How efficiency shapes market impact

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large metaorders is smaller than that of small metaorders. We formulate a stylized model of an algorithmic execution service and derive a fair pricing condition, which says that the average transaction price of the metaorder is equal to the price after trading is completed. We show that at equilibrium the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on the commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of metaorder size, with average permanent impact relaxing to about two-thirds of peak impact.     

Detecting trading response using transaction-based research designs

This paper examines issues pertinent to using number of transactions in event-type studies of market trading response. It presents rejection frequencies for portfolios of 20, 50, and 100 observations corresponding to different abnormal trading measures and test approaches. Findings include: (1) A cross-sectionalt-statistic approach performs almost as well as more elaborate test approaches and is robust to nonnomality in the number of transactions distribution; (2) a logarithmic transformation induces near-normality in the number of transactions distribution; and (3) for equal induced percentage increases in trading, rejection rates for number of transactions exceed those for percentage of outstanding shares trades (i.e., volume). The advantage of transactions over volume is relatively more important for small sample studies (e.g.,n<100) and those with small average increases in trading activity.     

Earnings Surprise "Materiality" as Measured by Stock Returns

Ranked earnings surprise portfolios formed from First Call files for 1992–97 are used to assess the annual earnings surprise magnitude for an individual firm sufficient to expect a "significant market reaction." We find that, for an individual firm, the maximum probability of a gain from trading on prior knowledge of any surprise magnitude is .622. The lack of probable trading gains is due to the S–shaped surprise/return relation and the large variance of returns for a given magnitude of surprise. In turn, we find that the S–shape is related empirically to the dispersion of analyst forecasts. Thus, factors underlying dispersion differences are related to the importance or "materiality" of earnings surprise as measured by stock returns and explain at least part of the S–shaped surprise/return relation.     

An evolutionary multi‐objective optimization of trading rules in call markets

We evaluate an agent‐based model featuring near‐zero‐intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices and which orders are executed, as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. We optimize these trading rules using a multi‐objective population‐based incremental learning algorithm seeking to maximize the trading volume and minimize the bid–ask spread. Our results suggest that markets should choose a small tick size if concerns about the bid–ask spread are dominating and a large tick size if maximizing trading volume is the main aim. We also find that unless concerns about trading volume dominate, time priority is the optimal priority rule. Copyright © 2011 John Wiley & Sons, Ltd.     

TIME-VARYING FACTORS AND CROSS-AUTOCORRELATIONS IN SHORT-HORIZON STOCK RETURNS

In this paper I show that the lead-lag pattern between large and small market value portfolio returns is consistent with differential variations in their expected return components. I find that the larger predictability of returns on the portfolio of small stocks may be due to a higher exposure of these firms to persistent (time-varying) latent factors. Additional evidence suggests that the asymmetric predictability cannot be fully explained by lagged price adjustments to common factor shocks: (i) lagged returns on large stocks do not have a strong causal effect on returns on small stocks; (ii) trading volume is positively related to own- and cross-autocorrelations in weekly portfolio returns; and (iii) significant cross-autocorrelation exists between current returns on large stocks and lagged returns on small stocks when trading volume is high.     

Predicting European Takeover Targets

This article extends the Palepu (1986) acquisition likelihood model by incorporating measures of a technical nature, e.g. momentum, trading volume as well as a measure of market sentiment. We use the proposed model to predict takeover targets in a large sample of European and cross‐border merger and acquisition deals and validate its performance on an in‐ and out‐of‐sample basis. The robustness of the proposed model is investigated across several dimensions. In addition we explore the ability of the model to form the basis of successful takeover timing investment strategies. The results of our empirical analysis suggest that the proposed model predicts European takeover targets with relatively high accuracy and is able to determine portfolios that earn significant returns which are not explained by conventional risk factors.     

FT coverage and UK target price run-ups

We focus on the market expectation hypothesis to explain the increase in share prices and trading volume of target firms before their merger announcements that have conventionally been attributed to either insider trading or market expectation. We use Financial Times (FT) coverage as a proxy of merger expectation and search for relevant articles for 783 UK target firms between 1998 and 2010. We identify a total of 1049 rumour articles and find that the FT market expectation proxy explains a small percentage of the target price run-ups. Results are strong during the sample period, even though the magnitude for both returns and trading volume tends to decrease within recent years. There is also a strong contemporaneous relation between abnormal returns and trading volume. Unexplained increases in target prices and trading volume may be attributed to insider trading.     

