Randomised Mixture Models for Pricing Kernels

Numerous kinds of uncertainties may affect an economy, e.g. economic, political, and environmental ones. We model the aggregate impact by the uncertainties on an economy and its associated financial market by randomised mixtures of Lévy processes. We assume that market participants observe the randomised mixtures only through best estimates based on noisy market information. The concept of incomplete information introduces an element of stochastic filtering theory in constructing what we term “filtered Esscher martingales”. We make use of this family of martingales to develop pricing kernel models. Examples of bond price models are examined, and we show that the choice of the random mixture has a significant effect on the model dynamics and the types of movements observed in the associated yield curves. Parameter sensitivity is analysed and option price processes are derived. We extend the class of pricing kernel models by considering a weighted heat kernel approach, and develop models driven by mixtures of Markov processes.     

The effects of analyst forecasts and earnings trends on perceptions of management forecast credibility

We examine whether analyst forecasts influence investors’ perceptions of the credibility of a good news management earnings forecast. We hypothesize that the effect of analyst forecasts will depend on whether the analyst forecast confirms management’s forecast and the extent to which management’s forecast is consistent with the prior earnings trend. Findings indicate that the positive effect of a confirming analyst forecast is greater when the management forecast is trend inconsistent than when it is trend consistent. The negative effect of a disconfirming analyst forecast does not differ based on management forecast trend consistency.     

Climate Change and Asset Prices: Are Corporate Carbon Disclosure and Performance Priced Appropriately?

This paper empirically assesses the relevance of information on corporate climate change disclosure and performance to asset prices, and discusses whether this information is priced appropriately. Findings indicate that corporate disclosures of quantitative greenhouse gas (GHG) emissions and, to a lesser extent, carbon performance are value relevant. We use hand‐collected information on quantitative GHG emissions for 433 European companies and build portfolios based on GHG disclosure and performance. We regress portfolios on a standard four factor model extended for industry effects over the years 2005 to 2009. Results show that investors achieved abnormal risk‐adjusted returns of up to 13.05% annually by exploiting inefficiently priced positive effects of (complete) GHG emissions disclosure and good corporate climate change performance in terms of GHG efficiency. Results imply that, firstly, information costs involved in carbon disclosure and management do not present a burden on corporate financial resources. Secondly, investors should not neglect carbon disclosure and performance when making investment decisions. Thirdly, during the period analysed, financial markets were inefficient in pricing publicly available information on carbon disclosure and performance. Mandatory and standardised information on carbon performance would consequently not only increase market efficiency but result in better allocation of capital within the real economy.     

Sectoral Survey‐based Confidence Indicators for Europe*

We analyse a novel dataset of Business and Consumer Surveys, using dynamic factor techniques, to produce composite coincident indices (CCIs) at the sectoral level for the European countries and for Europe. Surveys are timely available, not subject to revision, and fully comparable across countries. Moreover, the substantial discrepancies in activity at the sectoral level justify the interest in sectoral disaggregation. Compared with the confidence indicators produced by the European Commission we show that factor‐based CCIs, using survey answers at a more disaggregate level, produce higher correlation with the reference series for the majority of sectors and countries.     

Regulating Rates of Return Do Gravitate in US Manufacturing!

In this paper we test for the gravitation of regulating return rates, namely those return rates yielded by capital goods incorporating the best methods of production. We define them within a vintage capital model taking into consideration capacity utilization, capital depreciation and wages of workers using past capital vintages. We consider two data sets regarding US manufacturing activities and we find that gravitation does take place. Our results are contrasted with those of the previous literature. Research and policy implications are discussed.     

Beyond choice: investigating the sensitivity and validity of measures of strength of preference

Many experiments investigating different decision theories have relied heavily on pairwise choices between lotteries. These are easy to incentivise, but often yield only limited dichotomous information. This paper considers whether respondents’ judgments about their strength of preference (SoP) for one alternative over another can usefully supplement standard choice data. We report extensive evidence that such judgments show sensitivity to variations in question format and parameter values in the directions we should expect, not only within-subject but also between-sample. We illustrate how such judgments can usefully supplement standard pairwise choice data and enrich our understanding of observed behaviour.