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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 Risk
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.