ElsevierCervelló Royo, RE.; Guijarro Martínez, F.; Michniuk, K. (2015). AbstractThis study introduces a new approximation of the flag price pattern recognition. We develop a trading rule which provides positive risk-adjusted returns for intraday data of the Dow Jones Industrial Average Index. In order to mitigate the data snooping problem we use a data set of more than 90,000 observations, results are reported over 96 different configurations of the trading rule parameters. Furthermore, results are examined over 3 non-overlapping sub-periods. The trading rule provides positive results for all the configurations.

The 17 Sustainable Development Goals (SDGs) adopted by the United Nations are at the center of the global political agenda to eradicate extreme poverty, achieve universal education, promote gender equality and ensure environmental sustainability between others. These goals are organised in 169 indicators, which give an accurate perspective on the main dimensions related with country sustainable development. To gain insight into the relative position of involved countries, it is necessary to develop a composite index that summarises the global progress in the achievement of these goals, but considering possible conflicts and trade-offs between individual SDGs. The objective of this paper is to introduce a Goal Programming model to calculate a composite SDG index, capable of overcoming some of the limitations of celebrated approaches such as arithmetic and geometric averages. The proposed model balances between two extreme solutions: one which calculates a consensus index that reflects the majority trend of the SDGs, and another one which biases the estimated index towards those SDGs that show the most discrepancy with the rest. The model is applied on the EU-28 countries, and shows that the best performing countries regarding the sustainable development are Austria and Luxembourg, while Greece and Romania remain as the worst performers.

We propose an automatic and dynamic trading rule based on flag pattern recognition. The strategy does not depend on the ability of the trader to guess the best configuration of the trading rule. We include several filters for the trades, one of them considering the EMA indicator in short and medium timeframes. The trading rule is applied on a large intraday database for the DJIA index. We can conclude that our proposal is far superior to the previous flag pattern strategies as regards both profitability and risk.

ABSTRACT. Mass appraisal, or the automatic valuation of a large number of real estate assets, has attracted the attention of many researchers, who have mainly approached this issue employing traditional econometric models such as Ordinary Least Squares (OLS). However, this method does not consider the hierarchical structure of the data and therefore assumes the unrealistic hypothesis of the independence of the individuals in the sample. This paper proposes the use of the Hierarchical Linear Model (HLM) to overcome this limitation. The HLM also gives valuable information on the percentage of the variance error caused by each level in the hierarchical model. In this study HLM was applied to a large dataset of 2,149 apartments, which included 17 variables belonging to two hierarchical levels: apartment and neighbourhood. The model obtained high goodness of fit and all the estimated variances of the parameters in HLM were lower than those calculated by OLS. It can be concluded as well that no further neighbourhood variables need be added to the model to improve the goodness of fit, since almost all the residual variance can be attributed to the first hierarchical level of the model, the apartment level.

This paper presents the results of an efficiency study of Colombian public universities in 2012, conducted using the methodology of Data Envelopment Analysis (DEA) and the models CCR, BCC and SBM under output orientation. The main objective is to determine technical, pure technical, scale and mix efficiencies using data acquired from the Ministry of National Education. An analysis of the results shows the extent to which outputs of inefficient Higher Education Institutions (HEIs) could be improved and the possible cause of this inefficiency. The universities were also ranked using a Pareto efficient cross-efficiency model and a study was made of changes to overall productivity between 2011 and 2012. The results showed Tolima, Caldas and UNAD to be the best-performing universities, with Universidad del Pacífico as the worst performer.Malmquist index was applied to analyze the change in productivity from