Trading of foreign investors and stock returns in an emerging market - Evidence from Vietnam

This article investigates the impact of foreign investors' trading on stock returns in Vietnam, a key emerging market. We utilize a time series data set of foreign investors' trading volume and market returns of the Ho Chi Minh City stock exchange over an extended time frame before and after global financial crisis. The results indicate that foreign investors are positive feedback traders in Vietnam stock market. The findings also reveal the timing ability and trading strategy of foreign investors. The paper offers strong implications for market participants and portfolio investment.     

Trading behaviour and market sentiment: Firm-level evidence from an emerging Islamic market

We provide firm-level evidence from an emerging Islamic market that individual investors' trading behaviour causes weekend sentiment. Using data for 285 companies listed on the Dhaka Stock Exchange (DSE) for the period from 2002 to 2019 and applying appropriate econometric techniques, the paper has found evidence of weekend effect both on return and volatility. The results confirm that individual investors' sentiment drives the weekend effect in DSE. ‘Information content theory’ and ‘information processing hypothesis’ work for investors so that the market return and volatility become significantly different on Sunday. The market sentiment effect is significant for smaller firms and low dividend yield firms where individual investors are prevalent, suggesting that trading behaviour of individual investors determines weekend sentiment. A positive feedback relationship exists between returns on Sunday and the previous Thursday for both institutions and individuals. Our results are robust in various alternative specifications.     

Do Limit Orders Alter Inferences about Investor Performance and Behavior?

Individual investors lose money around earnings announcements, experience poor posttrade returns, exhibit the disposition effect, and make contrarian trades. Using simulations and trading records of all individual investors in Finland, I find that these trading patterns can be explained in large part by investors' use of limit orders. These patterns arise mechanically because limit orders are price‐contingent and suffer from adverse selection. Reverse causality from behavioral biases to order choices does not appear to explain my findings. I propose a simple method for measuring a data set's susceptibility to this limit order effect.     

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.     

Institutional investors and post-ICO performance: an empirical analysis of investor returns in initial coin offerings (ICOs)

We examine the role of institutional investors in initial coin offerings (ICOs). Taking a financial investor's perspective, we assess the determinants of post-ICO performance via buy-and-hold abnormal returns (BHAR) in a sample of 565 ICO ventures. Conceptually, we argue that institutional investors' superior screening (selection effect) and coaching abilities (treatment effect) enable them to partly overcome the information asymmetry of the ICO context and extract informational rents from their ICO investments. We find that institutional investor backing is indeed associated with higher post-ICO performance. Disentangling selection and treatment effects econometrically, we find that both of these effects explain the positive impact institutional investors have on post-ICO performance. Overall, our results highlight the importance of institutional investors in the ICO context.     

Informed local trading prior to earnings announcements

Do individual investors have better information about local stocks? Our results demonstrate that they do. Large trading imbalances by investors living close to a firm's headquarters predict the stock's earnings announcement return. Stocks with the most net buying by local investors average significantly higher market-adjusted announcement returns than stocks with the most net selling by local investors. This return difference is pronounced for small and medium-sized firms, but absent among large firms, which have significant analyst coverage. Local investors' information advantage comes at the expense of nonlocal traders.     

Institutional trading,information production,and corporate spin-offs

We use a large sample of transaction-level institutional trading data to analyze, for the first time in the literature, the role of institutional investors as producers of information around corporate spin-offs. Our results may be summarized as follows. First, there is a significant imbalance in post-spin-off institutional trading between the equity of new parent firms versus subsidiaries, suggesting that spin-offs increase institutional investors' welfare by relaxing a trading constraint. This imbalance in institutional trading is driven by differences in information asymmetry across the two spun-off firm divisions. Second, institutional trading around spin-offs has significant predictive power for the announcement effect of a spin-off and for post-spin-off long-run stock returns. Third, institutional investors are able to realize significant abnormal profits by trading in the subsidiary firm equity in the first quarter post-spin-off. Overall, we show that spin-offs enhance information production by institutional investors, who profit from this enhanced information production.     

Confidence and Investors' Reliance on Disciplined Trading Strategies

Researchers and practitioners in accounting and finance often investigate or advocate particular disciplined trading strategies, but little work investigates the determinants of individual investors' trading‐strategy reliance. We report two experiments, which provide evidence that the dual‐source model of overconfidence (Sniezek and Buckley [1991]) predicts the circumstances in which investors are more likely to rely on disciplined trading strategies. Our results indicate that reliance is more likely when investors trade portfolios of securities rather than trading on a case‐by‐case basis, particularly when investors have received feedback that their previous (unaided) trading decisions have been unprofitable. These results are driven by the number of shares that investors transact rather than by investors' directional agreement with the recommendations of the trading strategy, suggesting that the effects of a portfolio approach and trading experience occur by mitigating investors' overconfidence. The effects violate an aspect of economic rationality because our experiments ensure that investors in all conditions trade the same set of securities based on the same set of information.     

