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.     

What Makes Investors Trade?

A unique data set allows us to monitor the buys, sells, and holds of individuals and institutions in the Finnish stock market on a daily basis. With this data set, we employ Logit regressions to identify the determinants of buying and selling activity over a two-year period. We find evidence that investors are reluctant to realize losses, that they engage in tax-loss selling activity, and that past returns and historical price patterns, such as being at a monthly high or low, affect trading. There also is modest evidence that life-cycle trading plays a role in the pattern of buys and sells.     

Aggregate insider trading: Contrarian beliefs or superior information?

We decompose realized market returns into expected return, unexpected cash-flow news and unexpected discount rate news to test the relation between aggregate market returns and aggregate insider trading. We find that (1) the predictive ability of aggregate insider trading is much stronger than what was reported in earlier studies, (2) aggregate insider trading is strongly related to unexpected cash-flow news, (3) market expectations do not cause insider trading contrary to what others have documented, and (4) aggregate insider trading in firms with high information uncertainty is more likely to be associated with contrarian investment strategy. These results strongly suggest that the predictive ability of aggregate insider trading is because of insider’s ability to predict future cash-flow news rather than from adopting a contrarian investment strategy. These results hold even after we control for non-informative trades and information uncertainty.     

Mutual Fund Stock‐Picking Skill: New Evidence from Valuation‐ versus Liquidity‐Motivated Trading

We propose a novel Trade Motivation Matrix that allows differentiating funds’ valuation‐motivated (VM) and liquidity‐motivated (LM) trades on single trade level. It thus enables analyses of stock‐picking skill on three levels: trade, stock, and fund. On trade level, we find significant outperformance of VM buys and significant underperformance of VM sells, indicating manager stock‐picking skills, especially during illiquid market periods. VM trades outperform LM trades, confirming negative performance effects due to flow risk, especially when market liquidity is low. On stock level, collective VM buying explains high future stock returns while collective VM selling is related to future losses, indicating wisdom of the crowd. On fund level, higher trading discretion, measured by a higher degree of VM trading, is observed for smaller, older funds holding higher cash buffers. Finally, higher trading discretion is related to higher future fund alpha, especially during illiquid times.     

Caught on tape: Institutional trading,stock returns,and earnings announcements

Many questions about institutional trading can only be answered if one tracks high-frequency changes in institutional ownership. In the United States, however, institutions are only required to report their ownership quarterly in 13-F filings. We infer daily institutional trading behavior from the “tape”, the Transactions and Quotes database of the New York Stock Exchange, using a sophisticated method that best predicts quarterly 13-F data from trades of different sizes. We find that daily institutional trades are highly persistent and respond positively to recent daily returns but negatively to longer-term past daily returns. Institutional trades, particularly sells, appear to generate short-term losses—possibly reflecting institutional demand for liquidity—but longer-term profits. One source of these profits is that institutions anticipate both earnings surprises and post-earnings announcement drift. These results are different from those obtained using a standard size cutoff rule for institutional trades.     

INSTITUTIONAL TRADING AND OPENING PRICE BEHAVIOR: EVIDENCE FROM A FAST‐EMERGING MARKET

Using daily and intraday data, we investigate the cross‐sectional relation between stock prices and institutional trading in the Taiwan stock market. Consistent with the investigative herding hypothesis, we find that institutional herding exists because of institutional positive feedback trading behavior rather than following trades made by other institutions, as suggested by the information cascade hypothesis. Moreover, the positive correlation between institutional trade imbalance and stock returns mainly comes from institutional positive feedback trading. The institutional trading decisions rely on returns measured not only over the lagged trading day but also over the opening session during the same day.     

Institutional Investor Trading in a Short Investment Horizon: Evidence from the Korean Stock Market

We examine the weekly trading activities of institutional investors in the Korean stock market. First, we find that average net trades by institutional investors this week are negatively related to one-week lagged returns, suggesting that they could be contrarian traders. Second, our finding shows that institutional investors’ net trades this week are positively related to the net trades next week, consistent with persistent trading and/or herding behavior. Third, we find that institutional net trades are positively related to the post one-week returns. Finally, our findings are most pronounced in the group of short-term institutional investors.     

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.     

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.     

