Output Growth and its Volatility: The Gold Standard through the Great Moderation

This study examines the relationship between U.S. output growth and its volatility over the period 1876:I to 2012:II. We adjust the data for outliers and structural breaks. We employ generalized autoregressive conditional heteroskedasticity (GARCH) and exponential GARCH (EGARCH) specifications. Normality and homoskedasticity appear only in the GARCH or EGARCH model that corrects for the outliers. When including the break in the mean equation, high volatility persistence remains. After also accommodating the breaks in the variance equation, the integrated GARCH effect proves spurious, either for the symmetric or the asymmetric model. Finally, our empirical results suggest that the finding of higher output growth volatility stimulating output growth and higher output growth reducing its volatility obtained from the symmetric GARCH‐in‐mean (GARCH‐M) model also proves spurious as a result of the emergence of an asymmetric effect. Our more appropriately specified asymmetric EGARCH‐M model suggests positive volatility‐in‐mean and level effects in the long‐period real gross national product series.     

基于GARCH族模型的深证成分指数波动性研究

基于GARCH族模型对深证成分指数的波动性进行实证研究。用学生-t分布的GARCH(1,1)模型分析了尖峰厚尾和波动聚集特征,用基于CED分布的GARCH-M(1,1)模型研究了风险溢价情况,以及用基于标准正态分布的EGARCH(1,1)模型分析股市波动的杠杆效应。结果显示,残差确实存在异方差性,股市中收益与风险成正比,同等单位的利空消息对股市冲击更大。最后根据实证研究给出结论与建议。     

基于不同分布假设GARCH族模型对上证指数波动性分析的比较研究

股票市场的波动性研究已经成为众多研究者和投资者广泛关注的焦点。以上证股票收益率为研究对象,在三种不同的分布假设下,利用GARCH族模型对上证指数波动性进行了比较研究,分析表明:上证股票收益率具有显著的条件异方差性,且基于GED分布的GARCH(1,1)模型是消除该条件异方差性的最佳模型;上证股票收益率具有正的风险溢价,且基于GED分布的GARCH(1,1)-M模型是反映风险溢价情况的最优模型;上证股票收益率存在着明显的不对称性(杠杆效应),利空消息比利好消息更容易引起大的波动,且基于标准正态分布的EGRCH(1,1)模型是揭示该不对称性的最佳模型。     

基于日间高频交易数据的股市波动研究

本文利用上证综指在2005～2009年内的日间高频数据,通过已实现波动率这一概念对我国股市在这5年间的波动特性做了研究。进一步地,根据已实现波动率序列的统计特征,对其进行长记忆建模,并对模型的波动率预测效果与常规GARCH模型的预测效果做了对比分析。基于上证综指的研究结果表明,利用了日间高频信息的波动率模型在波动率预测上,比仅利用了收盘信息的GARCH模型更有优势。     

中国股市收益率与波动率跳跃性特征的实证分析

股票市场收益率通常小幅波动，但是当市场出现重大或者异常信息时，收益率会在短时间内发生大规模的运动．产生跳跃性变化，市场波动率也明显加剧。本文采用Jump—GARCH对沪深两市A股B股的这类跳跃性特征进行实证分析。根据该模型：当收益率小规模变化时，波动率由GARCH（1，1）平稳随机过程产生，但是当收益率发生跳跃性变化，波动率将背离GARCH（1，1）过程．调整到一个较高的水平。实证结果表明，该模型能够有效地估计出沪深两市收益率和波动率的跳跃性变化．比正态分布的GARCH模型更合理地反应了市场收益率和波动率过程。本文同时讨论了A股B股的跳跃性特征。     

Modeling exchange rate return volatility of RMB/USD using GARCH family models

The paper examines volatility of RMB exchange rate return of onshore and offshore markets. The onshore rate covered 4/01/2008–5/09/2016 while offshore spanned 31/12/2008-22/09/2016, the returns were not normally distributed and were integrated of order zero I(0). The Ljung-Box Q statistics depicts the presence of autocorrelation in return series and Ljung-Box Q² statistics of power transformed for conditional heteroscedasticity for lags of 6, 12 and 20 all indicated the presence of conditional heteroscedascity. The exchange rates volatility was persistent in both markets. However, offshore return was more persistent while leverage effects exist in both markets. Asymmetry power Autoregressive conditional Heteroscedastic (APARCH) model was the best model for forecasting purposes in both markets while Glosten, Jogannathan and Rankle, Generalized Autoregressive conditional Heteroscedastic (GJR-GARCH) model and Integrated Generalized Autoregressive conditional Heteroscedastic (I-GARCH) were the worst models in onshore and offshore return markets respectively. APARCH model should be adopted for future studies.     

