Dual long memory property in returns and volatility: Evidence from the CEE countries' stock markets

This paper investigates the presence of long memory in the eight Central and Eastern European (CEE) countries' stock market, using the ARFIMA, GPH, FIGARCH and HYGARCH models. The data set consists of daily returns, and long memory tests are carried out both for the returns and volatilities of these series. The results of the ARFIMA and GPH models indicate the existence of long memory in five of eight return series. The results also suggest that long memory dynamics in the returns and volatility might be modeled by using the ARFIMA–FIGARCH and ARFIMA–HYGARCH models. The results of these models indicate strong evidence of long memory both in conditional mean and conditional variance. Moreover, the ARFIMA–FIGARCH model provides the better out-of-sample forecast for the sampled stock markets.     

Realized Volatility Forecast: Structural Breaks,Long Memory,Asymmetry, and Day‐of‐the‐Week Effect

We investigate the properties of the realized volatility in Chinese stock markets by employing the high‐frequency data of Shanghai Stock Exchange Composite Index and four individual stocks from Shanghai Stock Exchange and Shenzhen Stock Exchange, and find that the volatility exhibits the properties of long‐term memory, structural breaks, asymmetry, and day‐of‐the‐week effect. In addition, the structural breaks only partially explain the long memory. To capture these properties simultaneously, we derive an adaptive asymmetry heterogeneous autoregressive model with day‐of‐the‐week effect and fractionally integrated generalized autoregressive conditional heteroskedasticity errors (HAR‐D‐FIGARCH) and use it to conduct a forecast of realized volatility. Compared with other heterogeneous autoregressive realized volatility models, the proposed model improves the in‐sample fit significantly. The proposed model is the best model for the day‐ahead realized volatility forecasts among the six models based on various loss functions by utilizing the superior predictive ability test.     

基于波动阶段划分的我国期铜市场长期记忆性实证研究

金融市场通常由于波动结构性突变的存在而出现伪长记忆性现象。运用ICSS算法寻找方差突变点进行阶段划分，运用V／S分析法对我国期铜市场波动阶段前后的长期记忆性进行检测和比较，并利用FIGARCH模型对波动序列的长期记忆性进行建模估计。研究结果表明，我国期铜市场存在全程长期记忆性；阶段划分后序列的长期记忆性显著降低；期铜波动的FIGARCH模型具有更优的拟舍效果和预测能力。     

ARCH族模型在上证收益率变动中的实证研究

股票价格的频繁波动是股票市场最明显的特征之一。利用ARCH模型及其扩展模型对上证综合指数的波动性进行实证研究,结果发现,我国上海股票市场收益率序列有明显的尖峰厚尾性、波动聚类性、非正态性以及存在条件异方差特性,波动的信息不对称性等特点。     

Value at risk and conditional extreme value theory via markov regime switching models

This study develops a new conditional extreme value theory‐based (EVT) model that incorporates the Markov regime switching process to forecast extreme risks in the stock markets. The study combines the Markov switching ARCH (SWARCH) model (which uses different sets of parameters for various states to cope with the structural changes for measuring the time‐varying volatility of the return distribution) with the EVT to model the tail distribution of the SWARCH processed residuals. The model is compared with unconditional EVT and conditional EVT‐GARCH models to estimate the extreme losses in three leading stock indices: S&P 500 Index, Hang Seng Index and Hang Seng China Enterprise Index. The study found that the EVT‐SWARCH model outperformed both the GARCH and SWARCH models in capturing the non‐normality and in providing accurate value‐at‐risk forecasts in the in‐sample and out‐sample tests. The EVTSWARCH model, which exhibits the features of measuring the volatility of a heteroscedastic financial return series and coping with the non‐normality owing to structural changes, can be an alternative measure of the tail risk. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:155–181, 2008     

Long memory models for daily and high frequency commodity futures returns

The volatility of daily futures returns for six important commodities are found to be well described as FIGARCH, fractionally integrated processes, whereas the mean returns exhibit very small departures from the martingale difference property. Several years of high frequency intraday commodity futures returns are also found to have very similar long memory in volatility features as the daily returns. Semiparametric local Whittle estimation of the long memory parameter in absolute returns also finds very significant long memory features. Estimating the long memory parameter across many different data sampling frequencies provides consistent estimates of the long memory parameter, suggesting that the series are self‐similar. The results have important implications for empirical work using commodity futures price data. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:643–668, 2007     

