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We propose a novel method of forecasting the level of informed trading at merger announcements. Informed traders typically take advantage of their knowledge of the forthcoming merger by trading heavily at announcement. They trade on positive volume or informed buys for cash mergers and negative volume or informed sells for stock mergers. In response, market makers set wider spreads and raise prices for informed buys and lower prices for informed sells. As liquidity traders trade on these prices, our vector autoregressive framework establishes the link between informed trading and liquidity trading through price changes. As long as the link holds, informed trading may be detected by measuring levels of liquidity trading. We observe the link during the −1 to +1 period for cash mergers and −1 to +5 period for stock mergers.

We examine the informational roles of trades and time between trades in the domestic and overseas US Treasury markets. A vector autoregressive model is employed to assess the information content of trades and time duration between trades. We find significant impacts of trades and time duration between trades on price changes. Larger trade size induces greater price revision and return volatility, and higher trading intensity is associated with a greater price impact of trades, a faster price adjustment to new information and higher volatility. Higher informed trading and lower liquidity contribute to larger bid–ask spreads off the regular daytime trading period.

This paper aims to propose a method of forecasting the level of informed trading at merger announcements by permitting liquidity traders to adjust their trading based upon signals from informed traders. Informed traders typically take advantage of their knowledge of forthcoming mergers by trading heavily at announcement. For cash mergers, they respond to a positive signal by purchasing stock, and for stock mergers, they respond to a negative signal by selling stock. In response, exchanges (market makers) set wider spreads (charge higher transaction fees) for informed buyers. Uninformed traders are subject to such excessive fees unless they can accurately predict the period during which such fees are charged.

This paper proposes a technique by which uninformed traders may make predictions by creating a vector autoregressive framework that links informed and liquidity trading through price changes.

For cash mergers, transaction fees remained excessive for days −1 to +1. For stock mergers, fees remained high on days −1 to +1, started declining on days 2 and 3, and vanished on days 4 and 5.

Most theoretical models of informed trading have viewed informed trading and liquidity trading as tangentially linked. This study finds a direct link between these two trading activities.

Uninformed traders may wish to limit their trading until after day +1 for both types of mergers.

This paper defines the time period during which transactions costs for traders are at the maximum level. Short sellers have more information about the direction of stock movements and may sell during days of informed selling set forth by this study and repurchase stock afterwards.

This paper aims to examine the prevalence of informed trading around corporate spinoffs and the relation between firm opacity and informed trading using option market data.

The author investigates the prevalence of informed trading by examining the relationship between abnormal stock returns associated with spinoffs and the volatility spread/volatility skewness of options prior to the spinoffs. Furthermore, the author examines how opacity and organizational complexity prior to the spinoffs affect informed trading.

The study shows that option volatility spread and volatility skewness for the five days prior to the spinoffs can predict the abnormal stock returns on the spinoff announcement days, suggesting that there is informed trading in the options market prior to spinoffs. The study shows that informed trading is more prevalent for firms that are more opaque prior to the spinoff. Furthermore, informed trading decreases after spinoffs.

To the best of knowledge, this is the first empirical research that examines the prevalence of informed trading around spinoffs by using options volatility spread/skewness and the relation between firm opacity and informed options trading.

The purpose of this paper is to empirically study the relationship between informed trading and overall corporate governance mechanisms.

A broad range of governance characteristics are used to measure the governance structure of firms in the Toronto Stock Exchange. The risk of informed trading is estimated using a PIN measure that avoids biases induced by trade classification errors. Our proxies for informed trading are regressed on measures of corporate governance.

Our most important result is that the observed trade‐off between CEO compensation and informed trading holds only for large firms. There is no correlation between CEO cash compensation and the risk of informed trading in small and medium sized firms. We find evidence that cross‐sectional differences in the risk of informed trading are explained by a firm's governance structure.

Research finding a trade‐off between CEO compensation and informed trading merits closer examination.

Limitations on insider trading, and more broadly on informed trading, may involve different costs and benefits for large firms than for medium and small firms.

This paper expands the set of governance characteristics shown to interact with informed trading activity. The Toronto market is well suited to focusing on relations between informed trading and firm‐level governance characteristics.

In this paper, the authors examine options trading in firms that soon become rumored takeover targets. This study also examines whether measures of informed trading can predict target returns (upon rumor announcement and over the post-rumor period) and/or predict which rumors lead to bids. The authors further assess whether the informed trading they observe is more prevalent in the options market or the equity market.

This study calculates abnormal options volume using a market-model approach that accounts for different attributes of options trading. The authors construct a control sample and compare equity options trading of firms in their sample with that of the control sample. In addition, the authors fit a series of regressions to examine whether pre-rumor abnormal options trading can predict rumor accuracy in a multivariate setting.

