International price discovery in the presence of microstructure noise

This paper addresses and resolves the issue of microstructure noise when measuring the relative importance of home and U.S. market in the price discovery process of Canadian interlisted stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, due to the considerable amount of microstructure noise inherent in return data at very high frequencies, these estimators are distorted. We offer a modified approach that identifies unique information shares based on distributional assumptions and thereby enables us to control for microstructure noise. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been underestimated so far. Moreover, we suggest that rather than stock specific factors, market characteristics determine information shares

Tell-tale tails: A data driven approach to estimate unique market information shares

The trading of securities on multiple markets raises the question of each market's share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions. Thereby we resolve the main drawback of the widely used Hasbrouck (1995) methodology which merely delivers upper and lower bounds of a market's information share. When these bounds diverge, as is the case in many applications, informational leadership becomes blurred. We show how fat tails and tail dependence of price changes, which emerge as a result of differences in market design and liquidity, can be exploited to estimate unique information shares. The empirical application of the new methodology emphasizes the leading role of the credit derivatives market compared to the corporate bond market in pricing credit risk during the pre-crisis period. --price discovery,information share,fat tails,tail dependence,liquidity,credit risk

International price discovery in the presence of market microstructure effects

This paper addresses and resolves the problems caused by microstructure effects when measuring the relative importance of home and U.S. market in the price discovery process of internationally cross listed stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, this entails a potential bias of estimated information shares induced by microstructure effects. We propose a modified approach that relies on distributional assumptions and yields unique and unbiased information shares. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been severely underestimated to date. Moreover, we find that rather than stock specific factors, market design determines information shares. --international cross-listings,market microstructure effects,price discovery

Limit order books and trade informativeness

In the microstructure literature, information asymmetry is an important determinant of market liquidity. The classic setting is that uninformed dedicated liquidity suppliers charge price concessions when incoming market orders are likely to be informationally motivated. In limit order book markets, however, this relationship is less clear, as market participants can switch roles, and freely choose to immediately demand or patiently supply liquidity by submitting either market or limit orders. We study the importance of information asymmetry in limit order books based on a recent sample of thirty German DAX stocks. We find that Hasbrouck’s (1991) measure of trade informativeness Granger-causes book liquidity, in particular that required to fill large market orders. Picking-off risk due to public news induced volatility is more important for top-of-the book liquidity supply. In our multivariate analysis we control for volatility, trading volume, trading intensity and order imbalance to isolate the effect of trade informativeness on book liquidity. JEL Classification: G14 Keywords: Price Impact of Trades , Trading Intensity , Dynamic Duration Models, Spread Decomposition Models , Adverse Selection Ris

International price discovery in the presence of market microstructure effects

This paper addresses and resolves the problems caused by microstructure effects when measuring the relative importance of home and U.S. market in the price discovery process of internationally cross listed stocks. In order to avoid large bounds for information shares, previous studies applying the Cholesky decomposition within the Hasbrouck (1995) framework had to rely on high frequency data. However, this entails a potential bias of estimated information shares induced by microstructure effects. We propose a modified approach that relies on distributional assumptions and yields unique and unbiased information shares. Our results indicate that the role of the U.S. market in the price discovery process of Canadian interlisted stocks has been severely underestimated to date. Moreover, we find that rather than stock specific factors, market design determines information shares

Tell-tale tails: A data driven approach to estimate unique market information shares

The trading of securities on multiple markets raises the question of each market's share in the discovery of the informationally efficient price. We exploit salient distributional features of multivariate financial price processes to uniquely determine these contributions. Thereby we resolve the main drawback of the widely used Hasbrouck (1995) methodology which merely delivers upper and lower bounds of a market's information share. When these bounds diverge, as is the case in many applications, informational leadership becomes blurred. We show how fat tails and tail dependence of price changes, which emerge as a result of differences in market design and liquidity, can be exploited to estimate unique information shares. The empirical application of the new methodology emphasizes the leading role of the credit derivatives market compared to the corporate bond market in pricing credit risk during the pre-crisis period

Understanding the limit order book: Conditioning on trade informativeness

Electronic limit order books are ubiquitous in markets today. However, theoretical models for limit order markets fail to explain the real world data well. Sandas (2001) tests the classic Glosten (1994) model for order book equilibrium and rejects it. We reconfirm this result for one of the largest European stock markets. We then relax one of the model's assumptions and allow the informational content of trades to change over time. Adapting Hasbrouck's (1991a,b) methodology to estimate time varying trade informativeness we find that it is a slowly mean reverting process. By conditioning on trade informativeness, we find support for the Glosten model's implication that books are more shallow during times of informative market orders. However, a high level of liquidity supply is committed up to an economically significant trade size volume, even when trade informativeness is high. This can be seen as a vindication of the open order book design which dispenses with dedicated market makers. We also find evidence for a market order trader population which is quite heterogenous with respect to price sensitivity

Common Scaling Patterns in Intertrade Times of U. S. Stocks

We analyze the sequence of time intervals between consecutive stock trades of thirty companies representing eight sectors of the U. S. economy over a period of four years. For all companies we find that: (i) the probability density function of intertrade times may be fit by a Weibull distribution; (ii) when appropriately rescaled the probability densities of all companies collapse onto a single curve implying a universal functional form; (iii) the intertrade times exhibit power-law correlated behavior within a trading day and a consistently greater degree of correlation over larger time scales, in agreement with the correlation behavior of the absolute price returns for the corresponding company, and (iv) the magnitude series of intertrade time increments is characterized by long-range power-law correlations suggesting the presence of nonlinear features in the trading dynamics, while the sign series is anti-correlated at small scales. Our results suggest that independent of industry sector, market capitalization and average level of trading activity, the series of intertrade times exhibit possibly universal scaling patterns, which may relate to a common mechanism underlying the trading dynamics of diverse companies. Further, our observation of long-range power-law correlations and a parallel with the crossover in the scaling of absolute price returns for each individual stock, support the hypothesis that the dynamics of transaction times may play a role in the process of price formation.Comment: 8 pages, 5 figures. Presented at The Second Nikkei Econophysics Workshop, Tokyo, 11-14 Nov. 2002. A subset appears in "The Application of Econophysics: Proceedings of the Second Nikkei Econophysics Symposium", editor H. Takayasu (Springer-Verlag, Tokyo, 2003) pp.51-57. Submitted to Phys. Rev. E on 25 June 200