Narrow Results

By utilizing vector error correction model (VECM) and EGARCH model, this article uses 5-minute intraday data to examine the interaction of return and volatility between Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the newly introduced TAIEX futures. VECM model shows that there exists bi-directional Granger causality between index spot and index futures markets, but spot market plays a more important role in price discovery. The results of impulse response function and information share indicate that most of the price discovery happens in index spot market. The evidence of EGRACH shows that the impacts of spot and futures innovations are asymmetrical, and the volatility spillovers between spot and futures markets are bi-directional. However, the information flow from spot to futures is stronger. These results suggest that the TAIEX spot market dominates the TAIEX futures market in terms of return and volatility.

This paper examines mispricing, volatility and parity on the Hang Seng Index (HSI) options and futures market. Most of the previous research has focused on futures contracts; we update this research and extend it by considering also option contracts. It is also important to examine these issues post 1997 Asian crisis. We find mispricing of HSI futures and option contracts if no transaction costs were considered. However, by incorporating transaction costs, the HSI futures are bounded within the arbitrage free region and most of the mispricing of the HSI options disappears. Additional tests on the mispricing series reveals that most of the derivative HSI contracts are positively autocorrelated and that the mispricing series for both derivative contracts are not identical among the different contract months. From our results we cannot conclude that there is causal relationship between the mispricing and the spot index volatility. Finally, our empirical results show that for HSI derivative contracts future and option parity holds, supporting our mispricing test that the HSI derivative market is efficient and has not been adversely affected by the Asian economic crisis.

This paper reports an empirical analysis of the relationship between return autocorrelation, trading volume and volatility, following the seminal paper by Campbell, Grossman and Wang (1992) using data for A shares traded on the Shanghai and Shenzhen stock exchanges for the period 1992–2002. Campbell et al. argue that autocorrelation of returns will be negatively related to trading volume given that market makers will need to be rewarded with higher returns for accommodating noise traders. For our full sample we find remarkably consistent support for the CGW hypothesis and results — return autocorrelations are negatively but non-linearly related to lagged trading volume and less strongly to volatility. These results are quite robust with respect to different messures of volume and volatility. We argue that this is a striking result in view of the substantial differences between the US market in the 1960s, 1970s and 1980s and the Chinese market of the 1990s. The relationship proves to be unstable over short sub-periods although whether this is due to the relatively short sample we use or to the inherent instability of the Chinese market in its first decade of operation will not be clear until much longer data sets are available for Chinese stock prices.

This paper uses ARCH models to examine if there is a leverage effect and also to test if A- and B-share holdings have different risks in Chinese stock markets before and after B-share markets open to domestic investors in February 2001. The empirical results suggest that leverage effect was not present and shocks have symmetric impact on the volatility of Chinese B-share stock returns in both periods and A-share returns in Period I. Thus GARCH model would be a better model to fit the Chinese B-share stock returns than EGARCH or GJR-GARCH model. But EGARCH or GJR-GARCH model fits recent (Period II) A-share markets data better than GARCH model. Another finding of this paper is that holding A- or B-share bears different risk in returns in the two Chinese markets. Furthermore, news or shocks have a larger impact on volatility of B-share returns in Period I than in Period II.

Using data from the Taiwanese stock market, an emerging market, this paper documents positive changes in liquidity and volatility around seasoned equity offerings (SEOs). These findings are consistent with the uncertain signal hypothesis that investors with diverse views on the information content of SEOs are likely to induce larger trading activity and subsequent higher stock return volatility. We also provide direct evidence that changes in liquidity is positively associated with stock price adjustment. However, the relations among liquidity, volatility and price movements appear to rely on how SEOs are conducted. A practical implication is that managers may influence liquidity and stock price movement through their choice of SEOs issuing methods.

This paper examines autocorrelation and cross-autocorrelation patterns for selected Asian stock returns. Special attention is given to examination of Asian stock returns and the impact on them of the past information. By employing a class of asymmetric specification of conditional mean and conditional variance models, we find the autocorrelation coefficient to be negative for the Japanese market and positive for the rest of the Asian markets studied. Our findings suggest that the Asian markets respond sensitively to the US market, especially on the down side. The asymmetric effects are found to be present in both mean and variance equations. The evidence is consistent with behavior in which investors in Asian markets tend to react more significantly to negative stock news originating from US sources than they do to positive news.

This paper investigates whether the introduction of trading by qualified foreign institutional investors (QFIIs) has impacted the lead and volatility behavior of the futures market when the macroeconomic effects and some major economic events are controlled. First, we detect that some market inefficiency exists in Taiwan index futures market. Second, the evidence shows a strengthening in the lead of index futures over index spot markets following the introduction of trading by QFIIs. Third, we find evidence of an increase in the level of futures market volatility, implying that the quantity of information flowing into the futures market increases following the onset of trading by QFIIs. Finally, the asymmetries do not reduce after the opening up of the futures market to QFIIs. This finding is inconsistent with the view that the introduction of informed foreign investors may improve the reliability and quality of information and mitigate the effect of noise traders on market volatility.

We reexamine the effects of price limits on stock volatility of Taiwan Stock Exchange using a new methodology based on the Extreme-Value technique. Consistent with the advocates of price limits, we find that stock market volatility is sharply moderated under more restrictive price limits.

Previous evidence suggests that the implied volatility from equity index options, as a measure of stock market uncertainty, can provide "forward-looking information" about the stock–bond return correlation. This paper uses an alternative regime-switching autoregressive model to characterize state-dependent stock–bond return comovement and to evaluate the contribution of implied volatility in understanding transition dynamics. We confirm that implied volatility provides information about transition dynamics which is not inherent in the stock and bond returns, notwithstanding several different features of our data set and methodological approach.