Margin Requirements and the Security Market Line

Between 1934 and 1974, the Federal Reserve changed the initial margin requirement for the U.S. stock market 22 times. I use this variation to show that investors' leverage constraints affect the pricing of risk. Consistent with earlier theoretical predictions, I find that tighter leverage constraints result in a flatter relation between betas and expected returns. My results provide strong empirical support for the idea that the constraints investors face may help explain the empirical failure of the capital asset pricing model.     

The turn-of-the-year effect and tax-loss-selling by institutional investors

Prior studies attribute the turn-of-the-year effect whereby small capitalization stocks earn unusually high returns in early January to tax-loss-selling by individual investors and window-dressing by institutional investors. My results suggest that a significant portion of the effect on turn-of-the-year returns that prior studies attribute to window-dressing is actually attributable to tax-loss-selling by institutional investors. Among small capitalization stocks, I find that institutional investors with strong tax incentives and weak window-dressing incentives realize significantly more losses in the fourth quarter than in the first three quarters of the calendar year, and that their fourth quarter realized losses have a significant impact on turn-of-the-year returns. A one percentage point change in these institutional investors' fourth quarter realized losses scaled by a firm's market capitalization results in an increase of 47 basis points in the firm's average daily return over the first three trading days of January, which represents a 46 percent change for the mean firm.     

Do Individual Investors Have Asymmetric Information Based on Work Experience?

Using a novel data set covering all individual investors' stock market transactions in Norway over 10 years, we analyze whether individual investors have a preference for professionally close stocks, and whether they make excess returns on such investments. After excluding own‐company stock holdings, investors hold 11% of their portfolio in stocks within their two‐digit industry of employment. Given the poor hedging properties of such investments, one would expect abnormally high returns. In contrast, all estimates of abnormal returns are negative, in many cases statistically significant. Overconfidence seems the most likely explanation for the excessive trading in professionally close stocks.     

Are investors consistent in their trading strategies? An examination of individual investor-level data

While it has been demonstrated that momentum or contrarian trading strategies can be profitable in a range of institutional settings, less evidence is available concerning the actual trading strategies investors adopt. Standard definitions of momentum or contrarian trading strategies imply that a given investor applies the same strategy to both their buy and sell trades, which need not be the case. Using investor-level, transaction-based data from China, where tax effects are neutral, we examine investors' buy-sell decisions separately to investigate how past returns impact differentially on the trading strategies investors adopt when buying and selling stock. After controlling for a wide range of stock characteristics, extreme price changes and portfolio value, a clear asymmetry in trading is observed; with investors displaying momentum behavior when buying stocks, but contrarian behavior when selling stocks. This asymmetry in behavior is not driven purely by reactions to stock characteristics or extreme stocks. We discuss behavioral and cultural explanations for our findings.     

Announcing the announcement

What drives investors’ attention? We study how far in advance earnings calendars are pre-announced and find that investors are more attentive to earnings news when such details are disclosed well ahead of time. This variation in investors' attention affects short-run and long-run stock returns, thereby creating incentives for firms to strategically pre-announce the report date on short notice when the earnings news is bad. Consistent with this idea, firms pre-announce their report dates well ahead of time when earnings are good and do it at the very last moment when earnings are bad. A trading strategy that exploits such variations yields abnormal returns of 1.5% per month.     

Insightful Insiders? Insider Trading and Stock Return around Debt Covenant Violation Disclosures

This study asks whether insider trading associates with an information advantage around first‐time debt covenant violation disclosures in SEC filings, which potentially results from early access to information about the debt covenant violation disclosure. We document two results. First, we find net insider selling up to 12 months before a debt covenant violation disclosure, which precedes investors' negative returns before disclosure; and net insider buying up to 12 months after disclosure, which precedes investors' positive returns after disclosure. Second, we show that net insider trading one to two months before and after the violation disclosure associates predictably with investors' short‐term reaction to the covenant violation announcement.     

