我国银行理财业务发展趋势研究

对国内商业银行理财业务的发展状况进行了简要概述， 进而对理财业务开展过程中的一些问题进行了分析， 强调指出市场化应该成为银行理财业务转型升级和创新发展的方向， 并提出了实现市场化发展方向的若干具体措施。     

Brexit: Tracking and disentangling the sentiment towards leaving the EU

On 23 June, 2016, the UK held a referendum to decide whether to stay in the European Union or leave. The uncertainty surrounding the outcome of this referendum had major consequences for public policy, investment decisions, and currency markets. We discuss some of the subtleties involved in smoothing and disentangling poll data in light of the problem of tracking the dynamics of the intention to Brexit, and propose a multivariate singular spectrum analysis method that produces trendlines on the unit simplex. The trendline yield via multivariate singular spectrum analysis is shown to resemble that of local polynomial smoothing, and singular spectrum analysis presents the nice feature of disentangling the dynamics directly into components that can be interpreted as changes in public opinion or sampling error. The merits and disadvantages of some different approaches for obtaining smooth trendlines on the unit simplex are contrasted, in terms of both local polynomial smoothing and multivariate singular spectrum analysis.     

Crime prediction by data-driven Green’s function method

We develop an algorithm that forecasts cascading events, by employing a Green’s function scheme on the basis of the self-exciting point process model. This method is applied to open data of 10 types of crimes happened in Chicago. It shows a good prediction accuracy superior to or comparable to the standard methods which are the expectation–maximization method and prospective hotspot maps method. We find a cascade influence of the crimes that has a long-time, logarithmic tail; this result is consistent with an earlier study on burglaries. This long-tail feature cannot be reproduced by the other standard methods. In addition, a merit of the Green’s function method is the low computational cost in the case of high density of events and/or large amount of the training data.     

Predicting bank insolvencies using machine learning techniques

Proactively monitoring and assessing the economic health of financial institutions has always been the cornerstone of supervisory authorities. In this work, we employ a series of modeling techniques to predict bank insolvencies on a sample of US-based financial institutions. Our empirical results indicate that the method of Random Forests (RF) has a superior out-of-sample and out-of-time predictive performance, with Neural Networks also performing almost equally well as RF in out-of-time samples. These conclusions are drawn not only by comparison with broadly used bank failure models, such as Logistic, but also by comparison with other advanced machine learning techniques. Furthermore, our results illustrate that in the CAMELS evaluation framework, metrics related to earnings and capital constitute the factors with higher marginal contribution to the prediction of bank failures. Finally, we assess the generalization of our model by providing a case study to a sample of major European banks.     

Debt Covenant Restriction,Financial Misreporting,and Auditor Monitoring*

Theory suggests that financial report-based debt covenants engender incentives for the manager to relax covenant constraints through accounting choices in order to avoid costly covenant violations. Prior studies directly testing this hypothesis in the context of financial misreporting fail to find consistent evidence. Using a more refined measure of debt covenant restriction, we find that debt covenant restriction is positively associated with the probability of financial statement misstatements. This positive association is driven by performance covenants rather than capital covenants and is more consistent with the manager striving to avoid a “false-positive” violation than to delay the violation. Our results also imply that managers resort to both income-increasing and non–income-increasing misreporting to relieve covenant constraints and rely more on the latter when faced with greater earnings management constraints. Additionally, the auditor charges higher audit fees to firms with more binding covenants even outside the violation state, and audit fees increase with constraints relative to both performance and capital covenants, reflecting greater financial reporting risk and bankruptcy risk, respectively. Within capital covenants, we find some evidence of even higher audit fees for tighter intangible-inclusive versus intangible-exclusive capital covenants. Lastly, our evidence suggests that the positive association between covenant constraints and misreporting is attenuated when the auditor has more experience with debt covenants, has greater bargaining power over the client, or faces greater litigation risk.     

Behaviour‐Based and Outcome‐Based Control Systems: A Meta‐Analytic Study

Sales control systems are instruments used by firms to improve performance and other organizational outcomes. To understand their antecedents and consequences, this paper conducts a meta‐analysis based on 104 studies. The results showed significant relationships between behaviour‐ and outcome‐based control systems and the complexity of the products, bonuses, financial performance, sales innovation, organizational support and satisfaction with supervisors. The outcomes revealed that behaviour‐based control systems were the most effective mechanism in turbulent markets and for determining financial performance. However, outcome‐based control systems were the most efficient instrument for complex products.     

The influence of personal and social identity on the clothing consumption of adolescents

We consider the influence of personal and social identity among adolescents on the importance they attach to clothing products and brands. The conceptual framework includes more conventional variables such as socialization (family, peers, media, and celebrities) and individual characteristics (gender and grade level). Based on a sample of 1,596 French high school adolescents, our results highlight: (i) the influence of identity on the importance attached to product and brand; (ii) the mediating effects of personal and social identities; and (iii) the moderating effects of gender and grade level. We conclude with an analysis of theoretical contributions, practical implications, and future research directions. Copyright © 2016 ASAC. Published by John Wiley & Sons, Ltd.     

The effect of economic policy uncertainty on China’s housing market

This study examines the relationship between economic policy uncertainty (EPU) and housing price at the macro-level in China as a developing country. The empirical evidence indicates that EPU has a leading effect on China’s housing market. In general, the housing market is prosperous when economic policy is stable and there is a positive relationship between housing price variation and EPU, which means housing market risk grows under unstable economic policies in this developing economy. Moreover, economic policy variation affects low-amplitude changes in housing prices. A variation of policy uncertainty enhances the risk premium of the housing market. By contrast, the level of EPU influences high-amplitude changes in housing prices, which reflects the trend of EPU dominating China's housing market.     

Is China’s Manufacturing Industry Efficient? Evidence from an Energy-Rebound Effect Perspective

Majority of the increase in global energy consumption is from China; hence, studying energy issues, especially in China’s manufacturing industry (CMI), is worthwhile and of much interest in the academic field. Based on the translog cost function, we develop a research framework to study the rebound effect of CMI. Considering the effect of asymmetric energy price, we augment the energy-cost function with asymmetric influence constraint of energy price. Again, we add time series data of CMI’s capital, labor, energy, and mid-input to the model to calculate the direct rebound effect of CMI. We find that the rebound effect of CMI is 44.2%, and CMI still has large energy-conservation potentials. Based on the results of this study, some policy recommendations are provided.