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Portfolio Selection for Insurance Linked Securities: An Application of Multiple Criteria Decision Making

Author

Listed:
  • Dominic Ho

    () (School of Risk and Actuarial Studies, Australian School of Business, University of New South Wales)

  • Michael Sherris

    () (School of Risk and Actuarial Studies and ARC Centre of Excellence in Population Ageing Research, Australian School of Business, University of New South Wales)

Abstract

The insurance linked securities (ILS) market is an increasingly important alternative asset class for which risk and return analysis differs from other asset classes. Measures of portfolio risk and return for an ILS portfolio are based on the expected losses and expected excess returns over the risk free rate. Multiple criteria decision making (MCDM) has found successful applications to many real world decision problems. This paper examines the application of two popular MCDM methods, Analytical Hierarchy Process (AHP) and ELECTRE III, to ILS portfolios. These methods are used to screen the securities before constructing portfolios using linear optimisation with constraints. The objective function is to minimise the portfolio expected loss for a given level of expected excess return. Upper and lower bounds are also placed on the investment in each individual ILS. The results demonstrate the benefits from applying MCDM to ILS portfolio selection.

Suggested Citation

  • Dominic Ho & Michael Sherris, 2012. "Portfolio Selection for Insurance Linked Securities: An Application of Multiple Criteria Decision Making," Working Papers 201203, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
  • Handle: RePEc:asb:wpaper:201203
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    File URL: http://cepar.edu.au/media/72659/portfolio_selection_for_insurance_linked_sec.pdf
    File Function: First version, 2012
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    More about this item

    Keywords

    Portfolio selection; insurance linked securities; multiple criteria decision making; Analytical Hierarchy Process; ELECTRE;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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