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.     

Intraday Variation in the Bid-Ask Spread: Evidence after the Market Reform

In this article we show that intraday variation in spreads for Nasdaq‐listed stocks has converged to intraday variation in spreads for NYSE‐listed stocks after the implementation of the new order‐handling rules. We attribute this convergence to the Limit Order Display Rule, which requires that limit orders be displayed in Nasdaq best bid and offer when they are better than quotes posted by market makers. Our findings suggest that the different patterns of intraday spreads between NYSE and Nasdaq stocks reported in prior studies can largely be attributed to the different treatment of limit orders between the NYSE and Nasdaq before the market reform.     

Does vega-neutral options trading contain information?

This study suggests a novel approach for decomposing net options demands into the options order imbalances with and without volatility risk. By analyzing a high-frequency index futures and options dataset, we examine the information content of (i) the direction-motivated order imbalance induced by a single option type, which is exposed to volatility risk, and (ii) that constructed by both calls and puts, which is vega-neutral. The aggregate options order imbalance does not convey information after controlling for futures market trading. However, the intraday options order imbalance by trading without volatility risk significantly predicts spot index returns, though its longer-horizon forecasting ability is relatively weak because of a possible cross-market hedging effect. The predictive abilities of informed foreigners’ trades and out-of-the-money options trading are prominent. Our empirical results suggest that the vega-neutral options trading conveys additional information distinct from the futures order imbalance.     

WHO ARE THE NOISE TRADERS?

Closed‐end funds often trade at a discount to net asset value. Previous research suggests that the positive correlation in discounts is associated with investor sentiment that causes systematic mispricing by noise traders. We use a newly available sample of daily fund valuations to examine the relation between intraday trading activity and discount changes. Contrary to the assumption that retail investors are noise traders, we find no relation between discount changes and the order‐flow imbalances of individual investors. Large daily discount changes are associated with institutional trading, and this may reflect the price inelasticity of closed‐end fund shares.     

Trading profitability from learning and adaptation on the Tokyo Stock Exchange

This study proposes unexamined technical trading rules, which are dynamically switching strategies among filter, moving average and trading-range breakout rules. The dynamically switching strategy is formulated based on a discrete choice theory consistent with the concept of myopic utility maximization. We utilize the transaction data of the individual stocks listed on the Nikkei 225 from September 1, 2005 to August 31, 2007. We demonstrate that switching strategies produce positive returns and their performance is better than those from the buy-and-hold and non-switching strategies over our sample periods. We also demonstrate equivalent performance for switching with different learning horizons, implying that behavioural heterogeneity of stock investors arises from the coexistence of different strategies with varying degrees of learning horizons. Our result supports several research assumptions and results on agent-based theoretical models that successfully replicate empirical features in financial markets, such as fat tails of return distributions and volatility clustering. However, upon considering the effects of data-snooping bias superior performance disappears.     

Intraday volume and volatility relations with and without public news

This paper reexamines the dynamic relation between intraday trading volume and return volatility of large and small NYSE stocks in two partitioned samples, with and without identifiable public news. We argue that the sequential information arrival hypothesis (SIAH) can be tested only in periods containing public news. After partitioning the sample into periods with and without public news, we find bi-directional Granger-causality between volume and volatility in the presence of public information as hypothesized by the SIAH. Our analysis further suggests that return volatility is higher in the periods with public news, while trading volume is significantly higher in the no-news period; perhaps owing to the importance of private information for trading stocks. Using the sample without public news, we find evidence that volume Granger-causes volatility without feedback. These results are broadly consistent with behavioral models like the overconfidence and biased self-attribution model of [Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and over-reactions. Journal of Finance 53, 1839–1885]. It appears that overconfident investors overrate the precision of their private news signals and therefore trade too aggressively in the absence of public news; when public news arrives, investors’ biased self-attribution triggers excessive return volatility.     

The intraday impact of company responses to exchange queries

This study investigates Australia’s unique continuous disclosure regime using intraday data on the Australian Securities Exchange (ASX) over the period January 2010–April 2012. We examine abnormal returns and trading volumes that accrue to shareholders immediately after an announcement responding to a trading induced query. The use of intraday data permits us to examine the direct impact of these events, and the length of time the market takes to incorporate this information with a higher degree of precision than the research currently on offer. The study is framed within an event study methodology, with a number of robustness measures: a matched sample approach; analysis of cross-sectional determinants; the removal of penny stocks; and, procedures to account for sample selection bias. We find significant share price reversals following a query announcement, with a reversal of 3.3% by the end of the widest event interval. Our study also provides evidence that the market takes up to 60 min to impound this information. Overall, we provide support for the efficacy of the query framework administered by the ASX.     