Volatility Relationship between Crude Oil and Petroleum Products

This paper utilizes calculated historical volatility and GARCH models to compare the historical price volatility behavior of crude oil, motor gasoline and heating oil in U.S. markets since 1990. We incorporate a shift variable in the GARCH/TARCH models to capture the response of price volatility to a change in OPEC’s pricing behavior. This study has three major conclusions. First, there was an increase in volatility as a result of a structural shift to higher crude oil prices after April 1999. Second, volatility shocks from current news are not important since GARCH effects dominate ARCH effects in the variance equation. Third, persistence of volatility in all commodity markets is quite transitory, with half-lives normally being a few weeks.

The Impact of Political Instability on Inflation Volatility in Africa

This paper investigates whether political instability leads to volatile inflation using a panel of 49 African countries. The study uses novel measures of political instability, particularly the state failure index and state fragility index. In the field of political instability and inflation volatility, this is the first study to measure inflation volatility as the conditional variance of inflation estimated from GARCH (1, 1) model. Adopting the system‐generalized method of moments estimator for linear dynamic panel models for the sample period 1985‐2009, the study documents a positive statistically significant effect of political instability on inflation volatility.     

Economic Liberalization and Conditional Volatility of Exchange Rate in Sub‐Saharan Africa: Asymmetric GARCH Analysis

Abstract: For small open economies, an understanding of movements in the exchange rate is imperative in analyzing trade and capital flows. In addition, reliable forecasting of exchange rate volatility is important in risk‐taking assessment and investment decision‐making, both of which are critical to long‐term growth. Using an asymmetric GARCH‐type approach, this paper examines the implications of economic liberalization on the stochastic behavior of the exchange rate series in a sample of sub‐Sahara African (SSA) countries over the 1970–2004 period. The results indicate that exchange rate volatility is variable, and is less volatile under fixed exchange rate regime (pre‐economic liberalization) and higher under flexible regime (post‐economic liberalization), that is, it is asymmetric. For most of the countries, the EGARCH and TGARCH models are robust to parameter stability and gives better forecasting performance compared to the standard GARCH model.     

Modeling the volatility of real GDP growth: The case of Japan revisited

Previous studies [e.g., Hamori, S., 2000. Volatility of real GDP: some evidence from the United States, the United Kingdom and Japan. Japan and the World Economy 12, 143–152; Ho, K.Y., Tsui, A.K.C., 2003. Asymmetric volatility of real GDP: some evidence from Canada, Japan, the United Kingdom and the United States. Japan and the World Economy 15, 437–445; Fountas, S., Karanasos, M., Mendoza, A., 2004. Output variability and economic growth: the Japanese case. Bulletin of Economic Research 56, 353–363] find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perron's [Bai, J., Perron, P., 1998. Estimating and testing linear models with multiple structural changes. Econometrica 66, 47–78; Bai, J., Perron, P., 2003. Computation and analysis of multiple structural change models. Journal of Applied Econometrics 18, 1–22] multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.     

Examining Stock Volatility in the Segmented Chinese Stock Markets: A SWARCH Approach

Abstract

This study adopts the SWARCH model to examine the volatile behavior and volatility linkages among the four major segmented Chinese stock indices. We find strong evidence of a regime shift in the volatility of the four markets, and the SWARCH model appears to outperform standard generalized autoregressive conditional heteroskedasticity (GARCH) family models. The evidence suggests that, compared with the A-share markets, B-share markets stay in a high-volatility state longer and are more volatile and shift more frequently between high- and low-volatility states. In addition, the relative magnitude of the high-volatility compared with that of the low-volatility state in the B-share markets is much greater than the case in the two A-share markets. B-share markets are found to be more sensitive to international shocks, while A-share markets seem immune to international spillovers of volatility. Finally, analyses of the volatility spillover effect among the four stock markets indicate that the A-share markets play a dominant role in volatility in Chinese stock markets.     

Volatility of real GDP: some evidence from the United States,the United Kingdom and Japan

This paper presents an empirical analysis of the volatility of real growth rates for the United States, the United Kingdom and Japan. Three ARCH-type models (GARCH, T-GARCH and E-GARCH) were estimated utilizing the maximum likelihood method. The GARCH version provided the best statistical fit, suggesting that volatility is variable and is symmetric than asymmetric to real growth rates in GDP.     

中美农产品市场整合及其价格传导机制研究——以大豆市场为例

本文在对中国和美国大豆价格进行格兰杰因果关系检验的基础上,运用VAR模型分析中美两国大豆市场动态的相互影响关系,并探索当面临由外部冲击所导致的上涨压力时,两个大豆市场分担上涨压力的贡献情况;之后运用VECH和TARCH模型分析中美大豆价格波动的传导机制和对称性问题。主要结论如下:首先,中美大豆市场相互影响,互为因果,但美国大豆市场对中国大豆市场的冲击要强于中国大豆市场对美国大豆市场的影响,且美国大豆市场应对外部冲击的能力要强于中国。其次,美国大豆价格的波动主要依靠上期自身波动的传导,而中国大豆价格波动更易受外部冲击的影响;美国大豆价格波动趋于收敛,而中国大豆价格波动趋于发散。再次,中美大豆市场的联合波动也主要受外部冲击影响,两个市场的整合机制较为脆弱。最后,中美大豆价格波动均体现出非对称的特征。     

备兑权证定价方法的务实改进与实现

为使备兑权证的定价更加贴近现实,文章以t分布代替原假设标的股票收益率服从的正态分布,以随机波动率代替历史波动率,通过GARCH模型来消除金融时间序列的异方差性,并考虑交易费用、红利等因素对权证价格的影响,在此优化了传统的定价模型。然后用Monte Carlo模拟的定价思路,并利用对偶方差减少技术提高其效率,最后编辑程序在Eviews中成功运行得出权证的定价.     

