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.     

TRADING VOLUME,VOLATILITY, AND GARCH EFFECTS IN THE SOUTH KOREAN WON/US DOLLAR EXCHANGE MARKET: EVIDENCE FROM CONDITIONAL QUANTILE ESTIMATION*

Under the MDH, this paper investigates the asymmetry in the positive relationship between unexpected volume and volatility, and whether the unexpected volume series as a proxy for the rate of information arrival absorbs the GARCH effects. This is achieved by applying a quantile regression approach to the won/dollar exchange market with reliable data on trading volumes. Interestingly, the results show that in a freely floating exchange rate system, the positive relationship increases as exchange rate returns are higher. Contrary to previous studies, despite a significantly positive relationship, the inclusion of volumes alone does not reduce volatility persistence at medium or high levels of returns. In addition, the reform of the South Korean exchange rate system had an impact on the relationship, which occurred in response to a financial crisis.     

Can asymmetric conditional volatility imply asymmetric tail dependence?

In this article, we investigate two types of asymmetries, that is, the asymmetry of conditional volatility and the asymmetry of tail dependence in the crude oil markets. We employ the two different sample datasets in which each dataset covers the time period of stable and unstable oil prices, individually. A variety of different copulas and three asymmetric GARCH regression models are used in order to capture the two types of asymmetries. In particular, we extend the TBL-GARCH model proposed by Choi et al. (2012) to the asymmetric GARCH regression type model. The findings from the two different approaches are congruent, in that there is no asymmetry of tail dependence and no asymmetric conditional volatility in crude oil returns over the two different sample periods. Our study reconfirms the findings of Aboura and Wagner (2016) by showing that asymmetric conditional volatility relates to asymmetric tail dependence.     

Standard and seasonal long memory in volatility: an application to Spanish inflation

The historical series of many economic variables, such as inflation, are characterized by a strong persistent behaviour in the form of long memory, not only in the long run or at zero frequency but often also at seasonal frequencies. In financial series, long memory is not apparent in levels but strong persistence in higher order moments such as volatility has been proven to be a stylized fact in stock returns. Interest in economic time series has, however, focused on the persistence of levels and little attention has been paid to higher order dependence, which can be important for assessing the stability of the series. We propose a semiparametric analysis of the standard and seasonal persistence of the volatility of a monthly Spanish inflation series. The conclusions can be summarized in three main results. First volatility shows strong persistence implying an unstable trend in prices, but its structure depends on the proxy used, the absolute values, the squares or the logarithms of squares. Second, the structure of the persistence of volatility changed with the first oil crisis in 1973, with a persistent trend in both periods, in contrast with levels. Third, the Taylor effect, which is well documented in financial series, does not apply in this series.     

Estimation of Asymmetric Stochastic Volatility Models for Stock-Exchange Index Returns

The objective of this paper is to put forward a new autoregressive asymmetric stochastic volatility model for modeling volatility and to compare results obtained for this model with an autoregressive stochastic model and another asymmetric volatility model, such as, asymmetric generalized autoregressive conditional heteroskedasticity model. The results obtained from the estimation by maximum likelihood have shown the volatility behavior is asymmetric in the majority of cases. This fact is better shown by the ARSVA model, than the rest of alternative models. Moreover, the ARSVA model is able to reproduce other stylized facts of such series, such as high kurtosis, no autocorrelation of returns, slow decreasing of the autocorrelation function of the squared returns and high persistence.

Is market liquidity less resilient after the financial crisis? Evidence for US Treasuries

Understanding market liquidity resilience, i.e. the capacity of liquidity to absorb shocks, of United States Treasuries is crucial from a financial stability standpoint. The conventional resilience measure has limitations due to the use of the liquidity level. We propose a new complementary approach to analyze resilience based on liquidity volatility. For this purpose, we focus on the link between returns volatility and liquidity volatility, which is a relatively unexplored field. We fit a bivariate conditional correlation (CC-) GARCH model for the 10-year bond returns and five liquidity indicators from January 2003 to June 2016 to analyze persistence and spillovers between these variables in a parsimonious way. We find that after the crisis, spillovers between liquidity volatility and returns volatility are higher, feedback loops are more likely and volatility persistence is lower, which is consistent with a lower resilience. Our results help to explain recent episodes of high volatility in this market.     

