רוברט אנגל رابرت انگل اقتصاددان آمریکایی رابرٹ ایف۔اینگل رابرٹ عنگل روبرت آنجل रॉबर्ट एफ एंगल রবার্ট এঙ্গেল რობერტ ენგლი ロバート・エングル 罗伯特·F·恩格尔
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