The intraday behaviors and relationships with its underlying assets: evidence on option market in Taiwan

In this paper, we use daily data to investigate the information asymmetric effects and the relationships between the trading volume of options and their underlying spot trading volume. Our results reveal that options with higher liquidity are near-the-money and expiration periods with 2 to 4 weeks have higher trading activity. We classify them into two parts with the ARIMA model: the expected trading activity impact and the unexpected trading activity impact. Using the bivariate generalized autoregressive conditional heteroscedasticity (GARCH) model, we investigate the trading activity effect and information asymmetric effect. In conclusion, the trading volume volatility of the spot and options markets move together, and a greater expected and unexpected trading volume volatility of the spot (options) market is associated with greater volatility in the options (spot) market. However, both markets generate higher trading volume volatility when people expect such an impact rather than when they do not. We also find that there are feedback effects within these two markets. Furthermore, when the spot (options) market has negative innovations, it generates a greater impact on the options (spot) market than do positive innovations. Finally, the conditional correlation coefficient between the spot and the option markets changes over time based on the bivariate GARCH model.     

Futures-Trading Activity and Stock Price Volatility

We examine whether greater futures-trading activity (volume and open interest) is associated with greater equity volatility. We partition each trading activity series into expected and unexpected components, and document that while equity volatility covaries positively with unexpected futures-trading volume, it is negatively related to forecastable futures-trading activity. Further, though futures-trading activity is systematically related to the futures contract life cycle, we find no evidence of a relation between the futures life cycle and spot equity volatility. These findings are consistent with theories predicting that active futures markets enhance the liquidity and depth of the equity markets.     

期货市场的交易量与价格波动

本文检验了美国期货市场WTI原油、S＆P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系,发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用,非预期的隔日交易量与期货价格波动之间有正相关关系,非预期的目内交易量对价格波动的影响不显著。从信息对称性的角度分析,预期的交易量中含有更多信息,能抑制期货价格的偏离;非预期的交易量主要由信息反馈者提供,他们往往对期货价格的变动做出过度反应,从而加剧价格波动。     

EXPECTED VOLATILITY,UNEXPECTED VOLATILITY,AND THE CROSS‐SECTION OF STOCK RETURNS

The existing literature finds conflicting results on the cross‐sectional relation between expected returns and idiosyncratic volatility. We contend that at the firm level, the sample correlation between unexpected returns and expected idiosyncratic volatility can cloud the true relation between the expected return and expected idiosyncratic volatility. We show strong evidence that unexpected idiosyncratic volatility is positively related to unexpected returns. Using unexpected idiosyncratic volatility to control for unexpected returns, we find expected idiosyncratic volatility to be significantly and positively related to expected returns. This result holds after controlling for various firm characteristics, and it is robust across different sample periods.     

Trading volume,time-varying conditional volatility,and asymmetric volatility spillover in the Saudi stock market

Despite the well known importance of volatility–volume relationship, there is a paucity of research on this topic in emerging markets. We attempt to partially fill this gap by investigating volatility–volume relationship in the most important exchange market in the Middle East. We test the effect of trading volume on the persistence of the time-varying conditional volatility of returns in the Saudi stock market. Overall our results support the mixture of distribution hypothesis at the firm level. We also use two different proxies for information arrival, intra-day volatility, and overnight indicators. We find that these are good proxies for information and are important as contemporaneous volume in explaining conditional volatility. We also test for the volatility spillover direction between large- and small-cap portfolios. Our results show that the spillover effect is larger and statistically significant from large to small companies.     

Trading Halts and Market Activity: An Analysis of Volume at the Open and the Close

This paper analyzes how the daily opening and closing of financial markets affect trading volume. We model the desire to trade at the beginning and end of the day as a function of overnight return volatility. NYSE data from 1933–88 indicate that closing volume is positively related to expected overnight volatility, while volume at the open is positively related to both expected and unexpected volatility from the previous night. We interpret the symmetric response of trading at the open and the close to expected volatility as being due to investor heterogeneities in the ability to bear risk when the market is closed. This desire of investors to trade prior to market closings indicates a cost of mandating marketwide circuit breakers.     

Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets

This paper first investigates the relationship between investor sentiment, captured by internet search behaviour, and the unexpected component of stock market volatility during the COVID-19 pandemic. According to data on 12 major stock markets, our research indicates a positive correlation between the Google search volume index on COVID-19 and the unexpected volatility of stock markets. The result suggests that greater COVID-19-related investor sentiment during this pandemic is associated with higher stock market uncertainty.Our study further examines whether country-level governance plays a role in protecting stock markets during this pandemic and reveals that the unexpected conditional volatility is lower when a country's governance is more effective. The impact of investor sentiment and country governance on unexpected volatility after the initial shock of COVID-19 is also investigated. The findings demonstrate the importance of establishing good country-level governance that can effectively reduce stock market uncertainty in the context of this pandemic, and support continual policy development related to investor protection.     

Bond market integration of emerging economies and bilateral linkages

Although there are numerous studies that have looked at the spillover effects in equity markets, little attention has been paid to explore the integration of bond markets of developed and emerging economies. Our paper is an attempt to fill this void by quantifying the spillovers from developed countries on the bond markets of 25 emerging economies. We apply volatility and return spillover models to quantify the extent of the spillovers from developed markets (i.e. the United States, UK and Japan) into emerging bond markets. We find that the extent of the return spillovers and volatility spillovers has not been symmetric across emerging markets. We explain these differences using bilateral factors such as trade volume, portfolio investment, cultural and geographical factors. The bilateral trade volume turns out to be the leading explanation for the extent of spillovers between our set of countries.     

Volatility clustering,leverage effects,and jump dynamics in the US and emerging Asian equity markets

This paper proposes asymmetric GARCH-Jump models that synthesize autoregressive jump intensities and volatility feedback in the jump component. Our results indicate that these models provide a better fit for the dynamics of the equity returns in the US and emerging Asian markets, irrespective whether the volatility feedback is generated through a common GARCH multiplier or a separate measure of volatility in the jump intensity function. We also find that they can capture several distinguishing features of the return dynamics in emerging markets, such as, more volatility persistence, less leverage effects, fatter tails, and greater contribution and variability of the jump component.     

Trading volume and stock market volatility: The Polish case

Relying on the mixture of distributions hypothesis (MDH), this paper investigates the relationship between daily returns and trading volume for 20 Polish stocks. Our empirical results show that in the majority of cases volatility persistence tends to disappear when trading volume is included in the conditional variance equation, which is in agreement with the findings of studies on developed stock markets. However, we cannot confirm the testable implications of the MDH in all cases, which indicates that future research on the causes and modeling of Polish stock market volatility is necessary.     

Daily institutional trades and stock price volatility in a retail investor dominated emerging market

We examine the short-run dynamic relation between daily institutional trading and stock price volatility in a retail investor-dominated emerging market. We find a significantly negative relation between volatility and institutional net trading that is mainly due to the unexpected institutional trading. The price volatility–institutional trade relation differs for institutional buys and institutional sells, and for small and large stocks. Institutional investors herd-trade in large stocks, but do not systematically engage in positive-feedback trading. We argue that the net impact of informational and noninformational institutional trades determines the relation between volatility and institutional trading, and that the relation is negative when informational trading by institutions prevails.     

Idiosyncratic risk and expected returns in frontier markets: Evidence from GCC

We investigate the pricing of idiosyncratic volatility of seven frontier markets in six GCC countries. We find a significant (marginal) negative relationship between expected returns and lagged idiosyncratic volatility for individual stocks in Saudi Arabia (Qatar) but none in Kuwait and Abu Dhabi. However, when we estimate conditional idiosyncratic volatility either by EGARCH or AR Models, the relationship turns positive. Introducing unexpected idiosyncratic volatility as an explanatory variable to control for any unexpected returns uncovers the true relationship between expected idiosyncratic volatility and expected returns. The evidence turns out to be robust for return reversals and other control variables. Moreover, the pricing of idiosyncratic risk is less evident in higher country governance and seems to be unrelated to the degree of financial development.     

Risk-Adjusted Performances of World Equity Indices

This article investigates whether equity indices of twenty-four emerging and twenty-eight developed markets compensate their investors equally after adjusting for total or downside risk, and examines the predictive power of reward-to-risk ratios for expected market returns. We find that when all fifty-two markets are ranked based on their alternative reward-to-risk ratios, almost all of the countries in the top (bottom) quartile are emerging (developed) markets. The pooled means of the reward-to-risk ratios are also significantly higher for emerging markets. Both portfolio and regressions analysis reveal that there is a significantly positive relation between various reward-to-risk metrics and expected market returns.     

