On the Stability of the Cross‐Section of Expected Stock Returns in the Cross‐Section: Understanding the Curious Role of Share Turnover

In this paper, we shed further light on cross‐sectional predictors of stock return performance. Specifically, we explore whether the cross‐section of expected stock returns is robust within stock groups sorted by past monthly return. We find that the book/market and momentum effects are remarkably robust to sorting on past returns. However, share turnover is negatively related to future returns for stocks with abnormally low stock price performance in the recent past, but postively related to returns for well‐performing stocks. This casts doubt on the use of turnover as a liquidity proxy, but is consistent with turnover being a proxy for momentum trading which pushes prices in the direction of past price movements. Our results are robust to both NYSE/AMEX and Nasdaq stocks, and also robust to stratifying the sample by time period.     

The dynamics of quote adjustments

Liquidity providers on the NYSE make faster quote adjustments towards equilibrium spreads and depths than they do on NASDAQ. Liquidity providers in both markets make faster spread and depth adjustments for stocks with more frequent trading, greater return volatility, higher prices, smaller market capitalizations, and smaller trade sizes. We find that stocks with greater information-based trading and in more competitive trading environments exhibit faster quote adjustments. The speed of quote adjustment is faster after decimalization in both markets. These results are robust and not driven by differences in stock attributes between the two markets or time periods. Overall, our results indicate that stock attributes, market structure, and tick size exert a significant impact on the speed of quote adjustment.     

The Operating Performance of Firms that Switch Their Stock Listings

In this article we examine the operating performance of stocks that switch from NASDAQ to the American Stock Exchange (AMEX) or the New Stock Exchange (NYSE) and from AMEX to the NYSE. Specifically, we investigate whether post‐listing operating performance is consistent with the reported negative long‐term drift of post‐listing stock returns and whether there is evidence of self‐selection of the listing time. We find evidence of negative post‐listing changes in operating return on assets and sales, which, on a match‐adjusted basis, are significant for the relatively small NASDAQ stocks switching to AMEX. We also find evidence that firms self‐select the time of listing changes.     

Short-term market reaction after extreme price changes of liquid stocks

In our empirical study we examine the dynamics of the price evolution of liquid stocks after experiencing a large intra-day price change, using data from the NYSE and the NASDAQ. We find a significant reversal for both intra-day price decreases and increases. Volatility, volume and, in the case of the NYSE, the bid–ask spread, which increase sharply at the event, stay significantly high days afterwards. The decay of the volatility follows a power law in accordance with the `Omori law'. While on the NYSE the large widening of the bid–ask spread eliminates most of the profits that can be achieved by an outside investor, on the NASDAQ the bid–ask spread stays almost constant, yielding significant short-term profits. The results thus give an insight into the size and speed of the realization of an excess return for providing liquidity in a turbulent market.     

Risk‐Adjusted Long‐Term Contrarian Profits: Evidence from Non‐S&P 500 High‐Volume Stocks

Can trading volume help unravel the long‐term overreaction puzzle? With portfolios of non‐S&P 500 NYSE stocks, we show that (1) both the high‐ and low‐volume (abnormal volume) contrarian portfolios earn a much higher market‐adjusted excess return than the normal‐volume contrarian portfolio, (2) however, when leverage‐induced risk is factored in, excess returns from contrarian portfolios with normal‐ and low‐volume stocks are insignificant, (3) only excess returns from high‐volume contrarian stocks are significant and cannot be explained by the time‐varying risk and return framework, and (4) such high‐volume, risk‐adjusted excess returns arise mainly from winner (glamour) stocks.     

Removing biases in computed returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.     

LIQUIDITY AND ASSET PRICING UNDER THE THREE‐MOMENT CAPM PARADIGM

We examine whether the use of the three‐moment capital asset pricing model can account for liquidity risk. We also make a comparative analysis of a four‐factor model based on Fama–French and Pástor–Stambaugh factors versus a model based solely on stock characteristics. Our findings suggest that neither of the models captures the liquidity premium nor do stock characteristics serve as proxies for liquidity. We also find that sensitivities of stock return to fluctuations in market liquidity do not subsume the effect of characteristic liquidity. Furthermore, our empirical findings are robust to differences in market microstructure or trading protocols between NYSE/AMEX and NASDAQ.     

