The linkages,persistence, asymmetry in the volatility,the price discovery and efficiency,and the effect of the US subprime mortgage financial crisis on the spot and the futures market’s returns: the case of India

This article examines the effects of persistence, asymmetry and the US subprime mortgage crisis on the volatility of the returns and also the price discovery, efficiency and the linkages and causality between the spot and futures volatility by using various classes of the ARCH and GARCH models, and through the Granger’s causality. We have used two indices: one for spot and the other for futures, for the daily data from 12 June 2000 to 30 September 2013 from Nifty stock indices. We have then tested for ARCH effects, and subsequently employed various models of the ARCH and GARCH conditional volatility. The GARCH(1,1) model is found to be significant, and it implies that the returns are not autocorrelated and have ‘short memory’. It supports the hypothesis of the efficiency of the markets. The negative ‘news’ has more significant effect on volatility, corroborating the ‘leverage impact’ in finance on market volatility. We have also tested the volatility spillover effects. The two methods we employed support the spillover effects and the causality is bidirectional. We also have used the dummy variable for the US subprime mortgage financial crisis and found that they are statistically significant. Indian stock market is thus integrated to the world stock markets.     

小麦期货市场价格波动与到期效应的实证研究

通过对小麦期货市场期货品种收益率的分布与波动性进行实证分析,论证其时间序列存在ARCH效应;运用ARMA-GARCH模型对小麦期货品种进行了拟合分析和统计检验,结果表明小麦期货品种的波动性具有很高的持续性。通过添加到期时间的哑变量,可以证明大多数小麦期货合约存在到期效应。     

Structural breaks and GARCH models of stock return volatility: The case of South Africa

This paper investigates the empirical relevance of structural breaks in forecasting stock return volatility using both in-sample and out-of-sample tests applied to daily returns of the Johannesburg Stock Exchange (JSE) All Share Index from 07/02/1995 to 08/25/2010. We find evidence of structural breaks in the unconditional variance of the stock returns series over the period, with high levels of persistence and variability in the parameter estimates of the GARCH(1,1) model across the sub-samples defined by the structural breaks. This indicates that structural breaks are empirically relevant to stock return volatility in South Africa. However, based on the out-of-sample forecasting exercise, we find that even though there structural breaks in the volatility, there are no statistical gains from using competing models that explicitly accounts for structural breaks, relative to a GARCH(1,1) model with expanding window. This could be because of the fact that the two identified structural breaks occurred in our out-of-sample, and recursive estimation of the GARCH(1,1) model is perhaps sufficient to account for the effect of the breaks on the parameter estimates. Finally, we highlight that, given the point of the breaks, perhaps what seems more important in South Africa, is accounting for leverage effects, especially in terms of long-horizon forecasting of stock return volatility.     

Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models.

     

Price and volatility dynamics between securitized real estate spot and futures markets

This study is among the first to examine the price, volatility and covariance dynamics between securitized real estate spot and futures markets. It provides a distinctive and yet complementary perspective on the predictability of real estate spot return and spot volatility based on the information from the spot market alone. The results show that for the EPRA/NAREIT Europe index, the spot market tends to lead its futures market in the long run during the sample period, which can be attributed to a rather illiquid real estate futures market in sharp contrast with a voluminous spot market. Furthermore, we find the V-shaped asymmetric effect of the basis on the futures market volatility, which represents the primary channel of strong volatility transmission between securitized real estate spot and futures markets during the whole sample and the post-crisis period. This sheds light on the hedging effectiveness for the REIT index.     

The Impact of Monetary Surprises on Australian Financial Futures Markets: An Insight into Cash Rate Target Announcements

This paper investigates the impact of unanticipated Australian monetary policy changes on AUD/USD exchange rate futures, and 3‐year and 10‐year Australian Treasury bond futures, during the period from January 1997 to April 2010. Our study contributes to the literature by using both the 30‐day and the 90‐day bank accepted bill (BAB) rates to disentangle the unexpected surprise component of monetary policy changes from overall cash rate target changes in the Australian money market, and by concurrently modelling the effects of monetary surprises and other key macroeconomic announcements in Australia. The empirical results suggest that the 30‐day BAB rate is the best proxy for the expected monetary policy actions. We find that the effect of monetary surprises on the volatility of the 3‐ and 10‐year bond future instruments is significant and persistent. We have also documented a strong monetary policy effect on the mean returns of the exchange rate futures, indicating that unexpected monetary policy adjustments have a significant impact on the level of the exchange rate movements rather than on the volatility of the FX futures market.     

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.     

