Institutional Trading Activity Research Articles

Institutional trading in volatile markets: Evidence from Chinese stock markets

We investigate the daily stock returns of all A-shares listed on the Shanghai and Shenzhen stock exchanges over the period 2010–2017. Using daily cash flow data on the largest category of trades by value, we construct a proxy for high-value institutional trading activity. We demonstrate that high-value institutional transactions consistently exacerbate firm-level abnormal stock returns on extreme market movement days. We then highlight the conflating influence of regulator imposed daily limits on firm-level stock price movements and conclude that binding price limits act to exacerbate the destabilizing effects associated with high-value institutional trades in Chinese stock markets.

INSTITUTIONAL TRADING AND STOCK PINNING

ABSTRACT This paper investigates the impact of institutional trading activity on stock pinning effect for both monthly and weekly equity options. After the introduction of weekly options over seven years, it shows the pinning effect with weekly options is stronger in comparison to monthly options. Furthermore, this paper shows that stock pinning remains pervasive on the expiration days and the effect is powerful with higher concentrated firm proprietary trading. We explore and find evidence that hedge rebalancing by firm traders might be a possible cause for stock pinning on option expiration days. The higher the fraction of firm trading, the more significant the clustering effect is. Keywords Stock Pinning, Weekly Options, Institutional trading, stock clustering

Co-impact: crowding effects in institutional trading activity

This paper is devoted to the important yet unexplored subject of crowding effects on market impact, that we call ‘co-impact’. Our analysis is based on a large database of metaorders by institutional investors in the U.S. equity market. We find that the market chiefly reacts to the net order flow of ongoing metaorders, without individually distinguishing them. The joint co-impact of multiple contemporaneous metaorders depends on the total number of metaorders and their mutual sign correlation. Using a simple heuristic model calibrated on data, we reproduce very well the different regimes of the empirical market impact curves as a function of volume fraction φ: square-root for large φ, linear for intermediate φ, and a finite intercept when . The value of grows with the sign correlation coefficient. Our study sheds light on an apparent paradox: How can a non-linear impact law survive in the presence of a large number of simultaneously executed metaorders?

The dynamics of institutional trading: Evidence from transaction data

I examine the cross-sectional relationship between institutional trading activity and daily and intradaily stock returns for a sample of NYSE, Amex, and Nasdaq securities. An analysis of the prior day's return sort indicates that, institutional investors are 13.6 percent more likely to be net buyers of securities that are in the winner (top performing decile) decile than of those that are in the loser decile. There is a strong daily contemporaneous relation between institutional imbalances and returns, and institutional trades follow the previous day's returns. The intradaily analysis suggests that the contemporaneous relation is primarily driven by institutional trades following the intradaily prices. There is no evidence of institutional return predictability.

Institutional trading and asset pricing

Abstract This paper examines whether the trading activity of different investor types, institutional versus retail, can affect the relation between beta and average returns. We find that the beta-return relation is strong and positive on days with high institutional trading activity, and negative and significant on low institutional trading days. Our findings are robust and not driven by recently documented effects such as macroeconomic news and leverage constraints, among others. The evidence is consistent with the hypothesis that the preferences and characteristics of various investor types, which are revealed through their trading activity, cause the slope of the Security Market Line to change.

Co-Impact: Crowding Effects in Institutional Trading Activity

This paper is devoted to the important yet unexplored subject of crowding effects on market impact, that we call co-impact. Our analysis is based on a large database of metaorders by institutional investors in the U.S. equity market. We find that the market chiefly reacts to the net order flow of ongoing metaorders, without individually distinguishing them. The joint co-impact of multiple contemporaneous metaorders depends on the total number of metaorders and their mutual sign correlation. Using a simple heuristic model calibrated on data, we reproduce very well the different regimes of the empirical market impact curves as a function of volume fraction Φ: square-root for large Φ, linear for intermediate Φ, and a finite intercept I_0 when Φ to 0. The value of I_0 grows with the sign correlation coefficient. Our study sheds light on an apparent paradox: How can a non-linear impact law survive in the presence of a large number of simultaneously executed metaorders?

How Does a Stock Trade? Stock-Specific Peer Group Analysis and Its Application to Portfolio Liquidity

The authors introduce an activity-based approach to trading performance comparisons, in which the common denominator is an individual security. The framework facilitates answers to three questions. 1) Is there valuable information in peer trading comparisons if one analyzes performance on a stock-by-stock basis? Aggregated comparisons across institutions and brokers disguise important differences in the effectiveness of the trading process. 2) How does a stock trade? An answer lies in the characterization of single-stock profiles. The approach exploits institutional trading activity, combining such information with market data and repurposing old tools with the goal of reducing institutional trading costs. 3) How does one characterize the liquidity profile of a portfolio? The answer relies on observed liquidity, as evidenced by institutional trading activity. The solution depends on building the portfolio profile up from individual securities and yields not only the implementation costs of liquidation, for example, but also the horizon over which this may be accomplished.

