VOLATILITY AND LIQUIDITY AT NYSE OPENING CALLS: A CLOSER LOOK

The literature suggests that the bid-ask spread is responsible, at least in part, for greater price volatility and more negative autocorrelation at the open than at the close. In this study, we find that these phenomena are not related to the bid-ask spread, but are related instead to pricing errors by specialists or limit-order traders around the open. We use George, Kaul, and Nimalendran's (1991) model, which is less biased than Roll's (1984) model, to estimate the implied spread. The results show that, on average, the implied spread earned by liquidity suppliers is lower at the open than at the close. These results refute the contention that specialists exploit their monopoly position and earn a higher profit at the opening call. The evidence is consistent with the hypothesis that specialists set a lower cost of immediacy to encourage trading and the release of more information at the opening call. This could reduce information asymmetry and make subsequent trades in the continuous market more profitable.     

Round-the-clock market efficiency and home bias: Evidence from the international Japanese government bonds futures markets

This paper examines how information is processed between almost identical international futures markets: London (LIFFE) and Tokyo (TSE) JGB futures. In these markets, variations in open-to-open changes are virtually the same as those of close-to-close changes, suggesting that information is transmitted efficiently across markets with small opening pricing errors. The overall results confirm market efficiency around the clock, yet the intraday U-shaped patterns in volume/volatility of the London JGB futures suggest home bias in international investments, indicating a less global view of trading than expected. Specifically, at the LIFFE open, London investors rush to rebalance portfolios instead of doing so at the TSE close, which is only one hour before the LIFFE opens.     

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.     

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, Trading, and Volatility: Evidence from Weather-Sensitive Markets

We find that trading‐ versus nontrading‐period variance ratios in weather‐sensitive markets are lower than those in the equity market and higher than those in the currency market. The variance ratios are also substantially lower during periods of the year when prices are most sensitive to the weather. Moreover, the comovement of returns and volatilities for related commodities is stronger during the weather‐sensitive season, largely due to stronger comovement during nontrading periods. These results are consistent with a strong link between prices and public information flow and cannot be explained by pricing errors or changes in trading activity.     

How do individual investors trade?

This paper examines how high-frequency trading decisions of individual investors are influenced by past price changes. Specifically, we address the question as to whether decisions to open or close a position are different when investors already hold a position compared with when they do not. Based on a unique data set from an electronic foreign exchange trading platform, OANDA FXTrade, we find that investors’ future order flow is (significantly) driven by past price movements and that these predictive patterns last up to several hours. This observation clearly shows that for high-frequency trading, investors rely on previous price movements in making future investment decisions. We provide clear evidence that market and limit orders flows are much more predictable if those orders are submitted to close an existing position than if they are used to open one. We interpret this finding as evidence for the existence of a monitoring effect, which has implications for theoretical market microstructure models and behavioral finance phenomena, such as the endowment effect.     

Cost-based transfer pricing

This paper compares the performance of alternative cost-based transfer pricing methods. We adopt an incomplete contracting framework with asymmetric information at the trading stage. Transfer pricing guides intra-company trade and provides incentives for value-enhancing specific investments. We compare actual-cost transfer prices that include a markup over marginal costs with standard-cost transfer prices that are determined either by the central office ex ante (centralized standard-cost transfer pricing) or by the supplying division at the trading stage (reported standard-cost transfer pricing). For the actual-cost methods, we show that markups based on the joint contribution margin (contribution-margin transfer pricing) dominate purely additive markups (cost-plus transfer pricing). We obtain the following results. (1) Centralized standard-cost transfer pricing dominates the other methods if the central office and the divisions ex ante face low cost uncertainty. (2) The actual-cost methods dominate the other methods if the central office and the divisions ex ante face high cost uncertainty and later, at the trading stage, the buying division receives sufficient cost information. (3) Reported standard-cost transfer pricing dominates the other methods if the central office and the divisions ex ante face high cost uncertainty, and the buyer has insufficient cost information at the trading stage.     

