Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

武汉金融安全区模式设计与研究

金融安全与稳定直接关系到一个国家或地区的经济安全与社会稳定。一个地区 ,在突出的支付风险得以逐一化解之后 ,适时启动创建金融安全区工程 ,并以此全面提高金融监管水平 ,实现区域金融业持续稳健发展已经成为当前我们面临的重要课题。本文在论证武汉市开展创建金融安全区的必要性和可行性的基础上 ,提出了构建以武汉金安指数为核心的指标监测体系、具体创建规划以及相应运行规程。     

中国外贸增长方式转变的评价指标体系与实证研究

从外贸规模、外贸结构、外贸效益、外贸可持续发展、外贸竞争力五个方面建立外贸增长方式及其转变的评价指标体系,以中国1995—2008年的数据,对外贸增长方式转变成效进行了实证研究表明,从总体上来看,外贸增长方式转变已有成效;规模指标显示外贸规模不断扩大;结构指标显示外贸结构在波动中优化,但优化程度与规模增长相比显得不足;效益指标、可持续发展指标、外贸竞争力指标,都有一定程度的上升。但贸易结构有待进一步优化,贸易条件需要进一步改善,环境、资源指标需要进一步提高,外贸增长方式转变的任务仍然十分艰巨。     

我国东部地区社会管理水平测度及分类研究——兼论社会管理水平与经济发展的关系

东部地区社会管理实践活动对全国具有示范效应。文章首先构建了包括社会保障、社会安全、公共服务和社会参与4个一级指标、25个二级指标的社会管理评价指标体系,为东部地区社会管理水平测度研究提供了科学的评价标准;其次,基于2011年东部11个省份的横截面数据,对东部地区社会管理水平进行了测度,并将其划分为社会管理水平较高、社会管理水平一般和社会管理水平较低三个等级区域;最后,依据社会管理水平及子系统的协调度,进一步将东部地区社会管理水平划分为6种类型,并通过相关性分析,检验社会管理水平及子系统水平与经济发展的相关关系。研究结果表明,2011年东部地区社会管理水平及子系统水平较低,省际间差异明显,且子系统水平呈现非均衡发展特征;社会管理水平与经济发展水平呈现显著正相关关系。因此,促进区域协调发展,增强区域经济实力,能够为提升社会管理水平提供物质保障。     

基于可持续发展的主要污染物总量指标预算管理体系初探

以环境容量为基础,结合我国总量控制的刚性减排制度,为提高污染减排积极性,明确地区环境支持经济发展的总量指标,提出总量指标预算管理体系。同时阐述了总量预算指标的定义,分析了总量预算指标从哪里来。通过剖析环境容量、污染物现状排放量、污染物新增排放量与总量预算指标的函数关系,建立基于环境容量的总量指标预算分配模型,以及年度预算演化模型,并对总量指标预算管理方法进行初步探讨。为污染减排提供政策激励机制,量化了环境保障经济社会发展的总量指标,促进环境和经济协调发展。     

On Forward Induction and Evolutionary and Strategic Stability

We analyze which normal form solution concepts capture the notion of forward induction, as defined by E. van Damme (1989, J. Econ. Theory48, 476-496) in the class of generic two player normal form games preceded by an outside option. We find that none of the known strategic stability concepts (including Mertens stable sets and hyperstable sets) capture this form of forward induction. On the other hand, we show that the evolutionary concept of EES set (J. Swinkels, 1992, J. Econ. Theory57, 306-332) is always consistent with forward induction. Journal of Economic Literature Classification Number: C72.     

DOES MONOPOLISTIC COMPETITION EXIST IN THE MENA REGION? EVIDENCE FROM THE BANKING SECTOR

The goal of this paper is to empirically assess the level of banking competition in selected Middle East and Northern African (MENA) countries. The analysis employs the estimation of a non‐structural indicator (H‐statistic) introduced by Panzar and Rosse and draws upon a panel dataset of eight MENA countries (Algeria, Egypt, Israel, Jordan, Morocco, Oman, Saudi Arabia, and United Arab Emirates) over the period 1997–2012. The empirical findings are robust towards three different panel data econometric techniques (Ordinary Least Squares, Pooled Generalized Least Squares with Fixed Effects, and Generalized Method of Moments) and consistent with other similar studies, providing sufficient evidence in favour of a banking monopolistic competition regime. Furthermore, the estimation of three other alternative measures of competition (Lerner index, adjusted Lerner index, and conduct parameter) provides similar results, revealing that the banking sector in the MENA region is characterized by a low level of Significant Market Power (SMP). Overall, the analysis shows that, despite similarities in the process of financial regulatory reforms undertaken in the eight MENA countries, the observed competition levels of banks vary substantially, with Algeria and Morocco consistently outperforming the rest of the region.     

数量指标和质量指标理论与应用评析

在各类《统计学》教科书中,对数量指标和质量指标概念的解释不大一样,但基本的含义却是相同的。两者从概念上区别并不困难,也容易理解,但在对一些特殊问题的分析时,却不易把握,特别是在比较复杂的统计分析中,那就更不容易做出准确的判断了。怎样才能对数量指标和质量指标的应用做出科学的评价和分析。本文拟就这方面的问题做些初步探索。