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Pension funds rules: Paradoxes in risk control

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  • Cadoni, Marinella
  • Melis, Roberta
  • Trudda, Alessandro

Abstract

Pension funds are financial institutions that invest retirement savings from workers to provide pension benefits. Due to this social security function, each country enforces laws to regulate investments. Usually regulations identify pension portfolio’s risk level based on the nature of its financial products. After the latest financial crisis, it became evident that such approach may not be sufficient to control the risk. In this paper we measure risk level with a multifractional Brownian motion with random exponent. We show how current rules can lead to paradoxes, where portfolios which comply with the laws are riskier than those that do not.

Suggested Citation

  • Cadoni, Marinella & Melis, Roberta & Trudda, Alessandro, 2017. "Pension funds rules: Paradoxes in risk control," Finance Research Letters, Elsevier, vol. 22(C), pages 20-29.
    • Handle: RePEc:eee:finlet:v:22:y:2017:i:c:p:20-29
    DOI: 10.1016/j.frl.2017.05.003
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    References listed on IDEAS

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    1. Solange M. Berstein & Rómulo A. Chumacero, 2012. "VaR limits for pension funds: an evaluation," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1315-1324, May.
    2. Ian Tower & Gregorio Impavido, 2009. "How the Financial Crisis Affects Pensions and Insurance and Why the Impacts Matter," IMF Working Papers 2009/151, International Monetary Fund.
    3. Marinella Cadoni & Roberta Melis & Alessandro Trudda, 2015. "Financial Crisis: A New Measure for Risk of Pension Fund Portfolios," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-12, June.
    4. Sergio Bianchi, 2005. "Pathwise Identification Of The Memory Function Of Multifractional Brownian Motion With Application To Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 255-281.
    5. Sergio, Bianchi & Alessandro, Trudda, 2008. "Global Asset Return in Pension Funds: a dynamical risk analysis," MPRA Paper 12011, University Library of Munich, Germany, revised 14 Jun 2008.
    6. Antoine Ayache & Jacques Vehel, 2000. "The Generalized Multifractional Brownian Motion," Statistical Inference for Stochastic Processes, Springer, vol. 3(1), pages 7-18, January.
    7. repec:cup:judgdm:v:9:y:2014:i:1:p:77-82 is not listed on IDEAS
    8. Thomas, Ashok & Spataro, Luca & Mathew, Nanditha, 2014. "Pension funds and stock market volatility: An empirical analysis of OECD countries," Journal of Financial Stability, Elsevier, vol. 11(C), pages 92-103.
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    10. Martin T. Bohl & Judith Lischewski & Svitlana Voronkova, 2011. "Pension Funds' Performance in Strongly Regulated Industries in Central Europe: Evidence from Poland and Hungary," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(0), pages 80-94, July.
    11. Edoardo Otranto & Alessandro Trudda, 2008. "Classifying Italian Pension Funds via GARCH Distance," Springer Books, in: Cira Perna & Marilena Sibillo (ed.), Mathematical and Statistical Methods in Insurance and Finance, pages 189-197, Springer.
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    Cited by:

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    2. Han, Bingyan & Wong, Hoi Ying, 2021. "Merton’s portfolio problem under Volterra Heston model," Finance Research Letters, Elsevier, vol. 39(C).

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    More about this item

    Keywords

    Pension funds; Investment risk; Risk control; Multifractional Brownian motion;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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