On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model

Recent multivariate extensions of the popular heterogeneous autoregressive model (HAR) for realized volatility leave substantial information unmodelled in residuals. We propose to employ a system of seemingly unrelated regressions to model and forecast a realized covariance matrix to capture this information. We find that the newly proposed generalized heterogeneous autoregressive (GHAR) model outperforms competing approaches in terms of economic gains, providing better mean–variance trade‐off, while, in terms of statistical precision, GHAR is not substantially dominated by any other model. Our results provide a comprehensive comparison of the performance when realized covariance, subsampled realized covariance and multivariate realized kernel estimators are used. We study the contribution of the estimators across different sampling frequencies, and show that the multivariate realized kernel and subsampled realized covariance estimators deliver further gains compared to realized covariance estimated on a 5‐minute frequency. In order to show economic and statistical gains, a portfolio of various sizes is used. Copyright © 2016 John Wiley & Sons, Ltd.     

Forecasting the Daily Time‐Varying Beta of European Banks During the Crisis Period: Comparison Between GARCH Models and the Kalman Filter

This intention of this paper is to empirically forecast the daily betas of a few European banks by means of four generalized autoregressive conditional heteroscedasticity (GARCH) models and the Kalman filter method during the pre‐global financial crisis period and the crisis period. The four GARCH models employed are BEKK GARCH, DCC GARCH, DCC‐MIDAS GARCH and Gaussian‐copula GARCH. The data consist of daily stock prices from 2001 to 2013 from two large banks each from Austria, Belgium, Greece, Holland, Ireland, Italy, Portugal and Spain. We apply the rolling forecasting method and the model confidence sets (MCS) to compare the daily forecasting ability of the five models during one month of the pre‐crisis (January 2007) and the crisis (January 2013) periods. Based on the MCS results, the BEKK proves the best model in the January 2007 period, and the Kalman filter overly outperforms the other models during the January 2013 period. Results have implications regarding the choice of model during different periods by practitioners and academics. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

基于可信群划分及评估值波动性和一致性的可信评估模型

提出一种基于兴趣相似度的可信群划分策略.将全局评估转化为群内评估,既解决了评估消息集聚的问题,又区分了不同兴趣域内的评估结果,提高了系统的服务成功率.同时提出一种结合评估值波动性和一致性的权重计算方法.仿真结果表明,新模型能抵抗各类恶意节点,且比以往的模型服务成功率更高.     

非对称信息条件下排污申报登记制度的策略

研究如何在污染物排放总量控制中通过排污申报登记获得真实的污染物排放量信息。用对策论的决策树方法建立了非对称信息条件下的惩罚模型 ,分析了在非对称信息条件下管理者与被管理者的策略选择。分析的结论是 :管理者可以以一定的费用与收益对被管理者的行为策略进行约束 ,并影响被管理者在整个对策博弈过程中更为理性地申报排污信息     

D0实验e~＋e~-前后不对称及弱混合角sin~2θW测量

我们在1.96TeV质子-反质子Tevatron对撞机D0实验中,测量了pp→Z/γ→e＋e-过程末态电子电荷前后不对称分布.通过这一过程,我们测量了基本物理常数弱混合角sin2θW=0.2309±0.0008（stat.）±0.0006（syst.）,以及Z玻色子与up-/down-轻夸克V-A耦合常数.这是迄今为止与轻夸克相关有效弱混合角、以及Zqq相互作用常数最精确的测量结果,从而为检验标准模型提供了新的实验标准.     

日元汇率波动及对华直接投资影响的实证研究

使用1989～2007年日本对我国8个制造业部门的外商直接投资数据和日元对人民币汇率数据，采用面板数据的GLS回归分析。研究发现：日元汇率波动对日本对华直接投资的影响存在显著的行业效应，具体为，日元升值显著促进日本时我国8个制造业部门的直接投资，日元贬值则抑制直接投资，且各行业间的影响程度有差别；日元汇率波动性对每个行业的影响均是负的，且对电子与运输设备行业的影响是显著的。     

基于交易费用的中小企业信贷融资问题分析

从交易费用的视角对中小企业从银行获得融资难的问题进行了分析,认为交易费用的存在加大了中小企业获得银行资金支持的难度,降低交易费用的制度措施能在一定程度上缓解融资难问题。     

Subspeciation or none? The hardun in the Aegean (Reptilia: Sauria: Agamidae: Laudakia stellio)

A study aimed at testing the contested validity of the subspecies Laudakia stellio daani yielded novel insights into the essence of subspecies. We examined morphologically museum specimens from Greece, Aegean islands, and Anatolia (n?=?118; not all could be used in all analyses). Beyond the conventional mensural, meristic and qualitative characters we quantified 14 coloration characters, thus totalling 34 characters (including sex). Biometry was statistically analysed within and between the two geographically defined presumed subspecies, L. s. daani and L. s. stellio. Excluding or including broken‐tailed specimens changed the outcome of tests. Significant minor directional asymmetry occurred in one of four character‐taxon combinations. Phenetic cluster analysis poorly separated the two presumed subspecies when all characters, including those with discordant variation, were included; after selection of characters, the separation improved. Some biometric characters distinguish the two presumed subspecies, confirming their validity. The associations of significant inter‐character correlations differed between the two subspecies. Additionally, the two differed in parameters reflecting selection pressures and social structure: L. s. stellio is more colourful than L. s. daani; its sexual dimorphism is mainly chromatic, versus mensural in L. s. daani; and its population seems to include many males with underdeveloped callous scales, presumably socially subordinate, versus very few in L. s. daani.     

上海证券交易所Ａ股市场的波动性分析

运用主要的三种条件异方差模型：ARCH、GARCH、EGARCH模型，对上海证券交易所A股指数的波动性进行拟合，分析模型对上证A股指数收益的波动性、杠杆效应的拟合情况，比较不 同模型对未来波动性的预测情况。实证分析结果表明：EGARCH模型比较适合对我国股票市场 波动性作长期预测，若假设收益序列服从t分布，由此改进的EGARCH-T模型会得到比正态分 布下更好的拟合与预测效果。