Does stardom affect the informativeness of a CEO's insider trades?

This study examines whether the celebrity or star status of a chief executive officer (CEO) affects the informativeness of his insider trades. Using three different measures to identify star CEOs in a sample of S&P 1500 firms, we find that trades of non‐star CEOs predict future abnormal returns and earnings innovations and that trades of star CEOs do not. The predictive power of non‐star CEO trades is mostly attributable to opportunistic trades, not routine trades. We also find evidence suggesting that the abnormal returns associated with non‐star CEO insider trades are due to the lower visibility and consequently less scrutiny of non‐star CEOs compared with star CEOs.     

NUMBER OF TRANSACTIONS AND VOLATILITY: AN EMPIRICAL STUDY USING HIGH‐FREQUENCY DATA FROM NASDAQ STOCKS

Our empirical evidence based on transactions data of a sample of Nasdaq stocks indicates that trades of large firms are related to the proxies of marketwide and firm‐specific information. For large firms, an increase in the number of trades seems to have a beneficial effect on liquidity as measured by bid‐ask spreads. On the other hand, trades of small and medium firms are associated with firm‐specific information and are not related to marketwide information. For small and medium firms, the frequency of trades is positively associated with bid‐ask spreads, apparently because of the adverse information content of trades. JEL classification: G10, G12, G13     

Intraweek and intraday trade patterns and dynamics

This paper investigates informed traders' order-splitting strategies on different days of the week and times of the day for a sample of stocks traded on the Australian Stock Exchange. Based on cumulative price changes, we document that informed traders tend to use medium size trades. We find that informed investors concentrate their strategic trading on Mondays and particularly during the first trading hour. In addition, informed investors also use large size trades around market opening and closing, as well as on days other than Mondays and Fridays. These results are more pronounced for the large market capitalization stocks.     

Size Effects in the Pricing of Corporate Bonds

Large orders for corporate bonds get preferential treatment unlike large orders for stocks on the NYSE. A structural explanation, namely, that the corporate bond market is dealer‐dominated, has been offered for the favorable pricing. In this paper, we offer an additional explanation, namely, that the improved pricing for large orders is due to the net impact such orders have on a market maker's costs. Using a data sample that is substantially free of timing mismatch, we support our assertion by sorting the sample into ‘brokered’ trades, which are trades where the dealer merely crosses buy and sell orders and ‘inventoried’ trades, where the dealer trades out of his inventory. We find that large orders raise information costs, but lower inventory costs for ‘inventoried’ trades. The net result is a smaller price advantage than received by large orders on ‘brokered’ trades which are not subject to these costs.     

Market transparency,liquidity externalities,and institutional trading costs in corporate bonds

We develop a simple model of the effect of public transaction reporting on trade execution costs and test it using a sample of institutional trades in corporate bonds, before and after initiation of the TRACE reporting system. Trade execution costs fell approximately 50% for bonds eligible for TRACE transaction reporting, and 20% for bonds not eligible for TRACE reporting, suggesting the presence of a “liquidity externality.” The key results are robust to changes in variables, such as interest rate volatility and trading activity that might also affect execution costs. Market shares and the cost advantage to large dealers decreased post-TRACE. These results indicate that market design can have first-order effects, even for sophisticated institutional customers.     

Preferencing, Internalization, Best Execution, and Dealer Profits

The practices of preferencing and internalization have been alleged to support collusion, cause worse execution, and lead to wider spreads in dealership style markets relative to auction style markets. For a sample of London Stock Exchange stocks, we find that preferenced trades pay higher spreads, however they do not generate higher dealer profits. Internalized trades pay lower, not higher, spreads. We do not find a relation between the extent of preferencing or internalization and spreads across stocks. These results do not lend support to the "collusion" hypothesis but are consistent with a "costly search and trading relationships" hypothesis.     

Secondary Trading Costs in the Municipal Bond Market

Using new econometric methods, we separately estimate average transaction costs for over 167,000 bonds from a 1‐year sample of all U.S. municipal bond trades. Municipal bond transaction costs decrease with trade size and do not depend significantly on trade frequency. Also, municipal bond trades are substantially more expensive than similar‐sized equity trades. We attribute these results to the lack of bond market price transparency. Additional cross‐sectional analyses show that bond trading costs increase with credit risk, instrument complexity, time to maturity, and time since issuance. Investors, and perhaps ultimately issuers, might benefit if issuers issued simpler bonds.     

