The dynamics of individual and institutional trading on the Shanghai Stock Exchange

We investigate the daily dynamic relation between returns and institutional and individual trades in the emerging Chinese stock market. Consistent with the hypotheses of trend-chasing and attention-grabbing trading, we find that the response of individual trading to return shocks is much stronger than that of institutional trading, and individuals are net buyers following return shocks. Second, we find that past individual buys and sells have predictive power, whereas past institutional buys and sells have predictive power for market returns in longer horizons. However, both institutional and individual trading activities are more strongly related to past trades than past returns, and individual trading is also influenced by institutional trading. Moreover, we find that institutional trading in the largest quintile leads the trading in the smallest quintile, but no such lead–lag relation is found for individual trades. Finally, we find that the average cumulative abnormal trading volume of individuals is much larger than that of institutions around the firms' earnings announcement, suggesting that less-informed individual investors are more heavily influenced by firm-specific information disclosures and attention-grabbing events.     

The Interim Trading Skills of Institutional Investors

Using a large proprietary database of institutional trades, this paper examines the interim (intraquarter) trading skills of institutional investors. We find strong evidence that institutional investors earn significant abnormal returns on their trades within the trading quarter and that interim trading performance is persistent. After transactions costs, our estimates suggest that interim trading skills contribute between 20 and 26 basis points per year to the average fund's abnormal performance. Our findings also indicate that any trading skills documented by previous studies that use quarterly data are biased downwards because of their inability to account for interim trades.     

Institutional trading and share returns

Using a unique database of daily transactions from Australian equity managers, we investigate the relation between institutional trading and share returns. The 34 institutional investors included in our sample exhibit a statistically and economically significant ability to predict large capitalization share returns for the ten days following their trades. Detailed analysis indicates that investment manager style is important in understanding the link between institutional trading and stock returns. The contemporaneous relation between institutional trading and returns depends on trade size, broker use, and investment style. We find growth-oriented managers are momentum traders, while style-neutral and value managers are contrarian.     

Short-run Returns around the Trades of Corporate Insiders on the London Stock Exchange

Previous work examined the long-run profitability of strategies mimicking the trades company directors in the shares of their own company, as a way of testing for market efficiency. The current paper examines patterns in abnormal returns in the days around these trades on the London Stock Exchange.
We find movements in returns that are consistent with directors engaging in short-term market timing. We also report that some types of trades have superior predictive content over future returns. In particular, medium-sized trades are more informative for short-term returns than large ones, consistent with Barclay and Warner's (1993) 'stealth trading' hypothesis whereby informed traders avoid trading in blocks.
Another contribution of this study is to properly adjust the abnormal return estimates for microstructure (spread) transactions costs using daily bid-ask spread data. On a net basis, we find that abnormal returns all but disappear.     

Whose money is smart? Individual and institutional investors’ trades based on analyst recommendations

This study explores how institutional and individual investors respond to analyst recommendations. Using a unique account-level trading dataset taken from the Shanghai Stock Exchange, we obtain direct evidence to show that (1) active institutional investors are significantly net buyers (net sellers) on “strong buy” and “buy” (“hold” and “sell”) recommendations; (2) active institutional investors condition their trades based on the buy-side pressure of analysts; (3) institutional investors earn abnormal returns by incorporating analysts’ buy-side pressure into their trading reactions to analyst recommendations; and (4) individual investors, in contrast, exhibit abnormal trade reactions opposite to those of active institutional investors. Our results are robust to alternative measures and different specifications. This study provides evidence that active institutional investors are more sophisticated processors of information and provides support for regulators’ concerns about the sub-optimal investment decisions made by individual investors who are unaware of the potential conflicts of interest analysts may face.     

Is trading behavior stable across contexts? Evidence from style and multi-style investors

In this paper we study priming of identity within the context of inherent vs. contextual financial decision making. We use a sample of individual trading accounts in equity-style funds taken from one fund family to test the hypothesis that trading styles are inherent vs. contextual. Our sample contains investors who invest either in a growth fund, a value fund, or both. We document behavioral differences between growth fund investors and value fund investors. We find that their trades depend on past returns in different ways: growth fund investors tend towards momentum trading and value fund investors tend towards contrarian trading. These differences may be due to inherent clientele characteristics, including beliefs about market prices, specific personality traits and cognitive strategies that cause them to self-select into one or the other style. We use a sample of investors that trade in both types of funds to test this proposition. Consistent with the contextual hypothesis, we find that investors who hold both types of funds trade growth fund shares differently than value fund shares.     

