ROBERT F. ENGLE New York University • Volatility and Risk
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Financial Econometrics Lecture Notes
Financial Econometrics Lecture Notes Professor Doron Avramov The Hebrew University of Jerusalem & Chinese University of Hong Kong Introduction: Why do we need a course in Financial Econometrics? 2 Professor Doron Avramov, Financial Econometrics Syllabus: Motivation The past few decades have been characterized by an extraordinary growth in the use of quantitative methods in the analysis of various asset classes; be it equities, fixed income securities, commodities, and derivatives. In addition, financial economists have routinely been using advanced mathematical, statistical, and econometric techniques in a host of applications including investment decisions, risk management, volatility modeling, interest rate modeling, and the list goes on. 3 Professor Doron Avramov, Financial Econometrics Syllabus: Objectives This course attempts to provide a fairly deep understanding of such techniques. The purpose is twofold, to provide research tools in financial economics and comprehend investment designs employed by practitioners. The course is intended for advanced master and PhD level students in finance and economics. 4 Professor Doron Avramov, Financial Econometrics Syllabus: Prerequisite I will assume prior exposure to matrix algebra, distribution theory, Ordinary Least Squares, Maximum Likelihood Estimation, Method of Moments, and the Delta Method. I will also assume you have some skills in computer programing beyond Excel. MATLAB and R are the most recommended for this course. OCTAVE could be used as well, as it is a free software, and is practically identical to MATLAB when considering the scope of the course. If you desire to use STATA, SAS, or other comparable tools, please consult with the TA. 5 Professor Doron Avramov, Financial Econometrics Syllabus: Grade Components Assignments (36%): there will be two problem sets during the term. -
Trepang Fisherman
Georges BaUdoux’s jean m’baraÏ THE trepang fIsherman Translated and with a Critical Introduction by Karin Speedy Georges BaUdoux’s jean m’baraÏ THE trepang fIsherman Translated and with a Critical Introduction by Karin Speedy PUBLICATION INFORMATION UTS ePRESS University of Technology Sydney Sydney NSW 2007 AUSTRALIA epress.lib.uts.edu.au Copyright Information This book is copyright. The work is licensed under a Creative Commons Attribution-Non Commercial-Non Derivatives License CC BY-NC-ND http://creativecommons.org/licenses/by-nc-nd/4.0/ First Published 2015 © 2015 in the text, Karin Speedy © 2015 in the cover artwork, book artwork, design and layout, Emily Gregory and UTS ePRESS Publication Details DOI citation: http://dx.doi.org/10.5130/978-0-9945039-1-6 Creator: Baudoux, Georges, 1870-1949, author. Other Creators/Contributors: Speedy, Karin, translator, writer of introduction. Title: Georges Baudoux’s Jean M’Barai^ the trepang fisherman / Translated and with a critical introduction by Karin Speedy. ISBN: 9780994503916 (ebook) Subjects: New Caledonian fiction (French) – Translations into English. New Caledonian fiction (French) – Translations into English—History and criticism. Dewey Number: 843.8 UTS ePRESS Manager: Julie-Anne Marshall Book Editor: Matthew Noble Design: Emily Gregory Enquiries: [email protected] For enquiries about third party copyright material reproduced in this work, please contact UTS ePRESS. OPEN ACCESS UTS ePRESS publishes peer reviewed books, journals and conference proceedings and is the leading publisher of peer reviewed open access journals in Australasia. All UTS ePRESS online content is free to access and read. CULTURALLY SENSITIVE INFORMATION Aboriginal and Torres Strait Islander people, and people of the Melanesian, Micronesian and Polynesian islands, should be aware that this book contains images of people who are now deceased. -
Advanced Financial Econometrics