Block Trade Price Asymmetry and Changes in Depth: Evidence from the Australian Stock Exchange

This paper examines the price response to large block transactions on the Australian Stock Exchange during the 1999 sample period. We find asymmetry in the price reaction between buyer‐ and seller‐initiated trades with respect to size and resiliency following the trade. We extend previous research by examining order book changes surrounding block trades and relating price effects to changes in book depth. Purchases are associated with persistent order book imbalance, while the sales imbalance is insignificant. Cross‐sectional analysis demonstrates that price resiliency following a trade is related to the speed at which limit orders arrive to replenish book depth.     

Ripples through markets: Inter-market impacts generated by large trades

This paper uses a sample of large trades executed on the London Stock Exchange's SEAQ-I market for European cross-traded firms to investigate their impact on home market prices when parallel markets suffer from information frictions. I find that (a) large London trades produce price impacts in home markets even though no timely information is published, (b) market makers appear to pre- and post-position their inventories by splitting orders across markets, and (c) the price discovery process across markets changes significantly around large trades with the foreign market making a significantly bigger contribution to price discovery at this time, even though information opaqueness exists.     

What's Not There: Odd Lots and Market Data

We investigate odd‐lot trades in equity markets. Odd lots are increasingly used in algorithmic and high‐frequency trading, but are not reported to the consolidated tape or in databases such as TAQ. In our sample, the median number of odd‐lot trades is 24% but in some stocks odd lots are 60% or more of trading. Odd‐lot trades contribute 35% of price discovery, consistent with informed traders using odd lots to avoid detection. Omitting odd‐lot trades leads to inaccuracies in order imbalance measures and makes sentiment measures unreliable. Excluding odd lots from the consolidated tape raises important regulatory issues.     

Are Japanese margin buyers informed?

Using Japanese long sample (1977–2010) market data, we examine whether margin buying is informed trades about future stock returns and whether they are related to undervaluation of the market. We find that margin buying increases when temporary returns are higher contemporaneously. We do not find that Japanese margin buying is well-informed in predicting future permanent changes in stock returns. Further, we find that margin buying is not related to the undervaluation of stock market prices.     

THE ROLE OF INFORMATION AND THE TIME BETWEEN TRADES: AN EMPIRICAL INVESTIGATION

Previous studies propose that the time between trades is a measure of the existence of information and a manifestation of the demand and supply of liquidity. I find evidence that the time between trades is a measure of the existence of information. However, the evidence does not imply that liquidity constraints are an unimportant determinant of price changes. Further investigation indicates that price changes are partially related to liquidity constraints, when the liquidity constraint is measured by the availability of multiple counterparties. Finally, I find some evidence that information about trades, not necessarily related to information about the underlying asset, also affects price changes.     

The summary informativeness of stock trades: an econometric analysis

In a security market with asymmetrically informed participants,trades are signals of private information. In this article,new measures of trade informativeness are proposed based ona decomposition of the variance of changes in the efficientprice into trade-correlated and -uncorrelated components. Thetrade-correlated component has a natural interpretation as anabsolute measure of trade informativeness. The ratio of thiscomponent to the total variance is a relative measure (i.e.,a proportion normalized with respect to the total public information).For a sample of NYSE-listed companies, trades are found to bemore informative for small firms in both absolute and relativesenses. From an analysis of intraday patterns, it appears thattrades are in absolute terms more informative at the beginningof trading, but slightly less informative in relative terms.     

The Effect of Option Listing on Bid-Ask Spreads,Price Volatility,and Trading Activity of the Underlying OTC Stocks

This paper examines the changes in spreads, price volatility, and trading activity surrounding option listing for a sample of 144 OTC stocks. For this sample, both price volatility and volume increase, but the evidence on spreads is mixed. The increase in price volatility is attributed primarily to an increase in residual return variances. Furthermore, price volatility increases even after controlling for volume, insider trading, and spreads. Although these variables do not fully explain the causes for the increase in price volatility after option listing, the results suggest that liquidity trading or volume has a stronger effect on price volatility than insider trading. This study also finds that both the number of trades and institutional holdings show substantial increases, which are supportive of the notion that listing of options on OTC stocks attracts more attention.     

