Asymmetric long memory GARCH: a reply to Hwang's model

Hwang (2001) proposes the FIFGARCH model to represent long memory asymmetric conditional variance. Although he claims that this model nests many previous models, we show that it does not and that the model is badly specified. We propose and alternative specification

Asymmetric long memory garch: a reply to hwang's model

Hwang (Econom. Lett. 71 (2001) 1) proposes the FIFGARCH model to represent long memory asymmetric conditional variances. However, the model is badly specified and does not nest some fractionally integrated heteroskedastic models previously proposed. We suggest an alternative specification and illustrate the results with simulated data.Publicad

Finite sample properties of a QML estimator of Stochastic Volatility models with long memory

We analyse the finite sample properties of a QML estimator of LMSV models. We show up its poor performance for realistic parameter values. We discuss an identification problem when the volatility has a unit root. An empirical analysis illustrates our findings.Publicad

PROPERTIES OF THE SAMPLE AUTOCORRELATIONS IN AUTOREGRESSIVE STOCHASTIC VOLATlLITY MODELS

Time series generated by Stochastic Volatility (SV) processes are uncorrelated although not independent. This has consequences on the properties of the sample autocorrelations. In this paper, we analyse the asymptotic and finite sample properties of the correlogram of series generated by SV processes. It is shown that the usual uncorrelatedness tests could be misleading. The properties of the correlogram of the log-squared series, often used as a diagnostic of conditional heteroscedasticity, are also analysed. It is proven that the more persistent and the larger the variance of volatility, the larger the negative bias of fue sample autocorrelations of that series.

Stochastic volatility models and the Taylor effect

It has been often empirically observed that the sample autocorrelations of absolute financial returns are larger than those of squared returns. This property, know as Taylor effect, is analysed in this paper in the Stochastic Volatility (SV) model framework. We show that the stationary autoregressive SV model is able to generate this property for realistic parameter specifications. On the other hand, the Taylor effect is shown not to be a sampling phenomena due to estimation biases of the sample autocorrelations. Therefore, financial models that aims to explain the behaviour of financial returns should take account of this property

Urban design dimension in the analysis of the Spanish peripheries: The case of Valladolid

During the last decades cities have developed as never before, and their configuration represents a potential testing ground from many different perspectives. The Spanish experience reveals that, although there has been an important increase of the population, the sprawl of urban areas is not proportionally to the increase of population. In the emerging territorial scheme, new urban categories are arising, as land consumption is primary made by infrastructure and some other complementary uses related to the residential ones. Taking this account, the specific aim of this paper is to study what is the spatial configuration and urban design of these new periphery. In other words, by analyzing the growth of the city in these last decades, we will be able to draw an inference from this new condition of occupying the territory in the design and spatial transformation of these new residential areas. Considering the case of Valladolid, an area that new developments have increased in almost 50 percent in the last twenty years -one of the highest rates in Spain-, it is particularly interesting to explore the guidelines that have been drawn in order to clarify the development of these new urban areas, mainly referred to the periphery of the city. The studio will focus not only on the urban politics that were outlined over these two last decades, but on a thorough research of the state of implemented local plans and neighborhoods. Finally, some specific conclusions that result from this study in reference to the residential uses and their urban design and spatial transformation will be stated

On the use of preference-based evolutionary multi-objective optimization for solving a credibilistic portfolio selection model

The portfolio selection problem tries to identify the assets to allocate the capital, and the proportion to be devoted to each asset, for maximizing the returns at the minimum risk. By nature, this is a multi-objective optimization problem. In this work, we propose a three-objective model for portfolio selection, in which the uncertainty of the portfolio returns is modelled by means of LR-power fuzzy variables. We consider as criteria the credibilistic expected return (to be maxi- mized), the below-mean absolute semi-deviation as a risk measure (to be minimized), and a loss function which evaluates the credibility of achieving a non-positive return (to be minimized). The uncorrelation among the risk and loss measures concludes that they provide different information. Budget, cardinality, and diversification constraints are considered. To generate non-dominated portfolios fitting the investor' expectations, preference-based evolutionary algorithms are applied. The preferences are given by aspiration values to be attained by the objectives and profiles representing aggressive, cautious, and conservative investors are analysed. The results for data of the IBEX35 show that portfolios improving the preferences are found in the cautious and aggressive cases, while portfolios with objective values as close as possible to the expectations are obtained in the conservative case. In the generation process, the credibilistic loss has played an important role to and diversified portfolios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec