We examine the impact of more than 2.5 million HotCopper messages on the Australian stock market. HotCopper is the largest online stock message board in Australia and the sample of messages covers over 2000 companies listed on the Australian Securities Exchange (ASX) from January 2003 through December 2008. We exclude messages surrounding public price-sensitive announcements released centrally by the ASX in order to examine the private information content of internet board messages. We find that the number of board messages and message sentiment significantly and positively relate to the contemporaneous returns of underperforming (low ROE, EBIT margin, EPS) small capitalization stocks with high market growth potential (low book-to-market). Posting activity is positively associated with trading volume for small stocks and negatively associated with bid-ask spreads for small and large stocks in the short term. Bullish small stocks outperform bearish ones significantly in respective days and months, exhibiting no return reversals to pre-message board activity levels in subsequent time periods. Large stocks are not found to be affected by message board activity. We conclude that higher message board activity quickly reflects itself into the prices of small capitalization stocks in a highly regulated market like the ASX.

While economic forecasting is ubiquitous within the industry, its role in the trading process has received little attention in the literature. We examine how economist forecasts are related to trading activity in the OTC treasury bond market at the participant level. Consistent with models of heterogeneous opinions, we show that the forecasting economists employing institution places a disproportionately large reliance on the forecast. There is pervasive evidence that this reliance is asymmetric. Only forecasts which imply a fall in future treasury bond prices are associated with an abnormal trading reaction consistent with the forecast. Reference dependence and loss aversion offer one possible explanation for this asymmetric trading response.

Signed small trade turnover (SSTT) measures temporary uninformed buy or sell pressure that is initiated by small trades in the same direction. Using Nasdaq OMX Helsinki tick-by-tick trade data with known investor category, we confirm that SSTT is a robust proxy for uninformed trading. In the short term (1–3 months), stocks with a high proportion of signed small trades outperform, but in the medium (4–6 months) and long term (7–36 months), SSTT by individual investors has a negative correlation to stock returns, while SSTT by institutional investors and foreign nominees is not related to stock returns. Systematic trading behavior appears to better explain the excess return generated by the low SSTT portfolio relative to the high SSTT portfolio when compared to traditional risk factors in the CAPM and Fama-French models. In the aggregate, small trades are noise in the spirit of Kyle (1985) and Black (1986), but small trade behavior impacts the performance of individuals and not the performance of institutions. Large trades by both individuals and institutions perform better in the intermediate and long term, which lends some credibility to the practice of classifying larger trades as informed, but our results show that these trades are not always by institutions.

This paper investigates whether the personal trading decisions of CEOs are related to their corporate acquisition decisions. We find that the personal trading performance of CEOs across all stocks they trade is significantly and positively related to the short-term performance of their mergers, and that CEOs exhibiting greater turnover on their personal common equity portfolios undertake acquisitions more frequently. Hence, a CEO's risk aversion, confidence and capability are consistent across their personal and corporate investment decisions.

How do managers comment on merger transactions? By analyzing the initial public announcements of mergers and acquisitions (M&As) from 1995 through 2020 and extracting the linguistic sentiment from statements made by managers of target and acquirer firms, we provide new evidence on the informational value of M&A disclosures. We find that positive sentiment by the target firm results in positive returns for the target. However, when the target firm disagrees with the sentiment of the acquirer, this results in lower returns for the target. Further, when the target displays positive sentiment, this increases the likelihood of merger completion and shortens the time to completion of the deal. We decompose acquirer sentiment into manipulative and fundamental components and demonstrate that acquirer CEOs with low confidence produce M&A statements that are more manipulative. This suggests that, while sentiment in M&A disclosures contains information about fundamentals and managerial attitudes, it can be manipulated to protect the personal interests of managers.

We design an adaptive framework for the detection of illegal trading behavior. Its key component is an extension of a pattern recognition tool, originating from the field of signal processing and adapted to modern electronic systems of securities trading. The new method combines the flexibility of dynamic time warping with contemporary approaches from extreme value theory to explore large-scale transaction data and accurately identify illegal trading patterns. Importantly, our method does not need access to any confirmed illegal transactions for training. We use a high-frequency order book dataset provided by an international investment firm to show that the method achieves remarkable improvements over alternative approaches in the identification of suspected illegal insider trading cases.

While momentum benefits from persistent trends of the market, such strategies are unable to distinguish between upside and downside risk and suffer consequently. We propose a Partial Moment Momentum (PMM) trading strategy that is sensitive to the sign of risk and show risk-adjusted outperformance compared to plain momentum and volatility-adjusted momentum strategies. The outperformance is robust across multiple time periods and in particular during market downturns. Further analysis based on conventional linear factor models shows negligible exposure to factor risk for our PMM portfolio. Finally, the performance of our proposed strategy appears to be enhanced when time series momentum is present and allows for improved risk management by distinguishing between upside and downside risks.

We conjecture that a firm's organization capital (OC) has a substitution effect on its executive pay-for-performance sensitivity (PPS) and empirically document a robust and significant substitution effect of OC on executive PPS. We use state-level unemployment insurance benefits as an instrumental variable for OC and show that the documented OC-PPS substitution effect is likely causal. Results are also robust to a stacked difference-in-differences estimation approach based on a quasi-natural experiment of exogenous CEO turnovers due to health-related issues. Our findings strongly suggest that greater OC substitutes for costly executive incentive compensation to sustain firm productivity and increase shareholder wealth.

We use Finnish OMX Helsinki data to examine the relationship between demographic variables, individual investors' broker choices and trade informativeness. We find that men prefer to use Full-Service-Retail over Discount-Retail brokers and that a higher level of income leads to a higher likelihood of using Discount-Retail brokers. Women present more heterogenous broker choice behaviors. However, both genders are more likely to carry out larger trades through Discount-Retail brokers. We show that trades executed via Discount-Retail brokers are more informative than those of Full-Service-Retail brokers and that only Discount-Retail brokers show trade informativeness differences across gender after controlling for age. Collectively, women make more informative trades then men, but this result reverses after partitioning by age. We conclude that conditioning on the type of broker reduces unobserved individual investor heterogeneity and that demographic variables are essential to the understanding of broker clientele effect. Furthermore, clientele differences observed across broker types are market specific and dominate the effects of financial advice in determining trade informativeness.