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Portfolio Optimization under Solvency Constraints: A Dynamical Approach

Asanga, S., Asimit, A.V., Badescu, A. & Haberman, S. (2014). Portfolio Optimization under Solvency Constraints: A Dynamical Approach. North American Actuarial Journal, 18(3), pp. 394-416. doi: 10.1080/10920277.2014.910127


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.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis Group in North American Actuarial Journal on 19 May 2014, available online at:
Publisher Keywords: Portfolio optimization, Capital requirements, Solvency constraint, Multivariate GARCH, Double rolling window
Subjects: H Social Sciences > HG Finance
Departments: Bayes Business School > Finance
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