Consumption-based equity valuation

Using a CCAPM-based risk-adjustment model, we perform yearly valuations of a large sample of stocks listed on NYSE, AMEX, and NASDAQ over a 30-year period. The model differs from standard valuation models in the sense that it adjusts forecasted residual income for risk in the numerator rather than through a risk-adjusted cost of equity in the denominator. The risk adjustments are derived based on assumptions about the time-series properties of residual income returns and aggregate consumption rather than on historical stock returns. We compare the performance of the model with several implementations of standard valuation models, both in terms of median absolute valuation errors (MAVE) and in terms of excess returns on simple investment strategies based on the differences between model and market prices. The CCAPM-based valuation model yields a significantly lower MAVE than the best performing standard valuation model. Both types of models can identify investment strategies with subsequent excess returns. The CCAPM-based valuation model yields time-series of realized hedge returns with more and higher positive returns and fewer and less negative returns compared with the time-series of realized hedge returns based on the best performing standard valuation model for holding periods from 1 to 5 years. In a statistical test of 1-year-ahead excess return predictability based on the models’ implied pricing errors, the CCAPM-based valuation model is selected as the better model. Using the standard series of aggregate consumption and the nominal price index, a reasonable level of relative risk aversion, and calibrated growth rates in the continuing value at each valuation date, the CCAPM-based valuation model produces small risk adjustments to forecasted residual income and low continuing values. Compared with standard valuation models, it relies less on estimated parameters and speculative elements when aggregating residual earnings forecasts into a valuation.     

The Dynamics of Security Trades,Quote Revisions,and Market Depths for Actively Traded Stocks

We examine the dynamics of return volatility, trading volume, and depth—in an intraday setting for a sample of actively traded NYSE and NASDAQ stocks. We show that depth is a useful intervening variable and mitigates the impact of trading activity on price volatility. Furthermore, depth is affected by the perception of prevailing information asymmetry between informed and uninformed traders. We demonstrate empirically that the NYSE supplies greater depth under conditions of high, perceived information asymmetry as compared to NASDAQ. NASDAQ makes up for this deficiency by its capability of managing large volume shocks without a major decline in depth.JEL Classification: C32, D82, G10     

The Post‐Cost Profitability of Momentum Trading Strategies: Further Evidence from the UK

This paper examines the post‐cost profitability of momentum trading strategies in the UK over the period 1988–2003 and provides direct evidence on stock concentration, turnover and trading cost associated with the strategy. We find that after factoring out transaction costs the profitability of the momentum strategy disappears for shorter horizons but remains for longer horizons. Indeed, for ranking and holding periods up to 6‐months, profitable momentum returns would not be available to most average investors as the cost of implementation outweighs the possible returns. However, we find post‐cost profitability for ranking and/or holding periods beyond 6 months as portfolio turnover and its associated cost reduces. We find similar results for a sub‐sample of relatively large and liquid stocks.     

Determinants of the components of bid-ask spreads on stocks

In this paper we show that George et al. (GKN, 1991) estimators of the adverse selection and order processing cost components of the bid-ask spread are biased due to intertemporal variations in the bid-ask spread. We use alternative estimators that correct this bias and that are applicable to individual securities, and estimate these cost components empirically using data on NYSE/AMEX stocks. As expected, our results indicate that on average adverse selection costs account for approximately 50% of the bid-ask spread, sharply higher than the estimates of 8-10% obtained by GKN for NASDAQ stocks and 21% that we obtain for NYSE/AMEX stocks using GKN's estimators. We then conduct cross-sectional regressions designed primarily to determine whether adverse selection costs vary across specialists after controlling for firm size and other factors. Consistent with previously established hypotheses, we find that adverse-selection costs vary across specialists, and that this variation is related to the number of securities that the specialist handles.     

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.     

IPO first‐day returns: Skewness preference,investor sentiment and uncertainty underlying factors

In this paper, we investigate the initial public offering (IPO) first-day returns. Our focus is to examine the irrational component of the agent behavior towards IPO lotteries. Based on 234 French IPOs performed between 2002 and 2012, we find that IPOs with high initial returns have higher idiosyncratic skewness, turnover and momentum. This finding provides empirical evidence for investors' preference for stocks with lottery-like features and investor sentiment. In addition, we show that the skewness preference and the investor sentiment effect are stronger during periods of favorable market conditions. Our results are robust to the integration of uncertainty underlying factors.     