中国股市波动的CARR模型分析

ARCH/GARCH模型在波动性的预测已被学者广泛使用并在实证上得到良好的效果。本文以上海股市为研究对象,分别运用CARR模型和GARCH模型进行波动性预测,进而对两种方法的预测能力进行比较,实证结果表明CARR模型在拟合波动性方面优于GARCH模型。     

Commonality in the LME aluminum and copper volatility processes through a FIGARCH lens

Dynamic representation of spot and three‐month aluminum and copper volatilities is considered. Aluminum and copper are the two most important metals traded in the London Metal Exchange. They share common business cycle factors and are traded under identical contract specifications. The bivariate FIGARCH model, which allows parsimonious representation of long memory volatility processes, is applied. The results show that spot and three‐month aluminum and copper volatilities follow long memory processes, that they exhibit a common degree of fractional integration and that the processes are symmetric. However, there is no evidence that the processes are fractionally cointegrated. This high degree of commonality may result from the common LME trading process. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:935–962, 2008     

国际股票市场收益率和波动率的长记忆性研究

股票市场长记忆性问题是金融学研究的一个热点问题,对于市场有效性的研究和系统非线性结构的分析有着重要的意义。本文运用修正R/S分析和V/S分析两种方法对世界上28个国家(地区)的股票指数的日、周收益序列和日、周收益波动序列进行了完整的长记忆性研究。结果表明:对于收益序列,以美国为代表的大多数发达国家股市一般不存在长记忆性,而中国等发展中国家大多存在显著的长记忆性,尤其中国股市的长记忆性最强;对于收益波动序列,所有国家(地区)都具有长记忆性,并强于收益序列。     

基于状态转移波动模型的金融市场动态风险测度研究

测度金融市场动态风险VaR的一个关键在于如何准确刻画金融市场收益波动率。引入马尔可夫状态转移的ARCH（Regime switching ARCH,SWARCH）模型。构建出基于状态转移波动模型的金融市场动态风险测度模型,然后运用其对中国大陆上证综指和伦敦金融时报100指数的市场风险进行测度,并运用Back-testing中的似然比率检验方法（Likelihood Ratio Test,LRT）对金融市场风险测度的准确性进行检验。实证结果表明,基于SWARCH的风险测度模型,不仅能够准确测度不同类型金融市场的动态风险,而且在测度金融市场大风险方面展现出同样具有优越的测度能力。     

证券交易税对市场波动性的影响:来自中国股市的证据

本文运用ARCH族模型检验了2001年股票交易印花税税率降低对沪、深股市波动性的影响,为有关证券交易税对市场波动性影响的讨论增添了一个来自新兴市场的证据。计量结果表明,该次税率变动对沪市波动性的影响在统计上是不显著的;深市的波动性在税率降低后虽然有统计上显著的增加,但是这个变化太小,没有实际意义。我们的研究结果表明,对于像中国股市这类市场结构和市场制度处于变化之中的新兴市场,如果试图通过调整证券交易税税率这类显性的交易成本来影响市场波动性,其效果是有限的。     

The specification of GARCH models with stochastic covariates

A number of studies investigate whether various stochastic variables explain changes in return volatility by specifying the variables as covariates in a GARCH(1, 1) or EGARCH(1, 1) model. The authors show that these models impose an implicit constraint that can obscure the true role of the covariates in the analysis. They illustrate the problem by reconsidering the role of contemporaneous trading volume in explaining ARCH effects in daily stock returns. Once the constraint imposed in earlier research is relaxed, it is found that specifying volume as a covariate does little to diminish the importance of lagged squared returns in capturing the dynamics of volatility. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:911–934, 2008     

Regime‐switching in stock index and Treasury futures returns and measures of stock market stress

