Investors typically measure an asset’s potential to diversify a portfolio by its correlations with the portfolio’s other assets, but correlation is useful only if it provides a good estimate of how an asset’s returns co-occur cumulatively with the other asset returns over the investor’s...

We review two complementary mixture-based clustering approaches for modeling unobserved heterogeneity in an insurance portfolio: the generalized linear mixed cluster-weighted model (CWM) and mixture-based clustering for an ordered stereotype model (OSM). The latter is for modeling of ordinal...

A fast method based on coordinate-wise descent algorithms is developed to solve portfolio optimization problems in which asset weights are constrained by Lq norms for 1=q=2. The method is first applied to solve a minimum variance portfolio (mvp) optimization problem in which asset weights are...

Diversification is a fundamental topic for all investors but there remains little agreement on how to measure it. Often it is defined ambiguously through risk-based portfolio construction techniques. Recently it has been suggested to connect maximising diversification with minimising risk...

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite dimensional states that are conditional distribution of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It...

We consider a stochastic multi-product inventory model with a ware-housing constraint with the objective of minimizing the expected long-run average cost. Using the vanishing discount approach, a dynamic programming equation and the corresponding verification result are established. The...

This paper is concerned with finding an optimal inventory policy for a finite horizon, two-stage inventory model. In this model, products may be manufactured in two stages. The first stage uses raw material from an external supplier and the second stage uses raw material from defective items...

We analyze a price-setting news-vendor problem with an additive – multiplicative demand. We show that the uni-modality of the news-vendor profit function holds when the underlying random term has an increasing failure rate and the demand functions satisfy certain concavity conditions....

Expectation maximization (EM) algorithm is a popular and powerful mathematical method for parameter estimation in case that there exist both observed data and hidden data. The EM process depends on an implicit relationship between observed data and hidden data which is specified by a mapping...