The Inefficient Use of Macroeconomic Information in Analysts' Earnings Forecasts in Emerging Markets

This paper presents empirical evidence that security analysts do not efficiently use publicly available macroeconomic information in their earnings forecasts for emerging market stocks. Analysts completely ignore forecasts on political stability, while these provide valuable information for firm-level earnings growth. Analysts do incorporate output growth forecasts, but these actually bear no relevant information for firm-level earnings growth. Inflation forecasts are taken into account correctly. In addition, the information environment appears to be crucially important in emerging markets, as we find evidence that analysts handle macroeconomic information in a better way for more transparent firms

A Recommitment Strategy for Long Term Private Equity Fund Investors

This paper develops a reinvestment strategy for private equity which aims to keep its portfolio weight equal to a desired strategic allocation, while taking into account the illiquid nature of private equity. Historical simulations (1980-2005) show that our dynamic strategy is capable of maintaining a stable investment level that is close to the target. This does not only hold for unrestricted portfolios, but also for investments limited to buyout or venture capital, a specific region, or management experience. This finding is of great importance for investors, because private equity funds have a finite lifetime and uncertain cash flows

The Success Of Stock Selection Strategies In Emerging Markets: Is It Risk Or Behavioral Bias?

We examine competing explanations, based on risk and behavioral models, for the profitability of stock selection strategies in emerging markets. We document that both emerging market risk and global risk factors cannot account for the significant excess returns of selection strategies based on value, momentum and earnings revisions indicators. The findings for value and momentum strategies are consistent with the evidence from developed markets supporting behavioral explanations. In addition, for value stocks, the most important behavioral bias appears to be related to underestimation of long-term growth prospects, as indicated by overly pessimistic analysts' earnings forecasts and above average earnings revisions for longer postformation horizons and by quite rapidly improving earnings growth expectations. Furthermore, we find that overreaction effects play a limited role for the earnings revisions strategy, as there is no clear return reversal up until five years after portfolio formation, setting this strategy apart from momentum strategies

The Economic Value of Fundamental and Technical Information in Emerging Currency Markets

We measure the economic value of information derived from macroeconomic variables and from technical trading rules for emerging markets currency investments. Our analysis is based on a sample of 21 emerging markets with a floating exchange rate regime over the period 1997-2007 and explicitly accounts for trading restrictions on foreign capital movements by using non-deliverable forward data. We document that both types of information can be exploited to implement profitable trading strategies. In line with evidence from surveys of foreign exchange professionals concerning the use of fundamental and technical analysis, we find that combining the two types of information improves the risk-adjusted performance of the investment strategies

Aquatic exposures of chemical mixtures in urban environments: approaches to impact assessment

Urban regions of the world are expanding rapidly, placing additional stress on water resources. Urban water bodies serve many purposes from washing and sources of drinking water to transport and conduits for storm drainage and effluent discharge. These water bodies receive chemical emissions arising from either single or multiple point sources, diffuse sources which can be continuous, intermittent or seasonal. Thus, aquatic organisms in these water bodies are exposed to temporally and compositionally variable mixtures. We have delineated source-specific signatures of these mixtures for diffuse urban runoff and urban point source exposure scenarios to support risk assessment and management of these mixtures. The first step in a tiered approach to assessing chemical exposure has been developed based on the Event Mean Concentration concept with chemical concentrations in runoff defined by volumes of water leaving each surface and the chemical exposure mixture profiles for different urban scenarios. Although generalizations can be made about the chemical composition of urban sources and event mean exposure predictions for initial prioritization, such modelling needs to be complemented with biological monitoring data. It is highly unlikely that the current paradigm of routine regulatory chemical monitoring alone will provide a realistic appraisal of urban aquatic chemical mixture exposures. Future consideration is also needed on the role of non-chemical stressors in such highly modified urban water bodies

Extending the SSD concept to explore some foundational model limitations: a Bayesian hierarchical approach

Species sensitivity distributions are statistical constructs which model interspecies variation of sensitivity to a particular toxic stressor. The current REACH technical guidance document permits the application of SSDs in risk assessment, subject to a number of criteria. Notwithstanding noteworthy criticism received, the SSD is considered by regulators to be a pragmatic model for extrapolating to environmental toxicant concentrations of concern. The manner in which SSDs are currently applied is implicitly dependent on a number of (overlapping) statistical and ecological assumptions. These include (but are not limited to): (1) the measured species toxicity values being precisely known; (2) independence of SSDs for each separate chemical risk assessment; (3) a priori exchangeability of species toxicity values; (4) no correlation between species. In this research we propose a model which generalizes the SSD concept to include chemical effects and shared species effects. It offers flexibility to address or refine each assumption by hierarchically adding layers into the model. Models are fitted to RIVM and US EPA acute-effect toxicity databases under a Bayesian statistical framework to allow for transparent quantification of and flexible propagation of uncertainty. Important insight is gained from the inclusion of ‘species effects’ modelling which, expectedly, indicates increasing differences as taxonomic distances in SSDs increase. The magnitude of measurement error estimated, based on within taxa homogeneity, which also properly accounts for censored measurements, is likely to be of significance to risk assessors and warrant further consideration in either modelling framework. The current quasi-meta-analysis approach towards aggregating multiple chemical-species data points is untenable from an uncertainty viewpoint. Initial results indicate deficiencies in the current SSD concept, thus reducing the credibility and meaningfulness of any subsequently derived hazardous concentrations. Other recent model proposals which act as precursory tools to SSD modelling may not sensibly propagate uncertainty and/or succumb to modelling contradictions. A hierarchical model may overcome this, however will require a more radical approach to defining protection goals and environmental concentrations of concern

Expected Risk as basis for assessment of safe use of chemicals

This paper describes a straightforward modeling procedure to derive ‘expected risk’ (ER) of chemical substances. Starting from proposed use volumes, intended uses, physical and chemical substance properties and toxicity information, the procedure combines multimedia environmental fate modeling with species sensitivity modeling to derive the probability that exposure concentrations exceed critical effect concentrations. The procedure was tested on 1977 so-called mono-constituent organic chemicals that had been registered to be marketed in the EU, after ‘possibility to be used safely’ had been demonstrated by showing that the possible Risk Quotients (RQ) defined as PEC/PNEC ratios (Predicted Exposure Concentration & Predicted No Effect Concentration) were expected to remain below the value of 1, as required by REACH. It appears from this study that (i) RQ and ER of chemicals can be calculated readily, reliably, transparently and reproducibly, that (ii) both RQ and ER can be used to assess whether a new chemical may exceed a chosen acceptability level, but that (iii) in addition ER can be straightforwardly used to rank chemicals according to expected environmental safety. In conclusion, the paper states that modeling ER of chemicals (instead of estimating RQ values), could strengthen the scientific basis of environmental risk assessment for use in REACH. The paper further recommends that more robust environmental risk calculation can be done by using acute EC50, instead of chronic NOEC as critical effect concentration