Technical analysis: An asset allocation perspective on the use of moving averages

In this paper, we analyze the usefulness of technical analysis, specifically the widely employed moving average trading rule from an asset allocation perspective. We show that, when stock returns are predictable, technical analysis adds value to commonly used allocation rules that invest fixed proportions of wealth in stocks. When uncertainty exists about predictability, which is likely in practice, the fixed allocation rules combined with technical analysis can outperform the prior-dependent optimal learning rule when the prior is not too informative. Moreover, the technical trading rules are robust to model specification, and they tend to substantially outperform the model-based optimal trading strategies when the model governing the stock price is uncertain.     

Trading imbalances,predictable reversals,and cross-stock price pressure

We test the implications of a multi-asset equilibrium model in which a finite number of risk-averse liquidity providers accommodate non-informational trading imbalances. These imbalances generate predictable reversals in stock returns. An imbalance in one stock also affects the prices of other stocks. The magnitude of the cross-stock price pressure depends on the correlations of the stocks’ underlying cash flows. The model implies that non-informational trading increases the volatility of stock returns. We confirm the model's implications using data from the Taiwan Stock Exchange.     

交易限制与股票市场定价效率——基于创业板涨跌幅限制放宽的准自然实验研究

本文基于2020年8月24日创业板涨跌幅限制由10%扩大到20%这一政策变化建立准自然实验,从市场层面与公司事件层面探讨交易限制放宽的外生冲击下市场定价效率的变化。研究发现,涨跌幅限制放宽政策实施后,股票价格能更灵敏地反映公开市场信息,更多地包含公司层面特质信息,整体市场定价效率显著提升。进一步研究表明,涨跌幅限制放宽有效缓解了交易干扰问题,避免了过度交易行为延后,缓解了波动性外溢与价格发现延迟。异质性分析表明,无论是市场层面定价效率改善,还是事件层面波动性外溢、价格发现推迟与交易干扰问题的缓解,均在低信息透明度公司中更为显著。本文研究发现为验证涨跌幅限制会抑制股票市场定价效率的理论提供了直接经验证据,同时为推广完善市场化交易制度提供了有益启示。     

INSTITUTIONAL TRADING AND OPENING PRICE BEHAVIOR: EVIDENCE FROM A FAST‐EMERGING MARKET

Using daily and intraday data, we investigate the cross‐sectional relation between stock prices and institutional trading in the Taiwan stock market. Consistent with the investigative herding hypothesis, we find that institutional herding exists because of institutional positive feedback trading behavior rather than following trades made by other institutions, as suggested by the information cascade hypothesis. Moreover, the positive correlation between institutional trade imbalance and stock returns mainly comes from institutional positive feedback trading. The institutional trading decisions rely on returns measured not only over the lagged trading day but also over the opening session during the same day.     

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book (LOB) markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in LOBs based on a recent sample of 30 German Deutscher Aktienindex (DAX) stocks. We find that Hasbrouck's (1991) measure of trade informativeness Granger causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news-induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis, we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity.     

The BOJ's ETF purchases and its effects on Nikkei 225 stocks

This paper examines the impacts of the Bank of Japan's (BOJ) exchange-traded funds (ETFs) purchasing program that has been conducted since December 2010. The program is a part of the BOJ's unconventional monetary policy and has accelerated since the introduction of the Quantitative and Qualitative Easing in April 2013. In this study, the influence of underlying stocks is assessed by comparing the performance of the stocks (those included in the Nikkei 225 and others) using a difference-in-difference analysis. We also separate morning and afternoon returns to control for the fact that the BOJ tends to purchase ETFs when performance of the stock market is weak in the morning session. We find that the Nikkei 225 component stocks' afternoon returns are significantly higher than those of non-Nikkei 225 stocks when the BOJ purchases ETFs. In addition, the subsample analysis demonstrates that the impact on Nikkei 225 stock returns becomes smaller over time despite the growing purchase amounts. Overall, our results indicate that the cumulative treatment effects on the Nikkei 225 are around 20% as of October 2017.     

