Modeling and Forecasting the Price of Asphalt Cement Using Generalized Auto Regressive Conditional Heteroscedasticity-Reference-Cited by-同舟云学术

Modeling and Forecasting the Price of Asphalt Cement Using Generalized Auto Regressive Conditional Heteroscedasticity

Published:2016-05-24 Issue: Volume: Page:
ISSN:
Container-title:Construction Research Congress 2016
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Author:

Ilbeigi Mohammad¹²³,Joukar Alireza¹²³,Ashuri Baabak¹²³

Affiliation:

1. Ph.D. Candidate, School of Building Construction, Georgia Institute of Technology, 280 Ferst Dr., 2nd Floor, Atlanta, GA 30332.

2. Ph.D. Candidate, Dept. of Construction Management, Louisiana State Univ., 3135 Patrik F. Taylor Hall, Baton Rouge, LA 79803.

3. Associate Professor, School of Building Construction and School of Civil and Environmental Engineering, Georgia Institute of Technology, 280 Ferst Dr., 2ns Floor, Atlanta, GA 30332.

Publisher

American Society of Civil Engineers

Link

http://ascelibrary.org/doi/pdf/10.1061/9780784479827.071

Reference16 articles.

1. Akaike H. (1998). "Information theory and an extension of the maximum likelihood principle." In Selected Papers of Hirotugu Akaike (pp. 199-213). Springer New York.

2. Time series analysis of ENR construction cost index;Ashuri B.;Journal of Construction Engineering and Management.,2010

3. Generalized autoregressive conditional heteroskedasticity

4. Daníelsson J. (2011). Financial risk forecasting: the theory and practice of forecasting market risk with implementation in R and Matlab (Vol. 588). John Wiley & Sons. New York.

5. Damnjanovic I. Anderson S. Wimsatt A. Reinschmidt K. & Pandit D. (2009). "Evaluation of Ways and Procedures to Reduce Construction Cost and Increase Competition." Texas Transportation Institute Texas A&M University System.

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