Re-examining the small-cap myth: problems in portfolio formation and liquidation

This study investigates the realizable returns on portfolios at the turn-of-the-year. Using an intraday simulation that accounts for the volumes offered or wanted at market bid-ask prices, large-capitalization securities significantly outperform small-capitalization securities by 2.4% and 6.5%, depending on whether the portfolios were formed on the last day of the taxation year or were formed over the last month of the trading year. In no one year could the small-capitalization portfolio be completely divested by the end of the holding period, suggesting that investors are not remunerated for the illiquidity in this portfolio. Results based on returns calculated by using the mean of the bid-ask spread show that the results are not derived solely from transaction costs.     

Inferring the Components of the Bid-Ask Spread: Theory and Empirical Tests

The relation between the square of the quoted bid-ask spread and two serial covariances—the serial covariance of transaction returns and the serial covariance of quoted returns—is modeled as a function of the probability of a price reversal, π, and the magnitude of a price change, ?, where ? is stated as a fraction of the quoted spread. Different models of the spread are contrasted in terms of the parameters, π and ?. Using data on the transaction prices and price quotations for NASDAQ/NMS stocks, π and ? are estimated and the relative importance of the components of the quoted spread—adverse information costs, order processing costs, and inventory holding costs—is determined.     

EMPIRICAL EVIDENCE ON THE IMPACT OF THE BID-ASK SPREAD ON THE CHARACTERISTICS OF CRSP DAILY RETURNS

It is widely recognized that Center for Research in Security Prices (CRSP) returns may differ from “true” returns because of the bid-ask effect. Using a large sample of New York Stock Exchange and American Stock Exchange securities, I confirm a discernible bid-ask effect, the magnitude and importance of which decrease with the security's price level (increase with the spread). I find volatility estimates using CRSP returns to be greater than those based on quote returns. However, market model properties, such as β and R², are generally unaffected. Bid-ask effects are clearly apparent in event studies, but because of certain offsetting effects commonly used test statistics remain unaffected. Low-priced stocks (below $2.00) do not conform to these patterns. Finally, the evidence raises the possibility that the existing literature on filter rule tests may underestimate the bid-ask spread component of transaction costs.     

An Investigation of Market Microstructure Impacts on Event Study Returns

We investigate the importance of bid-ask spread-induced biases on event date returns as exemplified by seasoned equity offerings by NYSE listed firms. We document significant negative return biases on the offering day which explain a large portion of the negative event date return documented in the literature. Buy-sell order flow imbalance is prominent around the offering and induces a relatively large spread bias. If order imbalances are suspected, the researcher can use returns calculated from the midpoint of the closing bid and ask quotes instead of returns calculated from closing transaction prices to avoid this return bias.     

Bid-Ask Spread Estimation For A Correlated Value Innovation Process

Previous studies of bid-ask spread estimators based on serial covariance in returns document high proportions of positive serial covariances and therefore negative spread estimates. These findings may be due to the effects of time-variation in expected returns. Although purging the effects of time-varying expected returns yields more reasonable results, the bid-ask spread estimates from daily and weekly returns are still materially different. We present a method that avoids the need for removing the effects of time-varying expected returns by using a spread estimator developed directly for a correlated value innovation process. The new spread estimator not only yields more reasonable estimates of the bid-ask spread than the Roll (1984) model, but the spread estimates from daily and weekly returns are almost equal.     

The effect of option transaction costs on informed trading in the options market around earnings announcements

We investigate the effect of option market transaction costs (a form of market imperfection) on the ability of option implied volatility-based measures to predict future stock returns and volatility around quarterly earnings announcements. We find that the predictability is significantly stronger for firms with lower option relative bid-ask spreads. The effect is more pronounced around positive rather than negative earnings news. We find no significant effect of option transaction costs around randomly chosen dates when there is no clustering of major information events. Trading strategies based on option market predictors and transaction costs earn monthly abnormal returns of 1.39% to 1.91%.     

Do accruals exacerbate information asymmetry in the market?

A considerable body of evidence, both archival and experimental, suggests that accounting accruals are heterogeneously interpreted by investors. We examine whether the information asymmetry among investors arising from this heterogeneous interpretation, implied in these empirical results, affects transactions costs in the form of the adverse selection component of the bid-ask spread. We examine this impact both, in a yearly setting and around the first release of quarterly accrual information. The results of the study provide empirical evidence of a positive association between the adverse selection component and accruals in the yearly analysis. Since wider bid-ask spreads are both theoretically and empirically linked to higher stock returns (Brennan & Subrahmanyam, 1996), our results provide a transaction cost basis for understanding one possible factor underlying the linkage between accruals and cost of equity capital, and accruals and information risk pricing as documented in Francis et al. (2005) and Ecker et al. (2006).     

