The interaction between opening call auctions and ongoing trade: Evidence from the NYSE

We investigate the impact that the opening batch has on trading for the remainder of the day and what impact the prior day's trading has on the subsequent day's open. Traders have an interest in these trading impacts as their trades may cluster around opening and closing time periods. We find that the larger the volume in the opening batches, the greater the volume across the day. We also find the prior day's volume being positively related to the subsequent day's opening volume. Combined, these results suggest a continuing pattern of trade volume rolling from one day to the next. Additionally, we find that the spread in the continuous market can be partially attributed to the price change in the opening batch. We also find evidence of opening trade price reversals. Combined with the absence of price reversals following the opening trade, we conclude that the opening process may be more efficient at handling information than the continuous market.     

The price discovery of day trading activities in futures market

Access to information is necessary for market transparency. However, contrary to trading volume and open interest, information related to day trading activities is rarely available. By incorporating unexplored day trading volume in the literature, this paper demonstrates that both the expected open interest and expected day trading volume are consistently and positively correlated with returns, but that one-lagged day trading volume is negatively correlated with futures returns. Meanwhile, both expected and unexpected day trading volume are negatively correlated with volatility, suggesting that arbitrage activities related to unexpected day trading volume may accelerate the movement of futures prices to a new equilibrium. Moreover, open interest provides liquidity but increases volatility. Finally, we strongly suggest that day trading transaction information be released by futures exchanges to achieve greater transparency.     

The Influence of Information Arrival on Market Microstructure: Evidence from Three Related Markets

This study examines the influence of information arrival on market microstructure for the MMI, NYSE, and S&P 500 stock index futures markets, with special emphasis on the effects of opening and closing of trading and expiration of contracts on price movements and trading activities. The results of the examination show that although the opening of the (MMI) futures market is associated with higher volatility, it is when the spot market opens that volatility reaches its highest level. Similarly, the closing of the futures markets, though more volatile, is not as volatile as the closing of the spot markets. Trading patterns, on the other hand, are distinct from volatility. For MMI, trading declines consistently after the close of the spot market. In contrast, the NYSE and S&P 500 continue to trade and reach a peak at the close of the futures markets. Expiration effects are evidenced by the increase in volatility and trading near the closing of the MMI and the spillover to the NYSE and S&P 500. In sharp contrast, the expirations of the NYSE and S&P 500 are only assooiated with decrease in trading, suggesting that efforts to dampen volatility by changing expiration days from Friday to Thursday and shifting settlement price from Friday close to Friday open, have been successful.     

Specialist participation and limit orders

We present a market microstructure model to examine specialist's strategic participation decisions in a security market where there are noise traders, limit order traders, an insider and a specialist. We argue that the specialist's participation rate depends on the depth of the limit book and its uncertainty. In particular, the specialist has incentives to trade against the market trend when the limit book depth is low and to trade with the market trend when the depth is high. Moreover, the specialist's participation rate is positively related to the limit book depth uncertainty and the asset price volatility, but is negative related to the average trading volume. We also discuss the specialist's participation strategies under the NYSE regulation that prohibits the specialist from trading with the market trend.     

Trading Behavior and the Unbiasedness of the Market Reaction to Dividend Announcements

This article examines the price formation process during dividend announcement day, using daily closing prices and transactions data. We find that the unconditional positive excess returns, first documented by Kalay and Loewenstein (1985) , are higher for small-firm and low-priced stocks. Price volatility and trading volume also increase during this period. Examination of trade prices relative to the bid-ask spread and volume of trades at bid and asked prices shows that the excess returns cannot be attributed to measurement errors or to spillover effects of tax-related ex-day trading. Rather, the price behavior is related to the absorption of dividend information.     

THE EMPIRICAL RELATIONSHIP BETWEEN TRADING VOLUME,RETURNS AND VOLATILITY

This paper presents an empirical analysis of the relationship between trading volume, returns and volatility in the Australian stock market. The initial analysis centres upon the volume-price change relationship. The relationship between trading volume and returns, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market. This finding also provides basic support for a positive relationship between trading volume and volatility. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for non-negative returns, thereby supporting an asymmetric relationship which is hypothesised to exist because of differential costs of taking long and short positions. Analysis at the individual stock level shows weaker support for the relationship. A second related hypothesis is tested in which the formation of returns is conditional upon information arrival which similarly affects trading volume. The hypothesis is tested by using the US overnight return to proxy for expected “news” and trading volume to proxy for news arrival during the day. The results show a reduction in the significance and magnitude of persistence in volatility and hence are consistent with explaining non-normality in returns (and ARCH effects) through the rate of arrival of information. The findings in this paper help explain how returns are generated and have implications for inferring return behaviour from trading volume data.     

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.     

