In this paper we exploit properties of the likelihood function of the stochastic volatility model to show that it can be approximated accurately and efficiently using a response surface methodology. The approximation is across the plausible range of parameter values and all possible data and is...

We consider the problem of choosing an optimal portfolio, assuming the asset returns have a Gaussian mixture (GM) distribution, with the objective of maximizing expected exponential utility. In this paper we show that this problem is convex, and readily solved exactly using domain-specific...

Fixed costs of ordering items or setting up a process arise in many real-life scenarios. In their presence, the most widely used ordering policy in the stochastic inventory literature is the (s, S) policy. Optimality of (s, S) policies and (s, S)-type policies have been investigated for various...

We propose estimators and analyze their large-sample distribution for two problems, data-oriented expected performance evaluation and data-oriented stochastic optimization, in presence of a specific class of non-stationarities in the observed data. The considered non-stationarities reflect...

Much of the previous research on supply network resilience examined what capabilities firms should develop and how they develop the capabilities as resilience investment. However, what has received less attention is where to invest resilience in the network. Scholars have debated over what nodes...

We consider the optimal dividend problem in the so-called degenerate bivariate risk model under the assumption that the surplus of one branch may become negative. More specific, we solve the stochastic control problem of maximizing discounted dividends until simultaneous ruin of both branches of...

We study an optimal liquidation problem with multiplicative price impact in which the trend of the asset's price is an unobservable Bernoulli random variable. The investor aims at selling over an infinite time-horizon a fixed amount of assets in order to maximize a net expected profit...