Forecasting realized volatility of crude oil futures with equity market uncertainty

This paper examines whether the equity market uncertainty (EMU) index contains incremental information for forecasting the realized volatility of crude oil futures. We use 5-min high-frequency transaction data for WTI crude oil futures and develop six heterogeneous autoregressive (HAR) models based on classical HAR-type models. The empirical results suggest that EMU contains more incremental information than the economic policy uncertainty (EPU) for forecasting the realized volatility of crude oil futures. More importantly, we argue that EMU is a non negligible additional predictive variable that can significantly improve the 1-day ahead predictive accuracy of all six HAR-type models, and improve the 1-week ahead forecasting performance of the HAR-RV, HAR-RV-J, HAR-RSV, HAR-RV-SJ models. These findings highlight a strong short-term and a weak mid-term predictive ability of EMU in the crude oil futures market.     

Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index

This article develops a leverage trend Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model by incorporating asymmetric trend of returns of the exponential autoregressive and asymmetric volatility of GARCH models to study the asymmetric effects. Using in-sample daily data of Taiex over the period 4 January 1980 to 25 August 1997 and postsample daily data over the period 26 August 1997 to 10 September 2007, the evidence reveals that a curvaceous risk–return relationship and both asymmetric volatility and asymmetric trend of returns are significant in Taiex. The episode of asymmetric trend of returns is that the positive information creates a higher return trend than the negative information of the same amount, while similarly to most studies, the evidence of asymmetric volatility appears that the negative information makes a higher volatility than the positive information of the same size. Most remarkably, we evidence that the volatility asymmetry effect is a conservative trading factor and the return trend asymmetry effect is an active trading factor. In comparison of post-sample performance using rolling-window technique, the leverage trend GARCH model indeed outperforms the other three models with single asymmetry adjusted or without asymmetry adjusted, while the asymmetry nonadjusted model performs the worst. It implies that the return trend asymmetry (active trading) and the volatility asymmetry effects (conservative trading) tend to compensate, but not offset each other.     

Forecasting the oil futures price volatility: A new approach

This study provides a new perspective of modelling and forecasting realized range-based volatility (RRV) for crude oil futures. We are the first to improve the Heterogeneous Autoregressive model of Realized Range-based Volatility (HAR-RRV) model by considering the significant jump components, signed returns and volatility of realized range-based volatility. The empirical results show that the volatility of volatility significantly exists in the oil futures market. Moreover, our new proposed models with significant jump components, signed returns and volatility of volatility can gain higher forecast accuracy than HAR-RRV-type models. The results are robust to different forecasting windows and forecasting horizons. Our new findings are strategically important for investors making better decisions.     

人民币汇率与股市收益的动态关联性实证研究

利用基于广义误差分布（GED）的多因素TGARCH模型,实证分析了2005年7月21日汇改后人民币汇率与中国股市收益的动态关系。估计结果显示：人民币汇率对股市收益有显著的价格扩散效应,汇率上升会引起上证指数收益率较大幅度的上升;股市收益波动存在显著的ARCH效应和GARCH效应,并且等强度的正向或负向新息的冲击会引起股市波动的非对称反应,正向冲击比同强度的负向冲击能带来股市更大的未来波动。     

Nonlinearities in carbon spot-futures price relationships during Phase II of the EU ETS

This paper uses the Vector Autoregressive (VAR) model and the Switching Transition Regression-Exponential GARCH models (STR-EGARCH) to examine the dynamic relationships between the EU Emission Allowances (EUA) spot and futures prices during Phase II. Compared to the majority of previous studies, our empirical approach allows us to simultaneously capture asymmetry and nonlinearity effects in both return and volatility processes of carbon allowance prices. Our main findings show that carbon spot and futures returns are asymmetrically and nonlinearly linked, suggesting the usefulness of nonlinear models in pricing and forecasting carbon allowances prices.     

有偏型EWMA的股指期货保证金设定的实证研究

本文是对建立在正态分布假设的EWMA期货保证金模型的改进.文中引入基于非对称Laplace分布发展起来的有偏型EWMA方法,建立了新的期货交易保证金模型,较好地反映了期货合约价格序列有偏、厚尾的现象.同时采用comish-Fisher(CF)方法确定出期货价格波动系数,降低了预测误差.将此模型应用到股指期货合约保证金水平的测定中,结果表明本研究所建立模型能够节省保证金的收取总量,预测结果较好.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence,modeling and forecasting

In existing researches, the investigations of oil price volatility are always performed based on daily data and squared daily return is always taken as the proxy of actual volatility. However, it is widely accepted that the popular realized volatility (RV) based on high frequency data is a more robust measure of actual volatility than squared return. Due to this motivation, we investigate dynamics of daily volatility of Shanghai fuel oil futures prices employing 5-minute high frequency data. First, using a nonparametric method, we find that RV displays strong long-range dependence and recent financial crisis can cause a lower degree of long-range dependence. Second, we model daily volatility using RV models and GARCH-class models. Our results indicate that RV models for intraday data overwhelmingly outperform GARCH-class models for daily data in forecasting fuel oil price volatility, regardless the proxy of actual volatility. Finally, we investigate the major source of such volatile prices and found that trader activity has major contribution to fierce variations of fuel oil prices.     

