英语分级教学对高等数学教学影响的方差分析

对高等数学课程考试的成绩进行了方差分析，分析的结果是英语分级教学对高等数学成绩无显著影响，而学生入学时的高考数学成绩对高等数学教学的影响值得重视。     

Agricultural land-use dynamics: Assessing the relative importance of socioeconomic and biophysical drivers for more targeted policy

A detailed understanding of multiple human and environmental factors influencing land allocations among agricultural uses can facilitate more efficient and targeted land policy. To show this, we used a comprehensive dataset of socioeconomic, physiographic, and climatic indicators to investigate potential determinants of land-use in Australia’s intensive agricultural region during the period 1992–2010. We applied a seemingly unrelated regressions land-use shares spatial error model with random effects coupled with variance decomposition analysis to identify the statistical significance, direction and magnitude of observed associations between land-use and its drivers.Population: density, rainfall, equity ratio, and access to markets were the most influential policy-relevant land-use factors. Land allocations to cereals and livestock production were significantly influenced by spatiotemporal rainfall and temperature variability. Improved pastures, cereals, annual and perennial crops plantations were larger in regions with better access to markets. Increases in equity ratio (i.e., better financial position) were associated with larger land allocations to improved pastures and annual crops and smaller extensive grazing area. Marginal associations were detected between land-use and output prices, and higher population density was associated with lower shares for all high value agricultural land-uses. The results suggest that improved transportation infrastructure, zoning regulations, and mechanisms to reduce farm debt exposure and risks from climate variability could have significant impact on the configuration of the Australian agricultural landscape.     

Clustering financial time series with variance ratio statistics

This study introduces a new distance measure for clustering financial time series based on variance ratio test statistics. The proposed metric attempts to assess the level of interdependence of time series from the point of view of return predictability. Simulation results show that this metric aggregates time series according to their serial dependence structure better than a metric based on the sample autocorrelations. An empirical application of this approach to international stock market returns is presented. The results suggest that this metric discriminates stock markets reasonably well according to size and the level of development. Furthermore, despite the substantial evolution of individual variance ratio statistics, the clustering pattern remains fairly stable across different time periods.     

Modelling and Estimation for Bivariate Financial Returns

Maximum likelihood estimates are obtained for long data sets of bivariate financial returns using mixing representation of the bivariate (skew) Variance Gamma (VG) and two (skew) t distributions. By analysing simulated and real data, issues such as asymptotic lower tail dependence and competitiveness of the three models are illustrated. A brief review of the properties of the models is included. The present paper is a companion to papers in this journal by Demarta & McNeil and Finlay & Seneta.     

中国经济波动对日本经济脉冲效果的分析

本文通过向量自回归理论的脉冲响应函数,对中日双边经贸关系建立了相应的冲击反应模型,在实证的基础上定量分析了中日间经济相互冲击的效果。同时利用方差分解技术,分析了各冲击因素对两国经济的影响及其贡献率大小,实证结果显示:中国经济对日本经济的冲击效果相当明显,日本经济对中国经济的依赖性越来越大。     

What׳s news in News? A cautionary note on using a variance decomposition to assess the quantitative importance of news shocks

This paper points out a conceptual difficulty in using a variance decomposition to assess the quantitative importance of news shocks. A variance decomposition will attribute to news shocks movements in endogenous variables driven both by news about future exogenous fundamentals that has yet to materialize (what I call “pure news”) as well as movements driven by realized changes in fundamentals that were anticipated in the past (what I call “realized news”). I present a stylized model in which news about yet unrealized changes in fundamentals is irrelevant for output dynamics, but in which a variance decomposition may nevertheless attribute a large share of the variance of output to news shocks. I then revisit the quantitative importance of news in the model of Schmitt-Grohe and Uribe (2012). In their model news shocks account for 40 percent of the variance of output growth, but this is mostly driven by realized news.     

均值方差偏好和下方风险控制下的动态投资组合决策模型

本文在均值方差框架下，研究了下方风险控制下的动态投资组合问题。在目标函数中考虑了投资组合的最坏结果，利用标准的期权定价理论，给出了最优投资策略的解析式。该投资策略等价于一个关于“资产”最小二阶矩组合的欧式看跌期权和无风险资产的组合，而且两基金分离定理仍然成立。     

On the Conditional Variance of Fuzzy Random Variables

The conditional variance of random variables plays an important role for well-known variance decomposition formulas. In this paper, the conditional variance is defined for fuzzy random variables and some properties are proved, which especially generalize to the mentioned variance decomposition. Moreover, results for two special types of fuzzy random variables and an outlook for possible applications are presented.     

MGARCH models: Trade-off between feasibility and flexibility

Multivariate GARCH (MGARCH) models need to be restricted so that their estimation is feasible in large systems and so that the covariance stationarity and positive definiteness of conditional covariance matrices are guaranteed. This paper analyzes the limitations of some of the popular restricted parametric MGARCH models that are often used to represent the dynamics observed in real systems of financial returns. These limitations are illustrated using simulated data generated by general VECH models of different dimensions in which volatilities and correlations are interrelated. We show that the restrictions imposed by the BEKK model are very unrealistic, generating potentially misleading forecasts of conditional correlations. On the other hand, models based on the DCC specification provide appropriate forecasts. Alternative estimators of the parameters are important in order to simplify the computations, and do not have implications for the estimates of conditional correlations. The implications of the restrictions imposed by the different specifications of MGARCH models considered are illustrated by forecasting the volatilities and correlations of a five-dimensional system of exchange rate returns.     

货币调控政策对房地产作用的时滞分析

影响房地产宏观调控效果的一个重要因素是政策的时滞性,本文通过脉冲效应函数、方差分解方法测算了1999年至2010年房地产宏观调控政策中货币政策对房地产投资与房价的作用时滞。同时,为了得到测算的精确性,还通过时差相关系数的方法对其进行对比分析。研究表明,货币供应量对房地产投资与房价的作用时滞都为4个季度,贷款对房地产投资与房价的作用时滞分别为4个季度、2个季度。