The authors find that the volume of options traded is abnormally high over the pre-rumor period while the direction of option trades (abnormal call volume minus abnormal put volume) prior to takeover rumors predicts forthcoming takeover announcements, rumor date target firm returns and post-rumor target firm returns. The results are robust when controlling for publicly available information, when using a control sample, and when using alternative measures of informed trading.

This study is the first to provide evidence of informed options trading prior to a broad sample of takeover rumors. In addition, this study contributes to the literature on takeover predictability and profitability by showing that various pre-rumor measures of informed options trading significantly predict bid announcements. The authors also contributes to the literature on price discovery by providing evidence that informed investors are more likely to trade in the options market than in the equity market during the pre-event period.

Informed trading has a strong liaison with the options market, as the risk in the options market is limited to the premium, leverage is high and the transaction cost is less. The purpose of this paper is to analyze the effect of options availability on the informed trading, occurring well before the merger and acquisition (M&A) announcements along with the crisis period and regulation effect.

The study employs event study methodology for 864 M&A announcements done by Indian acquiring companies in order to compute the abnormal returns and also examine the implied volatility and volume of call, putting options for the robustness check.

The results indicate that option listing status increases the possibility and magnitude of informed trading in the M&As, which gets more/less pronounced during and immediately after the crisis period when new regulatory reforms are introduced.

This study contributes to the efficient market theory and affirms that stock market of acquiring companies in India follow a semi-strong form of market efficiency around M&A announcements in the presence of options market.

This study investigates whether broker anonymity impairs the ability of the market to detect informed trading in the lead up to takeover announcements. Our research represents the first study in this area to analyse the effects of broker anonymity in the context of significant information asymmetry. Results indicate that informed traders are less detected, and therefore better off when broker identifiers are concealed. This finding has important policy implications for exchange officials deciding whether or not to reveal broker identifiers surrounding trades, especially considering that almost all prior research suggests that broker anonymity is correlated with improved liquidity.

The purpose of this paper is to examine the impact of trades by informed traders and uninformed traders on the asymmetric volatility relation, a stylized fact that has long been puzzling financial economists. Avramov, Chordia, and Goyal's hypothesized that asymmetric volatility, defined as the negative relationship between daily volatility and lagged unexpected return, is governed by the trading dynamics of informed traders and uninformed traders. However, the hypothesis has not been directly tested due to lack of a measure for informed and informed trades. The authors aim to test the hypothesis using a direct measure for informed trades and uninformed trades.

The authors employ the Computer Trade Reconstruction (CTR) data of Nasdaq‐100 index futures for the period of 2002 through 2004. The dataset contains a unique variable distinguishing informed trades and uninformed trades, allowing the authors to directly examine the impact of the trades (i.e. selling activities) on the asymmetric volatility relation.

Based on the Nasdaq‐100 index futures data, the asymmetric volatility relation is driven by the selling activity of uninformed traders, particularly from small‐size trades. These results are only significant during the first half of the period, which is more volatile than the second half. The selling impact of informed traders on the asymmetric volatility relation is at most weak for both subperiods.

While risk and returns are important for asset pricing and risk management, most financial researchers consider them from a fundamental perspective. This paper's results suggest that selling activity of uninformed traders can significantly influence asset return and volatility and, hence, deserves more attention from the researchers.

The paper is the first to provide a direct test for Avmarov et al.'s hypothesis and shows that uninformed trades cause the asymmetric volatility. The authors contribute to ongoing discussions of how noise trading behavior can impact asset return and volatility.

Recent studies suggested the ratio of option to stock volume reflected the private information. Informed traders were drawn to the options market for its leverage effect and relatively low transaction costs. Informed traders use different intervals of option moneyness to execute their strategies. The question is which types of option moneyness were traded by informed traders and what information was reflected in the market. In this study, the authors focused on this question and constructed a method for capturing the activity of informed traders in the options and stock markets.

The authors constructed the daily measure, moneyness option trading volume to stock trading volume ratio (MOS), to capture the activity of informed traders in the market. The authors formed quintile portfolios sorted with respect to the moneyness option to stock trading volume ratio and provided the capital asset pricing model and Fama–French five-factor alphas. To determine whether MOS had predictive ability on future stock returns after controlling for company characteristic effects, the authors formed double-sorted portfolios and performed Fama–Macbeth regressions.

The authors found that the firms in the lowest moneyness option trading volume to stock trading volume ratio for put quintile outperform the highest quintile by 0.698% per week (approximately 36% per year). The firms in the highest moneyness option trading volume to stock trading volume ratio for call quintile outperform the lowest quintile by 0.575% per week (approximately 30% per year).

The authors first propose the measures, moneyness option trading volume to stock trading volume ratio, that combined with the trading volume and option moneyness. The authors provide evidence that the measures have the predictive ability to the future stock returns.