Stochastic optimal control of annuity contracts

Devolder, Pierre; Príncep, Manuela Bosch; Fabián, Inmaculada Domínguez

doi:10.1016/s0167-6687(03)00136-7

Cited by 87 publications

(102 citation statements)

References 15 publications

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“…The literature on the accumulation phase of defined contribution pension schemes is full of examples of optimal investment strategies resulting from EU maximization. See, for instance, Boulier, Huang & Taillard (2001), Haberman & Vigna (2002), Deelstra, Grasselli & Koehl (2003), Devolder, Bosch Princep & Dominguez Fabian (2003), Battocchio & Menoncin (2004), Cairns, Blake & Dowd (2006), Xiao, Zhai & Qin (2007), Gao (2008), Di Giacinto, Federico & Gozzi (2011).…”

Section: Introductionmentioning

confidence: 99%

On efficiency of mean–variance based portfolio selection in defined contribution pension schemes

Vigna

2012

Quantitative Finance

103

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We consider the portfolio selection problem in the accumulation phase of a defined contribution (DC) pension scheme. We solve the mean-variance portfolio selection problem using the embedding technique pioneered by Zhou & Li (2000) and show that it is equivalent to a targetbased optimization problem, consisting in the minimization of a quadratic loss function. We support the use of the target-based approach in DC pension funds for three reasons. Firstly, it transforms the difficult problem of selecting the individual's risk aversion coefficient into the easier task of choosing an appropriate target. Secondly, it is intuitive, flexible and adaptable to the member's needs and preferences. Thirdly, it produces final portfolios that are efficient in the mean-variance setting.We address the issue of comparison between an efficient portfolio and a portfolio that is optimal according to the more general criterion of maximization of expected utility (EU). The two natural notions of Variance Inefficiency and Mean Inefficiency are introduced, which measure the distance of an optimal inefficient portfolio from an efficient one, focusing on their variance and on their expected value, respectively. We illustrate the general procedure for finding the mean-variance inefficiency for the HARA class of utility functions, and then focus on the popular classes of CARA and CRRA utility functions. In these cases we prove the intuitive but not trivial results that the mean-variance inefficiency decreases with the risk aversion of the individual and increases with the time horizon and the Sharpe ratio of the risky asset. As a byproduct we prove that the CARA and CRRA optimal portfolio are not mean-variance efficient.Numerical investigations stress the impact of the time horizon on the extent of mean-variance inefficiency of CARA and CRRA utility functions. While at instantaneous level EU-optimality and efficiency coincide (see Merton (1971)), we find that for short durations they do not differ significantly. However, for longer durations -that are typical in pension funds -the extent of inefficiency turns out to be remarkable and should be taken into account by pension fund investment managers seeking appropriate rules for portfolio selection. Indeed, we see this result as a fourth reason for supporting the use of the target-based approach in DC pension schemes.

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Section: Introductionmentioning

confidence: 99%

On efficiency of mean–variance based portfolio selection in defined contribution pension schemes

Vigna

2012

Quantitative Finance

103

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“…Por ejemplo, Devolder et al (2003) derivan múltiples estrategias óptimas para diferentes funciones de utilidad. Bajo las mismas condiciones, la eficiencia de la estrategia media-varianza en planes de pensiones DC es estudiada en Vigna et al (2014).…”

Section: Comisión Por Saldounclassified

Metodología para comparar comisiones por flujo y saldo en fondos de pensiones

Chavez-Bedoya

2016

Estudios de Economía

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“…Here, we note that if the elasticity parameter θ is zero, then σ θ becomes the constant σ 0 and (4.23) reduces to the optimal strategy corresponding to the Black-Scholes model, where risky asset price evolves with a geometric Brownian motion. Indeed, this is given by the classical (original) Merton coefficient (see Devolder et al [12]) as follows:…”

Section: Corrected Merton Strategiesmentioning

confidence: 99%

“…On the other hand, there is much literature about DC pension plans. See Boulier et al [3], Haberman and Vigna [19], Devolder et al [12] and Deelstra et al [11] to name a few. But these studies have assumed to take the geometric Brownian motion with constant volatility (the Black-Scholes model) for an underlying asset price model.…”

Section: Introductionmentioning

confidence: 99%