Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets

This study investigates intraday relations between price changes and trading volume of options and stocks for a sample of firms whose options traded on the CBOE during the first quarter of 1986. After purging the price change series of the effects of bid/ask spreads, multivariate time-series analysis is used to estimate the lead/lag relation between the price changes in the option and stock markets. The results indicate that price changes in the stock market lead the option market by as much as fifteen minutes. The analysis of trading volume indicates that the stock market lead may be even longer.     

Effect of the ban on short selling on market prices and volatility

We examine the effects of the short‐selling ban, imposed by Australian regulators in the wake of the global financial crisis, on the trading of financial stocks. Our findings argue against commonly stated reasons for imposing short‐sale bans. We find no evidence that short‐sale restrictions provide support for stock prices or that they reduce volatility. Moreover, stocks subject to the short‐selling ban suffered a severe degradation in market quality. Controlling for the adverse effects of the financial crisis on markets, we show that short‐selling restrictions increase intraday volatility, reduce trading activity and increase bid–ask spreads.     

Intraday futures market behaviour around major scheduled macroeconomic announcements: Australian evidence

This paper examines intraday futures market behaviour around major scheduled macroeconomic information announcements on the Sydney Futures Exchange (SFE). Prior literature analysing intraday price behaviour around announcements is extended to trading volume and quoted bid–ask spreads. The analysis of price volatility, trading volume and quoted bid–ask spreads indicates that the majority of adjustment to new information occurs rapidly, within 240 seconds of the scheduled time for major announcements, with some evidence of abnormal activity prior to announcements. Analysis of quoted bid–ask spreads suggests that they significantly widen in the 20 seconds prior to announcements and remain significantly wider for 30 seconds following announcements. The increase in quoted spreads is related to both expected and unexpected volatility, implying that market participants increase quoted spreads around information announcements as a consequence of adverse selection costs.     

A new methodology for studying intraday dynamics of Nikkei index futures using Markov chains

The empirical study of intraday patterns of stock trading volatilities and bid–ask spreads in the literature depends on assumptions of specific price generating process and may therefore not be robust to distributional assumptions. By creating discrete states that conform more naturally to the way prices are actually quoted in the derivatives and assets markets, we employ a new methodology of Markov chains for studying the intraday dynamics of derivative prices. We apply the method to study the intraday behavior of the Nikkei index futures prices, trading volumes, and spreads. We find some interesting results such as higher probabilities of transitions between larger volatilities at the opening and closing times. The volatility at lunch break is strikingly low. Contrary to most of the literature, the Nikkei intraday bid–ask spread does not show a U-shaped pattern. We offer some explanations.     

Does Trading Volume Contain Information to Predict Stock Returns? Evidence from China's Stock Markets

This paper examines empirical contemporaneous and causal relationships between trading volume, stock returns and return volatility in China's four stock exchanges and across these markets. We find that trading volume does not Granger-cause stock market returns on each of the markets. As for the cross-market causal relationship in China's stock markets, there is evidence of a feedback relationship in returns between Shanghai A and Shenzhen B stocks, and between Shanghai B and Shenzhen B stocks. Shanghai B return helps predict the return of Shenzhen A stocks. Shanghai A volume Granger-causes return of Shenzhen B. Shenzhen B volume helps predict the return of Shanghai B stocks. This paper also investigates the causal relationship among these three variables between China's stock markets and the US stock market and between China and Hong Kong. We find that US return helps predict returns of Shanghai A and Shanghai B stocks. US and Hong Kong volumes do not Granger-cause either return or volatility in China's stock markets. In short, information contained in returns, volatility, and volume from financial markets in the US and Hong Kong has very weak predictive power for Chinese financial market variables.     

The impact of tick size on intraday stock price behavior: evidence from the Taiwan Stock Exchange

This research examines the impact of tick size on intraday stock price behavior for stocks listed on the Taiwan Stock Exchange over the 2-year period of 1998–1999. The sample involves the same 80 firms that trade under the tick size of (New Taiwan Dollars) NT$0.1 and NT$0.5, respectively. The sample firms display a U-shaped intraday pattern of bid–ask spread, volatility, autocorrelation, and trading volume. The empirical results indicate that a larger tick size is associated with a wider bid–ask spread, larger volatility, and more negative autocorrelation. Moreover, a larger tick size is associated with a higher percentage increase of bid–ask spread and volatility in the middle of the trading period. Finally, the effect of tick size on trading volume is insignificant.     

