EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Covariance breakdowns and connectedness of crude oil futures markets with non-synchronous data

ABSTRACT

This article identifies the breakdowns in the covariance of three benchmark crude oil futures markets (WTI, Brent and Dubai) and investigates the changes of market connectedness across the breakdown periods. As the crude oil futures are traded in different regions, this article eliminates the non-synchronous trading data by employing the Vector Moving Average structure and the Bayesian data augmentation approach, which keeps the integrity of original data without changing its properties. The results show that there are significant breaks in the covariance structure of crude oil futures markets. The breakdown periods are consistent with the periods when the market volatilities are at high level and the returns are volatile. The changes of market connectedness are independent of the covariance states, which supports the globalization hypothesis for the crude oil market. The results also suggest that there is more information flow out of the WTI than to the WTI during the sample period, particularly during the breakdown periods in 2008–2009.     

智能制造有利于增加企业技术创新投入吗——基于智能制造试点的准自然实验

智能制造是我国制造业转型升级的主攻方向,而如何准确客观评价智能制造的实施效果成为亟待解决的问题.从技术创新投入视角,将智能制造试点政策实施视为一次准自然实验,采用2011-2019年制造业上市企业面板数据,通过PSM-DID方法研究智能制造对企业技术创新投入的影响.研究结果表明,智能制造显著影响企业技术创新投入,即通过提升客户集成度、供应商集成度进而提高企业技术创新投入,且促进作用仅发生在民营企业和非高新技术行业中.该发现扩展了现有研究外延,同时,为解决当前国际困局和促进智能制造的持续推广提供了重要实践价值.     

Effect of CSR and Ethical Practices on Sustainable Competitive Performance: A Case of Emerging Markets from Stakeholder Theory Perspective

Journal of Business Ethics - An extensive work has been done on corporate social responsibly practices (CSRPs) that mainly emphasized the larger firms within developed nations. Nonetheless, still...     

The practice of collective bargaining in the private sector in Quebec (Canada): the changing ‘rules of the game’

Drawing on 45 semi‐structured interviews with union negotiators active in the Quebec private sector, this article shows that local bargaining practices, despite their plurality, have tended to change following major trends. It also reveals, more fundamentally, a redefinition of the ‘rules of the game’. The transformation and stability of these social rules, which are much more focused on the needs of employers, have tended to weaken collective bargaining as a tool for industrial democracy.     

货币政策、企业家信心与上市公司投资效率*

企业、企业家等微观主体对货币政策的反应，在较大程度上影响货币政策的效果。货币政策可通过对企业家信心的影响，进而对公司投资效率产生作用。基于中国2007—2016年40个季度A股上市公司样本的实证研究表明：企业家信心在货币政策传导过程中有不可忽视的作用。企业家信心增强或者货币政策宽松时会加剧过度投资，减轻投资不足；企业家信心减弱或者货币政策紧缩时可以有效抑制过度投资，但会加剧投资不足。其中，国有企业对企业家信心和货币政策松紧的敏感性更强。进一步，货币政策对企业投资效率的影响，也会通过货币政策和企业家信心的交互作用而发挥作用。这种作用在国有企业和非国有企业之间无显著差异。     

The Effect of Media Coverage on the Pricing of Seasoned Equity Offerings

This paper examines the role of media coverage and investor attention on the outcomes of seasoned equity offerings (SEOs). I use an archive of Thomson Reuters news articles to proxy for firm visibility and investor attention. I find that the volumes of news articles prior to the offerings are positively associated with the offer price discounts of SEOs. Furthermore, the volumes of news articles are negatively associated with the cumulative abnormal returns three days around the SEOs. I conclude that the costs of equity increase with media coverage prior to SEOs. Overall, the evidence is consistent with the hypothesis that media coverage affects investors' information processing in SEOs. Copyright © 2018 ASAC. Published by John Wiley & Sons, Ltd.     

Foreign direct investment subsidy in a dynamic stochastic general equilibrium model with heterogeneous firms

This study analyzes the macroeconomic impacts of subsidies to attract multinational corporations when firms are determining whether to enter or how to serve foreign markets. We show that a small FDI subsidy scheme induces consumption gains and delivers short‐term welfare improvement for the FDI host country if firms differ in productivity. However, the subsidy generates a new problem and results in the wealth reallocation effect, leading to welfare deterioration for the host country in the long run. Moreover, we find that a subsidy program induces a welfare improvement for the host country if it is offered to all domestic producers instead of foreign producers only in the host country.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

高校跨学科创新团队知识互动程度评价研究

知识互动程度评价对改善高校跨学科创新团队知识互动具有重要意义。在界定高校跨学科创新团队知识互动及知识互动程度内涵的基础上，创新性地从知识互动深度、互动广度、互动时间3个维度建立知识互动程度评价指标体系。进一步地，采用三角模糊权重、熵权和模糊积分相结合的方法，构建知识互动程度评价模型。最后，选取一所高校跨学科创新团队进行实例分析，验证评价模型的可操作性，可为高校跨学科创新团队知识互动程度评价提供一个新视角。