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.     

Trading volume and short-horizon contrarian profits: Evidence from the Malaysian market

We provide evidence on short-term predictability of stock returns on the Malaysian stock market. We examine the relation between return predictability and the level of trading activity. This is particularly relevant in emerging stock markets, where thin trading is more pervasive. We find that the returns from a contrarian portfolio strategy are positively related to the level of trading activity in the securities. Specifically, the contrarian profits on actively and frequently traded securities are significantly higher than that generated from the low trading activity securities. We find that the differential behavior of high- and low-volume securities is not subsumed by the size effect, although for the small firms, the volume–predictability relation is most pronounced. We also suggest that the price patterns may be related to the institutional arrangement in the Malaysian stock market.     

Stock returns and trading at the close

This paper analyzes stock returns at the close across the stocks of the Russell 1000 using (a) Transaction-level data for the period June 1997–July 1998, and (b) The complete record of all market-on-close (MOC) order imbalance indications. The last 5 min of the trading day explains a disproportionate fraction of the variation in daily returns, consistent with the hypothesis that institutional trading interest induces a common component to stock returns at the end of the day. This phenomenon reflects a higher demand for immediacy in the closing period. We find systematic return reversals following order imbalance publications consistent with temporary price pressure related to liquidity trading.     

Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.     

A new paradigm for forecasting security returns in a market regulated by price limits

Numerous futures markets in the US and many stock markets around the world set a “limit” price before each trading session, based on the settlement price at the end of the previous trading day. Price limits are boundaries set by market regulators to restrict large daily fluctuations in the price of securities. Once the return limit is triggered, traders cannot observe the equilibrium return that would have prevailed in the absence of such regulation. We develop an innovative approach for forecasting security returns (and prices) in a market regulated by price limits. Our forecasting model allows for multiple limit-hits. The model is robust, straightforward and easy for practitioners to use. A few numerical predictions are provided for hypothetical securities, and for seven traded futures contracts.     

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.     

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 Joint Cross Section of Stocks and Options

Stocks with large increases in call (put) implied volatilities over the previous month tend to have high (low) future returns. Sorting stocks ranked into decile portfolios by past call implied volatilities produces spreads in average returns of approximately 1% per month, and the return differences persist up to six months. The cross section of stock returns also predicts option implied volatilities, with stocks with high past returns tending to have call and put option contracts that exhibit increases in implied volatility over the next month, but with decreasing realized volatility. These predictability patterns are consistent with rational models of informed trading.     

Individuals’ Trading Prior to Earnings Announcements

This paper investigates the relationship between individuals’ net trading and stock price movements before and after annual earnings announcements for the Taiwan Stock Exchange. We conduct an event study on the effects of pre‐event individual trade imbalances on pre‐ and post‐announcement abnormal returns. With a unique and comprehensive dataset, we accurately classify executed orders by aggressiveness of order price. The evidence indicates that while individuals, as a group, are not informed about impending earnings announcements, individuals who place aggressive orders are informed as their net trading coincides with contemporaneous and future stock returns. Aggressive individuals lose their edge during the financial crisis. More importantly, the advantage (disadvantage) for individuals who adopt aggressive (passive) orders weakens when foreign institutions own concentrated equity in firms. We also find that net individual trading contains information about abnormal returns that either past returns or volume does not subsume. Controlling for past returns, trading volume and volatility, or using an alternative measure of net individual trading does not change our conclusions.     

Volume and Autocovariances in Short-Horizon Individual Security Returns

This article tests for the relations between trading volume and subsequent returns patterns in individual securities' short-horizon returns that are suggested by such articles as Blume, Easley, and O'Hara (1994) and Campbell, Grossman, and Wang (1993) . Using a variant of Lehmann's (1990) contrarian trading strategy, we find strong evidence of a relation between trading activity and subsequent autocovariances in weekly returns. Specifically, high-transaction securities experience price reversals, while the returns of low-transactions securities are positively autocovarying. Overall, information on trading activity appears to be an important predictor of the returns of individual securities.     

Profitability of Nonlinear Dynamics Under Technical Trading Rules: Evidence from Pacific Basin Stock Markets

This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using Pacific Basin stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property, and that the asymmetric reverting property of stock returns is exploitable in generating profitable buy and sell signals for technical trading rules. We show that the positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric dynamics of stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical analysis.     