The Effect of Sequential Information Arrival on Asset Prices: An Experimental Study

A complete understanding of security markets requires a simultaneous explanation of price behavior, trading volume, portfolio composition (ie., asset allocation), and bid-ask spreads. In this paper, these variables are observed in a controlled setting—a computerized double auction market, similar to NASDAQ. Our laboratory allows experimental control of information arrival—whether simultaneously or sequentially received, and whether homogeneous or heterogeneous. We compare the price, volume, and share allocations of three market equilibrium models: telepathic rational expectations, which assumes that traders can read each others minds (strong-form market efficiency); ordinary rational expectations, which assumes traders can use (some) market price information, (a type of semi-strong form efficiency); and private information, where traders use no market information. We conclude 1) that stronger-form market models predict equilibrium prices better than weaker-form models, 2) that there were fewer misallocation forecasts in simultaneous information arrival (SIM) environments, 3) that trading volume was significantly higher in SIM environments, 4) and that bid-ask spreads widen significantly when traders are exposed to price uncertainty resulting from information heterogeneity.     

Futures trading volume as a determinant of prices in different momentum phases

Recent studies contend that trading volume has predictive power for ex ante stock prices, particularly small stocks that do not react quickly to macroeconomic information. This study postulates that a significant amount of macro-information that flows on to stock markets is derived from derivative markets. We examine the impact of short-term futures trading volume and prices on cash stock prices using a case study of 15-min data from the Australian stock index futures market which reports actual trading volume. After applying vector error correction modelling (VECM), variance decomposition and impulse functions, we conclude that futures prices provide a short-term information lead to stock prices that dominates trading volume effects. We also observe asymmetric changes in the impact of trading volume between bull and bear price momentum phases and after large trading volume shocks. These results suggest that, in future, studies on trading volume should control for the cross-correlation impact from derivative prices and the differential impact of trading phases.     

The total cost of trading Belgian shares: Brussels versus London

Since 1990, London’s SEAQ International (SEAQ-I) has attracted considerable trading volume in Belgian equities. This paper investigates competition between the Brussels CATS market and London’s SEAQ-I. Toward this end, we gathered extensive limit order book data as well as transactions and quotation information. With regard to liquidity (indirect costs), measured by the quoted and effective bid–ask spread, the paper concludes that CATS outperforms SEAQ International for both measures. The effective spread is of course substantially smaller than the quoted spread, with the CATS effective spread showing a U-shaped form. This paper, unique in employing an extensive data set that includes all hidden orders and the whole limit order book, produces results in line with the different market microstructure models. Total trading costs on CATS are lower (higher) for small (large) trade sizes.     

Continuous Trading or Call Auctions: Revealed Preferences of Investors at the Tel Aviv Stock Exchange

We use the move of Israeli stocks from call auction trading to continuous trading to show that investors have a preference for stocks that trade continuously. When large stocks move from call auction to continuous trading, the small stocks that still trade by call auction experience a significant loss in volume relative to the overall market volume. As small stocks move to continuous trading, they experience an increase in volume and positive abnormal returns because of the associated increase in liquidity. Overall, though, a move to continuous trading increases the volume of large stocks relative to small stocks.     

Whose trades convey information? Evidence from a cross-section of traders

This paper contributes empirically to our understanding of informed traders. It analyzes traders’ characteristics in a foreign exchange electronic limit order market via anonymous trader identities. We use six indicators of informed trading in a cross-sectional multivariate approach to identify traders with high price impact. More information is conveyed by those traders’ trades which—simultaneously—use medium-sized orders (practice stealth trading), have large trading volume, are located in a financial center, trade early in the trading session, at times of wide spreads and when the order book is thin.     

Driven to Distraction: Extraneous Events and Underreaction to Earnings News

Recent studies propose that limited investor attention causes market underreactions. This paper directly tests this explanation by measuring the information load faced by investors. The  investor distraction hypothesis  holds that extraneous news inhibits market reactions to relevant news. We find that the immediate price and volume reaction to a firm's earnings surprise is much weaker, and post-announcement drift much stronger, when a greater number of same-day earnings announcements are made by other firms. We evaluate the economic importance of distraction effects through a trading strategy, which yields substantial alphas. Industry-unrelated news and large earnings surprises have a stronger distracting effect.     

