The Steiner Travelling Salesman Problem (STSP) is a variant of the TSP that is suitable for instances defined on road networks. We consider an extension of the STSP in which the road traversal costs are both stochastic and correlated. This happens, for example, when vehicles are prone to delays due to rush hours, road works or accidents. Following the work of Markowitz on portfolio selection, w...

The portfolio optimization model, initially proposed by Markowitz in 1952 and known as mean-variance model (MV model), is applied to find the optimized allocation among assets to get higher investment return and lower investment risk. However, the MV model did not consider some practical limitations of financial market, including: (1) transaction cost and (2) minimal transaction lots. While the...

credit allocation through the usage of portfolio optimization mainly seeks tomaximize return and minimize the risk of the portfolio; but there are other importantissues including sustainable development which is important for government/publicsectors. this paper presents a novel credit allocation approach based on portfoliooptimization and investigates the effects of selected indicators of sust...

this paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. the mean variance model of portfolio optimization that was introduced by markowitz includes two objective functions; these two criteria, risk and return do not encompass all of the information about investment; information like annual dividends, s&p star ranking and return in later years which...

This paper extends Merton’s continuous time (instantaneous) mean-variance analysis and the mutual fund separation theory. Given the existence of a Markovian state price density process, the optimal portfolios from concave utility maximization are instantaneously mean-variance efficient independent of the concave utility function’s form. The Capital Asset Pricing Model holds with the market port...

For many image processing applications, the aim is to detect a certain event or occurrence in a noisy data set. Several algorithms may exist that solve the detection problem. An example is the detection of edges. The subsequent difficulty then is how to select a proper weighting scheme for the algorithms so that the results are combined optimally. To achieve proper fusion of detection outputs, ...

This work aims the development of an enhanced portfolio selection method, which is based on the classical portfolio theory proposed by Markowitz (1952) and incorporates the local Gaussian correlation model for optimization. This novel method of portfolio selection incorporates two assumptions: the non-linearity of returns and the empirical observation that the relation between assets is dynamic...

Several attempts have been made to reduce the impact of estimation errors on the optimal portfolio composition. On the one hand, improved estimators of the necessary moments have been developed and on the other hand, heuristic methods have been generated to enhance the portfolio performance, for instance the "resampled efficiency" of Michaud (1998). We compare the out-ofsample performance of tr...

This paper investigates the robustness of conventional mean-variance (MV) optimization model by making two adjustments within MV formulation. First, portfolio selection based on a behavioral decision-making theory that encapsulates statistics and investors psychology. The second aspect involves capturing asset dependence structure through copula. Using (BMV) copula (CBMV), results show stocks w...

In this paper, linear Data Envelopment Analysis models are used to estimate Markowitz efficient frontier. Conventional DEA models assume non-negative values for inputs and outputs. however, variance is the only variable in these models that takes non-negative values. Therefore, negative data models which the risk of the assets had been used as an input and expected return was the output are uti...