MFE 2013-14 Trinity Term | Advanced Financial Econometrics Advanced Financial Econometrics Kevin Sheppard Department of Economics Oxford-Man Institute of Quantitative Finance Course Site: http://www.kevinsheppard.com/Advanced_Econometrics Weblearn Site: https://weblearn.ox.ac.uk/portal/site/socsci/sbs/mfe2012_2013/ttafe 1 Aims, objectives and intended learning outcomes 1.1 Basic aims This course aims to extend the core tools of Financial Econometrics I & II to some advanced forecasting problems. The first component covers techniques for working with many forecasting models – often referred to as data snoop- ing. The second component covers techniques for handling many predictors – including the case where the number of predictors is much larger than the number of data points available. 1.2 Specific objectives Part I (Week 1 – 4) Revisiting the bootstrap and extensions appropriate for time-series data • Technical trading rules and large number of forecasts • Formalized data-snooping robust inference • False-discovery rates • Detecting sets of models that are statistically indistinguishable • Part I (Week 5 – 8) Dynamic Factor Models and Principal Component Analysis • The Kalman Filter and Expectations-Maximization Algorithm • Partial Least Squares and the 3-pass Regression Filter • Regularized Reduced Rank Regression • 1.3 Intended learning outcomes Following class attendance, successful completion of assigned readings, assignments, both theoretical and empiri- cal, and recommended private study, students should be able to Detect superior performance using methods that are robust to data snooping • Produce and evaluate forecasts in for macro-financial time series in data-rich environments • 1 2 Teaching resources 2.1 Lecturing Lectures are provided by Kevin Sheppard. Kevin Sheppard is an Associate Professor and a fellow at Keble College. -
An Introduction to Financial Econometrics
An introduction to financial econometrics Jianqing Fan Department of Operation Research and Financial Engineering Princeton University Princeton, NJ 08544 November 14, 2004 What is the financial econometrics? This simple question does not have a simple answer. The boundary of such an interdisciplinary area is always moot and any attempt to give a formal definition is unlikely to be successful. Broadly speaking, financial econometrics is to study quantitative problems arising from finance. It uses sta- tistical techniques and economic theory to address a variety of problems from finance. These include building financial models, estimation and inferences of financial models, volatility estimation, risk management, testing financial economics theory, capital asset pricing, derivative pricing, portfolio allocation, risk-adjusted returns, simulating financial systems, hedging strategies, among others. Technological invention and trade globalization have brought us into a new era of financial markets. Over the last three decades, enormous number of new financial products have been created to meet customers’ demands. For example, to reduce the impact of the fluctuations of currency exchange rates on a firm’s finance, which makes its profit more predictable and competitive, a multinational corporation may decide to buy the options on the future of foreign exchanges; to reduce the risk of price fluctuations of a commodity (e.g. lumbers, corns, soybeans), a farmer may enter into the future contracts of the commodity; to reduce the risk of weather exposures, amuse parks (too hot or too cold reduces the number of visitors) and energy companies may decide to purchase the financial derivatives based on the temperature. An important milestone is that in the year 1973, the world’s first options exchange opened in Chicago. -
1 June 2021 CURRICULUM VITAE Eric Ghysels PRESENT POSITION
June 2021 CURRICULUM VITAE Eric Ghysels PRESENT POSITION: Edward M. Bernstein Distinguished Professor Department of Economics Professor of Finance Kenan-Flagler Business School (joint appointment) University of North Carolina, Chapel Hill Faculty Research Director, Rethinc.Labs, Kenan Institute for Private Enterprise, UNC Chapel Hill Adjunct Professor Department of Electrical and Computer Engineering North Carolina State University CONTACT INFO: Phone: 919 966 5325 (office) 919 619 2539 (cell) Email: [email protected] Link to homepage Link to Google Citations Link to SSRN page LinkedIn page EDUCATION 1979 B.A. Economics, Supra Cum Laude, University of Brussels 