Sergio, Bianchi and Alessandro, Trudda (2008): Global Asset Return in Pension Funds: a dynamical risk analysis. Forthcoming in: Mathematical Methods in Economics and Finance
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Abstract
The aim of the paper is to develop a technique for rebalancing pension fund portfolios in function of their pointwise level of risk. The performance of pension funds is often measured by their global asset returns because of the latter’s influence on periodic contributions and/or future benefits. However, in periods of market crisis attention is focused on the risk level given their social security (and not speculative) function. We describe the process of the global asset return by a multifractional Brownian motion using the function H(t) to detect high or low volatility phases. A procedure is carried out to balance the asset composition when the established local degree of risk is exceeded. The application is carried out on portfolios obtained in accordance with Italian regulations regarding investment limits.
Item Type: | MPRA Paper |
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Original Title: | Global Asset Return in Pension Funds: a dynamical risk analysis |
Language: | English |
Keywords: | Pension Funds, risk control, multifractional Brownian motion |
Subjects: | G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice ; Investment Decisions G - Financial Economics > G2 - Financial Institutions and Services > G23 - Non-bank Financial Institutions ; Financial Instruments ; Institutional Investors C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes |
Item ID: | 12011 |
Depositing User: | Sergio Bianchi |
Date Deposited: | 04 Apr 2009 18:18 |
Last Modified: | 03 Oct 2019 16:11 |
References: | Ayache, A., J. Lévy Véhel (2000), The Generalized Multifractional Brownian Motion, Statistical Inference for Stochastic Processes, 3, 7-18 Arbeleche S., Dempster M.A.H. (2003) Econometric modeling for global asset liability management University of Cambridge, WP 13 Arnott, R., Fabozzi, F.J. (1988). Asset Allocation: a Handbook of Portfolio Policies, Strategies and Tactis. Chicago, Illinois: Probus Publishing Company Babbel, D.F., Gold, J., Merrill, C.B., (2002), Fair value of liabilities: the financial economics perspective. North American actuarial Journal 6(1), 12-27 Bader, L.N. (2003). The case against stock in corporate pension funds. Society of Acturies Newsletter of the Pension Section, 51, 17-19 Bianchi S. (2005), Pathwise Identification of the Memory Function of the Multifractional Brownian Motion with Application to Finance, International Journal of Theoretical and Applied Finance, 8, 2, 255-281 Bikker J. A., Broeders D., Drew J., Stock market performance and pension fund investment policy: rebalancing, free flot or market timing?, November 2007, DBN Working Paper Coeurjolly J. (2005), Identification of the multifractional Brownian motion, Bernoulli, 11(6), 987-1008 Fisher, L., & Weil,R. L., (1971). Coping with the risk of interest rate fluctuations: Return to bondholders from naive and optimal strategies. Journal of Business, 44, 408-431 Gerard R., Haberman S., Vigna E., (2003) Optimal investment choices postretirement in a defined contribution pension scheme. Auguts, Insurance: Mathematics and Economics, Vol. 35, 321-342 Haberman S, (1997), Stochastic investment returns and contribution rate risk in a defined benefit pension schemes. Insurance: Mathematics and Economics, Vol. 19, 119-127 Haberman S., Sung J.H (1994), Dynamic approaches to pension funding. Insurance, Mathematics & Economics. Vol. 15, 151-162 Hilli P., Koivu M., Pennanen T., (2007), A stochastic model for asset and liabilities of a pension institution Lévy Véhel, J. (1995), Fractal approaches in signal processing, Fractals, 3, 755-775 Mandelbrot B.B., Van Ness J.W. (1968), Fractional Brownian Motions, Fractional Noises and Applications, SIAM Review, 10, 422-437 Otranto E., Trudda A., (2007), Classifying the Italian pension funds via GARCH distance – in Mathematical and Statistical Methods for Insurance and Finance, Springer, 189-197 Otranto E., Trudda A., (2008), Evaluating the risk of Pension Funds by Statistical Procedures – In: Transition Economies: 21st Century Issues and Challenges. (G.M. Lakatos Ed.), Ch. 7, 189-204, Nova Science Publisher, Hauppauge, NY Peltier R.F., Lévy Véhel J. (1994), A New Method for Estimating the Parameter of Fractional Brownian Motion, Rapport de recherche INRIA n.2396, Le Chesnay Cedex, available at http://fractales.inria.fr/index.php?page=levy-vehel Peltier R.F., Lévy Véhel J. (1995), Multifractional Brownian Motion: definition and preliminary results, Rapport de recherche INRIA n.2645, Le Chesnay Cedex, available at http://fractales.inria.fr/index.php?page=levy-vehel Ramaswamy S., (1997) Global asset allocation in fixed income markets , September, WP n. 46 Bank for international settlement Richard H. B.,(1996), J.C. Gilbert and J. Nocedal, A Trust Region Method Based on Interior Point Techniques for Nonlinear Programming, INRIA Report n.2896 Ryan R.J., Fabozzi, F.J., (2003) The pension crisis revealed. The Journal of Investing, 12, 43-48 Samorodnitsky G. and M.S. Taqqu (1994), Stable non-Gaussian random processes, Chapman & Hall, London Stewart F., (2007). Pension fund investment in hedge funds., OECD Working Papers on Insurance and Private Pensions, No. 13, OECD Publishing doi:10.1787/086456868358 OECD Trudda A., (2005). Casse di Previdenza: Analisi delle dinamiche attuariali., 2nd edition 2008, Giappichelli, Torino |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/12011 |