Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

Earnings Announcements, Asymmetric Information, Trades and Quotes

This paper empirically analyses trades and quotes around the times of 37 earnings announcements in the Paris Bourse. We find that trading volume is larger on announcement days, spreads are wider after announcements, and the permanent positive (resp. negative) price impact of purchases (sales) is greater around announcements. While the findings pertaining to the spread and the permanent impact of trades are consistent with the view that earnings announcements correspond to an increase in information asymmetries, the result that trading volume is larger suggests that other effects are at work.     

Market Structure and Transaction Costs of Index CDSs

Despite regulatory efforts to promote all-to-all trading, the post–Dodd-Frank index credit default swap market remains two-tiered. Transaction costs are higher for dealer-to-client than interdealer trades, but the difference is explained by the higher, largely permanent, price impact of client trades. Most interdealer trades are liquidity motivated and executed via low-cost, low-immediacy trading protocols. Dealer-to-client trades are nonanonymous; they almost always improve upon contemporaneous executable interdealer quotes, and dealers appear to price discriminate based on the perceived price impact of trades. Our results suggest that the market structure is a consequence of the characteristics of client trades: relatively infrequent, large, and differentially informed.     

Information Disclosure and Stock Liquidity: Evidence from Borsa Italiana

This article examines the effect of increased corporate information disclosure on stock liquidity. Using the adoption of International Financial Reporting Standards (IFRS) in Italy as a natural experiment we extend previous work examining the effect on one measure of liquidity—bid‐ask spreads—to others, specifically depth and the price impact of transactions (or effective bid‐ask spreads). Consistent with previous research we find that bid‐ask spreads of stocks decline following the introduction of IFRS, which implies that stock liquidity increases for small traders. However, we also provide evidence that depth at the best quotes declines, which challenges the proposition that liquidity increases for large trades following an increase in disclosure. In additional tests, we find that effective bid‐ask spreads of block trades also decline following the introduction of IFRS. Overall, this evidence confirms that stock liquidity for both small and large trades increases following an increase in corporate information disclosure.     

Trading and Liquidity on the Tokyo Stock Exchange: A Bird's Eye View

The trading mechanism for equities on the Tokyo Stock Exchange (TSE) stands in sharp contrast to the primary mechanisms used to trade stocks in the United States. In the United States, exchange-designated specialists have affirmative obligations to provide continuous liquidity to the market. Specialists offer simultaneous and tight quotes to both buy and sell and supply sufficient liquidity to limit the magnitude of price changes between consecutive transactions. In contradistinction, the TSE has no exchange-designated liquidity suppliers. Instead, liquidity is provided through a public limit order book, and liquidity is organized through restrictions on maximum price changes between trades that serve to slow down trading. In this article, we examine the efficacy of the TSE's trading mechanisms at providing liquidity. Our analysis is based on a complete record of transactions and best-bid and best-offer quotes for most stocks in the First Section of the TSE over a period of 26 months. We study the size of the bid-ask spread and its cross-sectional and intertemporal stability; intertemporal patterns in returns, volatility, volume, trade size, and the frequency of trades; and market depth based on the response of quotes to trades and the frequency of trading halts and warning quotes.     

The role of trades in price convergence: A study of dual-listed Canadian stocks

We examine the role of trades in restoring price parity for equities trading in multiple markets. Using a sample of stocks trading on the Toronto Stock Exchange and on the NYSE, AMEX or NASDAQ, we contrast price convergence when market makers (a) observe only lagged quotes from both markets and (b) also observe local order flow. Traditional error correction model estimates show that prices in the two markets adjust towards parity in response to quoted price discrepancies, meaning that observation of the cross-market quote helps restore parity. Including order flow in an augmented error correction model, we find that incremental price convergence occurs when trades are routed to the market with the better price, and the importance of quotes in the price convergence process is reduced. Cross-sectional analysis reveals that the importance of order flow in each market is decreasing in firm size and increasing in measures of liquidity. Our findings point to an important, and hitherto unexamined, role for trades in promoting inter-market price convergence.     

Impacts of trades in an error-correction model of quote prices

In this paper we analyze and interpret the quote price dynamics of 100 NYSE stocks stratified by trade frequency. We specify an error-correction model for the log difference of the bid and the ask price with the spread acting as the error-correction term, and include as regressors the characteristics of the trades occurring between quote observations, if any. From this model we are also able to extract the implied model for the spread and the mid-quote. We find that short duration and medium volume trades have the largest impacts on quote prices for all one hundred stocks. Further, we find that buys have a greater impact on the ask price than on the bid price, while sells have a greater impact on the bid price than on the ask price. Both buys and sells increase spreads in the short run, but in the absence of further trades, the spreads mean revert. Trades have a greater impact on quotes for the infrequently traded stocks than for the more actively traded stocks.     

