Dividend policy

The aim of this article is to analyze the various aspects of dividend policy. Emphasizing tax issues, theoretical frameworks of informational asymmetry of corporate governance and life cycles, we show that a static vision of dividends has been gradually replaced by a dynamic vision. Nevertheless, in spite of the numerous studies dealing with this topic, Black’s (1976) dividend puzzle still remains unsolved

Quantitative Ultrasound and B-mode Image Texture Features Correlate with Collagen and Myelin Content in Human Ulnar Nerve Fascicles

We investigate the usefulness of quantitative ultrasound (QUS) and B-mode texture features for characterization of ulnar nerve fascicles. Ultrasound data were acquired from cadaveric specimens using a nominal 30 MHz probe. Next, the nerves were extracted to prepare histology sections. 85 fascicles were matched between the B-mode images and the histology sections. For each fascicle image, we selected an intra-fascicular region of interest. We used histology sections to determine features related to the concentration of collagen and myelin, and ultrasound data to calculate backscatter coefficient (-24.89 dB $\pm$ 8.31), attenuation coefficient (0.92 db/cm-MHz $\pm$ 0.04), Nakagami parameter (1.01 $\pm$ 0.18) and entropy (6.92 $\pm$ 0.83), as well as B-mode texture features obtained via the gray level co-occurrence matrix algorithm. Significant Spearman's rank correlations between the combined collagen and myelin concentrations were obtained for the backscatter coefficient (R=-0.68), entropy (R=-0.51), and for several texture features. Our study demonstrates that QUS may potentially provide information on structural components of nerve fascicles

The Limitations of Optimization from Samples

In this paper we consider the following question: can we optimize objective functions from the training data we use to learn them? We formalize this question through a novel framework we call optimization from samples (OPS). In OPS, we are given sampled values of a function drawn from some distribution and the objective is to optimize the function under some constraint. While there are interesting classes of functions that can be optimized from samples, our main result is an impossibility. We show that there are classes of functions which are statistically learnable and optimizable, but for which no reasonable approximation for optimization from samples is achievable. In particular, our main result shows that there is no constant factor approximation for maximizing coverage functions under a cardinality constraint using polynomially-many samples drawn from any distribution. We also show tight approximation guarantees for maximization under a cardinality constraint of several interesting classes of functions including unit-demand, additive, and general monotone submodular functions, as well as a constant factor approximation for monotone submodular functions with bounded curvature

Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model

The aim of this study is to show how a Kohonen map can be used to increase the forecasting horizon of a financial failure model. Indeed, most prediction models fail to forecast accurately the occurrence of failure beyond one year, and their accuracy tends to fall as the prediction horizon recedes. So we propose a new way of using a Kohonen map to improve model reliability. Our results demonstrate that the generalization error achieved with a Kohonen map remains stable over the period studied, unlike that of other methods, such as discriminant analysis, logistic regression, neural networks and survival analysis, traditionally used for this kind of task

International expansion and home-country resource acquisition: a signaling perspective of emerging-market firms’ internationalization

Despite growing attention to the role of home countries in studies of emerging-market multinational enterprises (EMNEs), there is limited focus on how international expansion affects EMNEs’ home conditions. Drawing on signaling theory, we propose that EMNEs’ international expansions serve as a signaling mechanism that shapes perceptions of stakeholders in their home countries and thus facilitate their resource acquisition from these stakeholders. The signaling effect is strengthened when EMNEs enter more advanced host countries where higher entry barriers incur higher signaling costs that serve as isolating mechanisms; and when they are located in less developed home markets where information asymmetry is more serious due to weaker institutional arrangements. Furthermore, congruent signals, such as patents, strengthen the main effect by cross-confirming the signaled content, while incongruent signals, such as political connections, weaken it due to ambiguity in interpreting the original signal. Using instrumental variables and a difference-in-differences design to account for potential endogeneity of international expansion, our empirical analysis of Chinese-listed privately owned enterprises from 1999 to 2019 supports our propositions