Speculate against speculative demand

Measuring individual investors' speculative demand for stocks using the Google search volume index (hereafter “SVI”) on penny stocks, we examine how it relates to the return dynamics of U.S. stock indices. Speculative demand leads to a short-term return reversal. A simple trading strategy that sells a stock index when SVI is high and buys it otherwise generates annual excess returns of up to 20% over the buy-and-hold strategy. Applying the trading strategy to the corresponding ETFs and index futures yields similar results. Transaction costs, liquidity risk and strong time variation of the excess returns can potentially limit the exploitation of arbitrage opportunities.     

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.     

Investor Overconfidence and Trading Volume

The proposition that investors are overconfident about theirvaluation and trading skills can explain high observed tradingvolume. With biased self-attribution, the level of investoroverconfidence and thus trading volume varies with past returns.We test the trading volume predictions of formal overconfidencemodels and find that share turnover is positively related tolagged returns for many months. The relationship holds for bothmarket-wide and individual security turnover, which we interpretas evidence of investor overconfidence and the disposition effect,respectively. Security volume is more responsive to market returnshocks than to security return shocks, and both relationshipsare more pronounced in small-cap stocks and in earlier periodswhere individual investors hold a greater proportion of shares.(JEL G11, G12)     

Individual Investor Trading and Stock Returns

This paper investigates the dynamic relation between net individual investor trading and short‐horizon returns for a large cross‐section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk‐averse individuals provide liquidity to meet institutional demand for immediacy.     

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.     

Order imbalance and liquidity supply: Evidence from the bubble burst of Nasdaq stocks

In this study we analyze the effect of order imbalance on the quotation behavior of Nasdaq market makers. We find that Nasdaq market makers use both price and quantity quotes when dealing with order imbalances. However, order imbalance affects only price movement, not spreads. We also find that Nasdaq market makers quote more shares and compete more intensively on bid-side (ask-side) when public sells (buys) exceed public buys (sells). These suggest that market makers increase liquidity supply when order imbalances exist. More interestingly, we show that both market conditions and price movements affect investors' trading behavior.     

The Dynamics of Institutional and Individual Trading

We study the daily and intradaily cross‐sectional relation between stock returns and the trading of institutional and individual investors in Nasdaq 100 securities. Based on the previous day's stock return, the top performing decile of securities is 23.9% more likely to be bought in net by institutions (and sold by individuals) than those in the bottom performance decile. Strong contemporaneous daily patterns can largely be explained by net institutional (individual) trading positively (negatively) following past intradaily excess stock returns (or the news associated therein). In comparison, evidence of return predictability and price pressure are economically small.     

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.     

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.     

Did institutions herd during the internet bubble?

We examine the trading behavior of institutional investors during the internet bubble and crash of 1998–2001, and its impact on stock prices. Similar to some recent findings concerning the trading behavior of hedge funds and NASDAQ 100 stocks, we find that during the bubble all types of institutions herded with great intensity into internet stocks for a comprehensive sample of institutional investors and internet stocks. In addition to this, we present three entirely new results. First, institutional herding was much greater than what can be explained by momentum trading. Second, institutions as a group continued to increase their holdings of internet stocks for two quarters past the market peak during the first quarter of 2000, and three quarters past the peak for individual stock prices, suggesting that institutions were unable to time the price peaks. Finally and most importantly, we find positive abnormal returns contemporaneous with institutional herding and negative abnormal returns (reversals) at the point that herding ceased. This finding suggests that institutions’ trading created temporary price pressures, and may have contributed to the bubble.     

IPO Trading without Market Makers or Underwriter Price Support

We investigate the trading behavior and liquidity supply of Chinese initial public offerings (IPOs) that trade in an order‐driven market system with pure limit order books where no market makers or price support is allowed. We find large trades and quoted depths dominate the first day of trading, but this pattern quickly reverses as small trades and quoted depths are more prevalent on subsequent trading days. Quoted depths are positively related to the number of shares offered in the IPO and trade size, but are negatively related to underpricing. Trade size and transaction immediacy are positively related, and large and positive (negative) order imbalance is associated with more aggressive buys (sells). Finally, long‐run performance is not related to initial order imbalance. Overall, our results suggest that despite underwriters not participating in the IPO aftermarket, liquidity provision evolves very quickly and price discovery is immediately reflected in prices.