This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictor...This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictors are highly persistent and their innovations are contemporarily correlated with dependent variable, the ordinary least squares estimator has a finite-sample bias, and its limiting distribution relies on some unknown nuisance parameter, which is not consistently estimable. Without correcting these issues, conventional test statistics are subject to a serious size distortion and generate a misleading conclusion in testing pre- dictability of asset returns in real applications. In the past two decades, sequential studies have contributed to this subject and proposed various kinds of solutions, including, but not limit to, the bias-correction procedures, the linear projection approach, the IVX filtering idea, the variable addition approaches, the weighted empirical likelihood method, and the double-weight robust approach. Particularly, to catch up with the fast-growing literature in the recent decade, we offer a selective overview of these methods. Finally, some future research topics, such as the econometric theory for predictive regressions with structural changes, and nonparametric predictive models, and predictive models under a more general data setting, are also discussed.展开更多
在超高频金融数据分析中,由于各种交易摩擦,观测到的资产价格通常受到市场微观结构嗓声的“污染”.已有文献通常认为噪声不包含任何信息并且对有效价格的推断带来诸多不便,因而是一个“丑陋”的现象。然而,最近一些研究表明噪声与有效...在超高频金融数据分析中,由于各种交易摩擦,观测到的资产价格通常受到市场微观结构嗓声的“污染”.已有文献通常认为噪声不包含任何信息并且对有效价格的推断带来诸多不便,因而是一个“丑陋”的现象。然而,最近一些研究表明噪声与有效价格相关,可能包含潜在价格有关的信息,基于门限预平均已实现方差估计,本文从中国股市逐笔交易数据中分离出噪声方差、跳跃波动与连续波动,进而采用异质自回归(Heterogeneous Autoregressive,HAR)模型和面板HAR模型考察噪声方差及其不同成分与有效价格波动之间相互预测能力的差异及其可能原因。研究发现:(1)噪声方差具有很强的相依性,与连续波动和跳跃波幼之间均存在一定的相互预测能力,特别是噪声方差与连续波动之间预测回归的显著性更强;(2)噪声方差与交易量同步知情交易者概率(Volume-synchronized Probability of Informed Trading,VPIN)显著正相关,在将噪声方差进一步分解为包含信息部分与非信息部分之后,实证发现噪声方差与连续波动之间相互预测作用主要体现在信息部分,噪声方差对跳跃波动预测作用主要体现在其信息部分,而跳跃波动主要对噪声方差的非信息部分具有预測作用。本文的研究对加强市场风险管理和理解市场微观结构理论均具有重要的意义.展开更多
基金supported by the National Natural Science Foundation of China(71631004,71571152)the Fundamental Research Funds for the Central Universities(20720171002,20720170090)the Fok Ying-Tong Education Foundation(151084)
文摘This paper highlights some recent developments in testing predictability of asset returns with focuses on linear mean regressions, quantile regressions and nonlinear regression models. For these models, when predictors are highly persistent and their innovations are contemporarily correlated with dependent variable, the ordinary least squares estimator has a finite-sample bias, and its limiting distribution relies on some unknown nuisance parameter, which is not consistently estimable. Without correcting these issues, conventional test statistics are subject to a serious size distortion and generate a misleading conclusion in testing pre- dictability of asset returns in real applications. In the past two decades, sequential studies have contributed to this subject and proposed various kinds of solutions, including, but not limit to, the bias-correction procedures, the linear projection approach, the IVX filtering idea, the variable addition approaches, the weighted empirical likelihood method, and the double-weight robust approach. Particularly, to catch up with the fast-growing literature in the recent decade, we offer a selective overview of these methods. Finally, some future research topics, such as the econometric theory for predictive regressions with structural changes, and nonparametric predictive models, and predictive models under a more general data setting, are also discussed.
文摘在超高频金融数据分析中,由于各种交易摩擦,观测到的资产价格通常受到市场微观结构嗓声的“污染”.已有文献通常认为噪声不包含任何信息并且对有效价格的推断带来诸多不便,因而是一个“丑陋”的现象。然而,最近一些研究表明噪声与有效价格相关,可能包含潜在价格有关的信息,基于门限预平均已实现方差估计,本文从中国股市逐笔交易数据中分离出噪声方差、跳跃波动与连续波动,进而采用异质自回归(Heterogeneous Autoregressive,HAR)模型和面板HAR模型考察噪声方差及其不同成分与有效价格波动之间相互预测能力的差异及其可能原因。研究发现:(1)噪声方差具有很强的相依性,与连续波动和跳跃波幼之间均存在一定的相互预测能力,特别是噪声方差与连续波动之间预测回归的显著性更强;(2)噪声方差与交易量同步知情交易者概率(Volume-synchronized Probability of Informed Trading,VPIN)显著正相关,在将噪声方差进一步分解为包含信息部分与非信息部分之后,实证发现噪声方差与连续波动之间相互预测作用主要体现在信息部分,噪声方差对跳跃波动预测作用主要体现在其信息部分,而跳跃波动主要对噪声方差的非信息部分具有预測作用。本文的研究对加强市场风险管理和理解市场微观结构理论均具有重要的意义.
