El Niño, La Niña, and forecastability of the realized variance of agricultural commodity prices: Evidence from a machine learning approach

被引：0
|
作者：
Bonato, Matteo [1 ,2 ]
Çepni, Oğuzhan [3 ,4 ]
Gupta, Rangan [5 ]
Pierdzioch, Christian [6 ]
机构：
[1] Department of Economics and Econometrics, University of Johannesburg, Auckland Park, Johannesburg, South Africa
[2] IPAG Business School, 184 Boulevard Saint-Germain, Paris,75006, France
[3] Copenhagen Business School, Department of Economics, Porcelænshaven 16A, Frederiksberg,DK-2000, Denmark
[4] Central Bank of the Republic of Turkey, Haci Bayram Mah. Istiklal Cad. No:10 06050, Ankara, Turkey
[5] Department of Economics, University of Pretoria, Private Bag X20, Hatfield,0028, South Africa
[6] Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, Hamburg,22008, Germany
来源：
Journal of Forecasting | 2023年 / 42卷 / 04期
关键词：
Compendex;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Agriculture - Costs - Forecasting - Higher order statistics - Machine learning - Random forests - Risk perception
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页码：785 / 801
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