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Motivated by the empirical evidence of high-frequency lead-lag effects and cross-asset linkages, we introduce a multi-asset price formation model which generalizes standard univariate microstructure models of lagged price adjustment. Econometric inference on such model provides: (i) a unified statistical test for the presence of lead-lag correlations in the latent price process and for the existence of a multi-asset price formation mechanism; (ii) separate estimation of contemporaneous and lagged dependencies; (iii) an unbiased estimator of the integrated covariance of the efficient martingale price process that is robust to microstructure noise, asynchronous trading, and lead-lag dependencies. Through an extensive simulation study, we compare the proposed estimator to alternative approaches and show its advantages in recovering the true lead-lag structure of the latent price process. Our application to a set of NYSE stocks provides empirical evidence for the existence of a multi-asset price formation mechanism and sheds light on its market microstructure determinants. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

The main goal of the analysis is the verification of whether asynchrony in transaction times is a considerable cause of the Epps effect on the Warsaw Stock Exchange among the most liquid assets. A method for compensating for the impact of asynchrony in trading on the Epps effect is presented. The method is easily applicable. Calculations are made using the exact time of transactions and prices of the assets. The estimation is not biased by intervals during which no transactions have taken place. Among all the analyzed stock pairs, asynchrony turns out to be the main cause of the Epps effect. However, the corrected correlation estimator seems to be more volatile than the regular estimator of the correlation. The presented analysis can be reproduced for the same data or replicated for another dataset; all R codes used in the process of writing this article are available upon request. The main novelty/value added of this paper is the application to an emerging market of a new method for compensating for asynchrony in trading. [ABSTRACT FROM AUTHOR]

Continuous asynchronous trading activity is a key to understanding real-world market behavior. However, it is not easy to implement an agent-based computational market model because of the ambiguity between time and space. In this study, we use a model of asynchrony in a continuous double auction market in the form of noise and order restrictions to link inside- and outside- uncertainties in the economic system. Our model shows intermittent behavior with a small parameter value, which leads to the misapplication of the price-update rule, and consequently drives burst behavior. The statistical property of time development shows a similar tendency to that in previous empirical studies. Thus, it demonstrates the relationship between the asynchronous property and the complexity of economic systems. [ABSTRACT FROM AUTHOR]