Trading Activity Of Investors Research Articles

The information content of retail investors’ order flow

In this paper, we provide evidence that the trading activity of small retail investors carries significant genuine information that can be exploited for the short-term out-of-sample forecasting of foreign exchange rates. Our findings are based on a unique dataset of around 2000 retail investors from the OANDA FXTrade electronic trading platform. Our results are consistent with the view that in the foreign exchange market private information is highly dispersed, but can be extracted by observing customer order flow. Previous studies, however, focused on the information content of costumer order flow of dealers in the interbank market, whose clients are themselves large institutional and professional investors. Our study is the first that analyzes a crowd of small retail investors and shows that even the trading activity of these investors contains, on aggregate, important non-public information that can be exploited for short-term exchange rate forecasting. Our findings lead us to conjecture that retail investors (on aggregate) are not pure noise traders but process dispersed information at least partially in a similar way as large institutional investors and hence place their orders accordingly.

The Information Content of Retail Investors' Order Flow

In this paper we provide evidence that the trading activity of small retail investors carries significant genuine information for the short term out-of-sample forecasting of foreign exchange rates. Our findings are based on a unique dataset of around 2000 retail investors from the OANDA FXTrade electronic trading platform. Our results are consistent with the view that in the foreign exchange market private information is highly dispersed, but can be extracted by observing customer order flow. Previous studies, however, focused on the information content of costumer order flow of dealers in the interbank market, whose clients are themselves large institutional and professional investors. Our study is the first that analyses a crowd of small retail investors and shows that even the trading activity of these investors contains, on aggregate, important non-public information, that can be exploited for short term exchange rate forecasting. Our findings lead us to conjecture that retail investors (on aggregate) are not pure noise traders but process dispersed information at least partially in a similar way as large institutional investors and hence place their orders accordingly.

Cross-listing, firm-specific information, and corporate governance: Evidence from Chinese A-shares and H-shares

We examine the impact of cross-listing on firm-specific information utilizing the unique features of the Chinese capital markets. By separating the trading activity of domestic Chinese investors from that of foreign non-Chinese investors, we are able to isolate each investor group's relative ability to impound firm-specific information into stock prices. We show that the cross-listed H-shares traded by foreign investors incorporate significantly more firm-specific information than their A-share counterparts traded by domestic Chinese investors. We find a similar pattern between H-shares and A-shares even after a 2007 regulatory change that allowed domestic Chinese investors to trade in the H-share market. This finding suggests that while institutional factors (e.g., stricter listing rules, stronger investor protection) can explain some of the benefits of cross-listing, foreign investors' ability to utilize firm-specific information plays a separate and distinct role in generating cross-listing benefits. The level of information improvement due to foreign investors depends on the quality of the cross-listed firm's corporate governance.

Are Trade Size Based Inferences About Traders Reliable? Evidence from Institutional Earnings-Related Trading

The use of observed transaction sizes to differentiate between “small” and “large” investor trading patterns is widespread. A significant concern in such studies is spurious effects attributable to misclassification of transactions, particularly those originating from large investors. Such effects can arise unintentionally, strategically, or endogenously. We examine comprehensive records of a sample of institutional investors (i.e., “large” traders), including their order sizes and overall position changes, to assess the degree to which such misclassifications give rise to spurious inferences about “small” and “large” investor trading activities. Our analysis shows that these institutions are heavily involved in small transaction activity. It also shows that they increase their order sizes substantially in announcement periods relative to non-announcement periods, presumably as an endogenous response to earnings news. In the immediate earnings announcement period, transaction size based inferences about directional trading are quite misleading -- producing spurious “small trader” effects and, more surprisingly, erroneous inferences about “large trader” activity.

