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.     

Daily Stock Trading by Investor Type and Information Asymmetry: Evidence from the Korean Market

We examine the influence of trading by heterogeneous investors on information asymmetry in the Korean stock market, which includes domestic and foreign institutional investors and individual investors. In particular, we examine the relationship between the daily trading volume and the level of information asymmetry reflected in the stock price. The results reveal that high-volume daily trading by domestic institutional and individual investors increases the degree of information asymmetry in the short term, but is more evident for individual investors. Foreign institutional investors tend to mitigate the information asymmetry. Finally, our findings are robust to an alternative measure of investor trading.     

In search of retail investors: The effect of retail investor attention on odd lot trades

We study the effect of retail investor attention on odd lot trading. We observe that increases in abnormal Google search volume predict odd-lot trading. Importantly, this relationship is share price-sensitive: For stocks priced below $11, an increase in abnormal search volume leads to less odd lot trading. For stocks priced above $46, on the other hand, an increase in abnormal search volume leads to more odd lot trading. For a stock priced at $78 – the mean share price in our sample – a one standard deviation increase of abnormal search volume increases the average share of odd lot trading by 10 basis points. This effect is even stronger for more expensive stocks. Our results are consistent with attention-induced trading when investors face wealth constraints and are robust to alternative channels including news and institutional investor attention.     

Institutional Investor Participation and Stock Market Anomalies

This paper investigates the impact of institutional trading volume on stock market anomalies. The paper proposes a measure that evaluates the percentage of total trading volume of a stock accounted for by institutional trades. The empirical analyses using a large sample of firms from 1980–2005 provide strong evidence that the strength of stock market anomalies such as price momentum, post‐earnings announcement drift, the value premium, and the investment anomaly is decreasing in institutional trading volume. Additionally, the effects of institutional trading volume are stronger than those of institutional ownership, the major measure of institutional investor participation in the finance literature. These findings suggest that institutional trading significantly improves stock price efficiency.     

投资者关注与市场反应——来自中国证券交易所交易公开信息的自然实验

涨停的股票能否被交易公开信息披露取决于收益率排名中的随机因素,与股票的基本面特征无关。本文利用这一机制设计自然实验检验了投资者关注对股价的影响。实证结果显示交易公开信息披露使股票受到投资者更多的关注,增加了小额资金的净流入,减少了大额资金的净流入和股价的短期收益率,抑制了股价短期波动率,同时降低了股价在长期发生反转的可能性。频繁登上交易公开信息的知名营业部买入的股票受到更多关注,相应的市场反应也更加显著。进一步的研究表明监管性信息披露引发的投资者关注通过降低市场信息不对称抑制了股价反转。     

Does Cross-Listing Really Enhance Market Efficiency for Stocks Listed in the Home Market? The Perspective of Noise Trading in the Chinese Stock Market

The investor recognition hypothesis and the bonding hypothesis, which help us understand the market quality of stocks that are cross-listed on different stock markets, imply improved market efficiency after cross-listing because of increased investor participation. However, the noise trading of inexperienced investors in the Chinese stock market negatively affects market efficiency. By employing propensity score matching and multivariate regression analysis, we show that the increased individual investor participation actually lowers market efficiency in their home market after cross-listing. This effect is more evident for stocks that were either listed first on the Chinese stock market or listed on the Chinese stock market and the Hong Kong stock exchange (SEHK) on the same date than for stocks that were listed first on the SEHK.     

基于佣金收入动机的机构投资者盈利预测偏离与股票交易量研究

本文基于信息反应模型研究了机构投资者盈利预测偏离与普通投资者交易需求之间的激励关系,并选取2006至2010年的相关盈利预测和股票交易数据进行实证分析。结果表明,机构投资者的盈利预测存在显著偏离前期市场平均预测值的倾向,而且这种偏离倾向会进一步诱发股票交易增量,从而增加机构投资者的佣金收入。这意味着普通投资者在参考机构投资者的盈利预测报告时,需要考虑其基于刺激交易量的自利因素。     

Institutional trading and stock returns

In this study, we explore the dynamics of the relation between institutional trading and stock returns. We find that stock returns Granger-cause institutional trading (especially purchases) on a quarterly basis. The robust and significant causality from equity returns to institutional trading can be largely explained by the time-series variation of market returns, that is, institutions buy more popular stocks after market rises. Stock returns appear to be negatively related to lagged institutional trading. A further analysis of the behavior of trading and the returns of the traded stocks reveals evidence that stocks with heavy institutional buying (selling) experience positive (negative) excess returns over the previous 12 months.     

The Effects of Stock Characteristics on the Direction and Extent of Herding by Foreign Institutional Investors in the Taiwan Stock Exchange

We use a dynamic herding measure to explore the causes of foreign institutional investor (FII) herding in the Taiwan stock market and examine the effects of stock characteristics on the direction and extent of such herding. We find that FII herding primarily results from cascades rather than habit investing or momentum trading. The result of a panel smooth transition regression shows that FIIs' negative cascades focus on their largest net purchases of stocks, but FIIs' positive cascades focus on winner and small-sized stocks. To increase portfolio returns, investors can use FIIs' cascades to inform their stock purchases.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

Trends in market reactions: stock dividends and rights offerings at Istanbul stock exchange

This paper examines the existence of different price reactions to the implementation of stock dividends and rights offerings as the stock market matures over time and the investor mix changes. For that purpose market reactions at the Istanbul Stock Exchange (ISE) are Investigated during three sub-periods displaying different developmental phases of the market defined in terms of institutional framework, transactions volumes and related investor profiles. Differences in price reactions and the accompanying trading volumes are tested as the investor mix changes and small investors enter ISE due to the cultivating of awareness about the stock market. Other possible causes of excess returns such as prior knowledge about the stocks being traded or a preferred trading range are also tested. Considering the characteristics of thinly traded emerging markets, non-parametric tests are employed besides traditional event study methodology and results are immune to the choice of relevant test statistics. The results indicate that the changing mix of investors shift the timing of market reaction from announcement to implementation of stock dividends and rights offerings. Since individual investors, who are attracted by lower relative prices, are not expected to be prompt in timing, excess returns persist over longer event windows and are accompanied by increasing trading volumes.     

