Behavioral influences in non-ferrous metals prices. (September 2015)

• Record Type: Journal Article
• Authors: Cummins, Mark; Dowling, Michael; Lucey, Brian M.
• Is Part Of: Resources policy. Volume 45(2015)
• Page Start: 9
• Page End: 22
• Publication Date: 2015-09
• Subjects: G13 -- G14 -- L61; Keywords -- Psychological barriers -- Clustering -- Non-ferrous metals; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Ressources naturelles -- Gestion -- Périodiques; Environnement -- Politique gouvernementale -- Périodiques; 333.8
• DOI: 10.1016/j.resourpol.2015.03.002
• Languages: English
• ISSNs: 0301-4207

Abstract

Abstract: Recent research has identified the presence of behavioral influences on traders in predominantly professionally traded markets such as oil, gold, and foreign exchange. Previous research had largely confined behavioral-based investigations to equity markets due to an assumption that noise traders would drive any influence and these traders were mainly absent from the professionally traded markets. This paper extends this research to the non-ferrous metals markets and demonstrates similar influences on prices. It is shown that psychological price barriers, where there is predictable trading patterns around psychologically important price points, are important. Specifically, lead, zinc, and aluminium alloy show anomalous price reactions in the days particularly following a breach of a $1000 price point. There is also evidence presented of negative price clustering before key price barriers. Subperiod tests further indicate that the relevant psychological price point is dependent on average prices. Recognizing the multiple hypothesis testing nature of the study, Generalized Bonferroni corrections are implemented to provide a robust control for the possibility of data mining. This represents a first investigation of behavioral influences in non-ferrous metals prices, and suggests that these markets are not immune to trader biases influencing the setting of prices. Abstract : Highlights: Find psychological price barriers influence non-ferrous metals prices. Prices display negative clustering and directional trends around price barriers. Subperiod tests suggest relevant price barriers dependent on average price. Apply a generalized Bonferroni correction to avoid multiple comparisons bias.