The Persistence of IPO Mispricing and the Predictive Power of Flipping

This paper examines underwriters' pricing errors and the information content of first-day trading activity in IPOs. We show that first-day winners continue to be winners over the first year, and first-day dogs continue to be relative dogs. Exceptions are "extra-hot" IPOs, which provide the worst future performance. We also demonstrate that large, supposedly informed, traders "flip" IPOs that perform the worst in the future. IPOs with low flipping generate abnormal returns of 1.5 percentage points per month over the first six months beginning on the third day. We show that flipping is predictable and conclude that underwriters' pricing errors are intentional.     

Applying developed‐country regulation in emerging markets: an analysis of Thai insider trading

This paper undertakes an out‐of‐sample test of developed‐country insider trading regulation in an emerging market environment (Thailand), where severe information asymmetry, lax enforcement and poor pricing efficiency are endemic. Thai insider trading regulation, which mimics developed market rules, fails on all three measures of success. Insiders trade with impunity during a regulated trading ban. Their trading performance outperforms other investors at all times, and they continue to exploit their privileged position with respect to information flow. Our study suggests it is inappropriate for emerging market regulators to adopt developed market regulation without first considering the unique characteristics of their own environment.     

THE RELATION BETWEEN OPTION MISPRICING AND VOLUME IN THE BLACK-SCHOLES OPTION MODEL

We investigate the relation between mispricing in the Black-Scholes option pricing (BSOP) model and volume in the option market. Our results indicate heavily traded call options are priced more efficiently and have lower mispricing errors than thinly traded options. However, this relation shifts significantly on days when call option trading is high. On high-volume days, the BSOP model mispricing errors are significantly larger than mispricing errors on normal-volume days. We believe large increases in volume may reflect new and changing market information, thus making pricing less efficient in the BSOP model.     

Endogenous market statistics and security pricing:: An empirical investigation

This study examines empirically the degree to which the history of daytime and overnight price changes and order flow affects estimates of traders' beliefs about future security price changes. Estimates indicate that forecasts of the permanent component of price changes occurring after the open of trading are significantly related to past price changes and order flow; but the same is not generally true for price changes occurring after the close. These results are consistent with models of technical analysis, and models in which the process of trading facilitates price discovery. The evidence also suggests that private information is an important determinant of price movements.     

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.     

The Timing of Opening Trades and Pricing Errors

After demonstrating that a zero investment trading strategy that buys stocks with overnight returns below the market average and sells stocks with overnight returns above the market average earns more than 1% monthly profit, I demonstrate that this profit is greater for stocks that start trading more quickly than for other stocks. These results control for trading costs. The resulting pricing errors are a material portion of stock price volatility and suggest that a quick response to overnight information adds non‐information‐based stock volatility to stock prices.     

卖空者与内幕交易——来自中国证券市场的证据

本文研究上市公司内部人减持、年报、诉讼、分析师评级、停复牌以及高送转等重大公告前后卖空交易行为的变化,系统考察卖空者是否参与内幕交易以及何种因素影响卖空者参与内幕交易,发现卖空率较高的股票具有较低的未来收益,表明卖空者拥有信息优势,属知情交易者;卖空者拥有非常精确的择时交易能力,在重大利空公告前显著增加卖空量,而在利好公告前则显著减少卖空头寸,表明卖空者作为知情交易者的信息优势源自内幕消息;公司内、外部投资者的信息不对称程度越低或公司所在地的法治水平越高,卖空者参与内幕交易的行为就越少。因此,监管机构应密切关注公司重大消息发布前后卖空量的异常变动,同时,完善信息披露规则、健全证券分析师制度并强化法律法规的执行力度,才能有效防范卖空者参与内幕交易。     

Investor structure and the informational efficiency of commodity futures prices

This article investigates the impact of the trading positions of hedgers (i.e., producers, merchants, processors, or users of a commodity), speculators (i.e., commodity pool operators, trading advisors, or hedge funds), and swap dealers on the price formation process in the agricultural, metal, and energy futures markets. The hedgers' relative positions exert negative impacts on price efficiency in commodity futures markets. Hedgers are less likely to be information motivated, so their trading delays the price formation process. However, speculators' positions have positive impacts on price efficiency because speculators correct pricing errors. This study also offers evidence that the role of swap dealers, similar to speculators in futures markets, is to provide liquidity and cross-market arbitrage. These findings highlight the role of producers, hedge funds, and swap dealers in price formation processes in commodity futures—information that is beneficial to academics, practitioners, and regulators.     

