浅析解决中小企业融资难问题之对策

文章从多种角度分析了我国中小企业融资难的问题,尤其是在金融危机爆发以后所带来的一系列负面影响,并提出了相应的解决方案。     

我国产学研结合的政策研究

产学研结合经历了解决国有企业技术落后、建立企业技术创新体系到成为建设国家技术创新体系的突破口三个发展阶段,政策目标层次越来越高,政策手段日趋丰富.但在其强调服务经济建设功能的同时,却忽视了培养人才的功能.从效果上看,政策促进了科研与经济的结合,基本确立了企业技术创新的主体地位,而企业自主创新能力却仍有待加强.展望未来,政府应为集约化、综合性、紧密型的产学研结合营造良好的政策环境.     

一种感知情景的存取控制策略的规范和分析方法

对RBAC的角色激活过程增加情景约束,建立了感知情景的存取控制策略;利用D ata-log逻辑语言来建立感知情景存取控制策略模型的形式化规范;使用一阶逻辑语言描述策略的一致性、完整性等性质,借助D atalog实现了一个控制策略自动决策原型系统。     

Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors

In this paper, we assess the predictive content of latent economic policy uncertainty and data surprise factors for forecasting and nowcasting gross domestic product (GDP) using factor-type econometric models. Our analysis focuses on five emerging market economies: Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies.     

Forecasting stock volatility in the presence of extreme shocks: Short-term and long-term effects

This paper introduces a novel generalized autoregressive conditional heteroskedasticity–mixed data sampling–extreme shocks (GARCH-MIDAS-ES) model for stock volatility to examine whether the importance of extreme shocks changes in different time ranges. Based on different combinations of the short- and long-term effects caused by extreme events, we extend the standard GARCH-MIDAS model to characterize the different responses of the stock market for short- and long-term horizons, separately or in combination. The unique timespan of nearly 100 years of the Dow Jones Industrial Average (DJIA) daily returns allows us to understand the stock market volatility under extreme shocks from a historical perspective. The in-sample empirical results clearly show that the DJIA stock volatility is best fitted to the GARCH-MIDAS-SLES model by including the short- and long-term impacts of extreme shocks for all forecasting horizons. The out-of-sample results and robustness tests emphasize the significance of decomposing the effect of extreme shocks into short- and long-term effects to improve the accuracy of the DJIA volatility forecasts.     

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR

As a representative emerging financial market, the Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conducts a comparative study about the predictive performance of artificial neural network, support vector regression (SVR) and autoregressive integrated moving average and selects SVR to study the asymmetry effect of investor sentiment on different industry index predictions. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed of young companies with high growth and high operative pressure and there are a great number of investment bubbles in those companies.     

中国环保产业高质量发展的异质性政策驱动研究

为了剖析环保产业高质量发展的政策驱动机制,将环保产业高质量发展的内涵具化为5个维度,同时构造环保产业高质量发展的系统动力学模型,通过4种政策情景仿真考察不同政策工具对环保产业高质量发展各维度的影响.结果 表明:政策工具对环保产业高质量发展的5个维度指标存在较为显著的目标差异性和时效差异性,其中税收政策对产出的激励效果最...     

Cross‐Section Stock Return and Implied Covariance between Jump and Diffusive Volatility

I examine the information content of option‐implied covariance between jumps and diffusive risk in the cross‐sectional variation in future returns. This paper documents that the difference between realized volatility and implied covariance (RV‐ICov) can predict future returns. The results show a significant and negative association of expected return and realized volatility–implied covariance spread in both the portfolio level analysis and cross‐sectional regression study. A trading strategy of buying a portfolio with the lowest RV‐ICov quintile portfolio and selling with the highest one generates positive and significant returns. This RV‐Cov anomaly is robust to controlling for size, book‐to‐market value, liquidity and systematic risk proportion. Copyright © 2015 John Wiley & Sons, Ltd.     

上市公司期权激励公告的市场反应研究

在回顾期权激励相关研究的基础上,利用事件研究法对《上市公司股权激励管理办法》实施以来我国上市公司期权激励公告的市场反应进行了研究,并检验了不同市场对期权激励公告的反应是否相同.研究表明,市场对期权激励公告持积极态度,公告公司股票能获得比非公告公司股票更高的累积超额收益,且不同市场股票的CAR没有差异.     

韩国科技管理体制发展与演变探析

自20世纪60年代以来,韩国的科技发展取得了巨大的成就,其科技管理体制发挥了重要的作用.针对韩国科技管理体制形成与发展演变过程中经历的科技管理体系初步形成,以科技部为宏观管理决策部门的集中协调型管理体制,以及李明博政府对科技管理体制的重大调整等三个重要阶段进行了系统的分析研究,并对韩国科技管理体制的特点进行了总结和讨论.