The liquidity of automated exchanges: new evidence from German Bund futures

Previous literature has suggested that automated exchanges such as the Deutsche Terminborse (DTB) may be less liquid than their open-outcry counterparts such as the London International Financial Futures Exchange (LIFFE), although evidence provided on this issue has been mixed. This paper provides new evidence on the relative magnitudes of bid-ask spreads in the Bund contract traded on the DTB and LIFFE using intraday data from a period in which each exchanges share of total Bund trading was closer than previous research. The findings suggest that quoted bid-ask spreads are wider on the LIFFE than the DTB, even after controlling for their determinants. Furthermore, bid-ask spreads on the DTB increase more rapidly as price volatility increases relative to the LIFFE. Overall, this evidence implies that while automated exchanges are capable of providing more liquidity than floor traded exchanges, the relative performance of automated exchanges deteriorates during periods of higher volatility.     

Price formation on stock exchanges: the evolution of trading within the day

Prior analyses of prices of the NYSE and other exchanges findthat transitory price volatility is greater at the open of tradingthan at the close. We extend this line of research by using40 years of hourly Dow Jones 65 composite price index data toestimate transitory volatility throughout the trading day. Ourresults indicate that transitory volatility steadily declinesduring the trading day. We find a similar intraday decline intransitory volatility for a 2-year sample of the individualfirms in the Dow Jones 30 Industrials Index. The results areconsistent with the hypothesis that trading aids price formationand do not support the argument that particular trading mechanismsare the source of greater volatility at the open of trading.     

Intraday Empirical Regularities in Interest Rate and Equity Index Futures Markets, and the Effect of Macroeconomic Announcements

This paper focuses on the intraday behaviour of returns, volatility, volume and price reversals for the Short Sterling interest rate and FTSE100 stock index futures contracts traded on the London International Financial Futures and Options Exchange (LIFFE). It also examines the effect of scheduled macroeconomic announcements and interest rate changes on the intraday behaviour of the variables of interest. We find clear differences and similarities with US studies and between the interest rate and equity contracts, which have important theoretical implications. This new evidence helps discriminate between the theories seeking to explain these intraday patterns.     

The impact of salient political and economic news on the trading activity

This paper investigates the impact of salient political and economic news on the intraday trading activity, namely, the stock return volatility, the stock price volatility, the number of shares traded, and the trading frequency. Using transactions data on 33 constituent stocks of the Hang Seng Index in the Stock Exchange of Hong Kong (SEHK), we find that political news has a distinct impact on market activity when compared with economic news. We argue that the observed phenomenon is related to the precision of signals associated with these two types of news and investors' perceptual biases.     

Return Volatility,Trading Imbalance and the Information Content of Volume

In this paper, we examine the relationship between volume and return volatility using the transaction data. We introduce transaction and volume imbalance measures to capture the information content of trades. These two information measures are shown to have a strong explanatory power for return volatility and contain incremental information about the asset values over and above that conveyed by the size and frequency of trades. Also, return volatility is significantly correlated with the percentage of trading volume taking place at NYSE. This result suggests that NYSE trades are more informative and contribute more to price discovery. There is evidence that price discovery concentrates in more heavily traded stocks, particularly the Dow Jones Stocks. Finally, return volatility is found to be persistent at the intraday level. The persistence level is higher for less frequently traded stocks. Return volatility also exhibits temporal variations. In particular, return volatility is significantly higher in the opening half-hour for less frequently traded stocks. Thus, stocks with different frequencies of trades may follow different volatility processes.     

Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation

We study two methods of adjusting for intraday periodicity of high-frequency financial data: the well-known Duration Adjustment (DA) method and the recently proposed Time Transformation (TT) method (Wu (2012)). We examine the effects of these adjustments on the estimation of intraday volatility using the Autoregressive Conditional Duration-Integrated Conditional Variance (ACD-ICV) method of Tse and Yang (2012). We find that daily volatility estimates are not sensitive to intraday periodicity adjustment. However, intraday volatility is found to have a weaker U-shaped volatility smile and a biased trough if intraday periodicity adjustment is not applied. In addition, adjustment taking account of trades with zero duration (multiple trades at the same time stamp) results in deeper intraday volatility smile.     

Intraday trading halts in the Nikkei futures market

The Osaka Securities Exchange (OSE) halts Nikkei 225 index-futures trading when the next transaction is to take place at a price more than ¥30 (prior to February 1994) or ¥60 (from February 1994) away from the previous trading price. This paper examines the efficacy of the intraday price limit rule in terms of price discovery, liquidity and volatility. We also include transaction data from the Singapore International Monetary Exchange (SIMEX) where Nikkei futures are traded simultaneously. The intraday price limit rule generally appears to be ineffective in reducing volatility and avoiding price jumps, at least partly because OSE traders have access to the alternative market at SIMEX.     

Stock market closure and intraday stock index futures market volatility: “contagion”, bid–ask bias or both?

