跳跃风险、结构突变与原油期货价格波动预测

本文主要是为了检验原油期货市场是否存在明显的跳跃风险和结构突变,并重点调查这两个因素是否对原油期货价格波动有预测作用。在经典或前沿的HAR-RV、HAR-S-RV和PSlev模型中,本文同时考虑跳跃风险和结构突变因素,构建了HAR-RV-J-SB、HAR-S-RV-J-SB和PSlev-J-SB模型。接着,以WTI原油期货的5分钟高频交易数据作为实证样本,对以上模型进行实证分析。实证结果显示：原油期货市场存在明显的跳跃风险和结构突变现象;HAR-RV-J-SB、HAR-S-RV-J-SB和PSlev-J-SB模型对原油期货价格波动的样本外预测精度都明显高于与之相对应的HAR-RV、HAR-S-RV和PSlev模型,且其结果是稳健的。特别地,在HAR-C和LHAR-RV等其它现有HAR族模型中加入跳跃风险和结构突变因素,也能得到类似的结果。本文的研究表明跳跃风险和结构突变因素能显著提高现有绝大多数HAR族模型对原油期货价格的预测精度,所以在HAR族模型的构建中这两个因素不能被忽视。     

国际油价、美国经济不确定性和中国股市的波动溢出效应研究

2008年金融危机以来的全球股市震荡,油价波动剧烈和经济的不确定性使得研究不同市场间的风险传导效应具有重要的意义。在综合评价现有研究的缺陷和既有改进方法的情况后,本文借鉴Diebold and Yilmaz （2012）的研究方法探索国际原油价格、美国经济不确定性和中国股市的波动溢出效应。本文选取1986年1月到2016年12月原油价格、美国经济不确定性指数和中国股票价格的月度数据,分别研究了静态波动溢出指数,动态波动溢出指数并做出了非线性检验。实证结果表明：变量国际油价解释了大部分的波动。方向性溢出指数是双向的和非对称的。在整个样本阶段系统的波动主要来自其他变量的冲击,变量国际油价的溢出效应占比重较大。变量国际油价、美国经济不确定性和中国股价对其他变量的波动溢出都存在非线性效应,前两者的正向变量的溢出效应较大,负向变量的溢出效应较小;后者的正向变量的溢出效应较小,负向变量的溢出效应较大。     

A robust statistical approach to select adequate error distributions for financial returns

In this article, we propose a robust statistical approach to select an appropriate error distribution, in a classical multiplicative heteroscedastic model. In a first step, unlike to the traditional approach, we do not use any GARCH-type estimation of the conditional variance. Instead, we propose to use a recently developed nonparametric procedure [31 D. Mercurio and V. Spokoiny, Statistical inference for time-inhomogeneous volatility models, Ann. Stat. 32 (2004), pp. 577–602.[Crossref], [Web of Science ®] , [Google Scholar]]: the local adaptive volatility estimation. The motivation for using this method is to avoid a possible model misspecification for the conditional variance. In a second step, we suggest a set of estimation and model selection procedures (Berk–Jones tests, kernel density-based selection, censored likelihood score, and coverage probability) based on the so-obtained residuals. These methods enable to assess the global fit of a set of distributions as well as to focus on their behaviour in the tails, giving us the capacity to map the strengths and weaknesses of the candidate distributions. A bootstrap procedure is provided to compute the rejection regions in this semiparametric context. Finally, we illustrate our methodology throughout a small simulation study and an application on three time series of daily returns (UBS stock returns, BOVESPA returns and EUR/USD exchange rates).     

Comparison of asymmetric stochastic volatility models under different correlation structures

This paper conducts simulation-based comparison of several stochastic volatility models with leverage effects. Two new variants of asymmetric stochastic volatility models, which are subject to a logarithmic transformation on the squared asset returns, are proposed. The leverage effect is introduced into the model through correlation either between the innovations of the observation equation and the latent process, or between the logarithm of squared asset returns and the latent process. Suitable Markov Chain Monte Carlo algorithms are developed for parameter estimation and model comparison. Simulation results show that our proposed formulation of the leverage effect and the accompanying inference methods give rise to reasonable parameter estimates. Applications to two data sets uncover a negative correlation (which can be interpreted as a leverage effect) between the observed returns and volatilities, and a negative correlation between the logarithm of squared returns and volatilities.     