期货价格收益率与波动性的实证研究——以中国上海与英国伦敦为例

采用协整模型、Granger因果关系检验、ECM模型及几种GARCH模型对中国上海与英国伦敦金属期货价格收益率和波动性做了研究.发现两市期货价格之间存在Granger因果关系、协整关系、同向变动关系和长期的共同趋势.采用ECM模型研究了两市的短期波动差异.GARCH类模型研究发现,两市波动性存在非对称性、溢出效应、杠杆效应.上海对伦敦市场的单向溢出效应显著存在.两市存在的利空消息均大于利多消息的作用,伦敦期货市场风险大于上海期货市场风险.     

沪深300指数期货与现货的相互引导关系研究

沪深300指数期货是中国证券市场上目前唯一的一款股指期货产品,通过Granger因果检验、向量误差修正模型、脉冲响应与方差分解等计量方法对其日交易数据的实证研究表明:沪深300指数期货、现货市场价格是协整的,且二者存在双向引导关系;沪深300指数期货市场对长期均衡偏离的调整力度更强,调整速度更快,对信息反应的效率更高,但在短期波动影响中,指数期货、现货市场总方差中来自期货市场的平均贡献为47.52%,来自现货市场的平均贡献为52.48%,指数现货市场对新信息融入的贡献度更高,其冲击对期货、现货市场的影响也更强烈、更持久。     

Simultaneity, Rationality and Price Determination in US Live Cattle

The results of recent research on the informational efficiency of the US live cattle futures market are ambiguous. Moreover, simultaneous, rational expectations models of spot and futures markets for non-storables are lacking in the literature. This paper addresses both issues: by developing a simultaneous rational expectations model of the US live cattle market, with functional relationships for short hedgers, long hedgers, net short speculators and consumers, the paper employs a wider information set than in previous research and it thus provides a more powerful test of the efficient market hypothesis (EMH). Tests indicate the possible presence of non-linearities in the long hedging and net short speculation equations.
The results suggest first, that there is support for Working's hypotheses of selective and operational hedging, for short and long hedgers respectively, second that speculators may be noise traders or risk-loving (although the non-linear version of the speculation function partially corrects this anomaly), and third that beef is a normal good while corn is a complementary input. Time-varying volatility is represented as an EGARCH ( p , q ) process. Post-sample, this model does not significantly outperform the futures price in spot price forecasting, implying non-rejection of the EMH.     

Forecasting the realized volatility in the Chinese stock market: further evidence

In this study, the impact of noise and jump on the forecasting ability of volatility models with high-frequency data is investigated. A signed jump variation is added as an additional explanatory variable in the volatility equation according to the sign of return. These forecasting performances of models with jumps are compared with those without jumps. Being applied to the Chinese stock market, we find that the jump variation has a significant in-sample predictive power to volatility and the predictive power of the negative one is greater than the positive one. Furthermore, out-of-sample evidence based on the fresh model confidence set (MCS) test indicates that the incorporation of singed jumps in volatility models can significantly improve their forecasting ability. In particular, among the realized variance (RV)-based volatility models and generalized autoregressive conditional heteroscedasticity (GARCH) class models, the heterogeneous autoregressive model of realized volatility (HAR-RV) model with the jump test and a decomposed signed jump variation have better out-of-sample forecasting performance. Finally, the use of the decomposed signed jump variations in predictive regressions can improve the economic value of realized volatility forecasts.     

Volatility–volume causality across single stock spot–futures markets in India

This study examines the causal relationships between volatility and volume across spot and futures market for the 50 constituent stocks of the CNX NIFTY Index. Granger non-causality tests implemented using vector autoregression (VAR) and asymmetric VAR models indicate the presence of significant causal relations from both the spot and futures volume to both the spot and futures volatility. Bidirectional causal relationships between spot and futures volume were observed for almost all stocks but few stocks displayed a similar relationship between volatilities. The results highlight the importance of volume in absorbing information and its behaviour as the conduit of information.