Returns of the same companies' common stocks, both non-market-adjusted and market-adjusted, exhibit greater volatility, on the Stock Exchange of Hong Kong where short selling is allowed than on the Shanghai Stock Exchange and Shenzhen Stock Exchange where short selling is restrained. This unique evidence indicates that short selling increases stock price volatility for the Chinese stocks in the Chinese stock markets.

In this paper, we apply several variants of the EGARCH model to examine the role of depreciation of the Indian rupee on India's stock market returns using daily data. Our findings suggest that volatility persistence has been high; depreciation of the rupee has increased volatility; and asymmetric volatility confirms that negative shocks generate more volatility than positive shocks. We also find that an appreciation of the Indian rupee over the 2002 to 2006 has generated more returns and less volatility.

This paper investigates the behavior of stock returns and volatility in 10 emerging markets and compares them with those of developed markets under different measures of frequency (daily, weekly, monthly and annual) over the period January 1, 2002 to December 31, 2006. The ratios of mean return to volatility for emerging markets are found to be higher than those of developed markets. Sample statistics for stock returns of all emerging and developed markets indicate that return distributions are not normal and return volatility shows clustering. In most cases, GARCH (1, 1) specification is adequate to describe the stock return volatility. The significant lag terms in the mean equation of GARCH specification depend on the frequency of the return data. The presence of leverage effect in volatility behavior is examined using the TAR-GARCH model and the evidence indicates that is not present across all markets under all measures of frequency. Its presence in different markets depends on the measure of frequency of stock return data.

Simultaneous volatility models are developed and shown to be separate from multivariate GARCH estimators. An example is provided that allows for simultaneous and unidirectional volatility and volume of trade effects. These effects are tested using intraday data from the Australian cash index and index futures markets. Overnight volatility spillover effects from the United States S&P500 index futures markets are tested using alternative estimates of this US market volatility. The simultaneous volatility model proves to be robust to alternative specifications of returns equations and to misspecification of the direction of volatility causality.

Based upon the theory of the "arrival of news", the main purpose of this paper is to investigate the impact of non-trading periods on the measurement of volatility for the S&P 500, FTSE 100, and TAIEX indices. Using an adaptation of the GJR (1,1) model, we find that both weekday holiday periods and half-day trading periods have significant impacts on the estimation of volatility for the S&P 500 and FTSE 100 indices. On the other hand, weekends have significant impacts for the TAIEX index. Our findings imply that for the UK and US markets, much less relevant information is produced during weekends, while more relevant information continues to be produced during other types of non-trading periods. However, the weekend volatility of the Taiwan market is specially driven because the US macro news is announced on Fridays and the trading time of the US market is later than that of the Taiwan market without any overlapping.

Previous studies have documented the informational role of order imbalances in price discovery of the Treasury market. In this paper, we explore the liquidity dimension of order imbalances. Through our research, we find evidence which indicates that order imbalances affect Treasury market liquidity. More importantly, order imbalances have significant effects on Treasury market returns and volatility, consistent with the contention that order imbalances can cause an inventory problem of marketwide concern. Results suggest that a significant portion of the effect of order imbalances on price and quoted spread is associated with the inventory premium that compensates market participants for providing liquidity to uninformed traders. The effects of order imbalances on market liquidity, returns and volatility are stronger for two- and five-year notes and Treasury bills. Furthermore, there is commonality in order imbalances. Sensitivity of order imbalances individual bonds to marketwide order imbalances varies across securities.

In this paper, we investigate the relationship between volatility of and liquidity provision through the aggregation of high-frequency data on the stock index option markets of Taiwan. Strong evidence shows the different behaviors of liquidity supply for market makers and nonmarket makers. In addition, evidence demonstrates that nonmarket makers are unwilling to offer liquidity on buy-side when option price is high, but the phenomena are not evident for the market makers. Overall, nonmarket makers provide less liquidity when volatility is high. In contrast, market makers provide the same or more liquidity on the limit order book when volatility is high. Therefore, the market makers play more important a role when market is volatile. The policy implication is that professional market makers on option markets are stable forces to offer liquidity when market is volatile, and it is referable for those pure order-driven option markets without market makers (e.g., Korea Exchange, KRX).

This study examines the pre-holiday effect in the Chinese stock market. It provides new insights into the weak-form efficiency of China's equity market indexes. Using the GARCH (1,1) model, we find the pre-holiday effect in broad-based Chinese stock returns and in size, value and growth style indexes. Further analysis using a GARCH (1,1)-M model suggests that the pre-holiday effect at both market and industry/sector levels can be attributed to time-varying risk. We show the pre-holiday effect reflects abnormal returns in small-cap, large-cap and growth style indexes while this same effect reflects compensation for bearing risk in value stocks.

This study empirically investigates the effect of investor sentiment on returns and volatility of eight commodities. The findings suggest that sentiment has a predictive power on these commodities’ return and volatility. Fundamentally, return and volatility are positively associated with sentiment, suggesting that investors in the commodity markets are irrational — entailing the existence of noise trading. The results confirm the prediction of the affect infusion model in which optimistic investors are willing to take more risks, thus, raising returns and volatility. Furthermore, sentiment has a significant asymmetrical impact on volatility, and negative sentiment has a significantly greater impact than positive sentiment.

This paper studies patterns of volatilities and their spillovers across six major segments of Indian financial market applying univariate GARCH model and estimating the Diebold and Yilmaz (DY) volatility spillover index. The study found increasing integration of financial market segments over time and that equity, bank index and corporate bond segments are net contributors while money, gsec and forex segments are net receivers of volatility. The study highlights the need for a healthy banking sector and the increasing significance of corporate bond market volatility and suggests segment specific policy responses to tackle financial market volatilities.