Editor’s Letter

1. Brian R. Bruce 1. Editor-in-Chief We open the fall issue of The Journal of Trading with Domowitz and Giritharan’s activity-based approach to trading performance comparisons, in which the common denominator is an individual security. The approach exploits institutional trading activity,

Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity

AbstractUsing order flow imbalance as a measure of sentiment we show that positive and negative shocks to sentiment lead to lower co‐movement between portfolio and market returns in the post‐shock period. Furthermore, an asymmetry is present as positive shocks to sentiment have less impact on co‐movement changes than negative shocks. Moreover, shocks to retail sentiment and the sentiment of two types of institutional investors lead to a reduction in co‐movement. Positive shocks to institutional order flow imbalance lead to smaller reductions in co‐movement than associated with retail shocks. These effects exist even after controlling for firm‐specific and market‐wide news.

Dash for Cash: Month-End Liquidity Needs and the Predictability of Stock Returns

We present broad-based evidence that the monthly cash needs of institutions induce systematic patterns in global stock returns. First, we document strong reversals in stock index returns around the last monthly trading day that guarantees cash settlement before month end. Second, we present direct evidence that links these reversals to institutional trading activity and funding conditions. Third, we find that the reversals are stronger for larger and more liquid stocks, and those more commonly held by mutual funds, a popular implementation vehicle among institutions. Finally, we show that mutual funds’ sensitivity to month-end reversals predicts their performance.

Institutional impact and quote behavior implications of the options penny pilot project

Abstract In this study, we expand the analysis of the impact of the options penny pilot project (PPP) using a sample that covers the first three phases of the project, a control group of options that were not part of the project, and options market specific control variables. We show that proportional national best bid offer spreads decrease significantly for the pilot securities, with the control sample demonstrating a general increase in relative spreads. Regression analysis indicates that a decrease in relative spreads can be explained by the switch to penny quoting. We find that the average quote size significantly declines and most pilot securities experience significant increases in quote traffic during the pilot period. For equity options in the pilot group we do not find a pattern of change in the average trading volume that can be attributed to the PPP. The average trading volume shows a general increase for the ETF options in the pilot group during the pilot period. Based on the findings derived from a sample of opening and closing “large” trades, we do not find conclusive evidence that trading in penny increments has a negative impact on the volume of institutional trading activity on the options exchanges during the first few months of Phase I. Our results for relative spreads, average quote size, quote traffic and trading volume are robust to Phases I–III of the PPP.

Institutional Investment and Commonality in Liquidity: Evidence from Transaction Data

We study whether institutional investors’ trading activity causes the liquidity of broad groups of stocks to move together, consistently with demand-side explanations of commonality in stock liquidity. In contrast to the previous literature, which uses stocks’ institutional ownership as a proxy for institutional investors’ trading activity, we use data on actual institutional investors’ trades. We flnd that stocks that are highly traded by institutional investors exhibit strong commonality in liquidity. This result appears to be the consequence of correlated trading, as pairs of stocks connected through common institutional trading covary more together. Finally, we exploit the mutual fund scandal of 2003 to investigate the causal link between institutional trading activity and commonality in liquidity and flnd evidence suggesting that institutional investors’ trades cause stock liquidity co-variation.

Market liquidity and institutional trading during the 2007–8 financial crisis

This paper shows that institutional sell-side herding increased bid–ask spreads and liquidity risk during the 2007–8 financial crisis. Such an impact on liquidity is most pronounced in firms with large numbers of institutions that sold the same stocks, that is, have correlated trades. For the same reason, we find institutional investors with a dedicated, buy-and-hold, investment style to be the least likely to herd; their trading activity did not affect stock market liquidity during the crisis. Our results are robust to alternative explanations, different test specifications and consistent with recent theories highlighting the negative impact of institutional trading activity on market liquidity during a crisis.

Speed of convergence to market efficiency: The role of ECNs

Abstract Chordia, Roll and Subrahmanyam (2005, CRS) estimate the speed of convergence to market efficiency based on short-horizon return predictability of the 150 largest NYSE firms. We extend CRS to a broad panel of NYSE stocks and are the first to examine the relation between electronic communication networks (ECNs) and the corresponding informational efficiency of prices. Overall, we confirm CRS's result that price adjustments to new information occur on average within 5–15 min for large NYSE stocks. We further show that it takes about 20 min longer for smaller firms to incorporate information into prices. Most importantly, we demonstrate that the speed of convergence to market efficiency is significantly related to the type of trading platform where orders are executed, even after controlling for relative order flows, trading costs, volatility, informational effects, trading conditions, market quality, institutional trading activity, and other firm-specific characteristics. Our findings provide direct answers and insights to issues raised in a recent SEC concept release document.