Which trades move prices in emerging markets?: Evidence from China's stock market

This paper extends Barclay and Warner's [Barclay, M.J. and J.B. Warner (1993), ‘Stealth trading and volatility: which trades move prices?’, Journal of Financial Economics, vol. 34, pp. 281–306.] original work on stealth trading by analysing which trades move price for the emerging Chinese stock market. A large block trade/manipulation hypothesis is proposed in addition to the stealth and public information hypotheses examined by Barclay and Warner. Using high-frequency data the results show that while medium and large-size trades are associated with disproportionately large, overall, cumulative stock price changes, it is the large-size trades (in terms of the number of transactions) which have the largest effect on cumulative price increases. Thus, while there is some support for stealth trading in the Chinese market, there are other effects in operation such as large block trades/price manipulation.     

Caught on tape: Institutional trading,stock returns,and earnings announcements

Many questions about institutional trading can only be answered if one tracks high-frequency changes in institutional ownership. In the United States, however, institutions are only required to report their ownership quarterly in 13-F filings. We infer daily institutional trading behavior from the “tape”, the Transactions and Quotes database of the New York Stock Exchange, using a sophisticated method that best predicts quarterly 13-F data from trades of different sizes. We find that daily institutional trades are highly persistent and respond positively to recent daily returns but negatively to longer-term past daily returns. Institutional trades, particularly sells, appear to generate short-term losses—possibly reflecting institutional demand for liquidity—but longer-term profits. One source of these profits is that institutions anticipate both earnings surprises and post-earnings announcement drift. These results are different from those obtained using a standard size cutoff rule for institutional trades.     

Day end returns—stock price manipulation

In this paper, we examine if closing prices are manipulated. Earlier research has shown that closing prices are one of the most used benchmarks against which trader performance is evaluated. If a trader takes a big net position a given day, it is likely that he wants to enhance his performance by manipulating the closing price. We build a simple regression model to test for closing price manipulation in the Finnish stock market. Robustness checks were made for the effect of: (a) size of the net position; (b) differences in returns across firms; (c) different size of net position for different firms, block trades and spread trades. The results before close, for the base case, were in line with our hypothesis. However, the robustness checks showed that block trades and spread trades explained a part, but not all, of our results. The results after close were generally weak, but tilted towards our hypothesis.     

Measuring the Information Content of Stock Trades

This paper suggests that the interactions of security trades and quote revisions be modeled as a vector autoregressive system. Within this framework, a trade's information effect may be meaningfully measured as the ultimate price impact of the trade innovation. Estimates for a sample of NYSE issues suggest: a trade's full price impact arrives only with a protracted lag; the impact is a positive and concave function of the trade size; large trades cause the spread to widen; trades occurring in the face of wide spreads have larger price impacts; and, information asymmetries are more significant for smaller firms.     

A stochastic dominance analysis of yen carry trades

Yen carry trades have made headline news for over a decade. We examine the profitability of such trades for the period 2001–2009. Yen carry trades generated high mean returns and Sharpe ratios prior to the recent financial crisis. They continued to outperform major stock markets for the full sample period. Given the non-normality of carry trade returns, we apply non-parametric tests based on stochastic dominance (SD) to evaluate whether the high returns of yen carry trades are compatible with risk as reflected in returns on US and global stock market indices. We apply a general test for SD developed recently by Linton, Maasoumi and Whang (2005) to six currencies as well as portfolios of these currencies. For a large class of risk-averse investors, profits from yen carry trades cannot be attributed to risks.     

Tick test accuracy in foreign exchange ECN markets

Recent computer quoting activity has increased the allure of the tick test because the quote rule and its variants require matching asynchronous trade and quote records. We find tick test accuracy of 1.2 million forex trades is about 67% which falls to 63% for zerotick trades (half the sample). Accuracy declines as quoted spreads decrease and as time to the previous trade increases. We observe extreme asymmetry for midquote changes, where buyer accuracy is 96% (27%) for up (down) changes, respectively. The quote rule is about 77% accurate. The group tick test is superior to the bulk volume classification method.