Chang et al. [Journal of Business 68 (1) (1995) 61] examine the impact of the closure of the New York Stock Exchange (NYSE) on S&P500 stock index futures traded on the Chicago Mercantile Exchange. They document a decline in futures market volatility immediately after the close of the NYSE, and an increase 15 minutes later when the futures market closes. They attribute this to contagion–i.e. a decline in information transfer from equities to futures markets following the closure of the underlying market. This paper examines the impact of the extension of trading hours in Hang Seng Index futures traded on the Hong Kong Futures Exchange on the 20 November, 1998 to 15 minutes after the close of the underlying market (the Stock Exchange of Hong Kong). Using the unique natural experiment provided by this change, a pattern similar to US markets is documented for the Hang Seng Index Futures following the change in trading hours. This provides strong evidence that the intraday pattern in volatility is caused by market closure. Unlike US futures exchanges, price reporters on the floor of the Hong Kong Futures Exchange collect quote data in addition to trade data. This data facilitates a test of another plausible microstructure explanation for the observed behaviour–bid–ask bounce associated with trading activity. This paper provides evidence that bid–ask bounce also explains part of the observed intraday behaviour in price volatility.     

The predictive power of the implied volatility of options traded OTC and on exchanges

This paper investigates the efficiency of stock index options traded over-the-counter (OTC) and on the exchanges in Hong Kong and Japan. Our findings suggest that implied volatility is superior to either historical volatility or a GARCH-type volatility forecast in predicting future volatility in both the OTC and exchange markets. This paper is also one of the first to compare the predictive power of the implied volatility of stock index options traded OTC to that of exchange-traded stock index options. Our evidence suggests that the OTC market is more efficient than the exchanges in Japan, but that the opposite is true in Hong Kong.     

When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions

We examine high-frequency market reactions to an intraday stock-specific news flow. Using unique pre-processed data from an automated news analytics tool based on linguistic pattern recognition we exploit information on the indicated relevance, novelty and direction of company-specific news. Employing a high-frequency VAR model based on 20 s data of a cross-section of stocks traded at the London Stock Exchange we find distinct responses in returns, volatility, trading volumes and bid-ask spreads due to news arrivals. We show that a classification of news according to indicated relevance is crucial to filter out noise and to identify significant effects. Moreover, sentiment indicators have predictability for future price trends though the profitability of news-implied trading is deteriorated by increased bid-ask spreads.     

Information arrivals and intraday exchange rate volatility

This paper investigates the link between information arrivals and intraday DEM/$ volatility. Information arrivals are measured by the numbers of news items that appeared in the Reuters News Service. We separate news stories into different categories and find that total headline news counts, US and German macroeconomic news and German Bundesbank monetary policy news all have a significant impact on intraday DEM/$ volatility. The larger quantitative effects of the German Bundesbank monetary policy news and US macroeconomic news at 15-min intervals are consistent with the findings of a two-stage adjustment process of public information arrivals [Fleming and Remolona, J. Finance (1999) 1901]. Our results suggest that the persistent of intraday exchange rate volatility set off by public information is extended by traders’ private information about 15 min later. The conclusions are obtained from ARCH models that incorporate intraday seasonal volatility terms.     

Intraday dynamics of volatility and duration: Evidence from Chinese stocks

We propose a new joint model of intraday returns and durations to study the dynamics of several Chinese stocks. We include three U.S. stocks for comparison. Flexible innovation distributions are used for durations and returns, and the total variance of returns is decomposed into different volatility components associated with different transaction horizons. The new model provides strong improvements in density forecasts for duration and returns and only modest gains for points forecasts of the variance of returns. The conditional hazard functions are non-monotonic and there is strong evidence for different volatility components. Although diurnal patterns, volatility components, and market microstructure implications are similar across the markets, there are interesting differences. Durations for lightly traded Chinese stocks tend to carry more information than heavily traded stocks. Chinese investors usually have longer investment horizons, which may be explained by the specific trading rules in China.     

Cyclical Changes in Firm Volatility

We characterize trends and cycles in the volatility of U.S. firms using a measure that we argue more cleanly captures firm‐specific volatility in sales and earnings growth than standard measures do. While earlier literature has emphasized a trend increase in the volatility of publicly traded firms, we find that a typical publicly traded firm has become more stable. We find that the negative association between firm‐specific volatility and the business cycle is weaker than earlier research based on dispersion measures suggests. We find that during the Great Recession of 2007–2009, firm‐specific volatility increased moderately but never substantially exceeded its sample mean. Our results are inconsistent with the hypothesis that firm‐specific volatility is an important driver of the business cycle, as it theoretically could be through an effect of default risk on credit spreads.     

Price discovery in bitcoin futures

This paper studies the contribution of the newly launched future contracts to the bitcoin price discovery process. Using well-established methodologies in the literature of the evaluation of price discovery in financial markets, we find evidence that, although the volume of bitcoins traded in the decentralized spot market overwhelms that of the futures market, the latter plays a more important role in incorporating new information about the value of bitcoin. Our empirical investigation also provides evidence of strong bi-directional dependence in the intraday volatility of the spot and futures markets.     

