Correlations in price changes and volatility across international stock markets

The short-run interdependence of prices and price volatilityacross three major international stock market is studied. Dailyopening and closing prices of major stock indexes for the Tokyo,London, and New York stock markets are examined. The analysisutilizes the autoregressive conditionally heteroskedastic (ARCH)family of statistical models to explore these pricing relationship.Evidence of price volatility spillovers from New York to Tokyo,London to Tokyo, and New York to London is observed, but noprice volatility spillover effects in other directions are foundfor the pre-October 1987 period.     

Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets

Emerging market stock returns have been characterized as having higher volatility than returns in the more developed markets. But previous studies give little attention to the fundamentals driving the reported levels of volatility. This paper investigates whether dynamics in key macroeconomic indicators like exchange rates, interest rates, industrial production and money supply in four Latin American countries significantly explain market returns. The MSCI world index and the U.S. 3-month T-bill yield are also included to proxy the effects of global variables. Using a six-variable vector autoregressive (VAR) model, the study finds that the global factors are consistently significant in explaining returns in all the markets. The country variables are found to impact the markets at varying significance and magnitudes. These findings may have important implications for decision-making by investors and national policymakers.     

Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets

This article examines sudden changes in volatility for five Gulf area Arab stock markets using the iterated cumulative sums of squares (ICSS) algorithm and analyzes their impacts on the estimated persistence of volatility. This algorithm identifies large shifts in volatility of the stock markets during the weekly period 1994 to 2001. In contrast to Aggarwal et al. [Aggarwal, R., Inclan, C., & Leal, R., 1999, Volatility in emerging markets. Journal of Financial and Quantitative Analysis 34, 33-55], this paper found that most of the Gulf Arab stock markets are more sensitive to major global events than to local and regional factors. The 1997 Asian crisis, the collapse of oil prices in 1998 after the crisis, the adoption of the price band mechanism by OPEC in 2000, and the September 11th attack have been found to have consistently affected the Gulf markets. Accounting for these large shifts in volatility in the GARCH(1,1) models significantly reduces the estimated persistence of the volatility in the Gulf stock markets.     

Procyclical volatility in Chinese stock markets

Review of Quantitative Finance and Accounting - We investigate the macroeconomic determinants of stock market volatility in China using the two-component GARCH-MIDAS model of Engle et al....     

Transmission of volatility between stock markets

This article investigates why, in October 1987, almost all stockmarkets fell together despite widely differing economic circumstances.We construct a model in which 'contagion' between markets occursas a result of attempts by rational agents to infer informationfrom price changes in other markets. This provides a channelthrough which a 'mistake' in one market can be transmitted toother markets. We offer supporting evidence for contagion effectsusing two different sources of data.     

Financial liberalization and changes in the dynamic behaviour of emerging market volatility: Evidence from four Latin American equity markets

This paper examines whether the dynamic behaviour of stock market volatility for four Latin American stock markets (Argentina, Brazil, Chile and Mexico) and a mature stock market, that of the US, has changed during the last two decades. This period corresponds to years of significant financial and economic development in these emerging economies during which several financial crises have taken place. We use weekly data for the period January 1988 to July 2006 and we conduct our analysis in two parts. First, using the estimation of a Dynamic Conditional Correlation model we find that the short-term interdependencies between the Latin America stock markets and the developed stock market strengthened during the Asian, Latin American and Russian financial crises of 1997–1998. However, after the initial period of disturbance they eventually returned to almost their initial (relatively low) levels. Second, the estimation of a SWARCH-L model reveals the existence of more than one volatility regime and we detect a significant increased volatility during the period of crisis for all the markets under examination, although the capital flows liberalization process has only caused moderate shifts in volatility.     

The relationship between stock returns and volatility in international stock markets

This study examines the relationship between expected stock returns and volatility in the 12 largest international stock markets during January 1980 to December 2001. Consistent with most previous studies, we find a positive but insignificant relationship during the sample period for the majority of the markets based on parametric EGARCH-M models. However, using a flexible semiparametric specification of conditional variance, we find evidence of a significant negative relationship between expected returns and volatility in 6 out of the 12 markets. The results lend some support to the recent claim [Bekaert, G., Wu, G., 2000. Asymmetric volatility and risk in equity markets. Review of Financial Studies 13, 1–42; Whitelaw, R., 2000. Stock market risk and return: an empirical equilibrium approach. Review of Financial Studies 13, 521–547] that stock market returns are negatively correlated with stock market volatility.     