Momentum in weekly returns: the role of intermediate‐horizon past performance

Gutierrez and Kelly (2008) recently documented momentum in weekly returns. Using the Australian market as a setting, we find that stocks with high 1‐week returns exhibit a continuation in returns up to 1 year after a brief initial return reversal. However, after controlling for the intermediate‐horizon past performance, the continuation in returns after 1‐week returns disappears. These findings suggest that different past investment horizons contain separate information about price momentum and that intermediate‐term trends dominate short‐term trends in driving future returns. Overall, we show that understanding momentum over different horizons facilitates the design of more profitable trading strategies.     

Emerging from Bankruptcy with When‐Issued Trading

We examine the set of firms that emerged from Chapter 11 bankruptcy and traded on a when‐issued basis before their official return to the regular way in NASDAQ, Amex, or NYSE. We find that this when‐issued market is liquid and price efficient. The when‐issued closing price is a good indicator of the first closing price in the regular way market. Emerging firms that have when‐issued trading experience lower regular way volatility and smaller relative spreads than those without when‐issued trading. Our probit regressions show that firm size is an important determinant of the adoption of when‐issued trading.     

Informed momentum trading versus uninformed “naive” investors strategies

We construct a zero net-worth uninformed “naive investor” who uses a random portfolio allocation strategy. We then compare the returns of the momentum strategist to the return distribution of naive investors. For this purpose we reward momentum profits relative to the return percentiles of the naive investors with scores that are symmetric around the median. The score function thus constructed is invariant and robust to risk factor models. We find that the average scores of the momentum strategies are close to zero (the score of the median) and statistically insignificant over the sample period between 1926 and 2005, various sub-sample periods including the periods examined in [Jegadeesh and Titman, 1993] and [Jegadeesh and Titman, 2001] . The findings are robust with respect to sampling or period-specific effects, tightened score intervals, and the imposition of maximum-weight restrictions on the naive strategies to mitigate market friction considerations.     

Trading volume,return variability and short-term momentum

We propose short-term averages of daily stock-level trading volume and return variability as proxies for latent corporate news flow. Conditioning momentum strategies on these two proxies give a significant boost to winner-minus-loser alphas. Regardless of the portfolio formation and holding periods, price drift is larger after elevated levels of volume and variability, supporting the view that prices underreact to news. This pattern is not driven by micro-cap stocks and it is robust to corrections for systematic risk factors and stock characteristics such as liquidity and credit quality.     

TRADING‐VOLUME SHOCKS AND STOCK RETURNS: AN EMPIRICAL ANALYSIS

We examine high‐volume premiums based on weekly risk‐adjusted returns. Significant average weekly abnormal high‐volume premiums up to 0.50% per week are documented for 1962–2005. Most premiums are generated in the first two weeks and monotonically decline as holding periods are extended. Evidence of reversal is found as the holding periods are extended. Premiums depend on realized turnover in the holding period. The last finding supports the theories of Miller and Merton. Finally, we test whether premiums are compensation for taking additional risk. Negative skewness, idiosyncratic risk, and liquidity risk do not explain the high‐volume premiums.     

Dealer attention,the speed of quote adjustment to information,and net dealer revenue

Using trade and quote data from the NYSE, we examine the relation between dealer attention, dealer revenue, and the probability of informed trade. We find that dealer revenue net of losses to better-informed traders in NYSE stocks is positively related to the speed at which quotes adjust to full information levels. The speed of quote adjustment is faster for stocks with greater dealer attention, as measured by a stock’s relative prominence at its post and panel location on the NYSE floor. The level of dealer attention in turn is positively related to a stock’s probability of information-based trading. The results are consistent with a theoretical model we derive in which dealers trade multiple securities and must optimally allocate their limited attention to monitoring order flow to minimize losses to better-informed traders.     

Liquidity biases in asset pricing tests

Microstructure noise in security prices biases the results of empirical asset pricing specifications, particularly when security-level explanatory variables are cross-sectionally correlated with the amount of noise. We focus on tests of whether measures of illiquidity, which are likely to be correlated with the noise, are priced in the cross-section of stock returns, and show a significant upward bias in estimated return premiums for an array of illiquidity measures in Center for Research in Security Prices (CRSP) monthly return data. The upward bias is larger when illiquid securities are included in the sample, but persists even for NYSE/Amex stocks after decimalization. We introduce a methodological correction to eliminate the biases that simply involves weighted least squares (WLS) rather than ordinary least squares (OLS) estimation, and find evidence of smaller, but still significant, return premiums for illiquidity after implementing the correction.