The impact of jumps and leverage in forecasting covolatility

ABSTRACT

The paper investigates the impact of jumps in forecasting covolatility, accommodating leverage effects. We modify the preaveraged truncated covariance estimator of Koike (2016 Koike, Y. (2016). Estimation of integrated covariances in the simultaneous presence of non-synchronicity, microstructure noise and jumps. Econometric Theory 32:533–611.[Crossref], [Web of Science ®] , [Google Scholar]) such that the estimated matrix is positive definite. Using this approach, we can disentangle the estimates of the integrated covolatility matrix and jump variations from the quadratic covariation matrix. Empirical results for three stocks traded on the New York Stock Exchange indicate that the cojumps of two assets have a significant impact on future covolatility, but the impact is negligible for forecasting weekly and monthly horizons.     

First hitting time of integral diffusions and applications

We study the first hitting time of integral functionals of time-homogeneous diffusions, and characterize their Laplace transforms through a stochastic time change. We obtain explicit expressions of the Laplace transforms for the geometric Brownian motion (GBM) and the mean-reverting GBM process. We also introduce a novel probability identity based on an independent exponential randomization and obtain explicit Laplace transforms of the price of arithmetic Asian options and other derivative prices that non-linearly depend on the integral diffusions. Numerical examples are given to demonstrate the accuracy and efficiency of the proposed method.     

产业政策对股票特质波动率的影响及机制研究

本文考察了宏观产业政策对重点发展行业股票特质波动率的影响及其作用机制。首先根据非参数方法提取不同行业公司股票的特质波动率,然后根据中国五年规划所包含的重点发展行业,分析了产业政策对重点发展行业股票特质波动率的影响,并使用中介效应模型检验了产品市场竞争程度、经营环境不确定性和会计信息披露质量的中介作用。研究表明,产业政策会通过加剧重点发展行业内产品市场的竞争程度、增加行业内经营环境的不确定性以及降低会计信息披露质量三条路径来提高重点发展行业的股票特质波动率。为降低内生性问题,采用倾向得分匹配等方法后,仍然发现产业政策可以增加重点发展行业的股票特质波动率。进一步考察规模异质性、产权异质性和区域异质性后,本文发现产业政策对股票特质波动率的增加作用在中小企业、东部地区更加明显,但在国有企业和民营企业中无明显差别。     

Detecting level shifts in ARMA-GARCH (1,1) Models

The purpose of this article is to present a new method to detect level shifts in the context of conditional heteroscedastic models. First, we define precisely what type of outlier we are referring to, a concept that has been scarcely touched in the field of GARCH (1,1) models, and then we go on to present our methodology based on the nature of the Lagrange multiplier tests. The validity and efficiency of the proposed procedure are demonstrated through different simulation experiments. To conclude, we present a practical application of the method to the time series of returns of US short-term interest rates.     

机构持股对房地产股票收益波动的影响研究——基于面板数据的门限分位回归模型

针对在不同的股市行情中机构持股与房地产公司股票收益波动之间的相关性问题,建立面板数据的门限分位回归模型进行检验。证实在不同的市场行情中,对于股票收益波动处于不同水平的房地产公司,机构持股的影响程度存在差异。当股市大盘出现极端情形,机构投资者加剧股市波动。大盘大跌,机构持股的促进作用随着股票收益波动的分位点的增大而增强。在盘整市,机构持股比例没有对股票收益波动产生显著影响,但其变动抑制股票收益波动。     

基于高频面板数据的人民币汇率波动规律研究

基于2006—2013年的1771个人民币汇率日值高频数据,采用 GARCH 模型对人民币与美元、港币、日元、欧元及英镑之间的汇率波动规律进行实证分析。结果显示：（1）人民币兑五大外汇币种汇率的波动存在 ARCH 效应,其收益表现出明显的群聚特征;（2）人民币兑五大外汇币种汇率的波动均具有一定的记忆性,但除港币和日元外,大都会随时间缓慢衰减;（3）人民币兑五大外汇币种汇率的波动存在明显的杠杆效应,但不同币种对人民币升值的反应存在一定的差异。