Sudden changes in volatility: The case of five central European stock markets

This paper investigates sudden changes in volatility in the stock markets of new European Union (EU) members by utilizing the iterated cumulative sums of squares (ICSS) algorithm. Using weekly data over the sample period 1994–2006, the time period of sudden change in variance of returns and the length of this variance shift are detected. A sudden change in volatility seems to arise from the evolution of emerging stock markets, exchange rate policy changes and financial crises. Evidence also reveals that when sudden shifts are taken into account in the GARCH models, the persistence of volatility is reduced significantly in every series. It suggests that many previous studies may have overestimated the degree of volatility persistence existing in financial time series.     

Intraday volatility in the stock index and stock index futures markets

We examine the intraday relationship between returns and returnsvolatility in the stock index and stock index futures markets.Our results indicate a strong intermarket dependence in thevolatility of the case and futures returns. Price innovationsthat originate in either the stock or futures markets can predictthe future volatility in the other market. We show that thisrelationship persists even during periods in which the dependencein the returns themselves appears to weaken. The findings arerobust to controlling for potential market frictions such asasynchronous trading in the stock index. Our results have implicationsfor understanding the pattern of information flows between thetwo markets.     

On detection of volatility spillovers in overlapping stock markets

This paper applies a recently proposed structural vector autoregressive model identification method to an established, previously unidentified theoretical model of stock market volatility spillovers. The structural model is identified and can be estimated with the method of maximum likelihood. Volatility spillovers can then be tested with the standard likelihood ratio test. This way our test, unlike the majority of the existing volatility spillover tests, has its foundations firmly in the economic theory. Our test is developed for fully overlapping stock markets. The empirical application of the paper considers stock markets of the eurozone in the years 2010–2011. Evidence of volatility spillovers is found.     

Asymmetric volatility connectedness between Islamic stock and commodity markets

This paper examines the asymmetric volatility connectedness amongst the Dow Jones Islamic Market Index (DJIM) and the Brent crude oil, gold, and silver markets. We use the Diebold and Yilmaz methodology to examine asymmetric volatility connectedness associated with bad (negative semi-variance) and good (positive semi-variance) volatility in these markets. We identify significant volatility connectedness between the DJIM and commodity markets, with the DJIM and Brent oil markets being the largest net contributors of spillovers. Furthermore, the evidence on semi-volatility connectedness displays asymmetric behavior. Bad volatilities are associated with net transmission of spillovers to other markets, except for silver. Our results have significant implications for investors dealing with the DJIM and commodity markets in terms of asset management and diversification.     

Modelling return and conditional volatility exposures in global stock markets

This article empirically investigates the exposure of country-level conditional stock return volatilities to conditional global stock return volatility. It provides evidence that conditional stock market return volatilities have a contemporaneous association with global return volatilities. While all the countries included in the study exhibited a significant and positive relationship to global volatility, emerging market volatility exposures were considerably higher than developed market exposures. JEL Classification G12     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Idiosyncratic volatility and cross‐sectional stock returns in Southeast Asian stock markets

We examine the role of idiosyncratic risk in five ASEAN markets of Malaysia, Singapore, Thailand, Indonesia, and the Philippines. Our research was motivated by the findings of Ang et al. (2006, 2009) of a ‘puzzling’ negative relation between idiosyncratic volatility and 1‐month ahead stock returns in developed markets and the suggestion of the ubiquity of these results in other markets. In contrast, we find no evidence of an idiosyncratic volatility puzzle in these Asian stock markets; instead, we document a positive relationship between idiosyncratic volatility and returns in Malaysia, Singapore, Thailand, and Indonesia and no relationship in the Philippines. The idiosyncratic volatility trading strategy could result in significant trading profits in Malaysia, Singapore, Thailand, and to some extent in Indonesia. Our study underscores the fact that generalizing empirical results obtained in developed stock markets to new and emerging markets could potentially be misleading.     

