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.

Valuation of Wind Energy Projects: A Real Options Approach

We address the valuation of an operating wind farm and the finite-lived option to invest in it under different reward/support schemes: a constant feed-in tariff, a premium on top of the electricity market price (either a fixed premium or a variable subsidy such as a renewable obligation certificate or ROC), and a transitory subsidy, among others. Futures contracts on electricity with ever longer maturities enable market-based valuations to be undertaken. The model considers up to three sources of uncertainty: the electricity price, the level of wind generation, and the certificate (ROC) price where appropriate. When analytical solutions are lacking, we resort to a trinomial lattice combined with Monte Carlo simulation; we also use a two-dimensional binomial lattice when uncertainty in the ROC price is considered. Our data set refers to the UK. The numerical results show the impact of several factors involved in the decision to invest: the subsidy per MWh generated, the initial lump-sum subsidy, the maturity of the investment option, and electricity price volatility. Different combinations of variables can help bring forward investments in wind generation. One-off policies, e.g., a transitory initial subsidy, seem to have a stronger effect than a fixed premium per MWh produced.