INFORMATION AND NOISE IN FINANCIAL MARKETS: EVIDENCE FROM THE E‐MINI INDEX FUTURES

I examine the informational contributions and effects on transitory volatility of trades initiated by different types of traders in three actively traded index futures markets. The results show that trades initiated by exchange member firms account for more than 60% of price discovery during the trading day. These institutional trades appear to be more informative than trades of individual exchange members or off‐exchange traders. I also find that off‐exchange traders introduce more noise into the prices than do exchange members. My findings provide new evidence on the role of different types of traders in the price formation process.     

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.     

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.     

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.     

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.     

Predictable behavior, profits, and attention

Stocks in the Shanghai market that hit upper price limits typically exhibit three characteristics: high returns, high volumes, and news coverage. We show that these price limit events attract investors' attention. Attention-grabbing events lead active individual investors to buy stocks they have not previously owned. Consistent with lowering investor search costs, events that affect a few (many) stocks lead to increased (decreased) buying. Upper price limit events coincide with initial price increases followed by statistically significant price mean reversion over the following week. Rational traders (statistical arbitrageurs) profit in response to attention-based buying. Smart traders accumulate shares on date t, sell shares on date t + 1, and earn a daily average profit of 1.16%. We show the amount they invest predicts the degree of attention-based buying by individual investors. We end by decomposing individual investor trades in order to estimate losses attributable to behavioral biases.     

Time and the Process of Security Price Adjustment

This paper delineates the link between the existence of information, the timing of trades, and the stochastic process of prices. We show that time affects prices, with the time between trades affecting spreads. Because the absence of trades is correlated with volume, our model predicts a testable relation between spreads and normal and unexpected volume, and demonstrates how volume affects the speed of price adjustment. Our model also demonstrates how the transaction price series will be a biased representation of the true price process, with the variance being both overstated and heteroskedastic.     

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.     

Time and the Price Impact of a Trade

We use Hasbrouck's (1991) vector autoregressive model for prices and trades to empirically test and assess the role played by the waiting time between consecutive transactions in the process of price formation. We find that as the time duration between transactions decreases, the price impact of trades, the speed of price adjustment to trade-related information, and the positive autocorrelation of signed trades all increase. This suggests that times when markets are most active are times when there is an increased presence of informed traders; we interpret such markets as having reduced liquidity.     

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.     

Inflation-indexed swaps and swaptions

This article considers the pricing and hedging of inflation-indexed swaps, and the pricing of inflation-indexed swaptions, and options on inflation-indexed bonds. To price the inflation-indexed swaps, we suggest an extended HJM model. The model allows both the forward rates and the consumer price index to be driven, not only by a standard multidimensional Wiener process but also by a general marked point process. Our model is an extension of the HJM approach proposed by Jarrow and Yildirim [Jarrow, R., Yildirim, Y., 2003. Pricing treasury inflation protected securities and related derivatives using an HJM model. Journal of Financial and Quantitative Analysis 38, 409–430] and later also used by Mercurio [Mercurio, F., 2005. Pricing inflation-indexed derivatives. Quantitative Finance 5 (3), 289–302] to price inflation-indexed swaps. Furthermore we price options on so called TIPS-bonds assuming the model is purely Wiener driven. We then introduce an inflation swap market model to price inflation-indexed swaptions. All prices derived have explicit closed-form solutions. Furthermore, we formally prove the validity of the so called foreign-currency analogy.     

Order Flow and Expected Option Returns

I show that the inventory risk faced by market‐makers has a first‐order effect on option prices. I introduce a simple approach that decomposes the price impact of trades into inventory risk and asymmetric information components. While both components are large for option trades, the inventory risk component is larger. Using the full panel of daily option returns, I find that option order imbalances attributable to inventory risk have five times larger impact on option prices than previously thought. Finally, I find that past order imbalances have greater predictive power than any other commonly used predictor of option returns.     

Price impact of block trades: the curious case of downstairs trading in the EU emissions futures market

Using high-frequency data from the European Climate Exchange (ECX), we examine the determinants of price impact of €21 billion worth of block trades during 2008–2011 in the European carbon market. We find that wider bid-ask spreads and volatility are characterised by a smaller price impact. Larger levels of price impact are more likely to occur during the middle of the trading day, specifically the four-hour period between 11 a.m. and 3 p.m., than during the first or final hours. Purchase block trades induce a relatively smaller price impact on price run-up, while sell block trades exhibit a larger price impact on price run-up. We conclude that block trades on the ECX induce less price impact than in equity or conventional futures markets, and that a significant proportion of the effects contradict findings on block trades in those markets; thus, we provide the first evidence of the curious bent to block trading in the European Union emissions trading scheme.     

Does stealth trading coexist with high levels of insider trading? Evidence from Kuwait

Stealth trading has been found to exist in the US, where informed investors submit medium-sized trades to reduce price impacts and camouflage their information. This paper reexamines this finding by placing the analysis in a different setting in which insider trading and private information sharing is very common during two different time periods — bull and bear markets. Using data on 34 stocks listed on the Kuwait Stock Exchange, I find that stealth trading exists in these two time periods. However, during bullish periods, stealth trading occurs through small-sized trades, while in bear markets, it occurs through medium-sized trades.     

Regime switching affine processes with applications to finance

We introduce the notion of a regime switching affine process. Informally this is a Markov process that behaves conditionally on each regime as an affine process with specific parameters. To facilitate our analysis, specific restrictions are imposed on these parameters. The regime switches are driven by a Markov chain. We prove that the joint process of the Markov chain and the conditionally affine part is a process with an affine structure on an enlarged state space, conditionally on the starting state of the Markov chain. Like for affine processes, the characteristic function can be expressed in a set of ordinary differential equations that can sometimes be solved analytically. This result unifies several semi-analytical solutions found in the literature for pricing derivatives of specific regime switching processes on smaller state spaces. It also provides a unifying theory that allows us to introduce regime switching to the pricing of many derivatives within the broad class of affine processes. Examples include European options and term structure derivatives with stochastic volatility and default. Essentially, whenever there is a pricing solution based on an affine process, we can extend this to a regime switching affine process without sacrificing the analytical tractability of the affine process.     

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).     

Intraday Behavior of Stock Prices and Trades around Insider Trading

Our evidence indicates that insiders' trades provide significant new information to market participants and they are incorporated more fully in stock prices as compared to noninsiders' trades. We find that market professionals do not front-run insiders' trades. Both insiders' purchases and sales result in significant contemporaneous and subsequent price impact, while sales by large shareholders result in a contemporaneous stock price decline that is subsequently reversed. The arrival of insider purchases reverse the prevailing negative order imbalances from third party trades and lead to piggy-backing by market professionals resulting in subsequent market purchase orders as well as stock price increases.     

Inferring Public and Private Information from Trades and Quotes

We propose a new model that uses nonsynchronous, ultra‐high frequency data to analyze the sequential impact of trades and quotes on the price process. Private information is related to the impact of trades and public information to the impact of quotes. The model is extended to include various other factors that affect public and private information. For 20 active Nasdaq stocks, private information causes, on average, 9.43% of daily stock price movements. Additionally, quotes are more informative when (1) many dealers set the best price and (2) traditional market makers rather than Electronic Communication Networks set the best price.     

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.     

Order anticipation around predictable trades

I study the presence of order anticipation strategies by examining predictable patterns in large order trades. I construct three simple signals based on child-order execution patterns and find empirical evidence that stronger signals are correlated with higher execution costs. I use the SEC's (Securities and Exchange Commission's) ban on unfiltered access and increase in noise trading as shocks to order anticipatory activities of algorithmic traders and find that the price impact of predictability is smaller when order anticipation becomes difficult. The empirical findings are mostly consistent with the back-running theory that predicts delayed price impact as strategic traders learn about large orders gradually.