The hedging effectiveness of constant and time-varying hedge ratios using three Pacific Basin stock futures

This paper investigates the hedging effectiveness of Australian, Hong Kong, and Japanese stock futures markets. The traditional hedge and the minimum variance hedge ratios are all constant whereas the bivariate GARCH hedge ratio is time varying. The effectiveness of the hedge ratio is compared by investigating the out-of-sample performance of the three ratios. The whole sample consists of weekly returns from January 1990 to December 2000. Two 1-year, out-of-sample periods are used: January 1999 to December 1999 and January 2000 to December 2000. Results show that the time-varying GARCH hedge ratio outperforms the constant ratios in most of the cases. This is true using both out-of-sample periods.     

Estimating Systematic Risk Using Time Varying Distributions

This article proposes a dynamic vector GARCH model for the estimation of time-varying betas. The model allows the conditional variances and the conditional covariance between individual portfolio returns and market portfolio returns to respond asymmetrically to past innovations depending on their sign. Covariances tend to be higher during market declines. There is substantial time variation in betas but the evidence on beta asymmetry is mixed. Specifically, in 50% of the cases betas are higher during market declines and for the remaining 50% the opposite is true. A time series analysis of estimated time varying betas reveals that they follow stationary mean-reverting processes. The average degree of persistence is approximately four days. It is also found that the static market model overstates non-market or, unsystematic risk by more than 10%. On the basis of an array of diagnostics it is confirmed that the vector GARCH model provides a richer framework for the analysis of the dynamics of systematic risk.     

An Empirical Study of Volatility in Seven Southeast Asian Stock Markets Using ARV Models

This paper investigates the volatility persistence, volatility variability from day to day and transmission of volatility in seven Southeast Asian stock markets from 1980 to 1991 using the ARV approach. We found strong evidence that shocks to volatility are persistent in Taiwan. Moreover, the Stock Exchange of Thailand Daily Index has the strongest interday volatility fluctuation. Instantaneous causality of volatility among six of the seven markets (except Seoul) was discovered. Besides, there is significant volatility spillover effect from Hong Kong to Taiwan, Malaysia to Singapore and Singapore to Malaysia in the period 1980 to 1991.     

Long-memory and heterogeneous components in high frequency Pacific-Basin exchange rate volatility

Recent research examining high-frequency financial data has suggested that volatility dynamics may be confounded by the existence of an intra-day periodic pattern and multiple sources of volatility. This paper examines whether these dynamics are present in the US Dollar exchange rates of five Pacific Basin economies. Using 30-min sampled returns, evidence of a ‘U’-shape intra-day pattern in volatility for regional markets is reported and controlled for using a Flexible Fourier transform. Supportive evidence for the existence of multiple volatility components is offered by semi-parametric fractional difference estimates of the long-memory properties of absolute exchange rate returns at various intra-day data sampling frequencies. Further parametric evidence of an explicit component structure in such high frequency exchange rate volatility is offered by the estimates of a component-GARCH model which comprises both a long-run volatility component exhibiting slow shock decay and a short-run volatility component exhibiting far more rapid decay, and provides a generally superior fit to the data. Further application of these C-GARCH models in the analysis of high frequency volatility spillovers between the currencies considered also reveals that such spillovers are predominantly transitory rather than highly persistent in nature, but that where volatility spillovers do impact on the long-run component of exchange rate volatility the Australian Dollar plays a pivotal role in the localised causality transmission mechanism.      

International Asset Excess Returns and Multivariate Conditional Volatilities

This paper constructs a multivariate model in relating multi-asset excess returns to their conditional variances. Applying weekly data to investigate the foreign-exchange risk premium, the evidence from a multivariate GARCH model shows that the foreign-exchange excess returns are significantly correlated with economic fundamentals such as the real interest-rate differential, long-short interest-rate spread differential, and equity-premium differential. The evidence also suggests that foreign-exchange excess returns are not independent of the conditional variances of these fundamental variables, supporting the time-varying risk-premium hypothesis.     

国际原油价格波动是否增加了国内CPI通胀率的不确定性?

本文选取2001年1月至2011年10月的月度统计数据,基于二阶矩意义的Granger因果检验方法,在多元GARCH模型框架下,运用残差向量的方差-协方差矩阵所包含的信息,构建非对称的BEKK模型,对国际油价波动与国内消费者价格指数(CPI)通胀率不确定性的因果关系进行了检验。结论表明,国际油价波动会向国内CPI输出不确定性因素,且短期油价上涨更容易增加国内CPI的不确定性;但国内CPI变动无法向国际油价输出不确定性。     

基于VaR-GARCH模型对证券投资基金风险的实证研究

根据证券投资基金收益率序列的尖峰厚尾特征,建立估计基金风险的VaR—GARCH模型。在正态分布、t分布及GED分布三种不同的分布假设下,对基金的VaR值进行估计,并应用Kupiec失败频率检验方法对VaR模型的准确性进行了返回检验。研究结果表明,相比之下,基于GED分布的GARCH模型计算的VaR值最能真实地反映基金风险。     

Good jump,bad jump,and option valuation

I develop a new class of closed‐form option pricing models that incorporate variance risk premium and symmetric or asymmetric double exponential jump diffusion. These models decompose the jump component into upward and downward jumps using two independent exponential distributions and thus capture the impact of good and bad news on asset returns and option prices. The empirical results show that the model with an asymmetric double exponential jump diffusion improves the fit on Shanghai Stock Exchange 50ETF returns and options and provides relatively better in‐ and out‐of‐sample pricing performance.     

Forecasting value‐at‐risk in oil prices in the presence of volatility shifts

Recent evidence suggests shifts (structural breaks) in the volatility of returns causes non‐normality by significantly increasing kurtosis. In this paper, we endogenously detect significant shifts in the volatility of oil prices and incorporate this information to estimate Value‐at‐Risk (VaR) to accurately forecast large declines in oil prices. Our out‐of‐sample performance results indicate that the model, which incorporates both time varying volatility (without making any distributional assumptions) and shifts in volatility, produces more accurate VaR forecasts than several benchmark methods. We make a timely contribution as the recent more frequent occurrences of unexpected large oil price declines has gained significant attention because of its substantial impact on the financial markets and the global economy.     

Option pricing based on hybrid GARCH-type models with improved ensemble empirical mode decomposition

The exploration of option pricing is of great significance to risk management and investments. One important challenge to existing research is how to describe the underlying asset price process and fluctuation features accurately. Considering the benefits of ensemble empirical mode decomposition (EEMD) in depicting the fluctuation features of financial time series, we construct an option pricing model based on the new hybrid generalized autoregressive conditional heteroskedastic (hybrid GARCH)-type functions with improved EEMD by decomposing the original return series into the high frequency, low frequency and trend terms. Using the locally risk-neutral valuation relationship (LRNVR), we obtain an equivalent martingale measure and option prices with different maturities based on Monte Carlo simulations. The empirical results indicate that this novel model can substantially capture volatility features and it performs much better than the M-GARCH and Black–Scholes models. In particular, the decomposition is consistently helpful in reducing option pricing errors, thereby proving the innovativeness and effectiveness of the hybrid GARCH option pricing model.