1982 M.A. Economics, Northwestern University 1984 Ph.D. Managerial Economics and Decision Science, Kellogg Graduate School of Management, Northwestern University Thesis Committee: V.V. Chari, T. Doan, R. Hodrick, P.E. Rossi 2019 Doctorate in Business Administration (Doctor Honoris Causa), HEC Liège 1 PUBLICATIONS 161. “In-sample Asymptotics and Across-sample Efficiency Gains for High Frequency Data Statistics” with Per Mykland and Eric Renault, Econometric Theory (forthcoming) 160. “Machine learning time series regressions with an application to nowcasting”, (with A. Babii and J. Striaukas), Journal of Business and Economic Statistics, (2021) https://doi.org/10.1080/07350015.2021.1899933 159. “Predicting the VIX and the Volatility Risk Premium: The Role of Credit Risk”, (with E. Andreou), Journal of Econometrics, 220, 366-398 (2021) https://doi.org/10.1016/j.jeconom.2020.04.006 158. “Price Discovery in High Resolution and the Analysis of Mixed Frequency Data - Comment on Price Discovery in High Resolution by Joel Hasbrouck”, Journal of Financial Econometrics (2021) https://doi.org/10.1093/jjfinec/nbz007 157. -
Significance Redux
The Journal of Socio-Economics 33 (2004) 665–675 Significance redux Stephen T. Ziliaka,∗, Deirdre N. McCloskeyb,1 a School of Policy Studies, College of Arts and Sciences, Roosevelt University, Chicago, 430 S. Michigan Avenue, Chicago, IL 60605, USA b College of Arts and Science (m/c 198), University of Illinois at Chicago, 601 South Morgan, Chicago, IL 60607-7104, USA Abstract Leading theorists and econometricians agree with our two main points: first, that economic sig- nificance usually has nothing to do with statistical significance and, second, that a supermajority of economists do not explore economic significance in their research. The agreement from Arrow to Zellner on the two main points should by itself change research practice. This paper replies to our critics, showing again that economic significance is what science and citizens want and need. © 2004 Elsevier Inc. All rights reserved. JEL CODES: C12; C10; B23; A20 Keywords: Hypothesis testing; Statistical significance; Economic significance Science depends on entrepreneurship, and we thank Morris Altman for his. The sympo- sium he has sparked can be important for the future of economics, in showing that the best economists and econometricians seek, after all, economic significance. Kenneth Arrow as early as 1959 dismissed mechanical tests of statistical significance in his search for eco- nomic significance. It took courage: Arrow’s teacher, the amazing Harold Hotelling, had been one of Fisher’s sharpest disciples. Now Arrow is joined by Clive Granger, Graham ∗ Corresponding author. E-mail addresses: [email protected] (S.T. Ziliak), [email protected] (D.N. McCloskey). 1 For comments early and late we thank Ted Anderson, Danny Boston, Robert Chirinko, Ronald Coase, Stephen Cullenberg, Marc Gaudry, John Harvey, David Hendry, Stefan Hersh, Robert Higgs, Jack Hirshleifer, Daniel Klein, June Lapidus, David Ruccio, Jeff Simonoff, Gary Solon, John Smutniak, Diana Strassman, Andrew Trigg, and Jim Ziliak. -
Stolper-Samuelson Time Series: Long Term US Wage Adjustment
Stolper-Samuelson Time Series: Long Term US Wage Adjustment Henry Thompson Auburn University Review of Development Economics, 2011 Factor prices adjust to product prices in the Stolper-Samuelson theorem of the factor proportions model. The present paper estimates adjustment in the average US wage to changes in prices of manufactures and services with yearly data from 1949 to 2006. Difference equation analysis is based directly on the comparative static factor proportions model. Factors of production are fixed capital assets and the labor force. Results have implications for theory and policy. Thanks for comments and suggestions go to Farhad Rassekh, Charles Sawyer, Roy Ruffin, Ron Jones, Manoj Atolia, Santanu Chaterjee, and Svetlana Demidova. Contact: Henry Thompson, Economics, Auburn University, AL 36849, 334-844-2910, fax 5999, [email protected] 1 Stolper-Samuelson Time Series: Long Term US Wage Adjustment The Stolper-Samuelson (SS, 1941) theorem concerns the effects of changing product prices on factor