Multiple diversity measures to identify complementary conservation areas for the Baja California peninsular cacti

The Baja California Peninsula is home to 85 species of cacti, of which 54 are endemic, highlighting its importance as a cactus diverse region within Mexico. Many species are under threat due to collection pressure and habitat loss, but ensuring maximal protection of cacti species requires a better understanding of diversity patterns. We assessed species richness, endemism, and phylogenetic and morphological diversity using herbarium records and a molecular phylogeny for 82 species of cacti found in the peninsula. The four diversity measures were estimated for the existing nature reserve network and for 314 hexagrids of 726 km2. Using the hexagrid data, we surveyed our results for areas that best complement the current protected cacti diversity in the Baja California Peninsula. Currently, the natural reserve network in Baja shelters an important amount of the cacti diversity (74% of the species, 85.9% of the phylogenetic diversity, 76% of endemics and all the growth forms). While species richness produced several solutions to complement the diversity protected, by identifying priority species (endemic species with high contribution to overall PD) one best solution is reported. Three areas (San Matías, Magdalena and Margarita Islands and El Triunfo), selected using species richness, PD and endemism, best complement the diversity currently protected, increasing species richness to 89%, PD to 94% and endemism to 89%, and should be considered in future conservation plans. Two of these areas could be included within nature reserves already established.

Principal-agent issues in asset acquisition: UK institutions and their investment agents

This paper explores principal‐agent issues in the stock selection processes of institutional property investors. Drawing upon an interview survey of fund managers and acquisition professionals, it focuses on the relationships between principals and external agents as they engage in property transactions. The research investigated the extent to which the presence of outcome‐based remuneration structures could lead to biased advice, overbidding and/or poor asset selection. It is concluded that institutional property buyers are aware of incentives for opportunistic behaviour by external agents, often have sufficient expertise to robustly evaluate agents’ advice and that these incentives are counter‐balanced by a number of important controls on potential opportunistic behaviour. There are strong counter‐incentives in the need for the agents to establish personal relationships and trust between themselves and institutional buyers, to generate repeat and related business and to preserve or generate a good reputation in the market.

Analytic approximations for multi-asset option pricing

We derive general analytic approximations for pricing European basket and rainbow options on N assets. The key idea is to express the option’s price as a sum of prices of various compound exchange options, each with different pairs of subordinate multi- or single-asset options. The underlying asset prices are assumed to follow lognormal processes, although our results can be extended to certain other price processes for the underlying. For some multi-asset options a strong condition holds, whereby each compound exchange option is equivalent to a standard single-asset option under a modified measure, and in such cases an almost exact analytic price exists. More generally, approximate analytic prices for multi-asset options are derived using a weak lognormality condition, where the approximation stems from making constant volatility assumptions on the price processes that drive the prices of the subordinate basket options. The analytic formulae for multi-asset option prices, and their Greeks, are defined in a recursive framework. For instance, the option delta is defined in terms of the delta relative to subordinate multi-asset options, and the deltas of these subordinate options with respect to the underlying assets. Simulations test the accuracy of our approximations, given some assumed values for the asset volatilities and correlations. Finally, a calibration algorithm is proposed and illustrated.

Corporate social performance and stock returns: UK evidence from disaggregate measures

This study examines the relation between corporate social performance and stock returns in the UK. We closely evaluate the interactions between social and financial performance with a set of disaggregated social performance indicators for environment, employment, and community activities instead of using an aggregate measure. While scores on a composite social performance indicator are negatively related to stock returns, we find the poor financial reward offered by such firms is attributable to their good social performance on the environment and, to a lesser extent, the community aspects. Considerable abnormal returns are available from holding a portfolio of the socially least desirable stocks. These relationships between social and financial performance can be rationalized by multi-factor models for explaining the cross-sectional variation in returns, but not by industry effects.

Non-normal real estate return distributions by property type in the UK

Investment risk models with infinite variance provide a better description of distributions of individual property returns in the IPD UK database over the period 1981 to 2003 than normally distributed risk models. This finding mirrors results in the US and Australia using identical methodology. Real estate investment risk is heteroskedastic, but the characteristic exponent of the investment risk function is constant across time – yet it may vary by property type. Asset diversification is far less effective at reducing the impact of non‐systematic investment risk on real estate portfolios than in the case of assets with normally distributed investment risk. The results, therefore, indicate that multi‐risk factor portfolio allocation models based on measures of investment codependence from finite‐variance statistics are ineffective in the real estate context