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Forecasting Steel Prices Using ARIMAX Model: A Case Study of Turkey

Authors: Adli, Kaveh A.;

Forecasting Steel Prices Using ARIMAX Model: A Case Study of Turkey

Abstract

{"references": ["Worldsteel Association. (2019). WORLD STEEL IN FIGURES 2019. Retrieved from", "ITA. (2019). Global Steel Report. Retrieved from", "ERDEMIR. (2019). 2019 12 Months Investor Presentation", "Blecker, R. A. (1989). Markup Pricing, Import Competition, and the Decline of the American Steel Industry. Journal of Post Keynesian Economics, 12(1), 70\u201387", "] Blonigen, B., Liebman, B., & Wilson, W. (2007). Trade policy and market power: The case of the us steel industry. In NBER Working Paper No. 13671. Retrieved from", "Grossman, G. M. (1986). IMPORTS AS A CAUSE OF INJURY: THE CASE OF THE U.S. STEEL INDUSTRY. Cambridge.", "Liebman, B. H. (2006). Safeguards, China, and the price of steel. Review of World Economics, 142(2), 354\u2013373.", "Mancke, R. (1968). The Determinants of Steel Prices in the U . S .: 1947-65. The Journal of Industrial Economics, 16(2), 147\u2013160."]}

Steel prices for Turkey as a major steel producer and exporter have substantial importance to be predicted. The ARIMA model with explanatory variables is used to assess the out-of-sample forecast accuracy with the univariate ARIMA as a benchmark. The results revealed that despite expectations, The ARIMA model with explanatory variables could not perform superior results comparing ARIMA models in a 6-month forecast horizon.

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Keywords

Forecast, Steel Prices, ARIMA, ARIMAX,

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