Self-organizing maps could improve the classification of Spanish mutual funds.

In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. The methodology that we propose allows us to identify which mutual funds are misclassified in the sense that they have historical performances which do not conform to the investment objectives established in their official category. According to this, we conclude that, on average, over 40% of mutual funds could be misclassified. Then, we propose an alternative classification, based on a double-step methodology, and we find that it achieves a significantly lower rate of misclassifications. The portfolios obtained from this alternative classification also attain better performances in terms of return/risk and include a smaller number of assets.Finance; Mutual funds; Clustering; Self-organizing map (SOM); Investment analysis;

Risk forecasting models and optimal portfolio selection.

This study analyses, from an investor's perspective, the performance of several risk forecasting models in obtaining optimal portfolios. The plausibility of the homoscedastic hypothesis implied in the classical Markowitz model is dicussed and more general models which take into account assymetry and time varying risk are analysed. Specifically, it studies whether ARCH-type based models obtain portfolios whose risk-adjusted returns exceed those of the classical Markowitz model. The same analysis is performed with models based on the Lower Partial Moment (LPM) which take into account the assymetry in the distribution of returns. The results suggest that none of the models achieve a clearly superior average performance. It is also found that models based on semivariance perform as well as those based on the variance, but not better than, even if the evaluation criterion is based on the Reward-to-Semivariance ratio. When attention turns to the analysis of worst case performance, the results are clearly different. Models which employ LPM with a high degree of risk aversion (n>2) as the risk measure are consistently superior to those which employ a symmetric measure, either homoscedastic or heteroscedastic.

Self-organizing maps could improve the classification of Spanish mutual funds

In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. The methodology that we propose allows us to identify which mutual funds are misclassified in the sense that they have historical performances which do not conform to the investment objectives established in their official category. According to this, we conclude that, on average, over 40% of mutual funds could be misclassified. Then, we propose an alternative classification, based on a double-step methodology, and we find that it achieves a significantly lower rate of misclassifications. The portfolios obtained from this alternative classification also attain better performances in terms of return/risk and include a smaller number of assets.Publicad

Characterization of dust activity on Mars from MY27 to MY32 by PFS-MEX observations

We present spatial and temporal distributions of dust on Mars from Ls = 331 in MY26 until Ls = 80 in MY33 retrieved from the measurements taken by the Planetary Fourier Spectrometer (PFS) aboard Mars Express. In agreement with previous observations, large dust opacity is observed mostly in the southern hemisphere spring/summer and particularly over regions of higher terrain and large topographic variation. We present a comparison with dust opacities obtained from Thermal Emission Spectrometer (TES) - Mars Global Surveyor (MGS) measurements. We found good consistency between observations of two instruments during overlapping interval (Ls = 331 in MY26 until Ls = 77 in MY27). We found a different behavior of the dust opacity with latitude in the various Martian years (inter-annual variations). A global dust storm occurred in MY28. We observe a different spatial distribution, a later occurrence and dissipation of the dust maximum activity in MY28 than in other Martian years. A possible precursor signal to the global dust storm in MY 28 is observed at Ls = 200 - 235 especially over west Hellas. Heavy dust loads alter atmospheric temperatures. Due to the absorption of solar radiation and emission of infrared radiation to space by dust vertically non-uniformly distributed, a strong heating of high atmospheric levels (40 - 50 km) and cooling below around 30 km are observed.Comment: in press in Icarus. 47 pages, 15 figure

REDES NEURONALES ARTIFICIALES: PREDICCIÓN DE LA VOLATILIDAD DEL TIPO DE CAMBIO DE LA PESETA

In this work, we propose the use of Artificial Neural Networks (ANNs), with theobjective of predicting the volatility of peseta exchange rate. Firstly, we perform anexhaustive analysis of the forecasting ability of ANNs by comparing them against otherARCH-type models. The results suggest that ANN are, on average, better than ARCHmodels. Finally, we also propose new hybrid prediction models of volatility, based onANNs, which use the forecasts of different parametric models. Our results show that themodel is generally better, in mean, than other parametric models as well as a linearaggregation of forecasts. El presente trabajo propone el empleo de las Redes Neuronales Artificiales (RNA) al objeto de predecir la volatilidad del tipo de cambio de la peseta. En primer lugar, realizamos una comparación exhaustiva de la capacidad predictiva de las RNA en relación con otros modelos de la clase ARCH. Los resultados sugieren que, en media, las RNA se comportan mejor que los modelos tipo ARCH. Finalmente, también proponemos nuevos modelos híbridos para predecir la volatilidad que, basados en la técnica de las RNA, utilizan las predicciones de diferentes modelos paramétricos. Nuestros resultados muestran que el modelo híbrido que proponemos, en media, por lo general se comporta mejor que los otros modelos paramétricos y que la agregación lineal de las predicciones.Volatilidad, predicción, no linealidad, modelos no paramétricos, redes neuronales artificiales (RNA). Volatility, prediction, no linearity, non parametric models, artificial neural networks (ANNs)

El diagnóstico participativo como herramienta metodológica en la asesoría educativa

El siguiente artículo pretende revisar el proceso de diagnóstico enmarcado dentro de la implementación de la asesoría al Programa Liceos Prioritarios que impulsara el Mineduc dentro de las políticas de apoyo a los establecimientos de Enseñanza Media más vulnerables del país. Se centra la discusión en la conceptualización del diagnóstico participativo y la delimitación de las condiciones básicas para una asesoría dentro de los marcos institucionales de Mineduc. Finalmente, a modo de cierre se presentan algunas indicaciones como propuestas para mejorar los procesos de implementación de asesorías educacionales

Evaluating the physical and mechanical properties of earth plasters with cow dung – a vernacular solution for earth building in Brazil

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Eco-efficient earth plasters: effect of cow dung and air lime on a kaolinitic clayish earth

Earth mortars are eco-efficiently used as plasters, but not all raw earth have a composition and behavior to meet the plasters nowadays requirements. Since long time ago, some stabilizing materials are often added to improve some characteristic of the earth mortars. Thus, to compare the performance of an industrial stabilizer recognized by the literature with a natural stabilizer already established by the Brazilian vernacular construction tradition, this research compared the effects caused by the addition of hydrated air lime and cow dung on the physical and mechanical properties of an earth mortar produced with a Kaolinitic Clay Earth (KCE). For this purpose, laboratory tests were carried out, following the guidelines of the German standard DIN 18947 for the analysis of earth plastering mortars. The results show that the earth mortars stabilized with cow dung presents superior results in all tests performed. Therefore, this is a material with great potential to be investigated as a stabilizer in earth plastering mortars.publishersversionpublishe