Adverse selection costs,trading activity and price discovery in the NYSE: An empirical analysis

This paper studies the role that trading activity plays in the price discovery process of a NYSE-listed stock. We measure the expected information content of each trade by estimating its permanent price impact. It depends on observable trade features and market conditions. We also estimate the time required for quotes to incorporate all the information content of a particular trade. Our results show that price discovery is faster after risky trades and also at the extreme intervals of the session. The quote adjustment to trade-related shocks is progressive and this causes risk persistency and unusual short-term market conditions.     

Informed trading and the price impact of block trades: A high frequency trading analysis

Using high frequency data from the London Stock Exchange (LSE), we investigate the relationship between informed trading and the price impact of block trades on intraday and inter-day basis. Price impact of block trades is stronger during the first hour of trading; this is consistent with the hypothesis that information accumulates overnight during non-trading hours. Furthermore, private information is gradually incorporated into prices despite heightened trading frequency. Evidence suggests that informed traders exploit superior information across trading days, and stocks with lower transparency exhibit stronger information diffusion effects when traded in blocks, thus informed block trading facilitates price discovery.     

Co-movements of index options and futures quotes

We report evidence that the co-movements of index options and index futures quotes differ sharply from perfect correlation in periods with option trades. In half-hour intervals with (without) option trades 25% (12%) of call option quote changes have either the opposite sign or are larger in magnitude than the corresponding index futures quote changes. We calibrate a stochastic volatility model that allows for trade and no-trade periods using real data and simulate the joint co-movements of index quotes and option quotes in this model. We show that for trade intervals the observed co-movements differ from the benchmark case established by our simulations approximately three times too often. We provide empirical evidence that market microstructure effects – specifically, stale quotes and aggressive quotes – explain the majority of the deviations from the benchmark. Our findings are relevant for techniques that use estimates of local co-movements as inputs to price or hedge options.     

Pricing and information content of block trades on the Shanghai Stock Exchange

We study the pricing mechanisms and information content of block trades on the Shanghai Stock Exchange (SSE) for the six year period from 2003 to 2009.There is an average of about 4% block discount, which is large in magnitude and statistically significant, reflecting compensation for locating counterparties and the cost of negotiating terms. We also examine permanent price impacts of the trades and find that discount block trades (DBTs) have significant negative permanent price impacts for various periods extended up to 60 trading days after the block trades. Conversely, premium block trades (PBTs) have small and statistically insignificant negative permanent price impacts, suggesting that buyers do not possess valuable private information. Finally, we classify the trades into buys and sells using a set of stricter rules and note similar results to those of DBTs and PBTs. Of additional note, block sells on stocks with expirations of restricted shares seem to have significant information content. As these trades are more likely to be originated from insiders, our results suggest that they strategically time the sale of these shares to maximize gains.     

FURTHER EXAMINATION OF PRICE DISCOVERY ON THE NYSE AND REGIONAL EXCHANGES

I re‐examine price discovery on the New York Stock Exchange (NYSE) and regional exchanges. I employ three common‐trend cointegration models to analyze the equilibrium dynamics between the NYSE and regional exchanges for the thirty Dow stocks. The overall results show that whether the regional exchanges free‐ride on the NYSE in obtaining equilibrium prices depends on whether trade prices or quotes are examined. The regional exchanges play a significant (though less important) role in the price‐discovery process for trade prices. However, the contributions of regional exchanges in price discovery of quotes are negligible. I explain the inconsistency between the results using quotes and those using trades. I also highlight the problems of using either quotes or trades in examining this free‐riding hypothesis and suggest future research on the different informativeness of trades on the NYSE and regional exchanges. JEL classification: G20, C32.     

Single-stock futures: Evidence from the Indian securities market

Although single-stock futures (SSFs) are useful multi-purpose stock derivatives, they have not received much attention in developed markets. We analyze SSFs in the Indian market to understand their contribution in price leadership. The findings indicate that trades in the stock market contribute more to price discovery than trades in the SSF market (72% and 28%, respectively), while quotes in the SSF market are more price innovative than quotes in the stock market (39% and 61%, respectively). Our analysis suggests that while stock and SSF trade returns have predictive ability for each other, in the case of quotes, only SSF quotes have predictive ability for stock and SSF returns.     