Market Segmentation and Cross‐predictability of Returns

We present evidence supporting the hypothesis that due to investor specialization and market segmentation, value‐relevant information diffuses gradually in financial markets. Using the stock market as our setting, we find that (i) stocks that are in economically related supplier and customer industries cross‐predict each other's returns, (ii) the magnitude of return cross‐predictability declines with the number of informed investors in the market as proxied by the level of analyst coverage and institutional ownership, and (iii) changes in the stock holdings of institutional investors mirror the model trading behavior of informed investors.     

Institutional investors: Arbitrageurs or rational trend chasers

This paper studies the relationship between institutional investor holdings and stock misvaluation in the U.S. between 1980 and 2010. I find that institutional investors overweigh overvalued and underweigh undervalued stocks in their portfolio, taking the market portfolio as a benchmark. Cross-sectionally, institutional investors hold more overvalued stocks than undervalued stocks. The time-series studies also show that institutional ownership of overvalued portfolios increases as the portfolios' degree of overvaluation. As an investment strategy, institutional investors' ride of stock misvaluation is neither driven by the fund flows from individual investors into institutions, nor industry-specific. Consistent with the agency problem explanation, investment companies and independent investment advisors have a higher tendency to ride stock misvaluation than other institutions. There is weak evidence that institutional investors make a profit by riding stock misvaluation. My findings challenge the models that view individual investors as noise traders and disregard the role of institutional investors in stock market misvaluation.     

How Investors Trade Around Interim Earnings Announcements

Abstract:   This study focuses on non‐institutional trading behaviour around interim earnings announcements in the emerging market. We separate the stock trading activity of Finnish households into five trading classes and compare the results to institutional trading. Data covering the years 1996–2000 shows that earnings news triggers trading in every trading class. We also find some evidence that actively trading individuals especially (compared to passively trading ones) show increased buying and selling activity before the event compared to the non‐event period. After the event we find that Finnish households in the most active investor class tend to follow a contrarian strategy, especially selling after good news. This adds to previous evidence by Grinblatt and Keloharju (2000b) . Furthermore, the performance of the active investor classes is superior to that of passive ones. Finally, the institutional trading class is clearly less affected by the announcement than the active investor classes, suggesting that institutions utilize a broader information set than individual investors.     

US and Domestic Market Gains and Asian Investors’ Overconfident Trading Behavior

We find that subsequent to both US and domestic market gains, both Asian individual and institutional investors increase their trading and that this effect is more pronounced in bull markets, in periods of relatively favorable investor sentiment, in periods of extremely high market returns, and in markets with short‐sale constraints. We also find that individual investors trade more in response to market gains than institutional investors. Moreover, we find that further integration of Asian stock markets with US stock markets after the Asian financial crisis in 1998 is an important reason for Asian investors’ response to US market gains.     

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.     

Which past returns affect trading volume?

Anecdotal evidence suggests and recent theoretical models argue that past stock returns affect subsequent stock trading volume. We study 3,000 individual investors over a 51 month period to test this apparent link between past returns and volume using several different panel regression models (linear panel regressions, negative binomial panel regressions, Tobit panel regressions). We find that both past market returns as well as past portfolio returns affect trading activity of individual investors (as measured by stock portfolio turnover, the number of stock transactions, and the propensity to trade stocks in a given month). After high portfolio returns, investors buy high risk stocks and reduce the number of stocks in their portfolio. High past market returns do not lead to higher risk taking or underdiversification. We argue that the only explanations for our findings are overconfidence theories based on biased self-attribution and differences of opinion explanations for high levels of trading activity.     

The Price Is (Almost) Right

Most previous research tests market efficiency using average abnormal trading profits on dynamic trading strategies, and typically rejects the joint hypothesis of market efficiency and an asset pricing model. In contrast, we adopt the perspective of a buy‐and‐hold investor and examine stock price levels. For such an investor, the price level is more relevant than the short‐horizon expected return, and betas of cash flow fundamentals are more important than high‐frequency stock return betas. Our cross‐sectional tests suggest that there exist specifications in which differences in relative price levels of individual stocks can be largely explained by their fundamental betas.     

The Determinants of Conditional Autocorrelation in Stock Returns

We investigate whether return volatility, trading volume, return asymmetry, business cycles, and day‐of‐the‐week are potential determinants of conditional autocorrelation in stock returns. Our primary focus is on the role of feedback trading and the interplay of return volatility. We present empirical evidence using conditional autocorrelation estimates generated from multivariate generalized autoregressive conditional heteroskedasticity (M‐GARCH) models for individual U.S. stock and index data. In addition to return volatility, we find that trading volume and market returns are important in explaining the time‐varying patterns of return autocorrelation.     

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.