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We examine the informational roles of trades and time between trades in the domestic and overseas US Treasury markets. A vector autoregressive model is employed to assess the information content of trades and time duration between trades. We find significant impacts of trades and time duration between trades on price changes. Larger trade size induces greater price revision and return volatility, and higher trading intensity is associated with a greater price impact of trades, a faster price adjustment to new information and higher volatility. Higher informed trading and lower liquidity contribute to larger bid–ask spreads off the regular daytime trading period.

This paper examines the information efficiency of KOSDAQ50 and KOSPI200 index futures markets. The study analyzes and compares both markets in three respects : 1) price discovery (lead-lag relationship between spot and futures markets.), 2) volatility-volume relationship, and 3) mispricings between spot and futures prices. The first, analysis shows the in the KOSPI200 market, futures price leads spot price. While spot price leads futures price in the KOSDAQ50 market. The second analysis shows that the volatility-volume relation is positive in the KOSPI200 futures market, supporting the hypothesis of mixture of distribution. In contrast, there is little relation between volume and volatility in the KOSDAQ50 futures market. This result casts doubt that the futures market price reflects information. The last analysis shows that the magnitude of mispricing becomes smaller with more volume in the KOSPI200 futures market, while it becomes larger with more volume in the KOSDAQ50 futures market. The overall results imply that the KOSDAQ50 futures market is less informationally efficient that the KOSPI200 market. The inefficiency appears due to the lack of institutional investor participation, especially securities firms, in making up the market.

The purpose of this paper is to re-examine the effectiveness of price limits on stock volatilities in China over a more recent time period spanning from 2007 to 2012. The motivation stems from the fact that very high stock market volatilities are observed in China and we are sceptical of the volatility mitigating effect claimed by advocates of price limits.

The effectiveness of price limits on volatilities is examined using an event study methodology and within an expanded framework of volatility-volume relationships. The sample stocks include the 300 component stocks of the CSI300 Index.

Both event study and regression analysis suggest that price limits exaggerate market volatilities by causing volatility spillovers. The destabilising effect is much more pronounced for small firm stocks and when the market falls. In addition to the informational source of volatilities (represented by volume), price limits create another non-trivial frictional source of volatilities in China’s stock market.

This research is the first to re-examine the price limit effect in China’s stock market in an expanded framework of volatility-volume relationships. It identifies price limits, in addition to information, as another non-trivial frictional source of volatilities. The findings derived from a recent sample period confirm the conventional view of inefficiency of price limits raised by Fama (1989) and provide evidence in support of the pervasive trend of stock market deregulations.

This study investigates the impact of simultaneously replacing both midday single-price call auction and lunch break with multi-price continuous trading on intraday volatility–volume patterns as well as the intraday volatility–volume nexus.

The analysis utilises 150 m tick-by-tick transaction data related to 333 stocks traded on Borsa Istanbul Equity Market covering a period of 2 months prior to and following the change. In addition to graphic comparisons, the study uses difference in mean tests, panel-fixed generalized least squares (GLS), panel-random GLS and random-effects linear models with AR(1) disturbance regression estimations.

The results show that intraday volatility and trading volume form an inverse J-shape and are positively correlated. It is observed that the implementation of the regulation change decreased intraday volatility and increased trading volume. Additionally, the results indicate a negative volatility–liquidity and a positive volume–liquidity relationship, supporting the mixture of distribution hypothesis.

Enhanced market efficiency provides greater opportunity for investment and risk management. Investors can benefit from the findings on the intraday volatility–volume nexus, which is an indicator of informed trading, and regulatory authorities can use volume to oversight volatility.

This very rare regulation change of the simultaneous replacement of the lunch break and midday call auction with continuous trading is investigated in the context of intraday volume and volatility. This study also expands upon some important findings on the volume–volatility nexus for the Turkish Stock Market.

This study aims to examine whether global gold futures returns volatilities and trading activities are threshold cointegrated.

This study considers 11 gold futures markets, including 3 developed futures markets and 8 developing futures markets. This study also analyzes futures trading activities for speculators and hedgers. This study uses a nonlinear threshold vector error correction model (TVECM) and a threshold Lagrange multiplier (LM) test proposed by Hansen and Seo (2002).

The findings show that global gold futures return volatilities (FRV) and trading activities are not always threshold cointegrated. Most developed futures markets exhibit threshold cointegrated of gold FRV and trading activities for speculators and hedgers, whereas some developing futures markets exhibit threshold cointegrated. It suggests that speculators and hedgers trading activity conveys valuable information about changes in market volatility dynamics. On the other hand, responses to error-correction effect among gold FRV and trading activities for speculators and hedgers are dramatically different for developed and developing gold futures markets, respectively, particular in the unusual regime.

Research results show that threshold cointegration between global gold FRV and trading activities matters but not always. Thus, threshold relations have improved the authors’ understanding of global gold futures price discovery process with a threshold. For research limitations, this study uses only near month futures contracts, as it contains more information but not using far month contracts.

The findings may have important trading implications with additional insights in a(n) (un)usual regime further regulation may be detrimental to the price responsiveness in futures markets if increased price volatility and trading volume are attributed to liquid and efficient markets.

The findings may have important policy implications with additional insights. For example, in a(n) (un)usual regime greater regulatory restrictions may be warranted to decrease market inefficiencies if increased price fluctuations are caused by increased trading volume. Policymakers could enhance futures trading liquidity or restrict speculating positions.

This study examines whether global gold futures returns volatilities and trading activities are threshold cointegrated by using a nonlinear TVECM. The authors detect that some global gold futures returns volatilities and trading activities are threshold cointegrated but some are not. Hence, the findings determine whether the volatility–volume threshold relation holds across countries and investigate the determinants of cross-country differences in different traders.

