Detecting speculative bubbles in metal prices: Evidence from GSADF test and machine learning approaches
Yükleniyor...
Dosyalar
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The importance of metal prices to real economic activity and financial markets has increased the focus on
detecting price bubbles in precious and industrial metals. Several studies looked at the influence of macroeco-
nomic factors in the formation of a single metal bubble and tried to identify bubble dates. Our study extends the
literature and analyzes monthly gold, platinum, palladium, rhodium, silver, and aluminum, copper, lead, nickel,
steel, tin prices over 1980M1-2019M12, and contributes to the literature in two ways: First, the analysis in-
corporates the Generalized Supremum Augmented Dickey-Fuller (GSADF) test to detect potential bubbles. Sec-
ond, the study evaluates the impact of potential financial, real, and speculative factors in the likelihood of price
bubbles using the random forest method. Our findings indicate that financial factors are more critical in pre-
dicting precious metal price bubbles. The monetary policy rate and the production index are important to predict
bubbles in industrial metal prices. However, our findings suggest that speculative activity may not adequately
predict metal price bubbles.
Açıklama
Anahtar Kelimeler
Metal prices, Multiple bubbles, Random forest algorithm, Macroeconomic factors
Kaynak
Resources Policy
WoS Q Değeri
Q1
Scopus Q Değeri
Cilt
74
Sayı
Künye
Ozgur, O., Yilanci, V., & Ozbugday, F. C. (2021). Detecting speculative bubbles in metal prices: Evidence from GSADF test and machine learning approaches. Resources Policy, 74 doi:10.1016/j.resourpol.2021.102306
