股权分置改革对股票市场吸收冲击能力的影响分析

根据经济学理论,股权分置改革最主要的意义在于解决影响中国股市发展的委托一代理问题。从改革后市场的反应看,2005年开始的股权分置改革较为成功地解决了这一问题。如此,改革后市场的运作应该比之前更加规范和理性,消化冲击能力更强。然而运用GARCH模型对此进行分析,得到的实证结果与提出的观点却相反。最后,对此现象进行了分析。     

Exchange rate volatility and United Kingdom trade: evidence from Canada,Japan and New Zealand

This paper investigates the influence of exchange rate volatility on the real imports of the United Kingdom from Canada, Japan and New Zealand during the period 1980–2003. The Johansen multivariate cointegration method and the constrained error correction (general-to-specific) method are applied to study the relationship between real imports and its determinants (including exchange rate volatility). Conditional variance from the GARCH(1,1) model is applied as exchange rate volatility. Both nominal and real exchange rates are employed in the empirical study. Results indicate a significant effect of the exchange rate volatility on real imports. These exchange rate volatility effects are mostly positive. The author thanks an anonymous referee, the editor and Myles Wallace for several useful comments and suggestions. Any remaining errors and omissions are the author’s responsibility alone.     

上交所新券和旧券的价差研究

新券和旧券价格差异被国际学术界普遍关注和解释。我们考察上海证券交易所交易的7年期国债,构造风险特征和久期相同的新券和旧券组合,采用均值和Wilcoxon-Whitney中位数检验,发现二者到期收益率平均存在14个基点的显著差异。使用换手率指标,应用AR(2)模型和GARCH(1,1)模型拟合分析发现,流动性是造成新券和旧券价差现象的显著原因。     

基于GARCH族模型的黄金价格收益率及波动性研究

文章应用GARCH族模型对黄金现货价格的收益率及波动性进行实证研究,实证结果表明黄金价格日收益率具有"尖峰厚尾"和"波动聚类"的特征。通过TGARCH及EGARCH模型发现我国黄金市场存在非对称性现象,正的冲击对黄金价格波动影响更大。     

中国创业板市场节日效应的实证分析

本文回顾了创业板市场建立过程,以香港创业板与深市创业板的时间序列数据,首先进行了香港创业板(GEM001)和深市创业板指(399006)对数收益率的波动性刻画,验证其分别服从GARCH(1,1)和ARCH(1)模型,且拟合优度较好;然后采用虚拟变量回归的方法,对其节日效应进行了检验,结果发现:港股在元旦、五一、春节时具有较为显著的节日效应(节前效应和节后效应);深创业板在国庆时具有较为明显的节日效应,在元旦和五一具有节前效应。最后针对创业板市场的关键问题,提出看法和建议。     

成交量、持仓量对我国大豆类期货价差波动影响的实证分析

采用GARCH(1,1)模型就成交量、持仓量对大豆类期货价差波动率的影响进行实证分析,结果显示：当期成交量、持仓量对大豆期货价差波动的整体影响是显著的;滞后成交量、持仓量对大豆期货价差波动的整体影响也是显著的;当成交量、持仓量同时进入条件方差方程时,它们对大豆类期货价差波动的影响整体上也是显著的。这一结论揭示了我国大豆期货市场信息传递过程,验证了我国大豆期货市场的信息非有效性,对期货市场投资者以及期货市场监管者具有一定的借鉴意义。     

Risk and seasonal effects: international evidence

Various explanations have been advanced for the January effect in the existing literature, but no consensus has been arrived at to distinguish one particular explanation from any others. In this paper, a time-series GARCH-M model with conditional variance as a proxy for market systematic risk is applied to investigate the seasonal effects in four countries with different tax system and tax year end: the USA, the UK, China and Australia. Empirical evidence showed a January effect in the USA, a January and an April effect in the UK, a July effect in Australia and no significant seasonal effect in China. This pattern consistently links to tax year end and the tax system in the sample countries; however, no clear evidence has been found to support the proposition that market risk is higher or priced highly only in calendar months with a seasonal effect. However, to reflect the seasonal effect, an interactive dummy variable is added into the time-series GARCH-M model, and the seasonal effects are explained away. The results of the sampled countries support the proposition that market volatility increases when it is close to the date of financial statement performance due to the uncertainty of the financial information.     

Modelling international tourism demand and volatility in small island tourism economies

Small island tourism economies (SITEs) vary in their size, land area, location, narrow resource bases, economic development, overwhelming reliance on tourism and consistent inflow of foreign direct investment for economic growth. Small island tourism economics differ in their ethnic diversity, political systems, economic and environmental vulnerability, ecological fragility and the risks facing investors. Owing to natural disasters, ethnic conflicts, crime and the threat of global terrorism, there have been dramatic changes in the arrivals of international tourists to SITEs. These variations in international tourism demand to SITEs, particularly the conditional variance (or volatility) in international tourist arrivals, have not previously been analysed in the tourism research literature. An examination of the conditional volatility of international tourist arrivals is essential for policy analysis and marketing purposes. This paper models the conditional mean and conditional variance of the logarithm of monthly international tourist arrivals and the growth rate (or log‐difference) in the monthly international tourist arrivals for six SITEs, namely Barbados, Cyprus, Dominica, Fiji, Maldives and Seychelles. Diagnostic checks of the regularity conditions of the logarithm of monthly international tourist arrivals and their growth rates suggest that the estimated univariate models of trends and volatility are statistically adequate. Therefore, the estimated models are appropriate for purposes of public and private sector management of tourism. Copyright © 2005 John Wiley & Sons, Ltd.     

Evidence on the contrarian trading in foreign exchange markets

This paper investigates the existence and price impacts of contrarian behavior in the foreign exchange markets. By utilizing a nonlinear behavioral model where the chartists and fundamentalists coexist, evidence obtained from two sample periods significantly supports the existence of contrarian trading in the British pound, the Japanese yen and the German mark markets. The contrarian trading can only partially offset the price impacts of trend-followers, therefore the price impact of the chartists as a whole is destabilizing. The ability that the contrarians can counterbalance the extrapolation of the trend-followers differs across markets. Traders in the BP market have the highest tendency to contrarian strategy, which in turn contributes to the least deviations of the BP exchange rates departing from its PPP fundamentals. The fundamentalists' confidence in trade fades during large misalignments, which make the mean reversion function of the fundamentalists weak under the circumstances. We find the magnitudes of interventions will be affected by the price impacts of contrarians and their abilities on market stabilization.     

基于多维动态模型的中国股指相关性预测研究

运用时间序列的ADCC(Asymmetric Dynamic Conditional Correlation)多维GARCH模型和CCC(Constant Conditional Correlation)多维GARCH模型对中国主要股指之间的相关性进行预测,并对预测结果进行评价和比较,结果表明ADCC多维GARCH模型拟合和预测中国股指相关性较好,这为投资组合管理和风险管理提供了理论支持。