Heterogeneous preferences and equilibrium trading volume

The representative-agent Lucas model stresses aggregate risk and hence does not allow us to study the impact of agents’ heterogeneity on the dynamics of equilibrium trading volume. In this paper, we investigate under what conditions non-informational heterogeneity, i.e., differences in preferences and endowments, leads to nontrivial trading volume in equilibrium. We present a non-informational no-trade theorem that provides necessary and sufficient conditions for zero equilibrium trading volume in a continuous-time Lucas market model with heterogeneous agents, multiple goods, and multiple securities. We explain in detail how no-trade equilibria are related to autarky equilibria, portfolio autarky equilibria, and peculiar financial market equilibria, which play an important role in the literature on international risk sharing.     

RECENT GROWTH IN NASDAQ TRADING VOLUME AND ITS RELATION TO MARKET VOLATILITY

We document a significant increase in Nasdaq trading volume relative to New York Stock Exchange (NYSE) and American Stock Exchange (AMEX) trading volumes. Although recent increases in the number of shares traded are reported in the financial press, we also find it present in the percentage of dollar values traded. We then examine correlations between trading volume and several measures of market volatility. Nasdaq volume appears to be more closely correlated with residual variance, while NYSE and AMEX volumes are more closely correlated with overall market variance. We conclude that the type and quantity of information driving trading are different on Nasdaq than on the two exchanges, and that the relative growth in Nasdaq volume cannot be attributed solely to differences in the methods of counting volume in the two market environments.     

Which Traders Contribute Most to Price Discovery? Evidence from the KOSPI 200 Options Market

We examine which group of investors—individuals, institutions, or foreigners—has more information about the true price process in the Korea Stock Price Index 200 (KOSPI 200) options market. Using the Hasbrouck (1995) information share and the Gonzalo and Granger (1995) common factor weight approach, we show that foreigners are the most informative about the efficient price process, and domestic institutional investors as well as individual investors have small contribution to price discovery. This result holds firmly, even after controlling for the effects of trading volume and the number of trades. Our empirical results suggest that foreigners are informed traders in the KOSPI 200 options market, consistent with the findings of Ahn, Kang, and Ryu (2008).     

Institutional investor’ proportions and inactive trading

We focus on a typical market anomaly-inactive trading: trading volume shrinks while stock price abnormally jumps. We calibrate a theoretical model with variance ambiguity heterogeneous among investors and illustrate that ambiguity averse investors' proportions enhance trading volume shrinkage and abnormal price jumps. We provide a cross-section analysis of stocks' inactive trading by introducing institutional investors' proportions to measure investor structures' differences among stocks. We also empirically measure relative inactive trading for constituent stocks in S&P 500 from 2014 to 2019 and demonstrate that institutional investors' proportion is negatively related to inactive trading. Finally, we demonstrate that higher proportions of institutional investors lead to less inactive trading anomalies.     

Forecasting asymmetries in aggregate stock market returns: Evidence from conditional skewness

This paper provides a time-series test for the Differences-of-Opinion theory proposed by Hong and Stein (2003) [Hong, H., Stein, J.C., 2003. Differences of opinion, short-sales constraints and market crashes. Review of Financial Studies 16, 487–525.] in the aggregate market, thus extending the cross-sectional test of Chen et al. (2001) [Chen, J., Hong, H., Stein, J.C.. 2001. Forecasting crashes: trading volume, past returns and conditional skewness in stock prices. Journal of Financial Economics 61, 345–381.] for this theory across individual stocks. An autoregressive conditional density model with a skewed-t distribution is used to estimate the effects of past trading volume on return asymmetry. Using NYSE and AMEX data from 1962 to 2000, we find that the prediction of the Hong–Stein model that negative skewness will be most pronounced under high trading volume conditions is not supported in our time-series analysis with market data.     

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.     

Endogenous informed trading in the presence of trading costs: Theory and evidence

The basic premise of the model we propose is that market frictions (trading costs) force traders with market-wide information to strategically choose which securities to trade in. We study the effect of recognizing trading costs on the choices of informed traders and the resulting statistical properties of security prices. Specifically, we show that (1) stocks with intermediate β's have the least informative prices, even though they are traded by the greatest number of informed traders; (2) for high β securities, the contemporaneous correlation of prices is close to the correlation in fundamental values; (3) a security with a higher β, higher volume of liquidity trading and lower idiosyncratic variance is more likely to lead another security. With market capitalization as a proxy for the level of liquidity trading, these specific predictions of the model on the lead–lag relationship are also shown to be strongly supported by the data.