How news affects the trading behaviour of different categories of investors in a financial market

We investigate the trading behaviour of a large set of single investors trading the highly liquid Nokia stock over the period 2003–2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behaviour. As endogenous factors, we consider returns and volatility, whereas the exogenous factors are the total daily number of news articles and a semantic variable based on a sentiment analysis of the news. Linear regression and partial correlation analysis of the data show that different categories of investors are differently correlated to these factors. Governmental and non-profit organizations are weakly sensitive to news and returns or volatility, and, typically, they are more correlated with the former than with the latter. Households and companies, on the contrary, are very sensitive to both endogenous and exogenous factors, and volatility and returns are, on average, much more relevant than the number of news articles and sentiment, respectively. Financial institutions and foreign organizations are intermediate between these two cases, in terms of both the total explanatory power of these factors and their relative importance. We explicitly consider the role of overnight news and overnight returns on the successive trading activity and trading balance of the different categories of investors. We observe the role of the overnight news, which is weaker than the ones observed between synchronous variables. By performing a vector autoregression (VAR) analysis, we show that the flux of news of the previous day affects the trading activity of companies, households and foreign investors and the dynamics of volatility. VAR is not detecting any role of the lagged sentiment in the successive values of the difference between the number of buying and selling investors for each category of investors.

Are Trade Size‐Based Inferences About Traders Reliable? Evidence from Institutional Earnings‐Related Trading

ABSTRACTThe use of observed transaction sizes to differentiate between “small” and “large” investor trading patterns is widespread. A significant concern in such studies is spurious effects attributable to misclassification of transactions, particularly those originating from large investors. Such effects can arise unintentionally, strategically, or endogenously. We examine comprehensive records of a sample of institutional investors (i.e., “large” traders), including their order sizes and overall position changes, to assess the degree to which such misclassifications give rise to spurious inferences about “small” and “large” investor trading activities. Our analysis shows that these institutions are heavily involved in small transaction activity. It also shows that they increase their order sizes substantially in announcement periods relative to nonannouncement periods, presumably as an endogenous response to earnings news. In the immediate earnings announcement period, transaction size‐based inferences about directional trading are quite misleading—producing spurious “small trader” effects and, more surprisingly, erroneous inferences about “large trader” activity.

Mutual Fund's Trading and Chinese Mergers and Acquisitions

In developing capital markets dominated by individual investors, there is a potential for greater disparity in the interests of institutional investors and controlling shareholders and this has implications for the trading and monitoring activities of institutional investors in these markets, particularly around high impact corporate decisions. We examine the trading activities of mutual funds (as the largest institutional investor in this market) in corporate acquisition activities where there is potential for a wide disparity of interest between institutional investors and controlling shareholders. We find that Top Mutual Fund Management Company (TFC) have strong incentives to trade and realize profits over the event months for fear of price drop due to the mean reversion and herding effect in Chinese capital market.

Attention on Options

This paper investigates the impact of retail investor attention, measured by Google search frequency, on option trading and option pricing as well as stock return volatility. We document a significant positive relation between Google search volume and future option trading activity of retail investors. Moreover, retail investors tend to take more bullish option positions following increased attention. Although option implied volatilities initially rise, the long run impact of Google search volume on option prices is negative, albeit small in magnitude. In contrast, we find a significantly positive and persistent relation between Google search volume and future realized stock return volatility. An option trading strategy of buying high attention delta-hedged straddles and selling low attention delta-hedged straddles generates an annual return of 6.44%, which is uncorrelated with standard risk factors. Our findings suggest that retail investor attention not only affects trading activity but also is a source of noise trader risk.

Foreign investor flows and “blue chip” stock returns

Purpose – The purpose of this paper is to investigate the direction of causality between the monthly stock returns and the monthly net foreign investor flows, and the existence of feedback trading by foreign investors for the “blue chip” stocks of the Istanbul Stock Exchange (ISE), an emerging stock market.Design/methodology/approach – Monthly net foreign investor flows and stock returns of “blue chip” stocks for the period January 1997‐June 2010 are used. Particularly, taking into account the structural changes in the foreign investor trading activity, the study focuses on the two sub‐periods – before and after the start of European Union (EU) accession negotiations of Turkey. The study uses the bivariate VAR Granger causality approach, impulse response analysis and uses regressions with the vector autoregressive structure and contemporaneous structure (without lag).Findings – Unidirectional Granger causality running from monthly stock returns to monthly net foreign investor flows is detected for the pre...