交易持续期、交易信息与投资者行为——基于PCD模型的研究

使用 PCD 模型,通过引入买卖价差、交易量、交易规模、委托指令流等交易信息变量探讨交易信息对投资者行为的影响。实证研究表明,买卖价差与期望交易持续期显著正相关,不支持 Easley 和 O’Hara (1992)的观点。同时大规模的交易能够显著地延长交易持续期,而中等规模的交易能够减小交易持续期,证实了知情交易者的隐藏交易假说。指令流信息中的买卖申报数量也对交易持续期有显著的影响,上期买卖申报数量与本期交易持续期正相关。     

Trading Patterns and Prices in the Interbank Foreign Exchange Market

The behavior of quote arrivals and bid-ask spreads is examined for continuously recorded deutsche mark-dollar exchange rate data over time, across locations, and by market participants. A pattern in the intraday spread and intensity of market activity over time is uncovered and related to theories of trading patterns. Models for the conditional mean and variance of returns and bid-ask spreads indicate volatility clustering at high frequencies. The proposition that trading intensity has an independent effect on returns volatility is rejected, but holds for spread volatility. Conditional returns volatility is increasing in the size of the spread.     

Components of the Bid-Ask Spread and the Statistical Properties of Transaction Prices

The bid-ask spread can be decomposed into two parts: one part due to asymmetric information and the other part due to other factors such as monopoly power. The part due to asymmetric information attenuates statistical biases in mean return, variance, and serial covariance. Thus, using spread data to adjust for biases in return moments requires knowing not only the spread but the composition of the spread. Furthermore, any spread-estimation procedure using transaction prices must estimate two spread components. On the other hand, the appropriateness of some previously suggested statistical corrections is independent of the spread composition.     

The no-arbitrage condition and financial markets with transaction costs and heterogeneous information: The bid-ask spread

This paper investigates the implications of the no-arbitrage (NA) condition in markets with transaction costs and heterogeneous information. Dermody and Prisman (1993) showed that, in financial markets with increasing marginal transaction costs, the NA condition is equivalent to the existence of a valuation operator. They explore the exact dependence of this operator on the structure of transaction costs. They show that equilibrium prices in the “corresponding” perfect markets plus a certain factor determine the valuation operator in markets with increasing marginal transaction costs. This paper emphasizes that their result is applicable to financial markets with decreasing marginal transaction costs. Furthermore, this paper shows that, in financial markets with transaction costs and heterogeneous information, the NA condition imposes a constraint on the bid-ask spread.     

Adverse Selection and the Required Return

An important feature of financial markets is that securitiesare traded repeatedly by asymmetrically informed investors.We study how current and future adverse selection affect therequired return. We find that the bid-ask spread generated byadverse selection is not a cost, on average, for agents whotrade, and hence the bid-ask spread does not directly influencethe required return. Adverse selection contributes to trading-decisiondistortions, however, implying allocation costs, which affectthe required return. We explicitly derive the effect of adverseselection on required returns, and show how our result differsfrom models that consider the bid-ask spread to be an exogenouscost.     

WINNERS AND LOSERS ON NYSE: A RE-EXAMINATION USING DAILY CLOSING BID-ASK SPREADS

We study a sample of NYSE stocks that experienced a large one-day price change during 1992 and were reported as daily largest percentage gainers and largest percentage losers in the Wall Street Journal. The sample indicates significant reversals during the immediate post-announcement period. We test for market efficiency by using bid-ask spreads obtained from the transactions data for the days immediately after the announcement. The overall results indicate that the returns during the reversal period are less than the average bid-ask spread during the same time. We also find that major losers, firms with ?20 percent to ?50 percent event-date abnormal returns, experience price reversals generating returns that are significantly greater than the average bid-ask spread during that period. We interpret this result as consistent with the overreaction hypothesis. A test of a trading rule to exploit this overreaction is not profitable, providing support for weak-form market efficiency.     

Optimal mean-reversion strategy in the presence of bid-ask spread and delays in capital allocations

A portfolio optimization problem for an investor who trades T-bills and a mean-reverting stock in the presence of proportional and convex transaction costs is considered. The proportional transaction cost represents a bid-ask spread, while the convex transaction cost is used to model delays in capital allocations. I utilize the historical bid-ask spread in US stock market and assume that the stock reverts on yearly basis, while an investor follows monthly changes in the stock price. It is found that proportional transaction cost has a relatively weak effect on the expected return and the Sharpe ratio of the investor's portfolio. Meantime, the presence of delays in capital allocations has a dramatic impact on the expected return and the Sharpe ratio of the investor's portfolio. I also find the robust optimal strategy in the presence of model uncertainty and show that the latter increases the effective risk aversion of the investor and makes her view the stock as more risky.     