Do Analyst Stock Recommendations Piggyback on Recent Corporate News? An Analysis of Regular‐Hour and After‐Hours Revisions

Analysts often update their recommendations following corporate news. Questions have been raised regarding analysts’ ability to generate new information beyond recent corporate events. Employing a comprehensive database on corporate news, we show that only a small minority, or 27.9%, of all recommendation revisions directionally confirm the information in the preceding corporate events and even these “confirming revisions” facilitate the information discovery of corporate events and thus cannot simply be dismissed as “piggybacking.” Our analysis further shows that analysts not only facilitate price discovery to corporate news through issuing trending revisions but also help reverse prevailing market sentiments following corporate news by issuing contrarian revisions. Our study is the first to investigate short‐window intraday market reactions to revisions issued after hours, which account for 70% of all recommendation revisions in our sample period. Analysts’ incentives to issue revisions after hours appear to reflect demands from large institutional clients, who dominate after‐hours trading. More importantly, we show that the after‐hours revisions are associated with significantly greater price reactions and different price reaction patterns than revisions issued during regular trading hours. Collectively, our evidence indicates that analysts are a significant source of new information beyond recent corporate news and they also help shape the market's assessment of corporate disclosures.     

An Empirical Analysis of Quoted Depths of NYSE and Amex Stocks

In this study, we find strong intertemporal/cross-sectional correlations between quoted depths and various security characteristics for a sample of stocks listed on the NYSE and Amex. Our empirical results indicate that although specialists are generally unable to discern insider trading as it occurs, they cope with insider trading by posting smaller depths for stocks with a greater tendency of insider trading. Empirical evidence also indicates that specialists/limit order traders quote smaller depths for riskier stocks to limit potential losses to better-informed traders. In addition, we find that specialists/limit order traders quote larger depths for stocks with greater trading volume, larger market capitalization, and higher competition. Overall, our findings suggest that depths are an important means through which specialists and limit order traders deal with the adverse selection problem, order processing problem, and competition.     

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.     

High-frequency trading and stock liquidity: An intraday analysis

This paper studies the impact of high-frequency trading (HFT) on intraday liquidity of CAC40 stocks listed on Euronext. Spreads display an intraday L-shaped pattern, while quoted depth follows an inverse pattern: low at the open and increasing towards the end of the trading day. When liquidity demand is particularly high, there is a high rate of order cancellations attributable to high-frequency traders who use frequent order cancellations to strategically manage their limit orders and close positions near the market close. Using the generalized method of moments estimator, we generate strong evidence that greater intensity of HFT is associated with lower spreads and higher depth. The positive effect of HFT on liquidity is due mainly to decreased adverse selection costs arising from asymmetric information among market participants.     

The Relationship Among Market-Making Revenue, Payment for Order Flow, and Trading Costs for Market Orders

We study the division of market-making revenue among dealer, broker, and trader. When Knight Securities, a major Nasdaq dealer, interacts with market orders in actively traded stocks during the fourth quarter of 1996, we estimate that its revenue is $0.057 per share. Knight pays brokers at least $0.025 per share (44% of revenue) for orders. To examine whether brokers appear to share these payments with traders, we compare net trading costs (trade price net of commissions) for traders using brokers routing Knight orders with estimated net trading costs for traders using the only discount broker we can determine did not directly receive market-making revenue. We find that the net trading cost of the broker refusing order-flow payments does not dominate the net trading cost of all brokers selling order flow to Knight. This finding suggests that order-flow payments do not unambiguously harm traders and challenges the conclusions of extant studies using only trade prices to assess market quality.     

Liquidity,liquidity risk,and information flow: Lessons from an emerging market

This paper examines the role of public and private information flows in intraday liquidity and intraday liquidity risk in the Tunisian stock market. Our empirical results are based on ARMA and GARCH-type models and show that, for major Tunisian stocks, gradually elapsed public information together with gradually elapsed private information in the market is the dominant factor in liquidity improvements in the Tunisian stock market. Liquidity improvements are generated by a decrease in the bid-ask spread accompanied by an increase in the depth at best limit. Our results clearly indicate that the arrival of public information in a sequential manner is the dominant factor generating increases in liquidity risk related to the bid-ask spread, while the advent of private information in a contemporaneous manner is the dominant factor generating increases in liquidity risk related to the depth at best limit. Additionally, our results show that liquidity risk persistence disappears when trading volume and order imbalance are included as explanatory variables in the conditional variance equation.     

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.