Australian Stock Market Volatility: 1875–1987*

This paper investigates the volatility of monthly Australian stock returns over the period 1875–1987. There has been extensive work on this question in the United States, but little with data outside that country. Our analysis centres upon whether the 'stylized facts' regarding returns in the US also hold true for Australia. We find that there are both similarities and differences. There is little evidence for asymmetry in Australian returns but strong persistence of shocks into volatility. What is particularly interesting in the Australian series is the large volatility of the last two decades, an experience not matched in the US data     

股市收益率与波动性长期记忆效应的实证研究

股票市场长期记忆效应问题是近来金融实证研究的一个热点.多数的研究集中在收益率长期相关性的考察上,较少有对波动率序列的研究.然而,波动率的长期记忆性不仅会导致金融市场上的波动持久性特征,而且将对波动率的预测与衍生证券定价产生重要的影响.基于此,本文通过修正的R/S分析与ARFIMA模型对我国股市收益率及其波动性的长期相关性进行了实证研究.结果表明:中国股市具有显著的非线性特征,虽然收益率序列的自相关性较弱,但波动性序列却表现出显著的长期记忆效应.这一结论将为研究股票价格行为特征与金融经济学理论提供新的方向.     

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.     

Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil

This study explores the relationship between Google search activity and the conditional volatility of oil and gold spot market returns. By aggregating the volume of queries related to the two commodity markets in the spirit of Da et al. ( 2015 ), we construct a weekly Searching Volume Index (SVI) for each market as proxy of households and investors information demand. We employ a rolling EGARCH framework to reveal how the significance of information demand has evolved through time. We find that higher information demand increases conditional volatility in gold and oil spot market returns. Information flows from Google SVI's reduce the proportion of the significant volatility asymmetry produced by negative shocks in both commodity markets. The latter is more profound in the gold market.     

What are returns outside trading hours capturing for volatility of individual stocks?

This study is the first to harness the negative returns and squared returns outside trading hours, trading volume and leverage effects in an augmented heterogeneous autoregressive model for forecasting volatility of individual stocks. Besides significant leverage effects and trading volume impact, we find that an increase in the negative returns is associated with a decline in volatility, but an increase in the squared returns is associated with a rise in volatility. This new finding suggests that the negative returns and squared returns outside trading hours are capturing additional leverage effects and additional volatilities, respectively. Moreover, the relations display differences amongst various firm categories which arise from firm heterogeneity.     

Measuring asymmetry and persistence in conditional volatility in real output: evidence from three East Asian tigers using a multivariate GARCH approach

We search for evidence of conditional volatility in the quarterly real Gross Domestic Product (GDP) growth rates of three East Asian tigers: Singapore, Hong Kong and Taiwan. The widely accepted Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH)-type model is used to capture the existence of asymmetric volatility and the potential structural break points in the volatility. We find evidence of asymmetry and persistence in the volatility of GDP growth rates. It is noted that the structural breakpoints of volatility correspond reasonably well to the historical economic and political events in these economies. Policy implications from our findings are discussed.     

Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.     

Asymmetric Conditional Volatility and Firm Size: Evidence from Australian Equity Portfolios

This paper examines the relationship between firm size and equity volatility for two portfolios of Australian equities. Univariate and Multivariate GARCH models are used to demonstrate that conditional variance is related to firm size. There is strong evidence to suggest that the variance-covariance matrix of returns is time varying and asymmetric. A negative innovation to the return of the large firm portfolio results in higher levels of conditional volatility in the small firm portfolio than would be the case for a positive innovation of equal magnitude. News about own returns appears to determine the conditional variance of the portfolio of large firms. The conditional covariance between the two portfolios also displays evidence of asymmetry.     

