The information content of trading halts

We investigate the impact of trading halts of NYSE-listed stocks on informationally related securities that continue to trade during the period of the halt. Informational relationships are established for companies in the same four-digit SIC industry based on the correlation of returns, volume, volatility, and the adverse selection components of spreads. We find a significant liquidity impact on informationally related securities with spreads and price impact of trades having substantial increases. However, we also find that quoted depths, the number of trades, and trade volume significantly increase. Our results are consistent with the trading halt model of Spiegel and Subrahmanyam [2000. Asymmetric information and news disclosure rules. Journal of Financial Intermediation 9, 363–403] and with the informed trading model of Tookes [2008. Information, trading, and product market interactions: cross-sectional implications of informed trading. Journal of Finance 63, 379–413]. In addition, our results indicate that there is a common liquidity response of informationally related securities to firm-specific trading halts.     

Optimal informed trading in the foreign exchange market

We formulate a market microstructure model of exchange determination that we employ to investigate the impact of informed trading on exchange rates and on foreign exchange (FX) market conditions. With our formulation, we show how strategic informed agents influence exchange rates via both the portfolio-balance and information effects. We outline the connection which exists between the private value of information, market efficiency, liquidity and exchange rate volatility. Our model is also consistent with recent empirical research on the micro-structure of FX markets.     

The efficiency of the information processing in the Australian dollar market: Price discovery following scheduled and unscheduled news

We jointly investigate the responses of the Australian dollar (AUD) order flow, realized volatility and trading volume to unscheduled Reuters news headline alerts and scheduled macroeconomic news from Australia, Japan, the Eurozone, the U.K., and the U.S. over the period 2 January 2007 to 31 December 2009. We find that Reuters foreign exchange and fixed income market news headlines are important, and those headlines that arrive during the Australian offshore trading hours matter more. Furthermore, the AUD market responded mostly to Australian and U.S. macroeconomic news which have direct relevance for the exchange rate. We also find that better than expected Japanese and Eurozone macroeconomic news elicited a response in the AUD and also that better than expected news from Australia, U.S. and U.K. matter more. Finally, we find that the volume response to news decreases at a slower rate than the volatility response and that order flows for the AUD respond only to scheduled news.     

The Impact of Firm-Specific Public News on Intraday Market Dynamics: Evidence from the Turkish Stock Market

This study attempts to discover the intraday firm-specific news announcements and return volatility relation in the Turkish stock market. The GARCH framework is utilized to investigate the impact of firm-specific public news announcements on volatility persistence with and without trading volume. For the majority of the stocks in the sample, the volatility persistence diminishes with the inclusion of firm-specific news, implying that news is impounded rapidly into prices. This effect is more pronounced for larger stocks. When there is no news, the trading volume does not appear to reduce the volatility persistence for the majority of stocks, possibly due to the presence of private information possessed by informed traders.     

Impact of macroeconomic news on metal futures

This paper uses intra-day data for the period 2002 through 2008 to examine the intensity, direction, and speed of impact of US macroeconomic news announcements on the return, volatility and trading volume of three important commodities - gold, silver and copper futures. We find that the response of metal futures to economic news surprises is both swift and significant, with the 8:30 am set of announcements - in particular, nonfarm payrolls and durable goods orders - having the largest impact. Furthermore, announcements that reflect an unexpected improvement in the economy tend to have a negative impact on gold and silver prices; however, they tend to have a positive effect on copper prices. In comparison, realized volatility and volume for all three metals are positively influenced by economic news. Finally, there is evidence that several news announcements exert an asymmetric impact on market activity variables.     

Trading Patterns and Prices in the Interbank Foreign Exchange Market

The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.     

The impact of macroeconomic news on quote adjustments, noise, and informational volatility

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. We decompose bid and ask returns into a common (“efficient return”) factor and two market-side-specific components capturing market microstructure effects. The corresponding variance components reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and are positively influenced by news. The proportion of noise-induced variances is highest before announcements and significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow imbalances.     

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.     

Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

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.     

Time and dynamic volume–volatility relation

This paper examines volume and volatility dynamics by accounting for market activity measured by the time duration between two consecutive transactions. A time-consistent vector autoregressive (VAR) model is employed to test the dynamic relationship between return volatility and trades using intraday irregularly spaced transaction data. The model is used to identify the informed and uninformed components of return volatility and to estimate the speed of price adjustment to new information. It is found that volatility and volume are persistent and highly correlated with past volatility and volume. The time duration between trades has a negative effect on the volatility response to trades and correlation between trades. Consistent with microstructure theory, shorter time duration between trades implies higher probability of news arrival and higher volatility. Furthermore, bid–ask spreads are serially dependent and strongly affected by the informed trading and inventory costs.     

The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity

We propose a model for determining the optimal bid-ask spread strategy by a high-frequency trader (HFT) who has an informational advantage and receives information about the true value of a security. We employ an information cost function that includes volatility and the volume of the asset. Subsequently, we characterize the optimal bid-ask price strategies and obtain a stable bid-ask spread. We assume that orders submitted by low-frequency traders (LFTs) and news events arrive at the market with Poisson processes. Additionally, our model supports the trading of the two-sided quote in one period. We find that more LFTs and a higher exchange latency both hurt market liquidity. The HFT prefers to choose a two-sided quote to gain more profits while cautiously chooses a one-sided quote during times of high volatility. The model generates some testable implications with supporting empirical evidence from the NASDAQ-OMX Nordic Market.     