Volatility and trading activity following changes in the size of futures contracts

This paper has two purposes. First, we examine the relationship between daily price volatility and trading activity one year before and after a change in contract size by examining the results of contract splits in the Australian share price index futures and the U.K. FTSE-100 futures contracts and a reverse contract split in the Australian Bank Bill Acceptance futures contract. Second, we evaluate the effect of the change in contract size on the use of the particular futures market. We find that after a contract size change, the change in total trading frequency has the power to explain the change in daily price volatility. Specifically, after a contract split, trading frequency increased, resulting in increased daily price volatility, and vice versa after a reverse contract split. Most of the average trade size variable has an immaterial impact on price volatility. However, decomposing the total trading frequency into four trade size classes, we find that the trading frequency for small and large trade size categories are highly significant in explaining changes in daily price volatility after the contract splits. Finally, we find the change in contract size for each futures market was successful because within three years following the change, the adjusted trading volume and open interest surpassed the levels prior to the change and have continued to increase thereafter.     

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.     

Explaining Intraday Pattern of Trading Volume from the Order Flow Data

Based on a comprehensive order flow data from the Taiwan stock market, this study examines directly how the intraday pattern of trading volume is related to the trading behavior of both informed and uninformed traders. The results indicate that both informed and uninformed investors have a strong desire to place orders at the market open and the close. Most of the orders at the market open are conservative and hence are waiting orders for price priority. The findings show that intraday trading volume as well as the real orders from both types of investors are J-shaped. In addition, both information and liquidity trading can explain the intraday pattern of trading volume. However, the impact of liquidity trading on volume is slightly higher than that of information trading.     

Information demand and stock market volatility

We study information demand and supply at the firm and market level using data for 30 of the largest stocks traded on NYSE and NASDAQ. Demand is approximated in a novel manner from weekly internet search volume time series drawn from the recently released Google Trends database. Our paper makes contributions in four main directions. First, although information demand and supply tend to be positively correlated, their dynamic interactions do not allow conclusive inferences about the information discovery process. Second, demand for information at the market level is significantly positively related to historical and implied measures of volatility and to trading volume, even after controlling for market return and information supply. Third, information demand increases significantly during periods of higher returns. Fourth, analysis of the expected variance risk premium confirms for the first time empirically the hypothesis that investors demand more information as their level of risk aversion increases.     

Individualism and Momentum around the World

This paper examines how cultural differences influence the returns of momentum strategies. Cross-country cultural differences are measured with an individualism index developed by Hofstede (2001) , which is related to overconfidence and self-attribution bias. We find that individualism is positively associated with trading volume and volatility, as well as to the magnitude of momentum profits. Momentum profits are also positively related to analyst forecast dispersion, transaction costs, and the familiarity of the market to foreigners, and negatively related to firm size and volatility. However, the addition of these and other variables does not dampen the relation between individualism and momentum profits.     

Gone fishin’: Seasonality in trading activity and asset prices

We use seasonality in stock trading activity associated with summer vacation as a source of exogenous variation to study the relationship between trading volume and expected return. Using data from 51 stock markets, we first confirm a widely held belief that stock turnover is significantly lower during the summer because market participants are on vacation. Interestingly, we find that mean stock return is also lower during the summer for countries with significant declines in trading activity. This relationship is not due to time-varying volatility. Moreover, both large and small investors trade less and the price of trading (bid-ask spread) is higher during the summer. These findings suggest that heterogeneous agent models are essential for a complete understanding of asset prices.     

Does proprietary day trading provide liquidity at a cost to investors?

Capitalizing on the special case of Malaysia in which proprietary day traders (PDTs) are mandated to boost liquidity and the recent availability of trading data, this paper empirically examines the liquidity effect of proprietary day trading. Using daily data spanning October 2012 to June 2018, we find evidence that PDTs' trade volume is associated with higher aggregate liquidity in the Malaysian stock market, which can be attributed to the theoretical channel of intense competition among informed traders. However, such improved liquidity comes at a cost to investors, as proprietary day trading is found to be associated with higher conditional volatility and conditional skewness of closing percent quoted spreads. The former is due to the exchange-imposed immediacy for PDTs to close their open positions, whereas the latter can be attributed to the exclusive rights granted to PDTs to engage in intraday short selling.     

When noise trading fades,volatility rises

We hypothesize and test an inverse relation between liquidity and price volatility derived from microstructure theory. Two important facets of liquidity trading are examined: volume and noisiness. As represented by the expected turnover rate (volume) and realized average commission cost per share (noisiness) of NYSE equity trading, both facets are found negatively associated with the ex post and ex ante return volatilities of the NYSE stock portfolios and the NYSE composite index futures. Furthermore, the inverse association between noisiness and volatility is amplified in times of market crisis. The negative noisiness–volatility relation is also supported by our analysis on the effects of trade size on price volatility. The overall results demonstrate that volatility increases as noise trading declines.     

