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.     

Information,sophistication, and foreign versus domestic investors’ performance

Using an intraday transaction dataset with trader identity, we study foreign and domestic investors’ trading activities and investment performance ahead of open-ending events of Taiwanese closed-end funds. Simply buying the funds at a discount and holding until open-ending generates large abnormal returns. All information required to execute this strategy is made public, so the events set up natural experiments to examine how investors trade, holding constant access to information. Foreign investors are net buyers ahead of the open-endings, more than doubling their positions and earning large abnormal returns. Domestic investors are net sellers while the discounts are still large, and forego large abnormal returns. The results suggest that investor sophistication in interpreting the same information is potentially an important determinant of investment performance differences across foreign and domestic investors.     

International order flows: Explaining equity and exchange rate returns

Macroeconomic models of equity and exchange rate returns perform poorly at high frequencies. The proportion of daily returns that these models explain is essentially zero. Instead of relying on macroeconomic determinants, we model equity price and exchange rate behavior based on a concept from microstructure–order flow. The international order flows are derived from belief changes of different investor groups in a two-country setting. We obtain a structural relationship between equity returns, exchange rate returns and their relationship to home and foreign equity market order flow. To test the model we construct daily aggregate order flow data from 800 million equity trades in the U.S. and France from 1999 to 2003. Almost 60% of the daily returns in the S&P100 index are explained jointly by exchange rate returns and aggregate order flows in both markets. As predicted by the model, daily exchange rate returns and order flow into the French market have significant incremental explanatory power for the daily S&P returns. The model implications are also validated for intraday returns.     

Overreaction of country ETFs to US market returns: Intraday vs. daily horizons and the role of synchronized trading

In this paper we study the intraday price formation process of country Exchange Traded Funds (ETFs). We identify specific parts of the US trading day during which Net Asset Values (NAVs), currency rates, premiums and discounts, and the S&P 500 index have special effects on ETF prices, and characterize a special intraday and overnight updating structure between these variables and country ETF prices. Our findings suggest a structural difference between synchronized and non-synchronized trading hours. While during synchronized trading hours ETF prices are mostly driven by their NAV returns, during non-synchronized trading hours the S&P 500 index has a dominant effect. This effect also exceeds the one that the S&P 500 index has on the underlying foreign indices and suggests an overreaction to US market returns when foreign markets are closed.     

WHO ARE THE NOISE TRADERS?

Closed‐end funds often trade at a discount to net asset value. Previous research suggests that the positive correlation in discounts is associated with investor sentiment that causes systematic mispricing by noise traders. We use a newly available sample of daily fund valuations to examine the relation between intraday trading activity and discount changes. Contrary to the assumption that retail investors are noise traders, we find no relation between discount changes and the order‐flow imbalances of individual investors. Large daily discount changes are associated with institutional trading, and this may reflect the price inelasticity of closed‐end fund shares.     

Intraday online investor sentiment and return patterns in the U.S. stock market

We implement a novel approach to derive investor sentiment from messages posted on social media before we explore the relation between online investor sentiment and intraday stock returns. Using an extensive dataset of messages posted on the microblogging platform StockTwits, we construct a lexicon of words used by online investors when they share opinions and ideas about the bullishness or the bearishness of the stock market. We demonstrate that a transparent and replicable approach significantly outperforms standard dictionary-based methods used in the literature while remaining competitive with more complex machine learning algorithms. Aggregating individual message sentiment at half-hour intervals, we provide empirical evidence that online investor sentiment helps forecast intraday stock index returns. After controlling for past market returns, we find that the first half-hour change in investor sentiment predicts the last half-hour S&P 500 index ETF return. Examining users’ self-reported investment approach, holding period and experience level, we find that the intraday sentiment effect is driven by the shift in the sentiment of novice traders. Overall, our results provide direct empirical evidence of sentiment-driven noise trading at the intraday level.     