Modelling exchange rate volatility with random level shifts

Recent literature has shown that the volatility of exchange rate returns displays long memory features. It has also been shown that if a short memory process is contaminated by level shifts, the estimate of the long memory parameter tends to be upward biased. In this article, we directly estimate a random level shift model to the logarithm of the absolute returns of five exchange rates series, in order to assess whether random level shifts (RLSs) can explain this long memory property. Our results show that there are few level shifts for the five series, but once they are taken into account the long memory property of the series disappears. We also provide out-of-sample forecasting comparisons, which show that, in most cases, the RLS model outperforms popular models in forecasting volatility. We further support our results using a variety of robustness checks.     

Volatility and dynamic conditional correlations of worldwide emerging and frontier markets

This study examines the relationship between time-varying correlations and conditional volatility among 32 worldwide emerging and frontier stock markets and the MSCI World stock market index from January 2000 to December 2012. Correlations are estimated in the standard and asymmetric dynamic conditional correlation model frameworks. The results can be summarized by three main findings: (1) asymmetry in volatility is not a common phenomenon in emerging and frontier markets; (2) asymmetry in correlations is found only with respect to the Hungarian stock market; and (3) the relationship between volatility and correlations is positive and significant in most countries. Thus, diversification benefits decrease during periods of higher volatility.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Investigating Intraday Interdependence Between Gold,Silver and Three Major Currencies: the Euro,British Pound and Japanese Yen

In this study, the interrelationship between major exchange rate returns (namely EUR/USD, GBP/USD, JPY/USD) and precious metal returns (gold and silver) is examined using a vector autoregressive model in a multivariate asymmetric GARCH framework on the intraday frequency. Our findings indicate a unidirectional volatility transmission from the majority of our currencies (EUR/USD, GBP/USD) to precious metals. The sluggish response of silver volatility to currency volatility shocks permits implementation of intraday profitable strategies, providing implications against market efficiency when analyzing intraday data. In the case of the British pound and Japanese yen, a volatility shock affects silver volatility more than gold volatility. Crisis events such as the Greek default and US credit rating downgrade reduce significantly the correlation of EUR/USD and gold/silver. The covariance between EUR/USD and silver increases after a volatility shock in EUR/USD. The same happens with JPY/USD and silver. These findings are important for portfolio managers and monetary authorities.     

Asymmetric Linkages between BRICS Stock Returns and Country Risk Ratings: Evidence from Dynamic Panel Threshold Models

This study investigates the asymmetric linkages between the five BRICS (Brazil, Russia, India, China and South Africa) countries’ stock markets and three country risk ratings (financial, economic and political risk) in the presence of major global economic and financial factors. Using the dynamic panel threshold models, we find evidence of asymmetry in most cases. However, the significance and the signs of the effects of these risk ratings on the BRICS market returns differ across the lower and upper regimes. Furthermore, improvements in the global stock, West Texas Intermediate (WTI) and gold markets enhance the BRICS stock market performance. Increases in implied volatility indices lead to drops in the BRICS markets.     

Long Range Dependence in the Indian Stock Market: Evidence of Fractional Integration,Non-Linearities and Breaks

This paper deals with the analysis of the Indian stock market prices using long range dependence techniques. In particular, we employ a variety of fractionally integrated models, which are very general in the sense that it allows us to incorporate structural breaks and non-linear structures. Our results indicate that the series corresponding to the NSE index is nonstationary and highly persistent, with an order of integration close to or above 1. The volatility, measured in terms of the squared returns indicates that the series is long memory, with an order of integration in the interval (0, 0.5). The results finally support the existence of a mean shift in the data at about January 2008, with the order of integration being around 1. Thus the Efficient Market Hypothesis (EMH) may be satisfied in the Indian stock market once a break is taken into account. However, the existence of short run dynamics suggests a degree of predictability in its behaviour.