Investor Sentiment and Return Comovements: Evidence from Stock Splits and Headquarters Changes*

We examine whether the trading activities of retail and institutional investors cause comovements in stock returns. Around stock splits, retail trading correlations (RTCs) decrease with stocks in the presplit price range and increase with stocks in the post-split price range. These shifts in RTCs induce changes in return comovements. In the cross section, return comovements among low-priced stocks are amplified when retail trades are more correlated and when aggregate uncertainty amplifies behavioral biases. We find similar patterns among local stocks and when firms change their corporate headquarters. In contrast to retail trading, institutional trading attenuates return comovements.

Investor behavior in the mutual fund industry: evidence from gross flows

Using a large sample of monthly gross flows from 1997 to 2003, we uncover several previously undocumented regularities in investor behavior. First, investor purchases and sales produce fund-level gross flows that are highly persistent. Persistence in fund flows dominates performance as a predictor of future fund flows. More importantly, failing to account for flow persistence leads to incorrect inferences with respect to the relation between performance and flows. Second, we document that investors react differently to performance depending on the type of fund, and that investor trading activity produces meaningful differences in the persistence of fund flows across mutual fund types. Third, at least some investors appear to evaluate and respond to mutual fund performance over much shorter time spans than previously assessed. Additionally, we document differences in the speed and magnitude of investors’ purchase and sales responses to performance.

Sentiment, Irrationality and Market Efficiency: The Case of the 2010 FIFA World Cup

Soccer games create sentiment, which affects stock prices. The World Cups before 2010 created exploitable abnormal profit in the U.S. stock market. The effect was not exploited, presumably because it was unknown before the 2010 games. However, just before the 2010 World Cup, the exploitable effect was published and widely cited by practitioners who even suggested recipe how to exploit it. Although the abnormal profit in 2010 surpassed 5%, the information on the abnormal profit created a price pattern which is different from those corresponding to the previous World Cups. Like other market anomalies, we expect that the trading activity of sophisticated investors will restore market efficiency, implying that this new effect will vanish in the future.

Foreign Investors’ Trading Behavior in Response to Crises: Evidence from Thailand

This paper examines the trading behavior of foreign investors in Thailand and its impact on the country’s stock market and currency value during January 1, 1975 to August 31, 2009. We also investigate if the trading strategy of foreigners has changed during the 1997 financial crisis, 2004 Tsunami crisis, and 2006 and 2008 political crisis. For the entire sample period, foreign investors were the net purchaser of Thai equity and implemented positive feed-back investment trading strategy, while domestic investors were the net sellers with a contrarian investment strategy. The trading behaviors of foreign investors do not change during the financial and tsunami turmoil and 2006 political upheaval in Thailand. These crises do not scare foreign investors out of Thailand. It was the trading activities of domestic individual investors that destabilized the stock market of Thailand during the 1997 Asian financial crisis. The trading activities of all investors cause a major destabilizing effect on Thai equity during the 2008 political crisis, particularly individual investors exert the strongest destabilizing effect. There is no evidence of price-destabilizing effect during the 2004 Tsunami crisis. The trading activities of domestic individual and institutional investors do not cause any destabilizing effect on Baht currency value caused by the trading activities of domestic individual and institutional investors were not found in any of the financial, tsunami, and political crises. Only did the trading activities of foreigners cause the baht to devalue during the 1997 Asian financial crisis.

Identification of clusters of investors from their real trading activity in a financial market

We use statistically validated networks, a recently introduced method of validating links in a bipartite system, to identify clusters of investors trading in a financial market. Specifically, we investigate a special database allowing us to track the trading activity of individual investors of Nokia stock. We find that many statistically detected clusters of investors show a very high degree of synchronization in time when they decide to trade and in the trading action taken. We investigate the composition of these clusters and find that several of them show an over-expression of specific categories of investors.