We investigate bivariate regime‐switching in daily futures‐contract returns for the US stock index and ten‐year Treasury notes over the crisis‐rich 1997–2005 period. We allow the return means, volatilities, and correlation to all vary across regimes. We document a striking contrast between regimes, with a high‐stress regime that exhibits a much higher stock volatility, a much lower stock–bond correlation, and a higher mean bond return. The high‐stress regime is associated with higher average values of stock‐implied volatility, stock illiquidity, and stock and bond futures trading volume. The lagged implied volatility from equity‐index options is useful in modeling the time‐varying transition probabilities of the regime‐switching process. Our findings support the notions that: (1) stock market stress can have a material influence on Treasury bond pricing, and (2) the diversification benefits of combined stock–bond holdings tend to be greater during times with relatively high stock market stress. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:753–779, 2010     

沪深300指数的ARCH效应

股价指数的收益率序列具有时变波动性、厚尾特征、波动性群集等特点,传统的计量分析无法刻画这些特点。通过对即将推出的股指期货的标的指数-沪深300指数的收益率序列进行AR-CH效应分析．采用ARCH模型及其扩展形式对沪深300指数的波动性进行实证分析,结果表明沪深300指数的收益率序列是有偏的,并具有尖峰厚尾的特点。同时也具有波动的群集性和不对称性的特点。     

What moves the gold market?

In this article, we provide a detailed characterization of the intraday return volatility in gold futures contracts traded on the COMEX division of the New York Mercantile Exchange. The approach allows the study of intraday patterns, interday ARCH effects, and announcement effects in a coherent framework. We show that the intraday patterns exert a profound impact on the dynamics of return volatility. Among the 23 U.S. macroeconomic announcements, we identify employment reports, gross domestic product, consumer price index, and personal income as having the greatest impact. Finally, by appropriately filtering out the intraday patterns, we find that the high‐frequency returns reveal long‐memory volatility dependencies in the gold market, which have important implications on the pricing of long‐term gold options and the determination of optimal hedge ratios. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:257–278, 2001     

不同目标类型的开放式基金收益率特征分析

本文利用传统的单指数模型和ARCH模型，分析了开放式基金的收益率的统计特征、ARCH效应及与股价指数的关系。实证结果表示开放式基金的收益率基本具备GARCH(1，1)特征，与股价指数有较强的相关性，但不同目标的开放式基金与股指的关系有所差异，说明基金管理公司在选择投资组合上与基金目标较为一致。有超过一半的样本基金的平均收益率低于同期股指收益率，盈利能力不甚理想。     

The stock closing calland futures price behavior: Evidence from the Taiwan futures market

This study examines the behavior of futures prices around stock market close before and after changes to the batching period of the stock closing call. On July 1, 2002, the Taiwan Stock Exchange expanded the length of the batching period roughly 10‐fold, from an average of 30 seconds to 5 minutes. This change presents an opportunity to analyze how a stock closing method affects the behavior of index futures prices. Empirical results indicate that an increase in the length of the batching period affects the return volatility and trading volume of index futures contracts around stock market close. Furthermore, preclose stock returns have a great impact on extended futures returns when the batching period of the stock closing call is long. © 2007 Wiley Periodicals, Inc. Jrl Fut Mark 27:1003–1019, 2007     

中国证券市场波动的区制关联性

应用单变量和二元向量SW-ARCH模型,本文发现我国证券市场收益率波动具有明显的"区制转移"特征,可以将其分为"高波动"和"低波动"两个区制.在"高波动区制"下,沪深两市间具有明显的波动"溢出"和"传染"特征,市场整体风险强;相反,在"低波动区制"下,市场间主要表现"低系统风险"特征,负相关的波动关联性使证券市场具有较强的风险分散功能和较高的资金配置效率.     

Pricing FTSE 100 index options under stochastic volatility

The autoregressive conditional heteroscedasticity/generalized autoregressive conditional heteroscedasticity (ARCH/GARCH) literature and studies of implied volatility clearly show that volatility changes over time. This article investigates the improvement in the pricing of Financial Times‐Stock Exchange (FTSE) 100 index options when stochastic volatility is taken into account. The major tool for this analysis is Heston’s (1993) stochastic volatility option pricing formula, which allows for systematic volatility risk and arbitrary correlation between underlying returns and volatility. The results reveal significant evidence of stochastic volatility implicit in option prices, suggesting that this phenomenon is essential to improving the performance of the Black–Scholes model (Black & Scholes, 1973) for FTSE 100 index options. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:197–211, 2001