Systematic liquidity: commonality and inter-temporal variation in the Portuguese stock market

[EN] The aim of this paper is to study systematic liquidity at the Euronext Lisbon Stock Exchange. The motivation for this research is provided by the growing interest in financial literature about stock liquidity and the implications of commonality in liquidity for asset pricing since it could represent a source of non-diversifiable risk. Namely, it is analysed whether there exist common factors that drive the variation in individual stock liquidity and the causes of the inter-temporal variation of aggregate liquidity. Monthly data for the period between January 1988 and December 2011 is used to compute some of the most used proxies for liquidity: bid-ask spreads, turnover rate, trading volume, proportion of zero returns and the illiquidity ratio. Following Chordia et al. (2000) methodology, some evidence of commonality in liquidity is found in the Portuguese stock market when the proportion of zero returns is used as a measure of liquidity. In relation to the factors that drive the inter-temporal variation of the Portuguese stock market liquidity, the results obtained within a VAR framework suggest that changes in real economy activity, monetary policy (proxied by changes in monetary aggregate M1) and stock market returns play an important role as determinants of commonality in liquidity.

Contributions to the efficient use of general purpose coprocessors: kernel density estimation as case study

142 p.

Understanding Density in an Uneven City, Santiago de Chile: Implications for Social and Environmental Sustainability

Efforts to promote infill development and to raise densities are growing in many cities around the world as a way to encourage urban sustainability. However, in cities polarized along socio-economic lines, the benefits of densification are not so evident. The aim of this paper is to discuss some of the contradictions of densification in Santiago de Chile, a city characterized by socio-spatial disparities. To that end, we first use regression analysis to explain differences in density rates within the city. The regression analysis shows that dwelling density depends on the distance from the city center, socioeconomic conditions, and the availability of urban attributes in the area. After understanding the density profile, we discuss the implications for travel and the distribution of social infrastructures and the environmental services provided by green areas. While, at the metropolitan scale, densification may favor a more sustainable travel pattern, it should be achieved by balancing density rates and addressing spatial differences in the provision of social services and environmental amenities. We believe a metropolitan approach is essential to correct these spatial imbalances and to promote a more sustainable and socially cohesive growth pattern.

Density-potential mapping in the standard and quantum electrodynamical time-dependent density functional theory

131 p.