How do valuations impact outcomes of asset sales with heterogeneous bidders?

Differences among bidder type-specific outcomes of asset sales are theoretically related to differences in bidders’ valuations and participation. The lead application to quantify these relations is takeover auctions: bidders are classified into strategic and financial, and bids are available. I structurally estimate valuations from all bids. The positive difference in premiums between strategic and financial acquirers is driven by the difference in dispersions of valuations (e.g., strategic bidders’ synergies are more dispersed) and the set of auction participants. The difference in average valuations is relatively unimportant. My approach can help explain outcomes of asset sales, even in settings with limited bidder data.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.     

Does ethics improve stock market resilience in times of instability?

This paper compares the resilience of ethical (Islamic and socially responsible) indexes among five developed (US, UK, Japan, Canada, Australia) and three emerging markets (Brazil, India, South Africa) during the period following the 2008 subprime crisis. It relies on a multivariate CAPM-EGARCH model that accounts for sudden changes in volatility through the application of an iterated cumulative sums of squares (ICSS) algorithm on daily data over the sample period 2008–2014 to model time-varying volatility and ensure reliable estimates. The study confirms the lower systemic risk associated with Islamic indexes during the bearish period and reports that SRI, despite being more subject to systemic risk, offered higher alphas in highly integrated markets, while Islamic indexes performed better in less integrated ones. The evidence also reveals a very limited increase in the models’ predictability power from the integration of sudden changes in volatility into the EGARCH models during the full sample period. This limit is more marked during the bearish sub-period. Our findings have important implications for international investment and portfolio diversification perspectives in times of financial downturn.     

Classification of intraday S&P500 returns with a Random Forest

Stock markets can be interpreted to a certain extent as prediction markets, since they can incorporate and represent the different opinions of investors who disagree on the implications of the available information on past and expected events and trade on their beliefs in order to achieve profits. Many forecast models have been developed for predicting the future state of stock markets, with the aim of using this knowledge in a trading strategy. This paper interprets the classification of the S&P500 open-to-close returns as a four-class problem. We compare four trading strategies based on a random forest classifier to a buy-and-hold strategy. The results show that predicting the classes with higher absolute returns, ‘strong positive’ and ‘strong negative’, contributed the most to the trading strategies on average. This finding can help shed light on the way in which using additional event outcomes for the classification beyond a simple upward or downward movement can potentially improve a trading strategy.     

THE REGIONAL EFFECTS OF MONETARY POLICY: A SURVEY OF THE EMPIRICAL LITERATURE

This survey provides an updated review of the empirical literature on the regional effects of monetary policy in economic activity by means of undertaking a threefold perspective. First, the main methodological dimensions of this literature are examined while pinpointing those modelling or methodological traits that constitute a source of diverging estimates and thereby produce inconclusive evidence. Secondly, the estimates yielded by the literature are summarized by carrying out a cross‐study analysis of the results for each monetary union. By drawing on empirical regularities that are robust across studies, the conclusiveness of the results is assessed, while those monetary unions for which conclusive evidence is still lacking are also identified. Lastly, the sources of regional heterogeneity identified by these studies are reviewed in order to shed some light on the linkage between monetary policy and territorial heterogeneity. As a result of this threefold perspective, this survey delivers overall structured conclusions and updated policy‐relevant lessons. Moreover, various research gaps and emerging topics in the literature are also identified.     

The impact on stock prices of deferral and elimination of internal control audit requirement for small firms

This paper examines the cumulative market reaction to the events related to deferral of internal control audit requirement under the Sarbanes-Oxley Act of 2002 and its elimination under the Dodd-Frank Act of 2010 for nonaccelerated filers (small firms). We document that small firms experienced negative cumulative abnormal returns around these events; and the differences between the cumulative abnormal returns for small firms and the two control groups (accelerated and large accelerated filers) were negative and significant at the 1% level. These results support the notion that market participants value the reliability of financial information irrespective of the firm size. Within the small firms, we find no firm characteristic significantly explains the market reaction to the events considered. That is, all small firms lost market value in reaction to the events that delayed and eliminated their internal control audit requirement.     

Financial development,economic growth and convergence clubs

To study the role of financial development in economic growth, we apply an array of convergence tests designed to capture nonlinear transitional dynamics to real outputs per capita. Strong evidence of multiple convergence clubs is observed, implying that the clubs are formed based on the initial level of real output per capita and average growth rate. Our empirical results show that the stage of economic growth of each country plays an important role for the composition of the convergence clubs. Furthermore, financial development emerges to be a significant determinant, albeit plays differently in the economic growth of each convergence club.     

Illegal waste disposal: Enforcement actions and decentralized environmental policy

Environmental non-compliance is affected by the decentralized shaping of environmental policy by local governments and enforcement actions by public bodies. Illegal waste disposal is examined in a relevant national case, by means of an original regionally disaggregated panel dataset for Italy, a country which witnesses heterogeneous environmental performances across regions and a decentralized policy system. Our empirical analysis produces two main insights of strong policy interest. First, commitment to a more stringent waste policy tends to increase illegal disposal of waste. Second, a nonlinear bell shaped relationship exists between the number of inspections and the quantity of illegal disposal. The key message is that deterrence might only result after a relatively high level of controls is implemented.     

Transboundary pollution externalities: Think globally,act locally?

We analyze the implications of transboundary pollution externalities on environmental policymaking in a spatial setting, in which pollution diffuses across the global spatial economy independently of the specific location in which it is originally generated. This framework gives rise to a simple regional optimal pollution control problem allowing us to compare the global and local solutions in which, respectively, the transboundary externality is and is not taken into account in the determination of the optimal policy by individual local policymakers. We show that it is not obvious that transboundary externalities are a source of inefficiency per se since this is strictly related to the spatial features of the initial distribution of pollution. If the initial pollution distribution is spatially homogeneous then the local and global solutions will coincide and thus no efficiency loss will arise from transboundary externalities, but if it is spatially heterogeneous the local solution will be suboptimal and thus a global approach to environmental problems will be needed to achieve efficiency. From a normative perspective, in this latter (and most realistic) case we also quantify the amount of policy intervention needed at local level in order to achieve the globally desirable goal of pollution eradication in the long run. Our conclusions hold true in a number of different settings, including situations in which the spatial domain is either bounded or unbounded, and situations in which macroeconomic–environmental feedback effects are taken into account.