Idiosyncratic return volatility and the role of firm fundamentals: A cross-country analysis

We investigate the relation between fundamental idiosyncratic volatility and stock returns idiosyncratic volatility using data from 56 countries. We find a strong positive relation between fundamental idiosyncratic volatility and idiosyncratic volatility of returns. This association, however, seems to be entirely concentrated in the developed economies, and we find no effect in the emerging markets. Specifically, fundamental idiosyncratic volatility does not lead to more idiosyncratic return volatility in countries with poor legal institutions and weak shareholder protection laws.     

Stock return volatility,operating performance and stock returns: International evidence on drivers of the ‘low volatility’ anomaly

This study highlights the link between stock return volatility, operating performance, and stock returns. Prior studies suggest that there is a ‘low volatility’ anomaly, where firms with a low stock return volatility out-perform firms with a high stock return volatility. This paper confirms that low volatility stocks earn higher returns than high volatility stocks in emerging markets and developed markets outside of North America. We also show that low volatility stocks have higher operating returns and this might explain why low volatility stocks earn higher stock returns. These results provide a partial explanation for the ‘low volatility effect’ that is independent from the existence of market anomalies or per se inefficiencies that might otherwise drive a low volatility effect. We emphasize the importance of controlling for stock return volatility when analyzing operating performance and stock performance.     

Asymmetric volatility in the cryptocurrency market: New evidence from models with structural breaks

Previous literature shows that major cryptocurrencies exhibit inverse asymmetric volatility: positive shocks increase price volatility more than negative ones. In this study, we revisit the asymmetric volatility dynamics of major cryptocurrencies using asymmetric GARCH models that incorporate endogenously detected structural breaks. Our results show that after incorporating structural breaks, volatility persistence decreases and asymmetric volatility increases for all cryptocurrencies in this study. Thus, prior research that ignores structural breaks underestimates the impact of unexpected news on price volatility in cryptocurrency markets. We also present important economic implications of our results: ignoring structural breaks adversely affects the hedging strategies, derivatives valuations, and risk exposure measurement of investors in cryptocurrency markets.     

Spatial linkage of volatility spillovers and its explanation across G20 stock markets: A network framework

This paper empirically estimates the spatial correlation relationship of volatility spillovers and its influencing factors across G20 stock market. We apply GARCH-BEKK model to estimate volatility spillover and construct dynamic volatility networks. The connectedness analysis shows that the spatial linkage of volatility spillover is time varying and has obvious multiple superposition phenomena. As somewhat innovation results, we use the factor analysis method to obtain centrality comprehensive indicators that can clearly depict the risk contagion intensity and risk acceptance intensity. In general, the developed markets are more influential than the emerging markets during periods of turbulence, and the emerging markets are more sensitive to volatility shocks than developed markets during any period. Finally, this paper introduces quadratic assignment procedure (QAP) method to identify the major factors that influence the spatial linkage of volatility spillovers. Results show that geography influences the volatility spatial correlation differently across economic cycles, and the centrality structure factors have greater impact on the spatial correlation than the external economic factors. The QAP regression analysis shows that these influencing factors can explain about 50% of the spatial correlation variation of international financial markets' volatility spillovers.     

Stock market contagion in Central and Eastern Europe: unexpected volatility and extreme co-exceedance

We examine whether there is contagion from the US stock market to six Central and Eastern European stock markets. We use a novel measure of contagion that examines whether volatility shocks in the US stock market coupled with negative returns are followed by higher co-exceedance between US and emerging stock markets. Using our approach and controlling for a set of market-related variables, we show that during the period from 1998 to 2014, financial contagion occurred, that is, unexpected negative events in the US market are followed by higher co-exceedance between US and Central and Eastern European stock markets. Even though contagion is stronger during the financial crisis, it also occurs in tranquil times.     

The Dynamic Relation Between Stock Returns, Trading Volume, and Volatility

We examine the dynamic relation between returns, volume, and volatility of stock indexes. The data come from nine national markets and cover the period from 1973 to 2000. The results show a positive correlation between trading volume and the absolute value of the stock price change. Granger causality tests demonstrate that for some countries, returns cause volume and volume causes returns. Our results indicate that trading volume contributes some information to the returns process. The results also show persistence in volatility even after we incorporate contemporaneous and lagged volume effects. The results are robust across the nine national markets.     

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.