Document Type
Journal Article
Faculty
Faculty of Business and Law
School
School of Accounting, Finance and Economics / Finance, Economics, Markets and Accounting Research Centre
RAS ID
14523
Abstract
It is generally accepted that asset returns are not normally distributed, especially during volatile economic circumstances such as those seen during the global financial crisis. Yet portfolio optimisation is often based on lower order moments of mean and standard deviation, which do not take into account the tail of a distribution. The mining industry can be extremely volatile during times of economic downturn. We compare extreme risk in mining share portfolios from each of the world’s seven leading mining areas using Conditional Value at Risk (CVaR) which measures those risks beyond traditional Value at Risk (VaR) metrics. We also show how CVaR, as opposed to traditional standard deviation measures, can be used to optimise mining portfolios and minimise extreme risk. We compare CVaR across two different periods and find that relative risk ranking between countries changes as volatility changes. We find significant differences between countries using CVaR as compared to standard deviation risk rankings, as well as differences in portfolios optimised using CVaR compared to portfolios using traditional variance methodology. This indicates that investors will not adequately minimise risk using traditional approaches.
Access Rights
free_to_read
Comments
Allen, D. E., Kramadibrata, A. R., Powell, R. , & Singh, A. (2012). Conditional Value at Risk Applications to the Global Mining Industry. Journal of Business and Policy Research, 7(3), 11-23. Available here