Threshold non-linear dynamics between Hang Seng stock index and futures returns

We test the joint dynamics between the Hong Kong Hang Seng Index futures and the underlying cash index using a Bivariate Threshold AutoRegressive model, which is better able to capture the complex return dynamics evident in financial time series. The results are consistent with a three-regime version of the model, where the lead-lag relation between the index and futures returns is a non-linear threshold-type and the regime switching process depends on the state of the threshold variable. This interaction is symmetric rather than unidirectional, with the strength of the interaction dependent on the regime. These three regimes are also characterised by significant variation in volume, which is consistent with liquidity-induced arbitrage trading.     

基于EGRACH模型的股指期货对股市非对称性波动影响的实证研究

本文基于EGRACH模型,利用高频数据,实证检验了沪深300股指期货对我国股市非对称波动的影响。实证研究表明,沪深300股指期货与现货市场之间存在互为格兰杰因果关系,在股指期货初期股指期货对股市的波动有放大作用,在远期降低了非对称性波动,具有稳定股市的功效。     

基于波动效应与价格发现的期指仿真交易研究

沪深300股指期货仿真交易的推出,对我国现货市场的影响如何以及这种影响是否有利于现货效率的改进。首次采用修正的GARCH模型和向量误差修正模型（VEC）将股指期货推出后现货市场波动性的变化和股指期货与现货市场的价格发现功能结合起来进行对比研究。结果表明,期指仿真交易的推出对于现货市场效率的改进确实存在正面的影响。其引入在短期内加大了现货市场的波动,但这一波动正是市场信息流动加速的反映,因而提高了市场信息的传递效率。同时期货价格领先于现货价格,存在由期货市场到现货市场长期的单向因果关系,说明期货价格具有引导现货价格向均衡方向调整的功能,从而在经验上支持了股指期货市场的开放政策。     

Forecasting Changes in Copper Futures Volatility with GARCH Models Using an Iterated Algorithm

There is a gap in the literature regarding the out-of-sample forecasting ability of GARCH-type models applied to derivatives. A practitioner-oriented method (iterated cumulative sum of squares) is applied to detecting breakpoints in the variance of two copper futures series. Short-, intermediate-, and long-term out-of-sample forecasts of copper future series are compared to forecasts from a benchmark random walk model for each series. Not only do the GARCH-type models dominate the random walk model, but the relative improvement is fairly consistent across series, forecast horizon, and GARCH-type model. The evidence makes clear that, with few exceptions, the forecast improvement of the GARCH-type models over the RW model lies somewhere between 20–30%. It is particularly true that for the long-term close to close forecasts, there is great coherence among the forecasts. These all fall within a fairly narrow range.     

VaR方法在房地产收益波动性度量中的应用

本文探讨了VaR方法在房地产收益波动性度量中的应用,并对上海二手房指数时间序列的收益率风险进行了实证研究,结果表明此方法对于指数收益率风险的度量具有较强的适用性。     

Forecasting variance using stochastic volatility and GARCH

This paper estimates the conditional variance of daily Swedish OMX-index returns with stochastic volatility (SV) models and GARCH models and evaluates the in-sample performance as well as the out-of-sample forecasting ability of the models. Asymmetric as well as weekend/holiday effects are allowed for in the variance, and the assumption that errors are Gaussian is released. Evidence is found of a leverage effect and of higher variance during weekends. In both in-sample and out-of-sample comparisons SV models outperform GARCH models. However, while asymmetry, weekend/holiday effects and non-Gaussian errors are important for the in-sample fit, it is found that these factors do not contribute to enhancing the forecasting ability of the SV models.     

Volatility Transmission in the Real Estate Spot and Forward Markets

How shocks in one market influence the returns and volatility of other markets has been an important question for portfolio managers. In the finance literature, many studies found evidence of volatility spillovers across international markets, as well as between spot and futures markets. Although real estate is often regarded as a good vehicle for diversification, the dynamics of its volatility transmission have been largely ignored. This paper provides the first study to examine volatility spillovers between the spot and forward (pre-sale) index returns of the Hong Kong real estate market through a bivariate GARCH model. Transaction-based indices were used so that our volatility modelling was free from any smoothing problem. Our results showed that real estate returns exhibited volatility clustering, and the volatility of the forward market was more sensitive to shocks than the spot market. Moreover, volatility was mainly transmitted from the forward market to the spot market, but not vice versa.