The purpose of this paper is twofold. The first is to estimate the correlation between market activity and volatility on an exchange that does not use continuous auctions to find prices. The second is to estimate the sensitivity of that relationship to differences in opinions across traders regarding asset value.

Both objectives are accomplished by using seven years of trader‐level data from the Tokyo Grain Exchange, which uses rapid sequences of Walrasian tâtonnement auctions to discover prices. On the TGE, only one futures contract trades at any given time and all of a commodity's futures contracts are auctioned in a rapid sequence, with only seconds between a sequence's auctions. The results are interpreted under the hypothesis that this design causes traders' beliefs to become more accurate and more uniform as a sequence progresses.

Intraday volume is u‐shaped while intraday volatility is downward sloping. The volume–volatility link is positive and stays constant or strengthens as traders' beliefs about value become more precise. The link is driven by trades originating from small futures commission merchants, especially those trades entered on behalf of customers.

Evidence that accounting for cross‐correlations when estimating volatility can have an important effect on estimates is presented. Researchers are encouraged to further explore the implications of cross‐correlations.

The paper includes implications for existing theory, the measurement of volatility, and the design of central exchanges.

This paper uses the TGE as a natural laboratory to test theory. It is the first such study to use data from an exchange that does not use continuous auctions, and the first to document the simultaneous existence of u‐shape volume and downward‐sloping volatility.

A composite sentiment index (CSI) from quantitative proxy sentiment indicators is likely to be a lag sentiment measure as it reflects only the information absorbed in the market. Information theories and behavioral finance research suggest that market prices may not adjust to all the available information at a point in time. This study hypothesizes that the sentiment from the unincorporated information may provide possible market leads. Thus, this paper aims to discuss a method to identify the un-incorporated qualitative Sentiment from information unadjusted in the market price to test whether sentiment polarity from the information can impact stock returns. Factoring market sentiment extracted from unincorporated information (residual sentiment or sentiment backlog) in CSI is an essential step for developing an integrated sentiment index to explain deviation in asset prices from their intrinsic value. Identifying the unincorporated Sentiment also helps in text analytics to distinguish between current and future market sentiment.

Initially, this study collects the news from various textual sources and runs the NVivo tool to compute the corpus data’s sentiment polarity. Subsequently, using the predictability horizon technique, this paper mines the unincorporated component of the news’s sentiment polarity. This study regresses three months’ sentiment polarity (the current period and its lags for two months) on the NIFTY50 index of the National Stock Exchange of India. If the three-month lags are significant, it indicates that news sentiment from the three months is unabsorbed and is likely to impact the future NIFTY50 index. The sentiment is also conditionally tested for firm size, volatility and specific industry sector-dependence. This paper discusses the implications of the results.

Based on information theories and empirical findings, the paper demonstrates that it is possible to identify unincorporated information and extract the sentiment polarity to predict future market direction. The sentiment polarity variables are significant for the current period and two-month lags. The magnitude of the sentiment polarity coefficient has decreased from the current period to lag one and lag two. This study finds that the unabsorbed component or backlog of news consisted of mainly negative market news or unconfirmed news of the previous period, as illustrated in Tables 1 and 2 and Figure 2. The findings on unadjusted news effects vary with firm size, volatility and sectoral indices as depicted in Figures 3, 4, 5 and 6.

The related literature on sentiment index describes top-down/ bottom-up models using quantitative proxy sentiment indicators and natural language processing (NLP)/machine learning approaches to compute the sentiment from qualitative information to explain variance in market returns. NLP approaches use current period sentiment to understand market trends ignoring the unadjusted sentiment carried from the previous period. The underlying assumption here is that the market adjusts to all available information instantly, which is proved false in various empirical studies backed by information theories. The paper discusses a novel approach to identify and extract sentiment from unincorporated information, which is a critical sentiment measure for developing a holistic sentiment index, both in text analytics and in top-down quantitative models. Practitioners may use the methodology in the algorithmic trading models and conduct stock market research.

The paper aims to explore the informational role of futures volume in the simultaneous relationship between option volume and spot volatility to forecast the volatility of the underlying asset.

The generalized method of moments is used to estimate the simultaneous equations of endogeneity between spot volatility and option volume. Futures volume is specified as an exogenous variable in both legs of the estimation of simultaneous equations. However, the future volume is also tested as a dependent variable to prove preference for investment by informed investors in futures along with options.

The result indicates that futures volume has a significant association with the bi-directional simultaneous equation estimation between spot volatility and option volume. Moreover, the result of this paper proves that informed investors also prefer futures markets over the spot market. However, there is no change observed in the relationship between option volume and spot volatility due to either call or put options or moneyness.

The possible role of futures volume in the simultaneous equations between spot volatility and option volume has not yet been researched. This paper pioneers in demonstrating that futures volume is an exogenous variable in the simultaneous equation modeling between spot volatility and option volume. Moreover, in the contemporaneous as well as predictive relationships between spot volatility and option volume, futures volume as an exogenous variable is significant in forecasting spot volatility. In addition to this, the current paper uniquely provides evidence of investment in futures also over the spot market by informed investors.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.

This study investigates whether broker anonymity impairs the ability of the market to detect informed trading in the lead up to takeover announcements. Our research represents the first study in this area to analyse the effects of broker anonymity in the context of significant information asymmetry. Results indicate that informed traders are less detected, and therefore better off when broker identifiers are concealed. This finding has important policy implications for exchange officials deciding whether or not to reveal broker identifiers surrounding trades, especially considering that almost all prior research suggests that broker anonymity is correlated with improved liquidity.