prices along the contract curve in the general equilibrium model of production with two factors and two products. The result is fundamental to neoclassical economics as relative product prices evolve with economic growth. The theoretical literature finding exception to the SS theorem is vast as summarized by Thompson (2003) and expanded by Beladi and Batra (2004). Davis and Mishra (2007) believe the theorem is dead due unrealistic assumptions. The scientific status of the theorem, however, depends on the empirical evidence. The empirical literature generally examines indirect evidence including trade volumes, trade openness, input ratios, relative production wages, and per capita incomes as summarized by Deardorff (1984), Leamer (1994), and Baldwin (2008). -
User Pays Applied to Pro-Life Advocates
A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Pope, Robin Working Paper The Big Picture of Lives Saved by Abortion on Demand: User Pays Applied to Pro-Life Advocates Bonn Econ Discussion Papers, No. 14/2009 Provided in Cooperation with: Bonn Graduate School of Economics (BGSE), University of Bonn Suggested Citation: Pope, Robin (2009) : The Big Picture of Lives Saved by Abortion on Demand: User Pays Applied to Pro-Life Advocates, Bonn Econ Discussion Papers, No. 14/2009, University of Bonn, Bonn Graduate School of Economics (BGSE), Bonn This Version is available at: http://hdl.handle.net/10419/37046 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen -
The Causal Direction Between Money and Prices
Journal of Monetary Economics 27 (1991) 381-423. North-Holland The causal direction between money and prices An alternative approach* Kevin D. Hoover University of California, Davis, Davis, CA 94916, USA Received December 1988, final version received March 1991 Causality is viewed as a matter of control. Controllability is captured in Simon’s analysis of causality as an asymmetrical relation of recursion between variables in the unobservable data-generating process. Tests of the stability of marginal and conditional distributions for these variables can provide evidence of causal ordering. The causal direction between prices and money in the United States 1950-1985 is assessed. The balance of evidence supports the view that money does not cause prices, and that prices do cause money. 1. Introduction The debate in economics over the causal direction between money and prices is an old one. Although in modern times it had seemed largely settled in favor of the view that money causes prices, the recent interest in real *This paper is a revision of part of my earlier working paper, ‘The Logic of Causal Inference: With an Application to Money and Prices’, No. 55 of the series of working papers in the Research Program in Applied Macroeconomics and Macro Policy, Institute of Governmental Affairs, University of California. Davis. I am grateful to Peter Oownheimer. Peter Sinclair, Charles Goodhart, Thomas Mayer, Edward Garner, Thomas C&iey, Stephen LeRoy, Leon Wegge, Nancy Wulwick, Diran Bodenhom, Clive Granger, Paul Holland, the editors of this journal, an anonymous referee, and the participants in macroeconomics seminars at the Univer- sity of California, Berkeley, Fall 1986, the University of California, Davis, Fall 1988, and the University of California, Irvine, Spring 1989, for comments on this paper in its various previous incamatio;ts. -
Professor Robert F. Engle," Econometric Theory, 19, 1159-1193
Diebold, F.X. (2003), "The ET Interview: Professor Robert F. Engle," Econometric Theory, 19, 1159-1193. The ET Interview: Professor Robert F. Engle Francis X. Diebold1 University of Pennsylvania and NBER January 2003 In the past thirty-five years, time-series econometrics developed from infancy to relative maturity. A large part of that development is due to Robert F. Engle, whose work is distinguished by exceptional creativity in the empirical modeling of dynamic economic and financial phenomena. Engle’s footsteps range widely, from early work on band-spectral regression, testing, and exogeneity, through more recent work on cointegration, ARCH models, and ultra-high-frequency financial asset return dynamics. The booming field of financial econometrics, which