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Asanga, S.; Asimit, A.V.; Badescu, A.; Haberman, S. (2014)
Languages: English
Types: Article
Subjects: HD61, HG
We develop portfolio optimization problems for a nonlife insurance company seeking to find the minimum capital required that simultaneously satisfies solvency and portfolio performance constraints. Motivated by standard insurance regulations, we consider solvency capital requirements based on three criteria: ruin probability, conditional Value-at-Risk, and expected policyholder deficit ratio. We propose a novel semiparametric formulation for each problem and explore the advantages of implementing this methodology over other potential approaches. When liabilities follow a Lognormal distribution, we provide sufficient conditions for convexity for each problem. Using different expected return on capital target levels, we construct efficient frontiers when portfolio assets are modeled with a special class of multivariate GARCH models. We find that the correlation between asset returns plays an important role in the behavior of the optimal capital required and the portfolio structure. The stability and out-of-sample performance of our optimal solutions are empirically tested with respect to both the solvency requirement and portfolio performance, through a double rolling window estimation exercise.
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    • [1] Alexander, S., Coleman, T., and Li, Y. (2006). Minimizing CVaR and VaR for a Portfolio of Derivatives. Journal of Banking and Finance, 30, 583-605.
    • [2] Acerbi, C., and Tasche, D. (2002). On the Coherence of Expected Shortfall. Journal of Banking and Finance, 26(7), 1487-1503.
    • [3] Artzner, P. (1999). Application of Coherent Risk Measures to Capital Requirements in Insurance. North American Actuarial Journal. 13, 11-25.
    • [4] Artzner, P., Delbaen, F., Eber, J. M., and Heath, D. (1999). Coherent measure of risk. Mathematical Finance, 9(3), 203-228.
    • [5] Artzner, P., Delbaen, F. and Koch-Medina, P. (2009). Risk Measures and E cient Use of Capital. ASTIN Bulletin, 39(1), 101-116.
    • [6] Asimit, V.A., Badescu, A., Siu, T.K., and Zinchenko, Y. (2012). Capital Requirements and Optimal Investment with Solvency Constraints. IMA Journal of Management Mathematics, In Press.
    • [7] Balbas, A. (2008). Capital Requirements: Are They the Best Solutions?. working paper, available at http://ideas.repec.org/p/ner/carlos/infohdl10016-3367.html.
    • [8] Barth, M. (2000). A Comparison of Risk-Based Capital Standards under the Expected Policyholder De cit and the Probability of Ruin Approaches. Journal of Risk and Insurance. 67(3), 397-413.
    • [9] Bauwens, L., Laurent, S., and Rombouts, J.K.V. (2006). Multivariate GARCH models: a survey. Journal of Applied Econometrics, 21, 79-109.
    • [25] FOPI. (2004). Federal O ce of Private Insurance, Whitepaper on Swiss Solvency Test.
    • [26] Gaivoronski, A., and P ug, G. (2004). Value at Risk in Portfolio Optimization: Properties and Computational Approach. Journal of Risk, 7(2), 1-31.
    • [37] Nemirovski, A., and Shapiro, A. (2006). Convex Approximations of Chance Constrained Programs. SIAM Journal of Optimization, 17(4), 969-996.
    • [38] P ug, G.C. (2000). Some Remarks on the Value-at-Risk and Conditional Value-at-Risk. Uryasev, S.P. ed. Probabilistic Constrained Optimization: Methodology and Applications, Kluwer, Norwell. MA, 278-287.
    • [39] Rockafellar, R.T. and Uryasev, S. (2000). Optimization of Conditional Value-at-Risk. Journal of Risk, Number 2, 21-41.
    • [40] Rockafellar, R.T. and Uryasev, S. (2002). Conditional Value-at-Risk for General Loss Distributions. Journal of Banking and Finance, 26(7), 1443-1471.
    • [41] Rombouts, J. V. K., and Stentoft, L. (2011). Multivariate Option Pricing with Time Varying Volatility and Correlations, Journal of Banking and Finance, 35, 2267-2281.
    • [42] Sandstrom, A. (2006). Solvency: Models, Assessment and Regulation. Chapman & Hall/CRC, Boca Raton.
    • [43] Santos, A.A.P., Nogales, F.J., Ruiz, E., and Van Dijk, D. (2012). Optimal Portfolios with Minimum Capital Requirements, Journal of Banking and Finance, 36, 1928-1942.
    • [44] Scollnik, D.P.M., and Sun, C. (2012). Modeling with Weibull-Pareto Models. North American Actuarial Journal, 16(2), 260-272.
    • [45] Silvennoinen, A., and Terasvirta, T. (2008). Multivariate GARCH Models. in Handbook of Financial Time Series, Springer, Andersen, T., Davis, R., Kreiss, J., and Mikosch, T. (Eds.).
    • [46] Tian R., Cox, S.H., Lin, Y, and Zuluaga, L.F. (2010). Portfolio Risk Management with CVaR-like Constraints. North American Actuarial Journal, 14(1), 86-106.
    • [47] Wozabal, D., Hochreiter, R., P ug, G. (2008). A D.C. Formulation of Value-at-Risk Constrained Optimization. Tech. Rep. TR2008-01, Department of Statistics and Decision Support Systems, University of Vienna, Vienna.
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