The relationship between bid–ask spreads and holding periods: The case of Chinese A and B shares

The Chinese stock markets for A (domestic) shares and B (foreign) shares were completely separated. This study examines the relationship between spreads and holding periods across these segmented markets on the same set of firms. Our major findings are as follows. (1) There is a positive relationship between holding periods and bid–ask spreads in the Chinese stock market. (2) Investors' sensitivity toward liquidity is approximately the same in the A and B share markets, even though bid–ask spreads are substantially different across the two markets. These results provide strong support for the theoretical argument of Amihud and Mendelson [Amihud, Y., & Mendelson, H. (1986). Asset pricing and the bid–ask spread. Journal of Financial Economics, 17, 223–249.] that stocks with higher spreads tend to be held by long-term investors. Evidence also suggests that liquidity has a role in explaining the B share discount, although the results are less than conclusive.     

Informed trading in the options market surrounding data breaches

This study investigated whether there is informed trading that takes advantage of data breach events. By analyzing the transactions in the options market, we conjectured that there are two distinct informed trading patterns: one that begins approximately 4 months prior and another that begins 8–12 months before the corporate data breach announcements. This is supported by evidence of higher trading volume and open interest for put options, a higher put-to-call volume ratio, a higher put-to-call open interest ratio, and lower spreads prior to such announcements. We also examined the stock reactions following data breach announcements and found significantly negative cumulative abnormal returns of −0.35% within one day. Moreover, a cross-sectional analysis showed that put-call ratios have predictive power for stock returns. Finally, additional evidence, such as trading strategies in the stock and options markets, is provided.     

The relationship between bid–ask spreads and holding periods: The case of Chinese A and B shares

The Chinese stock markets for A (domestic) shares and B (foreign) shares were completely separated. This study examines the relationship between spreads and holding periods across these segmented markets on the same set of firms. Our major findings are as follows. (1) There is a positive relationship between holding periods and bid–ask spreads in the Chinese stock market. (2) Investors' sensitivity toward liquidity is approximately the same in the A and B share markets, even though bid–ask spreads are substantially different across the two markets. These results provide strong support for the theoretical argument of Amihud and Mendelson [Amihud, Y., & Mendelson, H. (1986). Asset pricing and the bid–ask spread. Journal of Financial Economics, 17, 223–249.] that stocks with higher spreads tend to be held by long-term investors. Evidence also suggests that liquidity has a role in explaining the B share discount, although the results are less than conclusive.     

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.     

Disruption and stock markets: Evidence from Hong Kong

We examine the impact of disruption on stock markets using the 2019 Hong Kong protests for identification. We find that greater protest intensity corresponds to higher bid–ask spreads, lower trading volume, and greater return volatility for dual-listed Chinese firms’ Hong Kong (H) shares but not their home (A) shares. We also document negative abnormal returns only for these firms’ H-shares around major protest events, which shortly after exhibit reversal. Next, we validate our main findings by documenting similar results using Hong Kong-listed firms only. Overall, we provide new evidence highlighting the impact of protest-induced disruption on financial markets.     

Weather and intraday patterns in stock returns and trading activity

We examine the relation between weather in New York City and intraday returns and trading patterns of NYSE stocks. While stock returns are found to be generally lower on cloudier days, cloud cover has a significant influence on stock returns only at the market open. There are significantly more seller-initiated trades when there is more cloud cover at the market open, which is consistent with the return results. Cloudy skies are associated with higher volatility and less market depth over the entire trading day. Finally, cloud cover is not significantly correlated with spread measures and turnover ratios. The findings overall suggest that weather has a significant influence on investors’ intraday trading behavior.     

Relative performance of bid–ask spread estimators: Futures market evidence

The issue of transaction costs is the mainstay of the equity market microstructure. Research in the microstructure of futures markets has lagged behind. A primary reason is that futures exchanges in the U.S. do not record bid–ask quotes, requiring these costs to be imputed from transaction price data. A reliable estimator of bid–ask spreads would significantly enhance microstructure research in futures markets. Unique intraday data from the Sydney Futures Exchange (SFE) that include both transaction prices and bid–ask spreads allow us to compare bid–ask spread estimation techniques proposed in the literature against the benchmark of actual spreads in a futures market, and thus identify the best-performing estimator. To maximize relevance, we impose all the constraints that apply in U.S. futures data to perform our estimations. We find that the four bid–ask spread estimators considered significantly underestimate the actual spreads. However, simple moments-based estimators perform better in predicting spreads.     