Quote revision and information flow among foreign exchange dealers

In a multi-dealer market without transaction disclosure, quote revision partially reveals the posting dealer's private information/belief and may have an impact on other dealers’ pricing decision. Using continuous quotes from three major dealers in the interbank foreign exchange market, I find significant information externality from one dealer's quotes to others. The information content of quote revision is positively related to the overall order flow to the market, as opposed to order flow to the posting dealer. At 15-min interval or above, public information becomes the dominant component that drives quote revision. Furthermore, public information appears to induce positive serial correlation and private information causes negative serial correlation in short-term quote revision.     

Information-Based Trading and Price Improvement

Abstract:  In this study we test the information hypothesis of price improvement. Our results show that price improvement is negatively related to both the probability of information-based trading and the price impact of trades. We interpret these results as evidence that liquidity providers selectively offer price improvements according to the information content of trades. We also show that liquidity providers offer greater (and more frequent) price improvements when they are at the NBBO, and for stocks with wider spreads, fewer trades, or smaller trade sizes relative to the quoted depth. Buyer-initiated trades receive smaller (larger) price improvements than seller-initiated trades on the NYSE (NASDAQ).     

Quotes,Prices, and Estimates in a Laboratory Market

This study examines the behavior of laboratory markets in which two uninformed market makers compete to trade with heterogeneously informed investors. The data provide three main results. First, market makers set quotes to protect against adverse selection and to control inventory. Second, when investors are less well-informed, their trades are less reliable measures of their information, and market makers respond to those trades with greater skepticism. Third, errors in market makers' reactions to trades cause the time-series behavior of quotes and prices to depend on the information environment in ways beyond those captured in extant theory.     

Fluctuations and response in financial markets: the subtle nature of ‘random’ price changes

Using trades and quotes data from the Paris stock market, we show that the random walk nature of traded prices results from a very delilcated interplay between two opposite tendencies: long-range correlated market orders that lead to super-diffusion (or persistence), and mean revrting limit orders that lead to sub-diffusion (or anti-persistence). We define and study a model where the price, at any instant, is the result of the impact of all past trades, mediated by a non-constant ‘propagator’ in time that describes the response of the market to a single trade. Within this model, the market is shown to be, in a precise sense, at a critical point, where the price is purely diffusive and the average response function almost constant. We find empirically, and discuss theoretically, a fluctuation-response relation. We also discuss the fraction of truly informed market orders, that correctly anticipate short-term moves, and find that it is quite small.     

Do private firm valuations contain incremental information content over routine analyst valuations?

In this study, we seek to investigate whether private expert valuations commissioned for specific transactions outside the exchange contain incremental information content over public analyst valuations published routinely by investment houses. First, we find that public valuations are based to a larger extent on financial statements and market quotes, whereas private valuations tend to be based on other, non-public information. Second, we show that investors’ response to both public and private valuations is cautious in the short-run as well as in the long-run. Third, we provide evidence that despite the fact that private valuations have the advantage of time, human resources, and better access to non-public information, they do not provide different results than those obtained from public valuations. We conclude that while private valuations may be captured as more accurate and reliable, their superiority over public valuations is questionable at best.     

Trade classification algorithms for electronic communications network trades

Ellis et al. [Ellis, K., Michaely, R., O’Hara, M., 2000. The accuracy of trade classification rules: Evidence from Nasdaq. Journal of Financial and Quantitative Analysis 35 (4), 529–551] find that trade classification rules have limited success in classifying trades which execute inside the quotes. We reconfirm this result and propose an alternative algorithm to improve the classification accuracy for trades inside the quotes. This alternative algorithm improves the overall success rate for classifying trades, especially for trades that occur inside the quotes. Additionally, we show that the Lee and Ready [Lee, C., Ready, M., 1991. Inferring trade direction from intraday data. Journal of Finance 46, 733–747] and Ellis et al. (2000) trade classification algorithms provide biased estimates of the actual effective spreads and price impacts, while our algorithm provides statistically unbiased estimates of actual effective spreads and price impacts.     

Opening and closing behavior following the introduction of call auctions in Singapore

The Singapore Exchange introduced opening and closing call auctions in August 2000. We find that the frequency of call trades is lower than on other markets. However, when auctions are used, the percentage of daily volume traded in the auction is high. Many days without call trades have quotes during the pre-call periods so that there is an opportunity for learning about equilibrium prices even when there are no call trades. Consistent with prior research, the introduction of call auctions enhances market quality at the open and the close. The call auctions also helped to address the issues that motivated their introduction in Singapore. That is, they increased the volume traded at the opening in initial public offerings and reduced the incidence of closing price manipulation.