The impact of lunchtime closure on market behaviour: evidence from the Sydney Futures Exchange

This paper examines the impact of lunchtime closure on market behaviour. Between May and September, 1994 the Sydney Futures Exchange trialed lunchtime trading. The trial provides a unique natural laboratory experiment for examining the impact of lunchtime closure. The analysis reported in this paper documents abnormally high bid ask spreads, price volatility and trading volume on re‐opening of the market following lunchtime closure. These results confirm that closure has an impact on trading activity, and are consistent with the effects of strategic informed trading, a loss in price discovery and/or trading associated with risk transfer. An abnormal increase in trading volume prior to lunchtime closure is also documented, providing unambiguous evidence of trading activity motivated by risk transfer. Overall these results imply that lunchtime closure disrupts trading activity and reduces market quality by imposing additional costs on market participants.     

The impact of lunchtime closure on market behaviour: evidence from the Sydney Futures Exchange

This paper examines the impact of lunchtime closure on market behaviour. Between May and September, 1994 the Sydney Futures Exchange trialed lunchtime trading. The trial provides a unique natural laboratory experiment for examining the impact of lunchtime closure. The analysis reported in this paper documents abnormally high bid ask spreads, price volatility and trading volume on re‐opening of the market following lunchtime closure. These results confirm that closure has an impact on trading activity, and are consistent with the effects of strategic informed trading, a loss in price discovery and/or trading associated with risk transfer. An abnormal increase in trading volume prior to lunchtime closure is also documented, providing unambiguous evidence of trading activity motivated by risk transfer. Overall these results imply that lunchtime closure disrupts trading activity and reduces market quality by imposing additional costs on market participants.     

Public information arrival and volatility persistence in financial markets

This paper explores the relationship between daily market volatility and the arrival of public information in four different financial markets. Public information is measured as the daily number of economic news headlines, divided in six categories of news. Statistical analysis of the news data suggests the presence of particular seasonality effects, as well as a strong degree of autocorrelation. Over the period 1994–1998, significant effects of specific news categories on the volatility of US stocks, treasury bills, bonds and dollar were detected. However, the effects – in size and duration – vary by news category and by financial market. It is demonstrated that most of the volatility persistence, as observed by GARCH models, tends to disappear when news is included in the conditional variance equation.     

Public information arrival: Price discovery and liquidity in electronic limit order markets

How information is translated into market prices is still an open question. This paper studies the impact of newswire messages on intraday price discovery, liquidity, and trading intensity in an electronic limit order market. We take an objective ex ante measure of the tone of a message to study the impacts of positive, negative, and neutral messages on price discovery and trading activity. As expected, we find higher adverse selection costs around the arrival of newswire messages. Negative messages are associated with higher adverse selection costs than positive or neutral messages. Liquidity increases around positive and neutral messages and decreases around negative messages. Available order book depth as well as the trading intensity increases around all news. Our results suggest that market participants possess different information gathering and processing capabilities and that negative news messages are particularly informative and induce stronger market reactions.     

THE EFFECTS OF DECIMALIZATION ON RETURN VOLATILITY COMPONENTS,SERIAL CORRELATION,AND TRADING COSTS

We examine the composition of return volatility, serial correlation, and trading costs before and after decimalization on the New York Stock Exchange. We decompose the variance of price changes into components associated with public news, rounding errors, and market‐making frictions. We find that when stocks move from a fractional to a decimal trading system, the variance components due to market‐making frictions and rounding errors decline significantly, whereas the component due to public news remains unchanged. The serial correlation of price changes weakens substantially after decimalization. The uninformed component of bid‐ask spreads decreases significantly whereas the informed component has no significant change.     

How is macro news transmitted to exchange rates?

Macro news can affect currency prices directly and indirectly via order flow. Past research shows that the direct effects of scheduled macro news account for less than 10% of daily price variance. This paper shows that the arrival of macro news can account for more than 30% of daily price variance. Two features of our analysis account for this finding: (1) We consider the broad spectrum of macro news items that market participants observe, not just scheduled announcements. (2) We allow the arrival of news to affect prices indirectly via its impact on the volatility of order flow. Our analysis shows that order flow variations contribute more to currency price dynamics following the arrival of public macro news than at other times. This is not consistent with news effects being common knowledge that is impounded in price directly. Roughly two-thirds of the total effect of macro news on the DM/$ exchange rate is transmitted via order flow.     

The role of private information in return volatility,bid–ask spreads and price levels in the foreign exchange market

Trading volume and order flow have both been closely associated with informed trader activity in the market microstructure literature. Using theory that explains regular intraday patterns in trading data, we transform these two variables into proxies for private information and examine their relationships with bid–ask spreads and return volatility. We use a unique and unusually rich high-frequency intraday dataset from the world's largest financial market, namely, the electronic inter-dealer spot foreign exchange market. Our analysis takes account of institutional features peculiar to this order-driven market. Our empirical results strongly affirm our theoretical understanding of how these markets work. They also reveal how the structure of the inter-dealer spot FX market affects exchange rate volatility. Finally, we also explore how private information contributes to the evolution of prices.     

The reaction of the Australian financial markets to the interest rate news from the Reserve Bank of Australia and the U.S. Fed

This paper provides comprehensive evidence on the impacts of the Reserve Bank of Australia's (RBA) and the U.S. Fed's target interest rate announcement news on the Australian financial markets over the period 1998–2006. The RBA's news had a significant impact on the first moments of market returns/changes in line with a priori expectations, and the conditional volatility in most of the markets was significantly higher following the news. Asymmetric news effect is also observed for the Australian interest rates where markets tended to respond more strongly to unexpected rate rises than rate falls. While the U.S. Fed's news influenced only the USD/AUD exchange rate, the Australian market volatility was significantly lower in all market segments following the Fed's news.