Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous‐time Markowitz portfolio selection problem where the model uncertainty affects the covariance matrix of multiple risky assets. This problem is formulated into a min–max mean‐variance problem over a set of nondominated probability measures that is solved by a McKean–Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman–Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.     

Distinctive Features of Environmental Innovators: An Econometric Analysis

This paper analyzes the main determinants influencing environmental innovators (i.e. firms developing or adopting environmental innovations) in Spain with respect to non‐environmental innovators. Similarly to other contributions in the literature, our results show that Spanish environmental innovators respond to regulatory stimulus in the form of demand‐pull and technology‐push instruments. They have a high internal technological capability and combine internal and external information sources, mostly in cooperation with knowledge institutions. Environmental innovators are more concentrated in mature, traditionally highly polluting sectors, but new firms are not more environmentally innovative than incumbents. Most importantly, in contrast to other environmental innovation studies, mostly carried out in a German context, we have not found evidence of a market pull from either the domestic or international markets. Furthermore, cost savings are not found to be a distinctive driver for environmental innovators. These differential results are possibly related to the special features of Spain regarding its national innovation system and the degree of stringency of environmental regulation and environmental consciousness of its consumers. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment.     

Do institutional investors drive corporate transparency regarding business contribution to the sustainable development goals?

Institutional investors show increasing interest in how companies align their corporate social responsibility strategies with the sustainable development goals (SDGs) proposed by the United Nations (UN). The information disclosed in this regard is essential to know and monitor business contribution to the 2030 Agenda. In this paper, we analyze the influence that institutional investors have on the adoption of the disclosure strategy established by UN and the Global Reporting Initiative (GRI)—GRI‐SDG Compass. The results obtained for a sample of 989 international companies, which prepare their sustainability reports following the GRI guidelines, show that ownership by foreign investors, pension funds, and “other” investors boosts the relevance of the information disclosed in relation to the 2030 Agenda. On the contrary, government, financial institutions, and cross holdings have no impact on the information systems developed.     

Tests of Normality of Functional Data

The paper is concerned with testing normality in samples of curves and error curves estimated from functional regression models. We propose a general paradigm based on the application of multivariate normality tests to vectors of functional principal components scores. We examine finite sample performance of a number of such tests and select the best performing tests. We apply them to several extensively used functional data sets and determine which can be treated as normal, possibly after a suitable transformation. We also offer practical guidance on software implementations of all tests we study and develop large sample justification for tests based on sample skewness and kurtosis of functional principal component scores.     

A Geometrical Interpretation of Collinearity: A Natural Way to Justify Ridge Regression and Its Anomalies

Justifying ridge regression from a geometrical perspective is one of the main contributions of this paper. To the best of our knowledge, this question has not been treated previously. This paper shows that ridge regression is a particular case of raising procedures that provide greater flexibility by transforming the matrix X associated with the model. Thus, raising procedures, based on a geometrical idea of the vectorial space associated with the columns of matrix X , lead naturally to ridge regression and justify the presence of the well-known constant k on the main diagonal of matrix X ^′ X . This paper also analyses and compares different alternatives to raising with respect to collinearity mitigation. The results are illustrated with an empirical application.     

A unified framework for robust modelling of financial markets in discrete time

Finance and Stochastics - We unify and establish equivalence between the pathwise and the quasi-sure approaches to robust modelling of financial markets in finite discrete time. In particular, we...     

Police-Monitored Cameras and Crime*

We study the effects of police monitoring on crime. We exploit detailed information on the location and date of installation of police-monitored surveillance cameras, coupled with data at the street-segment level on all reported crimes in the city of Montevideo, Uruguay. We find that the introduction of police-monitored surveillance cameras reduces crime by about 20 percent in monitored areas relative to a pure control group located outside the city. We also explore potential displacement effects, and we do not find evidence of such effects.     

Disappearing investment-cash flow sensitivities: Earnings have not become a worse proxy for cash flow

According to a recent conjecture in the literature, earnings have become a poorer proxy for cash flow from operations over time. We find that since 1988, when cash flow statements started to be consistently reported in Compustat, the cash effectiveness of earnings has actually increased for a large sample of US manufacturing firms. This occurs despite the introduction of fair value accounting and increasing accounting accruals during the last three decades. Also contrary to the conjecture, using more comprehensive measures of cash flow does not restore the investment-cash flow sensitivity, which continues to be around 0.05 in more recent periods.     

Country-by-Country Reporting: A Step Towards Unitary Taxation?

Intereconomics - Multinational companies are now obliged to deliver an annual report to the tax authorities with information disaggregated by country (country-by-country reporting) in order to show...     

Do analysts add value when they most can? Evidence from corporate spin‐offs

This article investigates how securities analysts help investors understand the value of diversification. By studying the research that analysts produce about companies that have announced corporate spin‐offs, we gain unique insights into how analysts portray diversified firms to the investment community. We find that while analysts' research about these companies is associated with improved forecast accuracy, the value of their research about the spun‐off subsidiaries is more limited. For both diversified firms and their spun‐off subsidiaries, analysts' research is more valuable when information asymmetry between the management of these entities and investors is higher. These findings contribute to the corporate strategy literature by shedding light on the roots of the diversification discount and by showing how analysts' research enables investors to overcome asymmetric information. Copyright © 2013 John Wiley & Sons, Ltd.