Review of Economic Studies (1998) 65, 361-393 0 1998 The Review of Economic Studies Limited
0034-6527/98/00170361$02.00
Stochastic Volatility : Likelihood Inference and Comparison with ARCH Models
SAN
So, you want to go to grad school in Economics? A practical guide of the first years (for outsiders) from insiders
Ceyhun Elgin Mario Solis-Garcia University of Minnesota April 2007
1
Introduction You
Modelling the Asymmetric Volatility of Anti-pollution Technology Patents Registered in the USA
Felix Chana, Dora Marinovab, Michael McAleera a Department of Economics, University of Western Australia
ARCH
Ser-Huang Poon August 11, 2008
Financial market volatility is known to cluster. A volatile period is known to persist for some time before the market returns to normality. The ARCH (AutoRegressiv
Asymmetry and Long Memory in Dynamics of Interest Rate Volatility
Pei-Shih Weng a,
a
Department of Finance, National Central University, Jhongli, TY 32001, Taiwan May 2008
Abstract Empirically, the c
Q U A N T IT A T IV E F I N A N C E V O L U M E 3 (2003) 110 INSTITUTE O F PHYSICS PUBLISHING
RE S E A R C H PA P E R
quant.iop.org
Estimating GARCH models using support vector machines*
Fernando P re
Financial Analysts Journal Volume 61 Number 1 2005, CFA Institute
Practical Issues in Forecasting Volatility
Ser-Huang Poon and Clive Granger
A comparison is presented of 93 studies that conducted tes
The Lahore Journal of Economics 12 : 2 (Winter 2007) pp. 115-149
Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models G.R. Pasha*, Tahira Qasim* and Muhamm
The Lahore Journal of Economics 12 : 2 (Winter 2007) pp. 115-149
Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models G.R. Pasha * , Tahira Qasim * and Muh
Bank of Canada
Banque du Canada
Working Paper 2006-14 / Document de travail 2006-14
Forecasting Commodity Prices: GARCH, Jumps, and Mean Reversion
by
Jean-Thomas Bernard, Lynda Khalaf, Maral Kichian,
A FORECAST COMPARISON OF VOLATILITY MODELS: DOES ANYTHING BEAT A GARCH(1,1)?
PETER R. HANSENa AND ASGER LUNDEb
a Brown b Aarhus
University, Department of Economics, Box B, Providence, RI 02912, USA Sc
FORECASTING FINANCIAL VOLATILITY: EVIDENCE FROM CHINESE STOCK MARKET by HONGYU PAN and ZHICHAO ZHANG
WORKING PAPER IN ECONOMICS AND FINANCE No. 06/02 FEBRUARY 2006
School of Economics, Finance and Bus
TI 2000-104/4 Tinbergen Institute Discussion Paper
Forecasting the Variability of Stock F orecasting Index Returns with Stochastic Volatility Models and Implied Volatility
Eugenie Hol Siem Jan Koopman
Forecasting Volatility: Evidence from the German Stock Market*
Hagen H.W. Bluhma, Jun Yub
February 2001
Abstract In this paper we compare two basic approaches to forecast volatility in the German stoc
Published in Journal of Business, 51 (4), 1978, 549-564 Forecasting with Econometric Methods: Folklore versus Fact J. Scott Armstrong The Wharton School, University of Pennsylvania
Abstract Evidence f
Working Paper 01-08 Statistics and Econometrics Series 05 March 2001
Departamento de Estadstica y Econometra Universidad Carlos III de Madrid Calle Madrid, 126 28903 Getafe (Spain) Fax (34) 91 624-98-
Is Unlevered Firm Volatility Asymmetric?
By Hazem Daouk Cornell University David Ng1 Cornell University This version: January 11, 2007 Abstract We develop a new, unlevering approach to document how we
Quiz 6 Probability and Statistics
Bernardo Guimaraes September 2009
(For questions 1 to 10) A random sample of size n is drawn from X N ( ; 2 ). Denote an element of the sample by Pn X Xi ; 1 i n. I w
Quiz 4 Probability and Statistics
Bernardo Guimaraes September 2009
1. Which of the following are probability density functions of 2 independent variables? (a) fX;Y (x; y ) = 2; 0 x y 1, otherwise fX;
Q U A N T I T A T I V E F I N A N C E V O L U M E 1 (2001) 237245 INSTITUTE O F PHYSICS PUBLISHING
RE S E A R C H PA P E R
quant.iop.org
What good is a volatility model?
Robert F Engle and Andrew J Pa
ECON 371 2003 SUMMARY #4 COMPARATIVE STATICS: PROPERTIES OF CONSUMER DEMAND We are now ready to investigate what sort of implications the model we have discussed has on demand behaviour. We have alrea
Classical Demand Theory III (Welfare)
Benjamin Chiao
Nov 26, 2008 (Afterclass version 1pm) Lecture Notes for Graduate Level Advanced Microeconomics, Peking University Guanghua School of Management
1/2
Course: EC400 - Introductory Courses in Maths and Statistics
EC400 - Introductory Courses in Maths and Statistics
Moodle EC400
You are logged in as Marco Sun (Logout)
People
Welcome to EC400 Introduct
Chapter 10: Firms and Technology
10.1: Introduction
So far we have worked in a world without production in a pure-exchange world where people have initial endowments and might want to exchange them. W
Lecture 4
1 2
2.1 2.2 2.3 2.4
Summary of Lecture 1: Technology Summary of Lecture 2: Prot maximization
The prot maximization problem Implications of prot maximization The prot function Cost minimizati
Lecture 5
1 Summary of Lectures 1, 2, and 3: Technology, Prot maximization, The cost function and duality Summary of Lecture 4: Consumption theory
Preference orders The utility function The utility ma
Solow Model
1. No Technological Progress
Setup CRS production function: Y = K L1 y = f (k ) = k
13
Constant savings rate:
I = sY
Constant labour force growth rate:
L L=n
Capital accumulation:
K = sY