沪深300股指期货VaR-GARCH模型风险管理研究——基于恒指期货的比较视角

股指期货是以股票指数作为标的的金融衍生产品,其在金融风险管理中具有重要作用,同时自身也面临较大的风险。VaR—GARCH模型能够较好地模拟金融市场时间序列数据,并作出相应的估计值,是当前主流的风险管理方法。本文基于香港恒指期货的比较视角,对我国去年推出的沪深300股指期货交易进行VaR—GARCH模型实证分析,得出VaR—GARCH模型能够较好地管理沪深300股指期货的风险的结论,并建议加强VaR技术的运用和加强跨市监管,更好地管理股指期货的风险。     

Interdaily Volatility in a Continuous Order-Driven Market

Since Amihud and Mendelson (1987) documented a higher open-to-open return volatility compared to close-to-close return volatility in the US market, there have been various explanations offered, such as call auction opening, a long halt of trade, and specialist systems. No consensus has been reached so far. As an order-driven dealership market, the Hong Kong stock market provides another dimension for examination. If halt of trade is the major cause of the open-to-open volatility in the Hong Kong market, this volatility should also be higher. This is not observed. Positive autocorrelation of the open-to-open return series also suggests that there is no temporary price deviation at market opening. We view these as consistent with the specialist argument put forth by Stoll and Whaley (1990).     

Forecasting volatility in GARCH models with additive outliers

We model the volatility of a single risky asset using a multifactor (matrix) Wishart affine process, recently introduced in finance by Gourieroux and Sufana. As in standard Duffie and Kan affine models the pricing problem can be solved through the Fast Fourier Transform of Carr and Madan. A numerical illustration shows that this specification provides a separate fit of the long-term and short-term implied volatility surface and, differently from previous diffusive stochastic volatility models, it is possible to identify a specific factor accounting for the stochastic leverage effect, a well-known stylized fact of the FX option markets analysed by Carr and Wu.     

Fund Volatility Index using equity market state prices

The Fund Volatility Index (FVX) is proposed as a forward measure of volatility with applications in fund hedging and risk management. The method applies equity market state prices to individual fund pay‐offs. FVX is validated as a predictor of short‐term realised volatility for 30 exchange traded funds. Performance of the method is compared with existing methods using a data set of 14 925 non‐traded funds. FVX has lower bias and higher forecast accuracy than existing methods. As a more general measure, it allows for incorporation of terms to capture individual fund skewness and projection of higher moments of returns.     

A nesting framework for Markov-switching GARCH modelling with an application to the German stock market

In this paper, we establish a generalized two-regime Markov-switching GARCH model which enables us to specify complex (symmetric and asymmetric) GARCH equations that may differ considerably in their functional forms across the two Markov regimes. We show how previously proposed collapsing procedures for the Markov-switching GARCH model can be extended to estimate our general specification by means of classical maximum-likelihood methods. We estimate several variants of the generalized Markov-switching GARCH model using daily excess returns of the German stock market index DAX sampled during the last decade. Our empirical study has two major findings. First, our generalized model outperforms all nested specifications in terms of (a) statistical fit (when model selection is based on likelihood ratio tests) and (b) out-of-sample volatility forecasting performance. Second, we find significant Markov-switching structures in German stock market data, with substantially differing volatility equations across the regimes.     

融资融券交易对市场和标的个股波动影响的研究

作为证券市场的重要制度之一,融资融券交易理论上应具有价格发现,价格稳定,提高流动性等基本功能。本文从融资、融券交易对市场和个股两个层面系统而全面的分析融资交易和融券交易的价格稳定作用。对市场波动性的影响的研究上主要借助GARCH族模型,VAR模型,脉冲响应和方差分解等计量分析方法;在对个股的影响上主要是借助面板数据分对个股的总体效应和个体效应展开分析。研究发现：融资交易对指数波动没有显著影响,融券交易对指数波动有一定平抑作用;融资融券交易对标的个股有价格稳定作用,除极个别个股的融资作用表现不确定。     

International linkage of the Russian market and the Russian financial crisis: A multivariate GARCH analysis

This study considers the linkage of the Russian equity market to the world market, examining the international transmission of the Russia's 1998 financial crisis utilizing the GARCH–BEKK model proposed by Engle and Kroner [Engle, R.F., Kroner, K.F., 1995. Multivariate simultaneous generalized ARCH. Economet. Theor. 11, 122–150]. We find evidence of direct linkage between the Russian equity market with regards to returns and volatility, while the weakness of the linkage suggests that the Russian equity market was only partially integrated into the world market. At the time of the crisis, evidence of contagion is clear.     

