机构投资者对证券市场价格波动性的影响——基于Topview数据的实证研究

本文在完整的市场结构数据基础上,研究了市场波动性与机构投资者之间的相互关系。在研究数据方面,我们采用了深度、高频的Topview数据,既避免了前人在研究数据方面的以偏概全,也让我们可以采用更为先进、稳健的实证方法。我们设定了恰当的波动性度量指标,运用了稳健的因果推断方法。并用脉冲响应和方差分解的方法细腻刻画两者之间的相互关系。本文的主要结论是:机构投资者持股比率的波动对上证指数波动有显著的影响,是导致上证指数波动最为主要的原因,法人投资者和个人大户投资者持股比率的变动对上证指数的波动几乎没有影响,机构投资者持股比率波动还会向法人投资者、个人大户投资者持股比率溢出,这些表明在上海证券市场上机构投资者是市场波动的主要来源和主要原因。机构投资者的多元化、坚决推进市场的规范化改革应当成为未来政策关注的重点。     

欠发达地区金融支持农民增收问题研究

运用协整检验和格兰杰因果检验对广西1995-2008年农民收入和农村信贷投入之间的关系进行实证分析,结果表明农村信贷投入是农民收入增长的格兰杰原因,并存在长期均衡关系,由此提出了加大农村信贷投入的对策建议。     

浅析我国衍生金融工具所得性质、数量、时间的认定

衍生金融工具所得课税问题是一个国际难题。本文分别从衍生金融工具所得性质的认定、所得数量的认定、所得时间的认定三个方面展开阐述,分析了国际通行的做法,并联系我国实际对衍生金融工具所得课税进行了探讨。     

外籍人员个人所得税的计算缴纳

近年来,我国境内外籍人员不断增多,使得外籍人员在华纳税问题逐渐成为人们关注的焦点。本文从现行税收法律法规出发,介绍了外籍人员取得的工资薪金、奖金以及其他几种特殊情况的个人所得税的具体缴纳方法。     

A High‐Frequency Investigation of the Interaction between Volatility and DAX Returns

One of the most noticeable stylised facts in finance is that stock index returns are negatively correlated with changes in volatility. The economic rationale for the effect is still controversial. The competing explanations have different implications for the origin of the relationship: Are volatility changes induced by index movements, or inversely, does volatility drive index returns? To differentiate between the alternative hypotheses, we analyse the lead‐lag relationship of option implied volatility and index return in Germany based on Granger causality tests and impulse‐response functions. Our dataset consists of all transactions in DAX options and futures over the time period from 1995 to 2005. Analyzing returns over 5‐minute intervals, we find that the relationship is return‐driven in the sense that index returns Granger cause volatility changes. This causal relationship is statistically and economically significant and can be clearly separated from the contemporaneous correlation. The largest part of the implied volatility response occurs immediately, but we also observe a smaller retarded reaction for up to one hour. A volatility feedback effect is not discernible. If it exists, the stock market appears to correctly anticipate its importance for index returns.     

基于百度指数的碳交易市场波动率的实证研究

碳交易市场波动率研究主要基于成交量数据对收益率GARCH效应的解释作用。在互联网时代可以有更新更为有效的方法来衡量碳交易市场的波动性。基于“碳交易”词条的百度指数,以湖北碳交易市场中的收益率为样本,本文通过对比使用引入成交量和搜索量的IGARCH（1,1）模型,实证研究发现传统的量价方程的确没有解释力,而百度指数可以对收益率的GARCH效应做出部分合理的解释,这可以在某种程度上反映湖北碳交易市场的交易信息流。     

Efficient learning via simulation: A marginalized resample-move approach

In state–space models, parameter learning is practically difficult and is still an open issue. This paper proposes an efficient simulation-based parameter learning method. First, the approach breaks up the interdependence of the hidden states and the static parameters by marginalizing out the states using a particle filter. Second, it applies a Bayesian resample-move approach to this marginalized system. The methodology is generic and needs little design effort. Different from batch estimation methods, it provides posterior quantities necessary for full sequential inference and recursive model monitoring. The algorithm is implemented both on simulated data in a linear Gaussian model for illustration and comparison and on real data in a Lévy jump stochastic volatility model and a structural credit risk model.     

The role of oil futures intraday information on predicting US stock market volatility

This study investigates the role of oil futures price information on forecasting the US stock market volatility using the HAR framework. In-sample results indicate that oil futures intraday information is helpful to increase the predictability. Moreover, compared to the benchmark model, the proposed models improve their predictive ability with the help of oil futures realized volatility. In particular, the multivariate HAR model outperforms the univariate model. Accordingly, considering the contemporaneous connection is useful to predict the US stock market volatility. Furthermore, these findings are consistent across a variety of robust checks.     

On the predictability of the distribution of excess returns in currency markets

This paper investigates the predictability of foreign exchange (FX) volatility and liquidity risk factors on returns to the carry trade, an investment strategy that borrows in currencies with low interest rates and invests in currencies with high interest rates. Previous studies have suggested that this predictability could have been spuriously accounted for due to the persistence of the predictors. The analysis uses a predictive quantile regression model developed by Lee (2016) that allows for persistent predictors. We find that predictability changes remarkably across the entire distribution of currency excess returns. Predictability weakens substantially in the left tail once persistence is accounted for, implying a moderate negative predictive relation between FX volatility risk and carry trade returns. By contrast, it becomes stronger in the right tail. Furthermore, we provide evidence that FX volatility risk still dominates liquidity risk after controlling for persistence. These findings suggest that the persistence of the predictors needs to be taken into account when one measures predictability in currency markets. Finally, out-of-sample forecast performance is also presented.