The study area is focused on the Philippine Trench, a hadal trench located in the axe of the collision of the Philippine Sea Plate and Sunda Plate, west Pacific Ocean. The research is aimed at the analysis of the trench geomorphology by a correlation between changes in slope steepness and...

This paper presents a methodology which blends sensitivity analysis and fuzzy arithmetic for managing uncertainty in project financing transactions. Specifically, we adopt the perspective of the equityholders and use the average Return On Equity (ROE) to measure shareholder value creation and,...

This paper uses machine learning approaches to explore the association between traffic volume, air pollution, and meteorological conditions. A focus is the interaction between these factors. The paper does this using hourly data for Oslo, Norway. I considered a total of ten datasets to verify...

This paper formulates a conformity test for cointegration for a multivariate I(1) process obeying a VAR specification. The test statistic is a function of the characteristic roots of the sample covariance matrix of the cointegral vector; the latter is obtained from the unrestricted estimation of...

This paper takes a fresk look at testing hypotheses on dimensionality in the MANOVA model.

In this research, we optimized fixed, glide path and dynamic portfolios, aimed at providing a solid pension adjusted for inflation. We optimized these portfolios for two performance functions that take inflation rates into account. We compared the performance of these portfolios in terms of...

In this paper we suggest a new technique to construct Markov processes by means of products of copula functions, in the spirit of Darsow et al, (1992). The approach requires to define: i) a sequence of distribution functions of the increments of the process; ii) a sequence of copula functions...

The article investigates the use of adaptive learning algorithms in constructing dynamic portfolios replicating the return characteristics of a given hedge fund. The emphasis is on out of sample conditional predictive capabilites as necessary to serve as a valuable risk management tool, rather...

The purpose of this paper is to develop Bayesian inference for matrix-variate dynamic linear models (MV-DLMs), in order to allow missing observation and variance intervention, of any sub-vector or sub-matrix of the observation time series matrix. The established inverted Wishart distribution of...