本次经济危机主要大宗商品期货价格波动性研究

本文在分析本次次债危机以来主要大宗商品价格变动情况的基础上,建立了ARMA和E-GARCH模型及ARMA和TARCH模型来描述本轮经济周期中石油、铜、铝、黄金、大豆和玉米等大宗商品的期货价格收益序列的波动性特征。自相关分析发现不同商品期货市场的有效性略有差异,原油和铜市场更为有效;ARMA和非对称GARCH模型表明,主要商品收益波动均具有积聚效应,原油和铝收益波动具有杠杆效应,坏消息对原油收益波动的冲击大于好消息,好消息对铝收益波动的冲击大于坏消息。     

货币政策应对股票价格波动的策略研究

实证研究发现,我国货币供给量对股票价格的影响力度较小且影响的方向不确定,而利率对股票价格的影响力度相对较大且是单一的负向影响,不过两者均不是股票价格的格兰杰原因.当前我国货币政策不具备调控股票价格的能力,我国应该注重培育"运用货币政策工具来影响股票价格"的能力,并密切关注股票价格波动.同时,我国要加快利率市场化步伐,合理运用证券市场信用控制,完善股票质押贷款管理办法,运用窗口指导,将股票价格作为辅助监测指标.     

公司透明度与股价波动同步性的相关性研究

本文选取2001-2007年在深交所上市的所有A股上市公司为研究样本,以深交所的信息披露评级指标作为公司信息透明度的度量指标,在此基础上,考察公司透明度对股价波动同步性的影响。实证结果表明,随着公司信息透明度的改善,股价同波动性不断下降,但各信用评级等级之间的股价同波动性差异并不高。本文给出了可能的分析解释,并指出了下一步深入研究的方向。     

Modeling the Conditional Covariance Between Stock and Bond Returns: A Multivariate GARCH Approach

To analyze the intertemporal interaction between the stock andbond market returns, we assume that the conditional covariancematrix follows a multivariate GARCH process. We allow for asymmetriceffects in conditional variances and covariances. Using dailydata, we find strong evidence of conditional heteroskedasticityin the covariance between stock and bond market returns. Theresults indicate that not only variances, but also covariancesrespond asymmetrically to return shocks. Bad news in the stockand bond market is typically followed by a higher conditionalcovariance than good news. Cross asymmetries, that is, asymmetriesfollowed from shocks of opposite signs, appear to be importantas well. Covariances between stock and bond returns tend tobe relatively low after bad news in the stock market and goodnews in the bond market. A financial application of our modelshows that optimal portfolio shares can be substantially affectedby asymmetries in covariances. Moreover, our results show sizablegains due to asymmetric volatility timing.     

Correlation and Volatility Dynamics in International Real Estate Securities Markets

We study international correlation and volatility dynamics of publicly traded real estate securities using monthly returns from 1984 and 2006. We also examine, for comparison, the correlations among the corresponding stock markets. A multivariate dynamic conditional correlation model captures the time-varying correlation within the full period. We confirm lower correlations between all real estate securities market returns than those between the stock market returns themselves. Some significant variations and structural changes in the correlation structure happened within the sample period. We detect a strong and positive connection between real estate securities market correlations and their conditional volatilities. We also find the international correlation structure of real estate securities and the broader stock market are linked to each other. Our results have economic motivations regarding the potential integration of international real estate securities markets and the possibility of including information on changing correlations and volatilities to design more optimal portfolios for international real estate securities.

Inequality Constraints in the Fractionally Integrated GARCH Model

In this article we derive necessary and sufficient conditionsfor the nonnegativity of the conditional variance in the fractionallyintegrated generalized autoregressive conditional heteroskedastic(p, d, q) (FIGARCH) model of the order p 2 and sufficient conditionsfor the general model. These conditions can be seen as beinganalogous to those derived by Nelson and Cao (1992, Journalof Business & Economic Statistics 10, 229–235) forthe GARCH(p, q) model. However, the inequality constraints whichwe derive for the FIGARCH model illustrate two remarkable propertiesof the FIGARCH model which are in contrast to the GARCH model:(i) even if all parameters are nonnegative, the conditionalvariance can become negative and (ii) even if all parametersare negative (apart from d), the conditional variance can benonnegative almost surely. In particular, the conditions forthe (1, d, 1) model substantially enlarge the sufficient parameterset provided by Bollerslev and Mikkelsen (1996, Journal of Econometrics73, 151–184). The importance of the result is illustratedin an empirical application of the FIGARCH(1, d, 1) model toJapanese yen versus U.S. dollar exchange rate data.