Social media bots and stock markets

This study examines the link between information spread by social media bots and stock trading. Based on a large sample of tweets mentioning 55 companies in the FTSE 100 composites, we find significant relations between bot tweets and stock returns, volatility, and trading volume at both daily and intraday levels. These results are also confirmed by an event study of stock response following abnormal increases in the volume of tweets. The findings are robust to various specifications, including controlling for traditional news channel, alternative measures of volatility, information flows in pretrading hours, and different measures of sentiment.     

THE ECONOMIC GAINS OF TRADING STOCKS AROUND HOLIDAYS

I assess the economic gains of strategies that account for the effect of holiday calendar effects on the daily returns and volatility of the 30 stocks in the Dow Jones Industrial Average index. The dynamic strategies use forecasts from stochastic volatility models that distinguish between regular trading days and different types of holidays. More important, I assess the economic value of conditioning on holiday effects and find that a risk-averse investor will pay a high performance fee to switch from a dynamic portfolio strategy that does not account for the effect of holidays on daily conditional expected returns and volatility to a strategy that does. This result is robust to reasonable transaction costs.     

Intraday technical analysis of individual stocks on the Tokyo Stock Exchange

This paper conducts an intraday technical analysis of individual stocks listed on the Nikkei 225. In addition to the price-based technical rules popularly examined in the literature, we uniquely propose and statistically investigate technical rules that utilize information regarding (1) the order-flow imbalance and (2) the order-book imbalance. Technical analysis using the imbalance-based trading rules is motivated by the evidence presented first in this paper that short-term returns can be predicted from the information regarding the order-flow and order-book imbalances for more than half of Nikkei 225-listed stocks. However, we demonstrate that no strategies, including limit order trading where trading signals are derived from the order-book imbalance, beat the buy-and-hold strategy within our sample. The results imply that past prices and demand/supply imbalances do not contribute to profiting in intraday trading and that non-execution and picking-off risks are too large for limit order trading to be profitable in our sample.     

Volume and skewness in international equity markets

We examine the relation between trading volume and skewness in 11 international stock markets using daily and monthly data from January 1980 to August 2004. We construct single equation and VAR models of the relation between the first three moments of market returns and trading volumes. Our results show hitherto unrecognised channels of influence, and support the investor heterogeneity approach to explaining return asymmetries.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

Long-run returns following open market share repurchases

Past studies find abnormal returns to buying after repurchase program announcements. We analyze the profitability of trading after both program announcements and individual repurchase trade publication using different trading strategies – market and limit orders. The analysis of trades is possible because of a unique Canadian data set. The highest abnormal returns are earned by companies on their own repurchase trades which benefits the non-tendering shareholders. For the public investor, we find no strategies that, in practice, would earn abnormal returns to buying after program announcements. However, there is qualified evidence of abnormal returns to a limit order strategy following publication of individual repurchase trades.     

Option trading and individual investor performance

This paper examines the impact of option trading on individual investor performance. The results show that most investors incur substantial losses on their option investments, which are much larger than the losses from equity trading. We attribute the detrimental impact of option trading on investor performance to poor market timing that results from overreaction to past stock market returns. High trading costs further contribute to the poor returns on option investments. Gambling and entertainment appear to be the most important motivations for trading options while hedging motives only play a minor role. We also provide strong evidence of performance persistence among option traders.     

Order price clustering,size clustering,and stock price movements: Evidence from the Taiwan Stock Exchange

This paper examines order price clustering, size clustering, and stock price movements in an active emerging country’s equities market, the Taiwan Stock Exchange (TWSE). We first explore the relationships between investor types and order price/size clustering. Next, we investigate the joint determinants of the round-price and round-size orders based on daily and intraday data analyses. Finally, we look at the relationships among investor types, round prices/sizes, and stock price movements. The findings reveal that all investor types exhibit price and size clustering phenomena. After controlling for other factors, institutional investors have a relatively lower level of size clustering when compared with individuals. Our results confirm the price resolution hypothesis, whereby the levels of daily price and size clustering increase with firm risk, and the probability of a round-price or round-size order increases as transitory volatility rises. Partially consistent with the negotiation hypothesis, the probability of a round-price or round-size order increases when order competition turns fiercer. Mutual funds exhibit stronger quarter-end and session-end effects than do other investors. We also detect strategic trading behaviors, showing that the probability of an order with a tail price of one (nine) increases when buy (sell) order competition is fiercer. Lastly, stocks with mutual funds’ round-price or round-size buy (sell) orders experience rising (falling) future stock returns.     

