Eduardo Acosta-González

An empirical examination of the determinants of the shadow economy

Using a statistical methodology guided only by data and based on a genetic algorithm, we select the best econometric model for explaining the determinants of the size of the shadow economy, its main determinants being: taxes on capital gains of individuals, corporate taxes on income, profits and capital gains, domestic credit, bank secrecy, ethnic fractionalization, urban population, globalization, corruption and the socialist legal origin of country.

On the index tracking and the statistical arbitrage choosing the stocks by means of cointegration: the role of stock picking

In this paper, we propose a new methology for Index Tracking (IT) by means of cointegration which provides some significant improvements on that field. As the quality of the tracking portfolio (TP) depends highly on the stock selection procedure, we propose picking the stocks using a model selection technique based on optimizing the cointegration level of the TP and the benchmark index instead of selecting, as in previous papers the assets by ad hoc decisions. To illustrate an empirical application of these techniques we use daily closing prices in the Dow Jones Industrial Average (DJIA) index over two different periods; one period which goes from 1 January 1990 to 31 December 2001 previously used by other authors, and the bear and a turmoil period, which goes from January 2007 to May 2012, inside the current financial crisis. Using only five assets we are able to successfully track the DJIA index and our results improve the IT technique based on cointegration that chooses stocks with maximum capitalization level. We also have compared our results with a more traditional procedure based on correlation and again our results reveal superiority. The empirical illustration not only has been focused on the TP itself, but has also been extended to tracking the index with an added profitability of 5, 10, 15 or 20% and to long-short strategies, producing profitable results.

Assessing the Spatial and Environmental Characteristics of Rural Tourism Lodging Units Using a Geographical Weighted Regression Model

This paper presents a methodology to identify some factors influencing on the tourism market and not usually included in empirical analyses, such as those related to environment and location. The traditional quantitative analysis of spatially varying relationship assumes that the interdependence among variables measured at different locations is constant over the space. This assumption does not fit the data when the analysed variable presents spatial dependence. To face this problem, Geographical Weighted Regression (GWR) may be considered. The methodology proposed in this paper combines a genetic algorithm to automatically select the factors that best explain the dependent variable and GWR to determine the local estimations of the coefficient of regressors. A hedonic price model to analyse the rural tourism market in the island of La Palma (Canary Islands, Spain) was estimated in the study case. The results show that significant regressors are not homogeneously distributed throughout the island. Instead of a constant value, maps of values of the coefficients were obtained. These maps may be helpful to householders in order to implement local actions based on the attributes of the rental price of every house and estimate the economic returns of new rural houses sited in specific areas of the island.

Stock-bond decoupling before and after the 2008 crisis

ABSTRACT In this article, we analyse the co-movements of daily stock prices and government bond prices during the last 25 years, in major Western stock markets, extending previous results to take into account the impact of the current crisis. Our results confirm that bonds are viewed as instruments for improving portfolio diversification in periods of high volatility and falling stock market levels, which is when such diversification is most needed. The possibility of using government debt in portfolios as a means of hedging during times of financial crisis became especially apparent in the crises of 1997, 2001 and 2008. Nevertheless, during the current one, this diversification quality of bonds has disappeared in countries like Italy or Spain, which are also affected by sovereign debt issues.

Estimating time-varying variances and covariances via nearest neighbour multivariate predictions: applications to the NYSE and the Madrid Stock Exchange Index

In this article, we present a technique to obtain the time-varying covariance matrix for several time series for nearest neighbour predictors. To illustrate the use of this technique, we analyse the time-varying variances and correlations between the daily returns on two equity stock market indexes, the New York Stock Exchange and the Madrid Stock Exchange Index.