The pricing and performance of leveraged exchange-traded funds

Leveraged ETFs are a recent and very successful financial innovation. They provide daily returns that are in a multiple or a negative multiple of the daily returns on a market benchmark. In this paper, we examine the characteristics, trading statistics, pricing efficiency and tracking errors of a sample of leveraged ETFs. We find that these ETFs are traded mainly by retail traders with very short holding periods. Price deviations (from NAV) are small on average, but large premiums and discounts are prone to occur. More interestingly, the behavior of premiums is different between bull (i.e., those with a positive multiple) and bear ETFs (i.e., those with a negative multiple). Our findings are consistent with the argument that the end-of-day rebalancing of the funds’ exposures increases market volatility at the close of a trading day. As for tracking errors, they are small for holding periods of up to a week, but become increasingly larger for longer horizons.     

Asymmetric information and the bid-ask spread: an empirical comparison between automated order execution and open outcry auction

This study examines the components of the bid-ask spread on the Sydney Futures Exchange. The Exchange uses open outcry auction for daytime trading, and switches to a screen-based automated order execution system at 16:30 h for overnight trading. After controlling for proxies of order flow characteristics, the study finds that screen-based traders are more sensitive to market volatility than floor-based traders in setting the bid-ask spread. Spreads from floor trading have a smaller adverse information component but a larger order processing cost component relative to screen trading. The results suggest that floor traders can better assess the presence of adverse information than screen traders.     

The value of tradeability

This paper determines the value of asset tradeability in an option pricing framework. In our model, tradeability is valuable since it allows investors to exploit temporary mispricings of stocks. The model delivers several novel insights on the value of tradeability: The value of tradeability is the larger, the higher the pricing efficiency of the market is. Uncertainty increases the value of tradeability, no matter whether the uncertainty results from noise trading or from new information about the fundamental value of the stock. The value of tradeability is the larger, the longer the illiquid stock cannot be traded and the more trading dates the liquid stock offers.     

Volume autocorrelation,information, and investor trading

This study investigates whether the widely documented daily correlated trading volume of stocks is driven by individual investor trading, institutional trading, or both. We find that at least 95% of NYSE and AMEX stocks exhibit statistically significant, positive serial correlation. Volume autocorrelation decreases with the level of institutional ownership of a stock. We also show that the rate of arrivals of new information to the market contributes to the clustering of trades. When there is high information flow to the market, institutional trading generates a more pronounced effect on volume autocorrelation than individual investor trading. Our results are broadly consistent with the predictions of trading volume patterns suggested by most theoretical models of stock trading and by empirical research on investor trading.     

Stock market structure and volatility

The procedure for opening stocks on the NYSE appears to affectprice volatility. An analytical framework for assessing themagnitude of the structurally induced volatility is presented.The ratio of variance of open-to-open returns to close-to-closereturns is shown to be consistently greater than one for NYSEcommon stocks during the period 1982 through 1986. The greatervolatility at the open is not attributable to the way in whichpublic information is released since both the open-to-open returnand the close-to-close return span the same period of time.Instead, the greater volatility appears to be attributable toprivate information revealed in trading and to temporary pricedeviations induced by specialist and other traders. The impliedcost of immediacy at the open is significantly higher than atthe close. Other empirical evidence in this article documentsthe volume of trading at the open, the time delays between theexchange opening and the first transaction in a stock, the differencein daytime volatility versus overnight volatility, and the extendto which volatility is related to trading volume.