Opening price manipulation and its value influences

We investigate how opening price manipulation influences market behaviors and investors' returns. Analyzing direct evidence comprising 87 opening price manipulation cases, and indirect evidence consisting of 19,003 suspected cases detected by an opening price manipulation identification model that we construct, we examine the impact of manipulation on mispricing, investors' welfare, trading activity and price volatility. Our results indicate that manipulated stocks experience significantly lower returns and a higher probability of price reversal after manipulation. Investors who purchase manipulated stocks at their opening price, or the volume-weighted average price, on the manipulation day make losses on their investments. Further, manipulation increases market trading activity and price volatility due to the influx of retail investors. Our additional analysis demonstrates that enhancing the intensity of external supervision and internal governance can mitigate mispricing caused by opening price manipulation. Our study provides novel evidence of the economic consequences of open market manipulation and policy implications for governments and regulators to develop effective supervisory processes to reduce manipulation and mitigate its impact on efficient markets.     

The economic value of range-based covariance between stock and bond returns with dynamic copulas

The covariance between stock and bond returns plays important roles in the setting up of asset allocation strategies and portfolio diversification. In the present study, we propose a multivariate range-based volatility model incorporating dynamic copulas into a range-based volatility model to describe the volatility and dependence structures of stock and bond returns. We then go on to assess the economic value of the covariance forecasts based on our proposed model under a mean-variance framework. The out-of-sample forecasting performance reveals that investors would be willing to pay between 39 and 2081 basis points per year to switch from a dynamic trading strategy under the return-based volatility model to a dynamic trading strategy under the range-based volatility model, with more risk-averse investors being willing to pay even higher switching fees. Furthermore, additional economic gains of between 33 and 1471 annualized basis points are achieved when taking the leverage effect into consideration.     

Temperature and trading behaviours

It is well known that the weather has an impact on human behaviours. Motivated by the extant literature concerning the positive linear relationship between temperature and investors' trading based on regional data (e.g., Schmittmann et al., 2015), we re-examine the temperature effect by utilizing a dataset that encompasses a large number of individual investors' accounts and a wider range of weather conditions, and construct a comprehensive measure of sensed temperature, Apparent Temperature, which incorporates atmospheric temperature, relative humidity and wind velocity. Our results demonstrate that the relationship between Apparent Temperature and individual investors' purchasing tendency displays an inverted U-shape. At a comfortable temperature, investors are more aggressive and tend to buy more stocks relative to selling. However, the relationship between Apparent Temperature and trading volumes displays a U-shape, suggesting that investors trade less on days when the temperature is comfortable, reducing non-financial opportunity costs. Further, Apparent Temperature displays greater external validity than the three weather conditions when they are examined individually. Our study provides original evidence of non-linearity, instead of the linearity documented by previous research, in the relationships between temperature and retail investors' trading behaviours. Our findings contribute to the literature regarding the weather-induced sentiment misattribution of a diversity of investors.     

Weather,institutional investors and earnings news

We examine how pre-announcement weather conditions near a firm's major institutional investors affect stock market reactions to firms' earnings announcements. We find that unpleasant weather experienced by institutional investors leads to more delayed market responses to subsequent earnings news. Moreover, unpleasant weather of institutional investors is associated with higher earnings announcement premia. The influence of institutional investors' weather is robust after controlling for New York City weather, extreme weather conditions, and firm local weather. Additional cross-sectional evidence suggests that the strength of this weather effect is related to institutional investors' trading behavior.     

Can the probability of extreme returns be the basis for profitable portfolios? Evidence from China

Based on the generalized logit predicting model from Jang and Kang (2019), this paper estimates the ex-ante probability of extreme returns and finds that the significantly negative (positive) influence of the predicted crash (jackpot) probability is robust, whether based on the traditional portfolio construction, orthogonalized portfolio construction and Fame-Macbeth cross-section regression. Further analyses show both the behavioral speculators' trading and rational investors' arbitrage limits could be the sources of mispricing caused by extreme returns. Overall, this paper applies a predicting model to estimate the probabilities of the future extreme returns, and figures out the significant influence and possible sources of the crash and jackpot probabilities in China. Portfolios based on extreme return probabilities can be profitable and steady bases for uninformed investors in the Chinese stock market.     

Does good luck make people overconfident? Evidence from a natural experiment in the stock market

This paper examines the changes in investors' trading behavior after winning an IPO allotment in China—a purely luck-driven event. We find that these investors subsequently become overconfident: They trade more frequently and lose more money relative to other investors. This effect is stronger when investors are inexperienced and when investors' pre-existing level of overconfidence is low. We also show that investors exhibit a stronger gambling propensity and hold more lottery-like stock after winning an IPO allotment. Our findings are not explained by wealth effects or house money effects. Overall, our evidence indicates that the experience of good luck makes people overconfident about their prospects.