The liquidity effects associated with addition of a stock to the S&P 500 index: evidence from bid/ask spreads

This study examines changes in stock liquidity, as measured by the bid/ask spread, when a stock is added to the S&P 500 Index. The paper presents evidence of a significant decrease in the bid/ask spread upon S&P 500 addition, however, this effect is limited to only those stocks that were not trading listed options. Further, the decrease in the bid/ask spread for nonoptioned stocks is accompanied by a significant and permanent increase in share price and trading volume. While optioned stocks experience a permanent increase in trading volume, they experience only a temporary increase in share price. The findings for optioned stocks support the hypothesis that the price and volume effects associated with S&P 500 addition derive from temporary price pressure. Findings pertaining to the nonoptioned stocks indicate that the price and volume effects associated with S&P addition reflect enhanced stock liquidity. The decrease in the bid/ask spread for nonoptioned stocks is attributed to informational efficiencies achieved via index arbitrage trading, and it is argued that this effect is mitigated for optioned stocks due to the pre-existence of arbitrage trading between the option and the underlying stock.     

Market reaction to takeover rumour in Internet Discussion Sites

We examine the market reaction to takeover rumour postings in the Hotcopper Internet Discussion Site (IDS). Results from the interday analysis show abnormal returns and trading volumes on the day before and the day of the posting. Results of the intraday analysis show abnormal returns and trading volumes during the 10 min posting interval and abnormal trading volume during the 10 min interval immediately preceding it. Sensitivity analyses indicate that the results are robust to concerns regarding potential confounds, credibility and bid–ask spread bias. Taken together, these findings are consistent with the market reacting to the posting of takeover rumours in IDS.     

Do aggressive orders affect liquidity? An evidence from an emerging market

This paper investigates how aggressive orders affect spreads and trading activity measures on the stock market. Based on a sample of stocks listed on the Warsaw Stock Exchange this study finds that spreads and trading activity measures increase significantly when aggressive orders are executed, but quickly revert to initial levels. The reaction to these orders on the bid and ask side of the market is similar. The effect of aggressive orders differ depending on the size of the firms. Trading activity measures such as volumes or number of transactions increase stronger for bigger than for smaller stocks, while spreads increase more for smaller firms than for bigger ones. These findings enrich the understanding of liquidity dynamics especially on the emerging markets where liquidity is an important price formation factor.     

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.     

Microstructure and reverse stock splits

In this paper we show that, similar to NYSE/AMEX stocks, NASDAQ stocks exhibit significant ex date returns for reverse stock splits. Although the 10-day cumulative return after the ex date is close to –10%, this does not violate market efficiency, because the average bid-ask spread for the reverse split stock is at least double this return. We also document that these large negative returns are mostly due to a drop in the ask price while bid prices barely change at all. Furthermore, the ex date returns are negatively related to trading volume.These results suggest that there is abnormal selling and a significant buildup of market makers' inventories near the ex date. To reduce the inventory buildup, market makers lower ask prices to induce buying by investors, resulting in the observed negative returns. Lowering bid prices, an alternative strategy for reducing inventories, is not attractive to market makers due to competitive factors and the reduction of commissions associated with a smaller number of transactions. Notably, selling investors have no incentives to sell their stocks early to avoid the observed negative ex date return, since this return is largely an ask price phenomenon and does not represent realized returns to sellers.     

Intraday Patterns in the Cross‐section of Stock Returns

Motivated by the literature on investment flows and optimal trading, we examine intraday predictability in the cross‐section of stock returns. We find a striking pattern of return continuation at half‐hour intervals that are exact multiples of a trading day, and this effect lasts for at least 40 trading days. Volume, order imbalance, volatility, and bid‐ask spreads exhibit similar patterns, but do not explain the return patterns. We also show that short‐term return reversal is driven by temporary liquidity imbalances lasting less than an hour and bid‐ask bounce. Timing trades can reduce execution costs by the equivalent of the effective spread.     

Adverse selection and the presence of informed trading

We combine two concepts of informed trading – contrarian trades and stealth trading – to develop proxies for the probability of informed trading. These proxies are used to test the link between informed trading and adverse selection as measured by bid–ask spreads and stock illiquidity. The estimation results show that these proxies, which are based on the probability of contrarian trading (PC) and progressively refined thereon, are all highly significantly positive in various empirical specifications of the cross-sectional determinants of spreads and illiquidity across stocks, and after controlling for important firm characteristics and trading factors. The robustness of our PC-based proxies for informed trading in these analyses, especially for the further refined measures, suggests that they successfully capture the adverse selection component of bid–ask spreads and illiquidity due to information asymmetry.