Impact of Macroeconomic Announcements on Foreign Exchange Volatility: Evidence from South Africa

This study focuses on scheduled macroeconomic news announcements and evaluates their impact on the volatility of the South African rand (ZAR) and US dollar (USD) exchange rate using high frequency data. The following asymmetries are studied: news items by geographical location, no‐news vs. surprise news announcements and positive vs. negative news announcements. We make the following findings in our empirical study: (i) After the release of a news announcement, the level of foreign exchange volatility rises. This is independent of whether the news item surprised the market or not. (ii) Both South African and US news items significantly impact USD/ZAR volatility, suggesting that the news items are being used to formulate investor expectations regarding the future prospects of the currency pair. (iii) Negative news appears to have a greater impact on exchange rate volatility relative to positive news. This result is also state dependent, as investors tend to behave differently to news depending on the economic climate at that point in time. Investor cognitive biases give rise to the asymmetric news effects on exchange rate volatility. Finally, investors do not always act in rational manner, especially when faced with multiple news items that are contradictory to each other.     

The Great Moderation and the Relationship between Output Growth and Its Volatility

This study examines the effect of the Great Moderation on the relationship between U.S. output growth and its volatility over the period 1947 to 2006. First, we consider the possible effects of structural changes in the volatility process. We employ generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) specifications, which describe output growth rate and its volatility with and without a one-time structural break in volatility. Second, our data analyses and empirical results suggest no significant relationship between the output growth rate and its volatility; this favors the traditional wisdom of dichotomy in macroeconomics. Moreover, the evidence shows that the time-varying variance falls sharply or even disappears once we incorporate a one-time structural break in the unconditional variance of output starting in 1982 or 1984. That is, the integrated GARCH effect proves spurious. Finally, a joint test of a trend change and a one-time shift in the volatility process finds that the one-time shift dominates.     

LONG MEMORY IN THE VOLATILITY OF AN EMERGING FIXED‐INCOME MARKET: EVIDENCE FROM SOUTH AFRICA

This paper tests for long memory in volatility of fixed‐income returns; specifically, South Africa's local currency 10‐year government bond, given that the characterisation of stochastic long‐memory volatility is of interest and importance in portfolio and risk management. The long‐memory parameter is estimated using methods based on wavelets, which have gained prominence in recent years. Evidence of long memory in fixed‐income return volatility is conclusively demonstrated across a variety of volatility measures and wavelet forms. This finding suggests a pattern of time dependence, which may potentially be exploited to generate improved volatility forecasting performance especially over long horizons. This paper further extends the extant literature by comparing the predictive power of long‐memory forecasts with those obtained from a standard (short‐memory) generalised autoregressive conditional heteroskedasticity (GARCH) process. The results of this exercise suggest that the information content of long‐memory models does not lead to improved forecast accuracy. The GARCH(1,1) model is shown to provide the best forecasts across most horizons (i.e. daily, weekly and monthly). Forecast performance is further revealed to be sensitive to the choice of volatility proxy used. Finally, the derived volatility forecasts are generally very close, and in some cases, almost indistinguishable.     

Volatility spillover effects in interbank money markets

Using daily data from 2006 to 2015, this paper applies alternative multivariate GARCH models and a modified version of the spillover index methodology proposed by Diebold and Yilmaz (Int J Forecast 28(1):57–66, 2012) to test the existence of shock and volatility contagion effects across interbank money markets. Overall, we find evidence that money markets are highly interrelated, exhibiting dynamic cross market effects. Moreover, we emphasize the pertinence of conditional covariances and we show that volatility spillovers are time-varying and very responsive to the major economic events, increasing in periods of higher turbulence, which reinforces the importance of closely monitoring the evolution of money markets.     

“中小板”市场“牛市”和“熊市”的波动非对称性研究

运用广义误差分布的EGARCH（1,1）模型,分析中小板市场＂牛市＂和＂熊市＂行情（即样本）的波动非对称性。主要结论有：在牛市、熊市中等量＂利好＂消息与＂利空＂消息对股市产生的冲击是不对称的：在牛市中,＂利好＂消息对股市的影响要比相同力度的＂利空＂消息影响大;在熊市中,＂利空＂消息对股市的影响要比相同力度的＂利好＂消息影响大;中小板市场的波动性较大。