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Optimising a Mining Portfolio Using CVaR

  • David E Allen


    (School of Accounting Finance & Economics, Edith Cowan University)

  • Akhmad R. Kramadibrata


    (School of Accounting Finance & Economics, Edith Cowan University)

  • R. J. Powell


    (School of Accounting Finance & Economics, Edith Cowan University)

  • Abhay Kumar Singh


    (School of Accounting Finance & Economics, Edith Cowan University)

The mining industry can be extremely volatile during times of economic downturn. We compare extreme risk in mining share portfolios from each of the worldís 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 can be used to optimise portfolios and minimise extreme risk. We find significant differences between countries in 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.Classification-JEL:

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Paper provided by Edith Cowan University, School of Business in its series Working papers with number 2011-06.

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Length: 11 pages
Date of creation: Nov 2011
Date of revision:
Handle: RePEc:ecu:wpaper:2011-06
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  1. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228.
  2. David Edmund Allen & Robert John Powell & Abhay Kumar Singh, 2012. "Beyond reasonable doubt: multiple tail risk measures applied to European industries," Applied Economics Letters, Taylor & Francis Journals, vol. 19(7), pages 671-676, May.
  3. Ivan Roberts & Anthony Rush, 2010. "Sources of Chinese Demand for Resource Commodities," RBA Research Discussion Papers rdp2010-08, Reserve Bank of Australia.
  4. repec:ecu:wpaper:2009-05 is not listed on IDEAS
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