Local and global price memory of international stock markets

The prime focus of this paper is on the impact of the world’s leading markets (USA, Japan, Hong Kong, UK, France, Switzerland and Germany) on the returns of the small Nordic markets (Denmark, Finland, Norway and Sweden). The order and the degree of processing both ‘local’ and ‘global’ information are uncovered using a combination of cointegration analysis and structural VAR modeling utilizing daily index returns. The results indicate that the US price changes, conditioned on the same day changes on the other markets, have an impact on all other markets during the following day, including the US market itself. Price changes on the Asian–Pacific markets are completely absorbed in price changes in Europe and do not have any direct effect on US prices. Finally, a cointegration relationship between Sweden and Norway is found, which affects also Finland.     

Volume,volatility and information linkages in the stock and option markets

This paper examines the relationship between option trading activity and stock market volatility. Although the option market is uniquely suited for trading on volatility information, there is little analysis on how trading activity in this market is linked to stock price volatility. The bulk of the discussion tends to focus on whether trading activity in the stock market is informative about stock volatility. To analyze the information in option trading activity for stock market volatility, a sample of 15 stocks with the highest option trading volume is selected. For each stock, it is noted that the trading activities in the put and call option markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call option trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.     

Persistence characteristics of Latin American financial markets

The financial rates of return from Latin American stock and currency markets are found to be non-normal, non-stationary, non-ergodic, and long-term dependent, i.e., they have long memory. The degree of long-term dependence is measured by monofractal (global) Hurst exponents from wavelet multiresolution analysis (MRA). Scalograms and scalegrams provide the respective visualizations of these wavelet coefficients and the power spectrum of the rates of return. The slope of the power spectrum identifies the Hurst exponent and thereby the degree of time-scaling dependence that cannot be determined by Box–Jenkins type, stationarity-based, time series analysis. Our long-term dependence and time–frequency scaling results are consistent with similar empirical findings from American, European, and Asian financial markets. They extend the domain of the empirical investigation of the dynamics and risk characteristics of the global financial markets and refute the hypothesis of perfectly efficient financial markets.     

Influence of cultural factors on price clustering and price resistance in China's stock markets

This paper builds on prior research by analysing the impact of cultural factors on both price clustering and price resistance in China's stock markets. The results support the presence of cultural factors impacting on price clustering with the digit 8 showing a higher propensity for clustering and the digits 4 and 7 showing a lower propensity in the A‐share market, where stock is denominated in renminbi and traded by mainland Chinese. These results are further supported by an analysis of the B‐share market, where cultural factors have no (or less) impact on the price of Chinese stocks traded by foreign investors in US dollars (or in Hong Kong dollars). A range of measures for price resistance show the digits 0 and 5 to be significant resistance points in the A‐share market. Although digit 8 cannot be considered as a resistance point, its resistance level is highest among the remaining numbers. In conclusion, cultural factors help to explain not only price clustering in the Chinese stock markets but price resistance levels as well, albeit at a weak level.     

Enterprise digital transformation,breadth of ownership and stock price volatility

We investigate the impact of enterprise digital transformation on the breadth of ownership and stock price volatility. Our findings demonstrate that enterprise digital transformation has enhanced the breadth of ownership. Furthermore, through cross-sectional analysis, we find that this effect is more prominent in firms with lower investor attention, greater stock underpricing, and in regions with higher levels of digitalization. Additionally, we have discovered that the increase of media coverage and investor attention serve as the underlying economic mechanism between digital transformation and ownership dispersion. Our analysis also shows that digital transformation has the potential to worsen stock price volatility. Finally, our examination of open-end mutual funds reveals a digital preference among mutual fund investors; this preference has improved fund flows while exacerbating fund volatility. Our study has practical implications for regulators and corporate managers, as they highlight the impact of digital transformation on investor decision-making.     

Non-trading,market making,and estimates of stock price volatility

We examine the effects of market making and intermittent trading on estimates of stock price volatility. When observed price changes are correctly tied to a stock's true price dynamics, it is found that non-trading per se causes a loss of efficiency but no bias in traditional volatility estimates. Non-trading induces substancial inefficiency in the extreme value estimator of volatility which it biases downward. Market making's effects add to the non-trading induced inefficiency in the traditional estimator, while information trading causes a downward bias, and liquidity trading a potentially removable upward bias, in that estimator.