Households Learning in the Dark: New Evidence from Retail Traders

This paper uses a new dataset and a specific feature of the French stock exchange to study the behavior of individual investors actively trading stocks. Consistent with prior literature, the trading activity of individual investors increases (decreases) following high (low) performance. I carefully split individual investors' performance into (i) performance related to the exposure of their trades to systematic risk factors such as the market premium, the excess returns on small stocks and the excess returns on value stocks, and (ii) residual performance. I show that trading activity reacts to both (i) and (ii) and that this does not seem to be explained by any strategic behavior. Instead, a simple model where individual investors are ex ante uncertain about their ability and factor exposure and trade to learn about them generates predictions consistent with the above evidence as well as additional predictions about learning dynamics that are also borne out by the data.

Identification of Clusters of Investors from Their Real Trading Activity in a Financial Market

We use statistically validated networks, a recently introduced method to validate links in a bipartite system, to identify clusters of investors trading in a financial market. Specifically, we investigate a special database allowing to track the trading activity of individual investors of the stock Nokia. We find that many statistically detected clusters of investors show a very high degree of synchronization in the time when they decide to trade and in the trading action taken. We investigate the composition of these clusters and we find that several of them show an over-expression of specific categories of investors.

All the News That's Fit to Reprint: Do Investors React to Stale Information?

This article tests whether stock market investors appropriately distinguish between new and old information about firms. I define the staleness of a news story as its textual similarity to the previous ten stories about the same firm. I find that firms' stock returns respond less to stale news. Even so, a firm's return on the day of stale news negatively predicts its return in the following week. Individual investors trade more aggressively on news when news is stale. The subsequent return reversal is significantly larger in stocks with above-average individual investor trading activity. These results are consistent with the idea that individual investors overreact to stale information, leading to temporary movements in firms' stock prices. The Author 2011. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Investor Sentiment and Return Comovements: Evidence from Stock Splits and Headquarters Changes

This paper examines whether the trading activities of retail and institutional investors cause comovements in stock returns. Using stock splits and headquarters changes events and a variety of trading-based measures, we show directly that retail investors generate excess comovements in stock returns. Specifically, around stock splits, retail trading correlations decrease with stocks in the pre-split price range and increase with the post-split price range. Further, shifts in retail trading correlation influence return comovement changes around stock splits. In the cross-section, excess return comovements among low-priced stocks are amplified when retail trades are more correlated. We find similar patterns among local stocks and when firms change their corporate headquarters. These comovement patterns are stronger when uncertainty is high and behavioral biases are amplified. In contrast to retail trading, institutional trading attenuates return comovements.

Small trades and volatility increases after stock splits

In this paper, we examine the trading activity and return volatility pattern before and after splits. Unlike previous studies, we employ high-frequency transaction data and more powerful asymptotical tests on the impact of split on volatility. Furthermore, we examine the relationship between volatility and volume using different volatility measures and controlling for the effects of autocorrelation and trading costs. We find that small trades increase significantly after stock splits and the increase in return volatility is strongly related to the increase in small trades after stock splits. The results support our contention that the post-split volatility increase is driven primarily by the trading activity of smaller noise investors. Test results are robust to different measures of trading activity and return volatility.

Inter-temporal examination of the trading activities of foreign investors in the Korean stock market

In the full market-opening period of the Korean stock market (1999–2006), when foreign equity ownership reached as high as 40% of the total stock market capitalization, foreign net flows move in the same direction contemporaneously with the domestic market return, while lagged foreign flows are not followed by any significant changes in the domestic market return. On the other hand, an increase (decrease) in foreign net buy is followed by Won appreciation (depreciation) relative to the US dollar; however, the reverse relation does not hold. Throughout the entire sample period (1995–2006), foreign flows are not significantly related to stock market return volatility.