Intraday patterns in London listed Exchange Traded Funds

In this paper we examine the intraday trading patterns of Exchange Traded Funds (ETFs) listed on the London Stock Exchange. ETFs have been shown to be characterised by much lower bid–ask spread costs and by lower levels of information asymmetry than individual securities. One possible explanation for intraday trading patterns is that concentration of trading arises at the start of the trading day because informed traders have private information that quickly diminishes in value as trading progresses. Since ETFs have lower trading costs and lower levels of information asymmetry we would expect these securities to display less pronounced intraday patterns than individual securities. We fail to find that ETFs are characterised by concentrated trading bouts during the day and therefore find support for the argument that information asymmetry is the cause of intraday volume patterns in stock markets. We find that ETF bid–ask spreads and volatility are elevated at the open but not at the close. This lends support to the “accumulation of information” explanation that sees high spreads and volatility at the open as a consequence of information accumulating during a market closure and impacting on the market when it next opens.     

An empirical analysis of the dynamic relationship between mutual fund flow and market return volatility

We study the dynamic relation between aggregate mutual fund flow and market-wide volatility. Using daily flow data and a VAR approach, we find that market volatility is negatively related to concurrent and lagged flow. A structural VAR impulse response analysis suggests that shock in flow has a negative impact on market volatility: An inflow (outflow) shock predicts a decline (an increase) in volatility. From the perspective of volatility–flow relation, we find evidence of volatility timing for recent period of 1998–2003. Finally, we document a differential impact of daily inflow versus outflow on intraday volatility. The relation between intraday volatility and inflow (outflow) becomes weaker (stronger) from morning to afternoon.     

The Dynamics of Security Trades,Quote Revisions,and Market Depths for Actively Traded Stocks

We examine the dynamics of return volatility, trading volume, and depth—in an intraday setting for a sample of actively traded NYSE and NASDAQ stocks. We show that depth is a useful intervening variable and mitigates the impact of trading activity on price volatility. Furthermore, depth is affected by the perception of prevailing information asymmetry between informed and uninformed traders. We demonstrate empirically that the NYSE supplies greater depth under conditions of high, perceived information asymmetry as compared to NASDAQ. NASDAQ makes up for this deficiency by its capability of managing large volume shocks without a major decline in depth.JEL Classification: C32, D82, G10     

The Samuelson hypothesis in futures markets: An analysis using intraday data

This paper considers the Samuelson hypothesis, which argues that the futures price volatility increases as the futures contract approaches its expiration. Utilizing intraday data from 20 futures markets in six futures exchanges, we find strong support for the Samuelson hypothesis in agricultural futures. However, the Samuelson hypothesis does not hold for other futures contracts. We also provide supporting evidence that the ‘negative covariance’ hypothesis is the key factor for the empirical support of the Samuelson hypothesis. In addition, our findings remain largely unaltered even after we control for seasonality and liquidity effects.     

Forecasting Intraday Volatility and Value-at-Risk with High-Frequency Data

In this paper, we develop modeling tools to forecast Value-at-Risk and volatility with investment horizons of less than one day. We quantify the market risk based on the study at a 30-min time horizon using modified GARCH models. The evaluation of intraday market risk can be useful to market participants (day traders and market makers) involved in frequent trading. As expected, the volatility features a significant intraday seasonality, which motivates us to include the intraday seasonal indexes in the GARCH models. We also incorporate realized variance (RV) and time-varying degrees of freedom in the GARCH models to capture more intraday information on the volatile market. The intrinsic tail risk index is introduced to assist with understanding the inherent risk level in each trading time interval. The proposed models are evaluated based on their forecasting performance of one-period-ahead volatility and Intraday Value-at-Risk (IVaR) with application to the 30 constituent stocks. We find that models with seasonal indexes generally outperform those without; RV can improve the out-of-sample forecasts of IVaR; student GARCH models with time-varying degrees of freedom perform best at 0.5 and 1 % IVaR, while normal GARCH models excel for 2.5 and 5 % IVaR. The results show that RV and seasonal indexes are useful to forecasting intraday volatility and Intraday VaR.     

RECENT GROWTH IN NASDAQ TRADING VOLUME AND ITS RELATION TO MARKET VOLATILITY

We document a significant increase in Nasdaq trading volume relative to New York Stock Exchange (NYSE) and American Stock Exchange (AMEX) trading volumes. Although recent increases in the number of shares traded are reported in the financial press, we also find it present in the percentage of dollar values traded. We then examine correlations between trading volume and several measures of market volatility. Nasdaq volume appears to be more closely correlated with residual variance, while NYSE and AMEX volumes are more closely correlated with overall market variance. We conclude that the type and quantity of information driving trading are different on Nasdaq than on the two exchanges, and that the relative growth in Nasdaq volume cannot be attributed solely to differences in the methods of counting volume in the two market environments.