Trading patterns of big versus small players in an emerging market: An empirical analysis

This study uses a Vector Autoregressive (VAR) model to examine interdependencies among institutional investors, big individual investors, and small individual investors, and the effects of their trading on stock returns on the Taiwan Stock Exchange (TSE). The results imply that, during the sample period, big individual investors are the most well informed players; their trading affects not only stock returns but also small individual investors. Small individual investors are not well informed and are slow learners. Their orders to trade tend to provide liquidity to institutional and big individual investors, but there is no compensation for their liquidity services. We find that institutional investors follow neither positive-feedback nor negative-feedback trading strategies. Overall, the responses to shocks, except for those of small individual investors, decay quickly, indicating that the TSE can absorb shocks quickly and efficiently. Our analysis implies that small individual investors would be better off institutionalizing their investment decisions (e.g., by investing in mutual funds).     

Nonlinear mean reversion in stock prices

This paper provides new evidence on the time-series predictability of stock market returns by introducing a test of nonlinear mean reversion. The performance of extreme daily returns is evaluated in terms of their power to predict short- and long-horizon returns on various stock market indices and size portfolios. The paper shows that the speed of mean reversion is significantly higher during the large falls of the market. The parameter estimates indicate a negative and significant relation between the monthly portfolio returns and the extreme daily returns observed over the past one to eight months. Specifically, in a quarter in which the minimum daily return is −2% the expected excess return is 37 basis points higher than in a month in which the minimum return is only −1%. This result holds for the value-weighted and equal-weighted stock market indices and for each of the size decile portfolios. The findings are also robust to different sample periods, different indices, and investment horizons.     

REGIME CHANGES IN STOCK RETURNS

This paper studies three sources of instability in parameter estimates of stock return models (1) time-varying expected mean returns, (2) time-varying return volatility and (3) changing institutional factors. We model United States stock returns as a function of a constant expected return and financing costs resulting from an institutional feature, delayed delivery. We examine two eight-year periods and find that both contain a regime shift driven by an abrupt change in volatility. The first occurs during an international monetary crisis amid important Watergate developments. The second is on the first trading day after the reappointment of Paul Volcker as the chairman of the United States Federal Reserve Board.     

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.     

THE EMPIRICAL RELATIONSHIP BETWEEN TRADING VOLUME,RETURNS AND VOLATILITY

This paper presents an empirical analysis of the relationship between trading volume, returns and volatility in the Australian stock market. The initial analysis centres upon the volume-price change relationship. The relationship between trading volume and returns, irrespective of the direction of the price change, is significant across three alternative measures of daily trading volume for the aggregate market. This finding also provides basic support for a positive relationship between trading volume and volatility. Furthermore, evidence is found supporting the hypothesis that the volume-price change slope for negative returns is smaller than the slope for non-negative returns, thereby supporting an asymmetric relationship which is hypothesised to exist because of differential costs of taking long and short positions. Analysis at the individual stock level shows weaker support for the relationship. A second related hypothesis is tested in which the formation of returns is conditional upon information arrival which similarly affects trading volume. The hypothesis is tested by using the US overnight return to proxy for expected “news” and trading volume to proxy for news arrival during the day. The results show a reduction in the significance and magnitude of persistence in volatility and hence are consistent with explaining non-normality in returns (and ARCH effects) through the rate of arrival of information. The findings in this paper help explain how returns are generated and have implications for inferring return behaviour from trading volume data.     

Does Net Buying Pressure Affect the Shape of Implied Volatility Functions?

This paper examines the relation between net buying pressure and the shape of the implied volatility function (IVF) for index and individual stock options. We find that changes in implied volatility are directly related to net buying pressure from public order flow. We also find that changes in implied volatility of S&P 500 options are most strongly affected by buying pressure for index puts, while changes in implied volatility of stock options are dominated by call option demand. Simulated delta‐neutral option‐writing trading strategies generate abnormal returns that match the deviations of the IVFs above realized historical return volatilities.     

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.     

The Impact of Trades on Daily Volatility

This article proposes a trading-based explanation for the asymmetriceffect in daily volatility of individual stock returns. Previousstudies propose two major hypotheses for this phenomenon: leverageeffect and time-varying expected returns. However, leveragehas no impact on asymmetric volatility at the daily frequencyand, moreover, we observe asymmetric volatility for stocks withno leverage. Also, expected returns may vary with the businesscycle, that is, at a lower than daily frequency. Trading activityof contrarian and herding investors has a robust effect on therelationship between daily volatility and lagged return. Consistentwith the predictions of the rational expectation models, thenon-informational liquidity-driven (herding) trades increasevolatility following stock price declines, and the informed(contrarian) trades reduce volatility following stock priceincreases. The results are robust to different measures of volatilityand trading activity. (JEL C30, G11, G12)