Stationary bootstrapping for realized covariations of high frequency financial data

This paper studies the stationary bootstrap applicability for realized covariations of high frequency asynchronous financial data. The stationary bootstrap method, which is characterized by a block-bootstrap with random block length, is applied to estimate the integrated covariations. The bootstrap realized covariance, bootstrap realized regression coefficient and bootstrap realized correlation coefficient are proposed, and the validity of the stationary bootstrapping for them is established both for large sample and for finite sample. Consistencies of bootstrap distributions are established, which provide us valid stationary bootstrap confidence intervals. The bootstrap confidence intervals do not require a consistent estimator of a nuisance parameter arising from nonsynchronous unequally spaced sampling while those based on a normal asymptotic theory require a consistent estimator. A Monte-Carlo comparison reveals that the proposed stationary bootstrap confidence intervals have better coverage probabilities than those based on normal approximation.     

Estimation of parameters of SDE driven by fractional Brownian motion with polynomial drift

ABSTRACT

Strongly consistent and asymptotically normal estimators of the Hurst index and volatility parameters of solutions of stochastic differential equations with polynomial drift are proposed. The estimators are based on discrete observations of the underlying processes.     

中国股票市场波动率的多重分形分析与实证

我国股票市场波动表现出随时间变化的动态特征。文章采用多重消除趋势波动分析法(MFDFA),对沪深股市四个主要指数的日波动率时间序列进行了分析。结果表明,沪深股市四个主要指数的日波动率时间序列均表现出多重分形特征,且上证指数和中证500指数日波动率序列相对于其他两个指数日波动率序列表现出更强的多重分形特征。各指数日波动率时间序列的多重分形特征均是自身的长程相关性和波动的厚尾分布共同作用的结果,且波动的厚尾分布对原始序列的多重分形特征的影响比长程相关性大。     

基于混频数据模型的宏观经济对股票市场波动的长期动态影响研究

股票价格时间序列与宏观经济变量时间序列原始数据的不同频直接导致传统计量模型在处理宏观经济波动与股票市场波动的关系问题中产生模型误设和估计偏误。本文运用混频自回归条件异方差模型从水平值和波动率两个维度实证分析生产者价格指数、居民消费价格指数、宏观经济景气指数及同业拆借利率四个宏观经济变量对股票市场波动的长期动态影响。同时,运用主成分分析提取宏观经济第一主成分并构建一个宏观经济综合指数,进一步探究宏观经济总体状况对股票市场波动的长期影响。研究发现：股票市场已实现波动率显著地放大了股票市场的长期波动。生产者价格指数、居民消费价格指数、宏观经济景气指数的水平值和波动率均对股票市场长期波动产生显著影响;且其波动率维度呈现出较强的持续效应;同业拆借利率仅在水平值维度对股票市场波动长期成分产生微弱影响。宏观经济第一主成分和宏观综合指数的波动率对股票市场波动长期成分均具有显著的正向放大作用,但持续效应较弱;而其水平值对股票市场波动长期成分的影响虽然微弱,但持续时间较长。     

中国沪深股市的开盘效应与收盘效应

股票市场的日历效应历来受到学者和投资者的广泛关注,研究发现股市存在节日效应、月份效应与周内效应,但是针对日内效应的研究不多见.利用沪深股指2004年~2016年的高频数据,实证检验中国沪深股市是否存在日内效应,结果表明:中国沪深股市整体上存在开盘效应与收盘效应,但在牛市、熊市期间的表现形式存在差异,股指收益在牛市期间表现出正向开盘效应,在熊市期间表现出负向开盘效应,股指波动在熊市期间的开盘效应更为明显.基于滚动窗口法的进一步研究发现:股指收益开盘效应和收盘效应的变化领先于股指走势的变化,股指收益和波动的开盘效应或收盘效应存在一定程度的替代现象.研究有助于投资者合理地制定投资策略,对监管部门维护市场秩序具有一定的参考价值.     

Affine LIBOR models driven by real-valued affine processes

The class of affine LIBOR models is appealing since it satisfies three central requirements of interest rate modeling. It is arbitrage-free, interest rates are nonnegative, and caplet and swaption prices can be calculated analytically. In order to guarantee nonnegative interest rates affine LIBOR models are driven by nonnegative affine processes, a restriction that makes it hard to produce volatility smiles. We modify the affine LIBOR models in such a way that real-valued affine processes can be used without destroying the nonnegativity of interest rates. Numerical examples show that in this class of models, pronounced volatility smiles are possible.     

Intraday Serial Correlation,Volatility, and Jump: Evidence from China's Stock Market

In this article, we investigate the relationships among intraday serial correlation, jump-robust volatility, positive and negative jumps based on Shanghai composite index high frequency data. We implement variance ratio test to quantify intraday serial correlation. We also measure the continuous part of realized volatility using jump-robust MedRV estimator and disentangle positive and negative jumps using Realized Downside Risk Measure and Realized Upside Potential Measure proposed by Bi et al., (2013 Bi, T., Zhang, B., Wu, H. (2013). Measuring downside risk using high frequency data–realized downside risk measure. Communications in Statistics–Simulation and Computation 42(4):741–754.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). We find that intraday serial correlation are positively correlated with jump-robust volatility and negatively correlated with negative jumps which confirm the LeBaron effect.     

股票供给曲线凸现向后弯曲与理性投资决策

股票市场价格的高低及变动是对股票内在价值高低及变动的综合反映和表现,其价格的形成直接取决于市场的供求关系,而影响和调节股票供求量的并不是单位股票的绝对价格水平的高低及变动,它是股票作为投资品的单位内在价值的市场价格水平的高低及变动。由于股票收入效应和替代效应的存在又使股票供给曲线向后弯曲提升了股票的内在价值,这一表象成为引起股价波动背后的主要理性因素,从而为投资决策提供理性依据。     

国家能力、出口复杂度与经济增长波动 ——来自178个国家面板数据的经验证据

作为生产产品所需要的不可交易的投入品集合,国家能力的增加不但有利于经济产出的增长,而且能够增强经济体系中供给和需求的稳定性,进而有利于降低经济产出的波动性;出口复杂度的高低可以反映一国能力的多少,因而出口复杂度的提高可以降低供给波动、需求波动和产出波动.对1998—2017年178个样本国家的分析发现:出口复杂度的提高...     

高频数据瞬时波动率核估计的窗宽选择及算法研究

在瞬时波动率的各种估计量中,非参数估计量因其能准确地度量瞬时波动率,一直是学者们的研究热点。然而,这类估计量在实际应用中都面临着最优窗宽的确定问题。由于最优窗宽中往往携带一些难以估计的未知参数,使得在实际应用过程中确定最优窗宽的具体数值存在困难。本文以瞬时波动率的核估计量为例,借鉴非参数回归分析中窗宽选择的思想,构建了一种能从数据中准确计算出最优窗宽具体值的算法。理论的分析和数值上的验证表明：文中所构建的算法具有良好的稳定性、适应性和收敛速度。算法的提出为瞬时波动率的后续应用研究铺平道路。