Top of page
Main Content
  • Portfolio optimisation using CVaR and downside risk-metrics

    Portfolio optimisation using CVaR and downside risk-metrics

Portfolio optimisation using CVaR and downside risk-metrics

This project investigates investment portfolio optimisation using assessment techniques such as:

  • Conditional Value at Risk (CVaR)
  • Downside risk-metrics 
  • Non-linear measures of dependency such as entropy based metrics and R-Vine Copulas
A variety of alternative programming routines have been developed using daily and higher frequency data to select portfolios.

This work commenced with Dr Seyed-Ali Hosseini-Yekani of Shiraz and Tabriz universities in Iran. Dr Hosseini-Yekani was a visiting scholar at ECU for a period of nine months in 2007-2008.  

In 2012 Mr M.A. Ashraf joined ECU for a two-month summer internship whilst on-leave from The Indian Institute of Technology, Karaghpur, India, to work on dependency metrics using R-Vine Copulas. It is expected that these should better capture non-symmetric dependencies which will then be incorporated in our portfolio optimisation routines.

Dr Abhay-Kumar Singh has also been working on this topic since joining the Finance, Economics, Markets and Accounting Research Centre (FEMARC) in June 2009. 

Researchers

Skip to top of page