did not exist twenty-five years ago, is built in large part on the volatility models pioneered by Engle, and their many variations and extensions, which have found widespread application in financial risk management, asset pricing and asset allocation. (We began in fall 1998 at Spruce in Chicago, the night before the annual NBER/NSF Time Series Seminar, continued in fall 2000 at Tabla in New York, continued again in summer 2001 at the Conference on Market Microstructure and High-Frequency Data in Finance, Sandbjerg Estate, Denmark, and wrapped up by telephone in January 2003.) I. Cornell: From Physics to Economics FXD: Let’s go back to your graduate student days. I recall that you were a student at Cornell. Could you tell us a bit about that? RFE: It depends on how far back you want to go. When I went to Cornell I went as a physicist. -
Schofield R 2017.Pdf
School of Media, Culture and Creative Arts The Dissenter and Anti-authoritarian Aspects of Australian History and Character that Inform the Moral Ambiguity that Marks Australian Crime Fiction Robert James Schofield This thesis is presented for the Degree of Doctor of Philosophy of Curtin University November 2017 DECLARATION To the best of my knowledge and belief this thesis contains no material previously published by any other person except where due acknowledgment has been made. This thesis contains no material which has been accepted for the award of any other degree or diploma in any university. 2 CONTENTS DECLARATION 2 ABSTRACT 4 THE GRASS MUD HORSE: A NOVEL 7 Exegesis: The dissenter and anti-authoritarian aspects of Australian history and character that inform the moral ambiguity that marks Australian crime fiction 314 Chapter 1: Introduction 314 Chapter 2: Towards a definition of Noir 324 Chapter 3: Robbery Under Arms by Rolfe Boldrewood 334 Chapter 4: The Forger’s wife by John Lang 366 Chapter 5: Mark Brown’s wife by Charles de Boos 375 Chapter 6: Irralie’s Bushranger by E.W. Hornung 383 Chapter 7: Wanted by the Police by Henry Lawson 393 Chapter 8: Summary and Conclusion 401 References 405 END 409 3 ABSTRACT This thesis consists of two distinct but related parts: a creative component, the novel ‘The Grass Mud Horse’, and an exegesis. Both will attempt to answer the question: How has the moral ambiguity that marks both colonial and contemporary Australian crime fiction been informed and influenced by the dissenter and anti- authoritarian aspects of Australian history and character? Crime fiction has a long tradition in Australian culture, ensured by its Western origins as a penal colony. -
CNBC TV Asia Schedule Shows and Times Subjected to Change
CNBC TV Asia Schedule Shows and times subjected to change. Please check your local listings. 16th December to 22nd December Time Monday Tuesday Wednesday Thursday Friday Saturday Sunday 12:00 AM Tonight Show Tonight Show The Call The Call The Call The Call The Call 12:30 AM with Jay Leno with Jay Leno 1:00 AM Suze Orman Suze Orman 1:30 AM 2:00 AM Power Lunch Power Lunch Power Lunch Power Lunch Power Lunch On the Money On the Money 2:30 AM 3:00 AM Street Signs Street Signs Street Signs Street Signs Street Signs 3:30 AM The Travel The Travel Channel Channel 4:00 AM 4:30 AM Closing Bell Closing Bell Closing Bell Closing Bell Closing Bell (U.S.) (U.S.) (U.S.) (U.S.) (U.S.) 5:00 AM Managing Asia Meet The Press 5:30 AM The Leaders Scam of the 6:00 AM Squawk Australia Squawk Australia Squawk Australia Squawk Australia Squawk Australia Fast Money Century: Bernie 6:30 AM Asia Market MadoffAsia Market& The 7:00 AM EuropeWeek This Week 7:30 AM Business Arabia Week Europe This 8:00 AM BusinessWeek 8:30 AM Asia Squawk Box Asia Squawk Box Asia Squawk Box Asia Squawk Box Asia Squawk Box Pakistan CNBC Reports India Business 9:00 AM Week Asia Market 9:30 AM Week Global Players 10:00 AM with Sabine Closing Bell 10:30 AM World Business CNBC's Cash CNBC's Cash CNBC's Cash CNBC's Cash CNBC's Cash (U.S.) 11:00 AM Flow Flow Flow Flow Flow Managing Asia Global Players 11:30 AM 7th ABLA 2008 with Sabine 12:00 PM Meet The Press Fast Money Fast Money Fast Money Fast Money 12:30 PM 1:00 PM Capital Capital Capital Capital Capital CNBC Sports CNBC Sports 1:30 PM Connection