Overconfidence among option traders

The investor overconfidence theory predicts a direct relationship between market‐wide turnover and lagged market return. However, previous research has examined this prediction in the equity market, we focus on trading in the options market. Controlling for stock market cross‐sectional volatility, stock idiosyncratic risk, and option market volatility, we find that option trading turnover is positively related to past stock market return. In addition, call option turnover and call to put ratio are also positively associated with the past stock market return. These findings are consistent with the overconfidence theory. We also find that overconfident investors trade more in the options market than in the equity market. We rule out explanations other than investor overconfidence, such as momentum trading and varying risk preferences, for our findings.     

Trading frequency and the efficiency of price discovery in a non-dealer market

The increasing popularity of non-dealer security markets that offer automated, computer-based, continuous trading reflects a presumption that institutionally-set trading sessions are economically obsolete. This theoretical paper investigates the effect of the trading frequency, a key feature of the trading mechanism, on the efficiency of price discovery in a non-dealer market. By tracing the market pricing error to the correlation structures of arriving information and pricing errors of individual traders, the effect of diverging expectations on error-based and overall return volatility is isolated. The analysis reveals that, due to a portfolio effect, an increase in the trading time interval has contradictory effects on the portion of return volatility stemming from pricing errors. The greater accumulation of information increases error-based return volatility, but the greater volume and number of traders per session have the opposite effect. The net effect on overall return volatility can go either way. It is found that the return volatility of heavily traded securities is likely to be minimized under continuous trading, but that of thinly traded securities may be minimized under discrete trading at moderate time intervals. The latter is more likely to occur the greater is the divergence of expectations among traders. These findings challenge the presumption that automated continuous trading in a non-dealer market is more efficient than discrete trading for all securities, regardless of trading volume. The findings are applicable to all economies, but have special importance for developing countries where typically a single market is dominated by small issues and a low volume of trade. As a by-product of the analysis, it is shown how to correct the biased estimate of inter-session price volatility when observations are less frequent than the trading sessions themselves.     

The impacts of futures trading on volatility and volatility asymmetry of Bitcoin returns

The impact of Bitcoin futures introduction on the underlying Bitcoin volatility has been a controversial topic. Conflicting results had been obtained from different sample periods and methodologies. To address this debate, this study examines the impact of futures trading on volatility and volatility asymmetry of Bitcoin returns in the short and long run. Using exponential GARCH models, we introduce a dummy in the variance equation to capture the changes in the volatility after the introduction of Bitcoin futures. We find that after the introduction, spot return volatility decreases in the short run, but increases in the long run. Besides, in the short run, there exists an inverse leverage effect before and after the introduction; in the long run, the inverse leverage effect before the introduction changes to a usual level effect after the introduction. Finally, we examine whether greater futures trading activity, proxied by trading volume and open interest, is associated with greater Bitcoin volatility. To do so, we decompose each proxy into expected and unexpected components and document that, in the long run, Bitcoin volatility covaries positively with unexpected futures trading volume, but negatively with unexpected futures open interest.     

Dual long-memory, structural breaks and the link between turnover and the range-based volatility

This paper investigates the issue of temporal ordering of the range-based volatility and turnover volume in the Korean market for the period 1995–2005. We examine the dynamics of the two variables and their respective uncertainties using a bivariate dual long-memory model. We distinguish volume trading before the Asia financial crisis from trading after the crisis. We find that the apparent long-memory in the variables is quite resistant to the presence of breaks. However, when we take into account structural breaks the order of integration of the conditional variance series decreases considerably. Moreover, the impact of foreign volume on volatility is negative in the pre-crisis period but turns to positive after the crisis. This result is consistent with the view that foreign purchases tend to lower volatility in emerging markets—especially in the first few years after market liberalization when foreigners are buying into local markets—whereas foreign sales increase volatility. Before the crisis there is no causal effect for domestic volume on volatility whereas in the post-crisis period total and domestic volumes affect volatility positively. The former result is in line with the theoretical underpinnings that predict that trading within domestic investor groups does not affect volatility. The latter result is consistent with the theoretical argument that the positive relation between the two variables is driven by the uninformed general public.     

A call auction's impact on price formation and order routing: Evidence from the NASDAQ stock market

Electronic call auctions are used globally to open and close equity market trading; as such, they are a critically important facility that needs to be better understood. The paper focuses on the impact NASDAQ's calls (introduced in 2004) have had on bid-ask spreads, price volatility, and order routing in the continuous market that follows daily openings and which precedes daily closings. NASDAQ's closing call has significantly reduced both spreads and volatility for all market capitalization groups. Its opening call similarly reduced spreads, while a generally similar, though somewhat weaker, pattern of volatility reduction was realized. Although the pattern of trading volume has, for the most part, not been significantly affected, our findings, comprehensively viewed, suggest that the calls have had a positive spillover effect on the dynamic behavior of price formation in NASDAQ's continuous market.