Institutional stock trading on loan market information

One of the most important developments in the corporate loan market over the past decade has been the growing participation of institutional investors. As lenders, institutional investors routinely receive private information about borrowers. However, most of these investors also trade in public securities. This leads to a controversial question: Do institutional investors use private information acquired in the loan market to trade in public securities? This paper examines the stock trading of institutional investors whose portfolios also hold loans. Using the Securities and Exchange Commission filings of loan amendments, we identify institutional investors with access to private information disclosed during loan amendments. We then look at abnormal returns on subsequent stock trades. We find that institutional participants in loan renegotiations subsequently trade in the stock of the same company and outperform trades by other managers and trades in other stocks by approximately 5.4% in annualized terms.     

Empirical Identification of Non-Informational Trades Using Trading Volume Data

This paper empirically identifies non-informational and informational trades using stock returns and trading volume data of the U.S., Japanese, and U.K. stock markets and five individual firms. We achieve the identification by imposing a restriction from theoretical considerations. Our results show that trading volume is mainly driven by non-informational trades, while stock price movements are primarily driven by informational trades. We also find that, around the 1987 stock market crash, trading volumes due to non-informational trades increased dramatically, while the decline in stock market prices was due mainly to informational trades. Increases in volatilities both in returns and in trading volumes during and after the crash are mainly due to non-informational trades. Regarding the trading volume-serial correlation in the stock returns relationship, we find evidence that is consistent with theoretical predictions that non-informational components can account for high trading volume accompanied by a low serial correlation of stock returns.     

Institutional Herding

Institutional investors' demand for a security this quarteris positively correlated with their demand for the securitylast quarter. We attribute this to institutional investors followingeach other into and out of the same securities ("herding") andinstitutional investors following their own lag trades. Althoughinstitutional investors are "momentum" traders, little of theirherding results from momentum trading. Moreover, institutionaldemand is more strongly related to lag institutional demandthan lag returns. Results are most consistent with the hypothesisthat institutions herd as a result of inferring informationfrom each other's trades.     

Informed Futures Trading and Price Discovery: Evidence from Taiwan Futures and Stock Markets

This article focuses on the information effects between the futures market and its spot market. Intraday data are used to investigate the lead-lag relationships between the returns and trading activity of Taiwan stock index futures and the spot returns. We focus on the transmission direction and the sources of information. Consistent with most previous studies, our results show that other than the contemporaneous relationship predicted by carry-cost theory and efficient market theory, futures returns significantly lead spot returns, which implies that informed trades may occur in the futures market. Using private transaction information, net open buy, as a proxy for futures trading activity and distinguishing different types of futures traders, we find that foreign institutional traders are the major source of informed trades because their trading has predictive power for future movements in both spot and futures prices. Traders in other categories are information laggards.     

Insider trading,future earnings,and post-earnings announcement drift

This paper examines the association between insider trading prior to quarterly earnings announcements and the magnitude of the post-earnings announcement drift (PEAD). We conjecture and find that insider trades reflect insiders’ private information about the persistence of earnings news. Thus, insider trades can help investors better understand and incorporate the time-series properties of quarterly earnings into stock prices in a timely and unbiased manner, thereby mitigating PEAD. As predicted, PEAD is significantly lower when earnings announcements are preceded by insider trading. The reduction in PEAD is driven by contradictory insider trades (i.e., net buys before large negative earnings news or net sells before large positive earnings news) and is more pronounced in the presence of more sophisticated market participants. Consistent with investors extracting and trading on insiders’ private information, pre-announcement insider trading is associated with smaller market reactions to future earnings news in each of the four subsequent quarters. Overall, our findings indicate insider trading contributes to stock price efficiency by conveying insiders’ private information about future earnings and especially the persistence of earnings news.     

The role of institutional investors in seasoned equity offerings

Do institutional investors possess private information about seasoned equity offerings (SEOs)? If so, do they use this private information to trade in a direction opposite to this information (a manipulative trading role) or in the same direction (an information production role)? We use a large sample of transaction-level institutional trading data to distinguish between these two roles of institutional investors. We explicitly identify institutional SEO allocations for the first time in the literature. We analyze the consequences of the private information possessed by institutional investors for SEO share allocation, institutional trading before and after the SEO and realized trading profitability, and the SEO discount. We find that institutions are able to identify and obtain more allocations in SEOs with better long-run stock returns, they trade in the same direction as their private information, and their post-SEO trading significantly outperforms a naive buy-and-hold trading strategy. Further, more pre-offer institutional net buying and larger institutional SEO allocations are associated with a smaller SEO discount. Overall, our results are consistent with institutions possessing private information about SEOs and with an information production instead of a manipulative trading role for institutional investors in SEOs.     

Why Do Individual Investors Disregard Accounting Information? The Roles of Information Awareness and Acquisition Costs

We investigate the frictions that impede individual investors’ use of accounting information and, in particular, their costs of monitoring and acquiring accounting disclosures. We do so using an archival setting in which individuals are presented with automated media articles that report both current earnings news and past stock returns. Although these investors have earnings information readily available, we find no evidence that their trades incorporate it. Instead we find that their trading responds to the trailing stock returns presented in the articles. Our study raises questions about the efficacy of regulations that aim to aid less sophisticated investors by increasing their awareness of and access to accounting information.     