Option‐Adjusted Delta Credit Spreads: a Cross‐Country Analysis

Abstract This study analyses the determinants of the variation in option‐adjusted credit spreads (OASs) using a unique database and enlarges the traditional analysis to include disaggregated indexes, new variables, and a complete set of markets (USA, UK, and the Eurozone). An extended set of regressors explains almost half the variability of OASs in the three markets. We find that institutional trading activity significantly affects corporate bond spreads, signalling either variation in perceptions of risk or the existence of an indirect measure of liquidity. We also find that US business cycle indicators significantly affect the variability of OASs in the UK and the Eurozone. Finally, we find evidence that stock returns have more influence on high‐yield bonds in the Eurozone than in the USA.

Market Liquidity and Institutional Trading During the 2007-8 Financial Crisis

This paper shows that institutional sell-side herding increased bid-ask spreads and liquidity risk during the 2007-8 financial crisis. Such an impact on liquidity is most pronounced in firms with large numbers of institutions that sold the same stocks, that is, have correlated trades. For the same reason, we find institutional investors with a dedicated, buy-and-hold, investment style to be the least likely to herd; their trading activity did not affect stock market liquidity during the crisis. Our results are robust to alternative explanations, different test specifications and consistent with recent theories highlighting the negative impact of institutional trading activity on market liquidity during a crisis.

Speed of Convergence to Market Efficiency: The Role of ECNs

Chordia, Roll and Subrahmanyam (2005, CRS) estimate the speed of convergence to market efficiency based on short-horizon return predictability of the 150 largest NYSE firms. We extend CRS to a broad panel of NYSE stocks and are the first to examine the relation between electronic communication networks (ECNs) and the corresponding informational efficiency of prices. Overall, we confirm CRS’s result that price adjustments to new information occur on average within five to fifteen minutes for large NYSE stocks. We further show that it takes about twenty minutes longer for smaller firms to incorporate information into prices. Most importantly, we demonstrate that the speed of convergence to market efficiency is significantly related to the type of trading platform where orders are executed, even after controlling for relative order flows, trading costs, volatility, informational effects, trading conditions, market quality, institutional trading activity, and other firm-specific characteristics. Our findings provide direct answers and insights to issues raised in a recent SEC concept release document.

Liquidity Provision of Limit Order Trading in the Futures Market Under Bull and Bear Markets

Abstract: This study investigates how limit orders affect liquidity in a purely order‐driven futures market. Additionally, the possible asymmetric relationship between market depth and transitory volatility in bull and bear markets and the effect of institutional trading on liquidity provision behavior are examined as well. The empirical results demonstrate that subsequent market depth increases as transient volatility increases in bull markets. Market depth exhibits significantly positive relationship to subsequent transient volatility in bull markets. Additionally, although trading volume positively influences transient volatility in bull markets, no such relationship exists in bear markets. Liquidity provision decreases when institutional trading activity intensifies during bear markets. Thus, liquidity provision for limit orders differs between bull and bear markets.

Institutional Investors and the Informational Efficiency of Prices

Using a broad panel of NYSE-listed stocks between 1983 and 2004, we study the relation between institutional shareholdings and the relative informational efficiency of prices, measured as deviations from a random walk. Stocks with greater institutional ownership are priced more efficiently, and we show that variation in liquidity does not drive this result. Onemechanismthroughwhichpricesbecomemoreefficientisinstitutionaltradingactivity, even when institutions trade passively. But efficiency is also directly related to institutional holdings, even after controlling for institutional trading, analyst coverage, short selling, variation in liquidity, and firm characteristics. (JEL G12, G14) Institutional shareholdings and trading have increased dramatically over the past several decades. In 1965, members of the Securities Industries Association held 16% of U.S. equities; in 2001, they held 61% according to the Securities Industry Association Fact Book (2002). Moreover, nonretail trading accounted for 96% of New York Stock Exchange (NYSE) trading volume in 2002 (Jones and Lipson 2004). How this broadened scope of institutional ownership and trading affects the quality of equity markets, however, is an open question. Using a broad cross-section of NYSE-listed stocks between 1983 and 2004, we link institutional ownership to the informational efficiency of transaction prices. Intraday prices of stocks with greater institutional ownership more closelytrackfundamentalvalues,inthattheymorepreciselyresemblearandom walk, than prices of stocks with less institutional ownership. Moreover, we use proprietary NYSE data to establish institutional trading activity as one source of the improved short-horizon information environment. These findings have

Institutional Investors and the Informational Efficiency of Prices

The percentage of U.S. equity held by institutional investors has quadrupled in the past four decades, and a prominent share of trading activity is due to institutions. Yet we know little about how institutions affect the informational efficiency of share prices, one important dimension of market quality. We study a broad cross-section of NYSE-listed stocks between 1983 and 2004 using measures of the relative informational efficiency of prices constructed from transaction data. We find that stocks with greater institutional ownership are priced more efficiently in the sense that their transaction prices more closely follow a random walk. This result cannot be attributed to liquidity effects and is not likely the result of reverse causality. We also show that institutional trading activity is one mechanism by which prices become more efficient, even when institutions trade passively or follow momentum strategies.