In this paper we focus on robust linear optimization problems with uncertainty regions defined by φ-divergences (for example, chi-squared, Hellinger, Kullback-Leibler). We show how uncertainty regions based on φ-divergences arise in a natural way as confidence sets if the uncertain parameters contain elements of a probability vector. Such problems frequently occur in, for example, optimization problems in inventory control or finance that involve terms containing moments of random variables, expected utility, etc. We show that the robust counterpart of a linear optimization problem with φ-divergence uncertainty is tractable for most of the choices of φ typically considered in the literature. We extend the results to problems that are nonlinear in the optimization variables. Several applications, including an asset pricing example and a numerical multi-item newsvendor example, illustrate the relevance of the proposed approach.
In this paper we focus on robust linear optimization problems with uncertainty regions defined by φ-divergences (for example, chi-squared, Hellinger, Kullback-Leibler). We show how uncertainty regions based on φ-divergences arise in a natural way as confidence sets if the uncertain parameters contain elements of a probability vector. Such problems frequently occur in, for example, optimization problems in inventory control or finance that involve terms containing moments of random variables, expected utility, etc. We show that the robust counterpart of a linear optimization problem with φ-divergence uncertainty is tractable for most of the choices of φ typically considered in the literature. We extend the results to problems that are nonlinear in the optimization variables. Several applications, including an asset pricing example and a numerical multi-item newsvendor example, illustrate the relevance of the proposed approach.
This study examines a setting in which a tax‐reporting decision is delegated to a firm's tax manager. Using financial accounting measures of tax expense to evaluate the tax manager allows the firm to efficiently attain the level of tax avoidance it prefers, despite the fact that the consequences of the tax‐reporting decision will occur in the future. The study also examines how well two accounting measures of tax aggressiveness — cash taxes paid and the unrecognized tax benefit — distinguish between conservative and aggressive firms.
Payments of life insurance products depend on the uncertain future evolution of survival probabilities. This uncertainty is referred to as longevity risk. Existing literature shows that the effect of longevity risk on single life annuities can be substantial, and that there exists a (natural) hedge potential from combining single life annuities with death benefits or from investing in survivor swaps. The effect of financial risk on these hedge effects is typically ignored. The aim of this paper is to quantify longevity risk in portfolios of mortality-linked assets and liabilities, taking into account the effect of financial risk. We find that investment risk significantly affects the impact of longevity risk in life insurance products. It also significantly affects the hedge potential that arises from combining life insurance products, or from investing in longevity-linked assets. For example, our results suggest that ignoring the effect of financial risk can lead to severe overestimation of the natural hedge potential from death benefits, and underestimation of the hedge effects of survivor swaps.
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