Daily institutional trades and stock price volatility in a retail investor dominated emerging market

We examine the short-run dynamic relation between daily institutional trading and stock price volatility in a retail investor-dominated emerging market. We find a significantly negative relation between volatility and institutional net trading that is mainly due to the unexpected institutional trading. The price volatility–institutional trade relation differs for institutional buys and institutional sells, and for small and large stocks. Institutional investors herd-trade in large stocks, but do not systematically engage in positive-feedback trading. We argue that the net impact of informational and noninformational institutional trades determines the relation between volatility and institutional trading, and that the relation is negative when informational trading by institutions prevails.     

Institutional Herding in the ADR Market

This study examines institutional herding in the ADR market between 1985 and 1998. We find a significant positive relation between changes in institutional ownership and ADR returns over the same period. The positive relation persists after we control for the momentum effect in the US stock markets. We also find that in the ADR market, past winners (losers) in the herding period continue to be the winners (losers) in the post-herding period. The lack of a returns reversal suggests institutional herding is related to momentum trading. However, the positive relation between institutional ownership changes and ADR returns remains after controlling for momentum trading in the ADR market. Our results also rule out that positive feedback trading is related to institutional herding in the ADR market.     

Insider trading and future stock returns in firms with concentrated ownership levels

We investigate the relationship between insider trading and stock returns in firms with concentrated ownership. To this end, we employ data from East Asian countries which span the period January 2003 to May 2012. Consistent with the previous literature, we find a significantly negative relation between the selling activity of insiders and stock returns. However, contrary to studies which focus on highly developed markets, we find that the buying activity of insiders is also inversely related to future stock returns. Our analysis shows that top directors with higher ownership levels drive this result, suggesting that the trading activity of insiders is not always associated with profit-making motives and can be explained by their level of ownership. Furthermore, we demonstrate that a trading strategy which focuses solely on purchases made by top directors with high ownership levels yields negative returns. The paper has important implications for outside investors who mimic the trading activity of insiders with the aim to realise profits.     

Trading on inside information: Evidence from the share-structure reform in China

We examine stock trading activities in days before Chinese listed firms made public announcement to start share-structure reform. There is significant evidence that, relative to a benchmark period, institutional investors bought more event firms’ shares in the last two trading days prior to announcement. Randomization tests show significant differences in institutional trading activities between event firms and matched control firms, which suggests that some institutions had inside information. Moreover, large trades account for a significant proportion of daily stock price changes in the last 2 days. The evidence is consistent with the prediction by Holden and Subrahmanyam (1992) that, when multiple informed investors acquire the same piece of information, they will trade aggressively. We also find that over the reform period, the median share value change of event firms is 6% higher than that of control firms. Our findings have important implications for enforcement of insider trading regulations in China.     

TAX-LOSS SELLING,INSTITUTIONAL INVESTORS,AND THE JANUARY EFFECT: A NOTE

In this note we test the hypothesis that trading by tax-motivated individual investors is responsible for the January effect. We examine the ownership structure of a large sample of firms over a four-year period and find that the small firms that usually exhibit high January returns have low institutional ownership. After controlling for firm size, we still find that institutional ownership is significantly related to January abnormal returns. These results suggest that one reason the January effect may concentrate in small firms is because these firms are held by tax-motivated individual investors.     

The Effect of Decimalization on Trade Size and Adverse Selection Costs

Abstract:   We examine adverse selection costs around NYSE decimalization. Further, we analyze the relation between adverse selection costs and trade size. We find a significant increase in the percentage adverse selection cost and a reduction in dollar adverse selection cost (percentage adverse selection multiplied by the spread) following complete decimalization on the NYSE. On estimating the adverse selection components by trade size classes, we find a decline in dollar adverse selection costs in trades of all sizes, with the strongest evidence coming from medium size trades, followed by small and large size trades. One implication of our findings is that there appears to be less stealth trading following complete decimalization and less institutional trading overall.     

Institutional trading in firms rumored to be takeover targets

In this paper we examine institutional trading in proximity to takeover rumors by combining the ANcerno dataset of transaction-level institutional trades with a unique sample of takeover rumor ‘scoops’. We find that institutions are net buyers in firms which subsequently become subject to takeover speculation and that institutional trading predicts which rumored firms will eventually receive takeover bids. Segregating funds according to their propensity to trade, we show that those less likely to purchase rumored targets by chance over the pre-rumor period are more likely to identify firms which will receive bid proposals and that they trade more profitably over both the pre- and post-rumor periods. We test for the presence of informed trading in a variety of ways and conclude that institutional investors appear to trade on material private information which identifies the firms soon to be the target of takeover speculation.