The Information Content of Dividend Initiations and Firm Size: An Analysis Using Bid-Ask Spreads

The bid-ask spread of stock prices is examined for a sample of dividend initiating firms. The average percentage and dollar bid-ask spreads increase significantly on the day preceding the Wall Street Journal Index announcement date, possibly reflecting, on average, the market maker's anticipatory uncertainty. The day -1 increase in spread is inversely associated with firm size, an information environment proxy, after considering the simultaneous effects of dividend yield, returns variance, dollar trading volume and share price. The average percentage spread declines significantly on day 0 from its day -1 level and remains lower, on average, over a 365 day post-announcement period than 90 day pre-announcement levels. Similar results are obtained for dollar spread averages. The post-announcement percentage spread decline suggests a resolution of uncertainty, and is positively associated with the dividend yield. Dividend initiation announcements appear to reduce informational asymmetry.     

Third Market Broker-Dealers: Cost Competitors or Cream Skimmers?

This article compares the bid-ask spread for New York Stock Exchange (NYSE)-listed securities before and after a major third market broker-dealer, Bernard L. Madoff Investment Securities (Madoff), begins to selectively purchase and execute orders in those securities. Tests reveal the quoted bid-ask spread tightens when Madoff enters the market. Furthermore, trading costs as measured by the difference between the transaction price and the midpoint of the contemporaneous bid-ask spread do not increase. Together, these results suggest that the adverse selection problem associated with allowing agents to selectively execute orders in exchange-listed securities may be economically insignificant.     

Intraday Return Volatility Process: Evidence from NASDAQ Stocks

This paper presents a comprehensive analysis of the distributional and time-series properties of intraday returns. The purpose is to determine whether a GARCH model that allows for time varying variance in a process can adequately represent intraday return volatility. Our primary data set consists of 5-minute returns, trading volumes, and bid-ask spreads during the period January 1, 1999 through March 31, 1999, for a subset of thirty stocks from the NASDAQ 100 Index. Our results indicate that the GARCH(1,1) model best describes the volatility of intraday returns. Current volatility can be explained by past volatility that tends to persist over time. These results are consistent with those of Akgiray (1989) who estimates volatility using the various ARCH and GARCH specifications and finds the GARCH(1,1) model performs the best. We add volume as an additional explanatory variable in the GARCH model to examine if volume can capture the GARCH effects. Consistent with results of Najand and Yung (1991) and Foster (1995) and contrary to those of Lamoureux and Lastrapes (1990), our results show that the persistence in volatility remains in intraday return series even after volume is included in the model as an explanatory variable. We then substitute bid-ask spread for volume in the conditional volatility equation to examine if the latter can capture the GARCH effects. The results show that the GARCH effects remain strongly significant for many of the securities after the introduction of bid-ask spread. Consistent with results of Antoniou, Homes and Priestley (1998), intraday returns also exhibit significant asymmetric responses of volatility to flow of information into the market.     

Effects of the volatility smile on exchange settlement practices: The Hong Kong case

The well-documented volatility smile phenomenon in the US options market has affected the option settlement practices of other markets. To settle Hang Seng Index (HSI) options, the Hong Kong Stock Exchange artificially builds in a piecewise linear “smile” or “sneer” volatility function, which is determined daily by market makers rather than directly by market forces. In this study, we investigate the time-varying settlement function and find the following economic determinants of the volatility function: lag parameters, current-day HSI returns, the distribution of HSI returns, transaction costs as proxied by the bid-ask spread, and the “Monday effect”. For evaluation purposes, we use as a benchmark the estimated piecewise linear volatility function as directly driven by market forces. The comparison analyses show that base volatilities set by market makers run somewhat high, while downside slopes are not steep enough. This results in the overpricing of the lion’s share of traded options. An economic determinants analysis of market-force-driven parameters reveals that market makers can better align artificial volatility parameters both by reducing reliance on the function parameters of prior days and by more precisely accounting for current-day HSI returns, option time-to-maturity, bid-ask spreads and buying pressure.     

The Effects of Beta,Bid-Ask Spread,Residual Risk,and Size on Stock Returns

Merton's [26] recent extension of the CAPM proposed that asset returns are an increasing function of their beta risk, residual risk, and size and a decreasing function of the public availability of information about them. Associating the latter with asset liquidity and following Amihud and Mendelson's [2] proposition that asset returns increase with their illiquidity (measured by the bid-ask spread), we jointly estimate the effects of these four factors on stock returns.     

Density estimation through quasi-analytic Monte-Carlo simulation: Options arbitrage with transactions costs

Discretely rebalanced options arbitrage strategies in the presence of transaction costs have path dependent returns that are difficult to model analytically. I instead use a quasi-analytic procedure that combines the computational efficiency of analytical solutions with the flexibility of simulations. The central feature is the estimation of the distribution of returns of the arbitrage strategy by mapping simulated returns percentiles and the input parameter set. Using the estimated density, I evaluate the tradeoff between transaction costs and risk exposure under generalized transaction costs structures that includes bid-ask spread and brokerage commission. I show that the optimal strategy depends on transaction costs, volatility, and option moneyness. Strategies such as rebalancing when the hedge ratio changes by 0.25, balances transaction costs and risk exposure, and can be optimal.