Weather and intraday patterns in stock returns and trading activity

We examine the relation between weather in New York City and intraday returns and trading patterns of NYSE stocks. While stock returns are found to be generally lower on cloudier days, cloud cover has a significant influence on stock returns only at the market open. There are significantly more seller-initiated trades when there is more cloud cover at the market open, which is consistent with the return results. Cloudy skies are associated with higher volatility and less market depth over the entire trading day. Finally, cloud cover is not significantly correlated with spread measures and turnover ratios. The findings overall suggest that weather has a significant influence on investors’ intraday trading behavior.     

Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events

To investigate the complex interactions between market events and investor sentiment, we employ a multivariate Hawkes process to evaluate dynamic effects among four types of distinct events: positive returns, negative returns, positive sentiment, and negative sentiment. Using both intraday S&P 500 return data and Thomson Reuters News sentiment data from 2008 to 2014, we find: (a) self-excitation is strong for all four types of events at 15 min time scale; (b) there is a significant mutual-excitation between positive returns and positive sentiment and negative returns and negative sentiment; (c) decay of return events is almost twice as fast as sentiment events, which means market prices move faster than investor sentiment changes; (d) positive sentiment shocks tend to generate negative price jumps; and (e) the cross-excitation between positive and negative sentiments is stronger than their self-excitation. These findings provide further understanding of investor sentiment and its intricate interactions with market returns.     

Overconfidence and Investor Size

Recent research documents that institutional or large investors act as antagonists to other investors by showing opposite trading behaviour following the disclosure of new information. Using an extremely comprehensive official transactions data set from Finland, we set out to explore the interrelation between investor size and behaviour. More specifically, we test whether investor size is positively (negatively) correlated with investor reaction following positive (negative) news. We document robust evidence of that investor size affects investor behaviour under new information, as larger investors on average react more positively (negatively) to good (bad) news than smaller investors. We furthermore find that the performance of smaller, or more overconfident, investors is in general hurt by their behaviour.     

Investor Trading Behavior and Sentiment in Futures Markets

This study investigates the effects of investor trading behavior and investor sentiment on futures market return. We find that the spot investor trading behavior, futures investor trading behavior, spot market sentiment, and futures market sentiment all have positive effects on daily futures returns in Chinese financial market. More importantly, we show that the effect of (spot) futures investor trading behavior has better explanatory power than (spot) futures market sentiment on futures returns. Further supporting our results, high investor trading behavior and high investor sentiment strengthen the positive relation between sentiment-returns and behavior-returns.     

An encyclopedia for stock markets? Wikipedia searches and stock returns

We present empirical evidence that collective investor behavior can be inferred from large-scale Wikipedia search data for individual-level stocks. Drawing upon Shannon transfer entropy, a model-free measure that considers any kind of statistical dependence between two time series, we quantify the statistical information flow between daily company-specific Wikipedia searches and stock returns for a sample of 447 stocks from 2008 to 2017. The resulting stock-wise measures on information transmission are then used as a signal within a hypothetical trading strategy. The results evidence the predictive power of Wikipedia searches and are in line with the previously documented notion of buying pressure revealed by online investor attention and the trading patterns of retail investors.     

International equity flows and country funds

This study investigates the relationships between U.S. equity flows in foreign countries and returns of closed-end country funds for emerging Latin American markets, emerging Asian markets and developed markets. The major issues addressed are (1) relationships between flows and fund returns based on two basic models—information contribution and feedback trading effects, (2) the role of volatility in these relationships, and (3) the effects of the Asian crisis. Basic findings include: (1) information contribution (past flows affect returns) and feedback trading arguments (past returns affect flows) are supported; (2) strong evidence is found for the market segmentation argument rather than the investor sentiment argument; (3) there exists strong evidence of significant volatility effects under information contribution and feedback trading; (4) the Asian crisis effects are important but limited to Asian funds.