Improved estimation of the covariance matrix of stock returns with an application to portofolio selection

This paper proposes to estimate the covariance matrix of stock returnsby an optimally weighted average of two existing estimators: the samplecovariance matrix and single-index covariance matrix. This method isgenerally known as shrinkage, and it is standard in decision theory andin empirical Bayesian statistics. Our shrinkage estimator can be seenas a way to account for extra-market covariance without having to specifyan arbitrary multi-factor structure. For NYSE and AMEX stock returns from1972 to 1995, it can be used to select portfolios with significantly lowerout-of-sample variance than a set of existing estimators, includingmulti-factor models.

An attempt to go beyond conventional financial accounting information

Conventional financial accounting informationis slanted in favour of certain economic interests. This paper argues in favour ofaccounting information capturing and showingrelevant aspects of the economic-social situation,and of decision-making based on it allowingfor decisions to be taken with economic-social,and not purely economic-weighted, awareness.

Flexible multivariate GARCH modeling with an application to international stock markets

The goal of this paper is to estimate time-varying covariance matrices.Since the covariance matrix of financial returns is known to changethrough time and is an essential ingredient in risk measurement, portfolioselection, and tests of asset pricing models, this is a very importantproblem in practice. Our model of choice is the Diagonal-Vech version ofthe Multivariate GARCH(1,1) model. The problem is that the estimation ofthe general Diagonal-Vech model model is numerically infeasible indimensions higher than 5. The common approach is to estimate more restrictive models which are tractable but may not conform to the data. Our contributionis to propose an alternative estimation method that is numerically feasible,produces positive semi-definite conditional covariance matrices, and doesnot impose unrealistic a priori restrictions. We provide an empiricalapplication in the context of international stock markets, comparing thenew estimator to a number of existing ones.

Indentifying human capital externalities: Theory with an application to US cities

The identification of aggregate human capital externalities is still not fully understood. The existing (Mincerian) approach confounds positive externalities with wage changes due to a downward sloping demand curve for human capital. As a result, it yields positive externalities even when wages equal marginal social products. We propose an approach that identifies human capital externalities whether or not aggregate demand for human capital slopes downward. Another advantage of our approach is that it does not require estimates of the individual return to human capital. Applications to US cities and states between 1970 and 1990 yield no evidence of significant average -schooling externalities.

Level shifts in a panel data based unit root test : an application to the rate of unemployment

Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

Level shifts in a panel data based unit root test : an application to the rate of unemployment

Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

Breaking the panels: an application to the GDP per capita

This paper proposes a test statistic for the null hypothesis of panel stationarity that allows for the presence of multiple structural breaks. Two different speci¿cations are considered depending on the structural breaks affecting the individual effects and/or the time trend. The model is ¿exible enough to allow the number of breaks and their position to differ across individuals. The test is shown to have an exact limit distribution with a good ¿nite sample performance. Its application to a typical panel data set of real per capita GDP gives support to the trend stationarity of these series

An introduction to Mediterranean deep-sea biology

This chapter presents the state of the art concerning the deep-sea Mediterranean environment: geology, hydrology, biology and fisheries. These are the fields of study dealt with in the scientific papers of this volume. The authors are specialists who have addressed their research to the Mediterranean deep-sea environment during the last years. This introduction is an overview but not an exhaustive review.

Sequential partitioning: an alternative to understanding size distributions of avalanches in first-order phase transitions

We study the problem of the partition of a system of initial size V into a sequence of fragments s1,s2,s3 . . . . By assuming a scaling hypothesis for the probability p(s;V) of obtaining a fragment of a given size, we deduce that the final distribution of fragment sizes exhibits power-law behavior. This minimal model is useful to understanding the distribution of avalanche sizes in first-order phase transitions at low temperatures.

Assessment of the potential skin irritation of lysine-derivative anionic surfactants using mouse fibroblast and human keratinocytes as an alternative to animal testing

Purpose. The aim of this study was to identify new surfactants with low skin irritant properties for use in pharmaceutical and cosmetic formulations, employing cell culture as an alternative method to in vivo testing. In addition, we sought to establish whether potential cytotoxic properties were related to the size of the counterions bound to the surfactants. Methods. Cytotoxicity was assessed in the mouse fibroblast cell line 3T6, and the human keratinocyte cell line NCTC 2544, using the MTT assay and uptake of the vital dye neutral red 24 h after dosing (NRU). Results. Lysine-derivative surfactants showed higher IC50s than did commercial anionic irritant compounds such as sodium dodecyl sulphate, proving to be no more harmful than amphoteric betaines. The aggressiveness of the surfactants depended upon the size of their constituent counterions: surfactants associated with lighter counterions showed a proportionally higher aggressivity than those with heavier ones. Conclusions. Synthetic lysine-derivative anionic surfactants are less irritant than commercial surfactants such as sodium dodecyl sulphate and Hexadecyltrimethylammonium bromide and are similar to Betaines. These surfactants may offer promising applications in pharmaceutical and cosmetic preparations, representing a potential alternative to commercial anionic surfactants as a result of their low irritancy potential.

Observational methodology in football: Development of an instrument to study the offensiva game in football.

The following paper introduces a new approach to the analysis of offensive game in football. Therefore, the main aim of this study was to create an instrument for collecting information for the analysis of offensive action and interactions game. The observation instrument that was used to accomplish the main objective of this work consists of a combination of format fields (FC) and systems of categories (SC). This methodology is a particular strategy of the scientific method that has as an objective to analyse the perceptible behaviour that occurs in habitual contexts, allowing them to be formally recorded and quantified and using an ad hoc instrument in order to obtain a behaviour systematic registration that, since they have been transformed in quantitative data with the necessary reliability and validity determined level, will allow analysis of the relations between these behaviours. The codifications undertaken to date in various games of football have shown that it serves the purposes for which it was developed, allowing more research into the offensive game methods in football.

An approach to predicting bowing control parameter contours in violin performance

We present a machine learning approach to modeling bowing control parametercontours in violin performance. Using accurate sensing techniqueswe obtain relevant timbre-related bowing control parameters such as bowtransversal velocity, bow pressing force, and bow-bridge distance of eachperformed note. Each performed note is represented by a curve parametervector and a number of note classes are defined. The principal componentsof the data represented by the set of curve parameter vectors are obtainedfor each class. Once curve parameter vectors are expressed in the new spacedefined by the principal components, we train a model based on inductivelogic programming, able to predict curve parameter vectors used for renderingbowing controls. We evaluate the prediction results and show the potentialof the model by predicting bowing control parameter contours from anannotated input score.