5 A numerical technique based on the embedding technique proposed in [21, 33] for dynamic 6 mean-variance (MV) optimization problems may yield spurious points, i.e. points which are not 7 on the efficient frontier. In [27], it is shown that spurious points can be eliminated by examining 8 the left upper convex hull of the solution of the embedded problem. However, any numerical 9 algorithm will...

Over the past twenty years, macroeconomic performance has improved in industrialized and developing countries alike. In a broad cross-section of countries inflation volatility has fallen markedly while output variability has either fallen or risen only slightly. This increased stability can be attributed to either: 1) more efficient policymaking by the monetary authority, 2) a reduction in the ...

This study evaluates operation performances of 67 international tourist hotels in Taiwan by using the Context-dependent DEA model of Date Envelopment Analysis (DEA) in order to find out the performance of these hotels and their competitive advantages. This study differentiates the levels of efficient frontier with the efficiency of each international tourist hotel. Based on the efficiency, the ...

We compare, using data envelopment analysis (DEA), the performance of Islamic and conventional banks prior to, during and immediately after the 2008 financial crisis (2004-2009). There is no significant difference in mean efficiency between conventional and Islamic banks when efficiency is measured relative to a common frontier. A meta-frontier analysis (MFA), new to the banking context, howeve...

In data envelopment analysis (DEA) efficient decision making units (DMUs) are of primary importance as they define the efficient frontier. By means of modified CCR model, in which the test DMU is excluded from the reference set, we are able to determine what perturbations of data can be tolerated before frontier DMUs become nonfrontier. In this paper we discuss simultaneous data perturbations i...

Many important problems of graph enumeration and indexing can be solved by frontier-based methods, which construct ZDDs in a breadth-first manner from the top to the bottom. We present new techniques toward an efficient framework to deal with the frontier-based methods. Ad hoc parts of the algorithm are encapsulated using the recursive specifications that represent properties to be compiled int...

Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances of the individual subsystems. It then becomes necessary to consider the tradeoffs that occur in a ...

In many practical investment situations the amount of available memory on stock data is extremely huge. Thus many investors are attracted to base their decisions on the information "currently available in their minds" (see [1, 2]). In the present paper various risk measurement models having application in the investment management are discussed. First we explain the concept of mean variance eff...

Markov chain Monte Carlo (MCMC) methods have become a ubiquitous tool in Bayesian analysis. This paper implements MCMC methods for Bayesian analysis of stochastic frontier models using the WinBUGS package, a freely available software. General code for cross-sectional and panel data are presented and various ways of summarizing posterior inference are discussed. Several examples illustrate that ...

The paper addresses the constrained mean-semivariance portfolio optimization problem with the support of a novel multi-objective evolutionary algorithm (n-MOEA). The use of semivariance as the risk quantification measure and the real world constraints imposed to the model make the problem difficult to be solved with exact methods. Thanks to the exploratory mechanism, n-MOEA concentrates the sea...