Abstract

http://ssrn.com/abstract=1782214
 
 

Footnotes (14)



 


 



Forecasting Commodity Prices with Mixed-Frequency Data: An OLS-Based Generalized ADL Approach


Yu-Chin Chen


University of Washington - Department of Economics

Wen-Jen Tsay


Academia Sinica - Institute of Economics

April 29, 2011


Abstract:     
This paper presents a generalized autoregressive distributed lag (GADL) model for conducting regression estimations that involve mixed-frequency data. As an example, we show that daily asset market information - currency and equity market movements - can produce forecasts of quarterly commodity price changes that are superior to those in the previous research. Following the traditional ADL literature, our estimation strategy relies on a Vandermonde matrix to parameterize the weighting functions for higher-frequency observations. Accordingly, inferences can be obtained using ordinary least squares principles without Kalman filtering, non-linear optimizations, or additional restrictions on the parameters. Our findings provide an easy-to-use method for conducting mixed data-sampling analysis as well as for forecasting world commodity price movements.

Number of Pages in PDF File: 35

Keywords: Mixed Frequency Data, Autoregressive Distributed Lag, Commodity Prices, Forecasting

JEL Classification: C22, C53, F31, F47, Q02

working papers series


Download This Paper

Date posted: March 10, 2011 ; Last revised: May 1, 2011

Suggested Citation

Chen, Yu-Chin and Tsay, Wen-Jen, Forecasting Commodity Prices with Mixed-Frequency Data: An OLS-Based Generalized ADL Approach (April 29, 2011). Available at SSRN: http://ssrn.com/abstract=1782214 or http://dx.doi.org/10.2139/ssrn.1782214

Contact Information

Yu-Chin Chen (Contact Author)
University of Washington - Department of Economics ( email )
Box 353330
Seattle, WA 98195-3330
United States
206-543-6197 (Phone)
HOME PAGE: http://faculty.washington.edu/yuchin
Wen-Jen Tsay
Academia Sinica - Institute of Economics ( email )
128 Academia Road, Section 2
Nankang
Taipei, 11529
Taiwan
Feedback to SSRN


Paper statistics
Abstract Views: 1,693
Downloads: 357
Download Rank: 45,802
Footnotes:  14

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo1 in 0.360 seconds