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What factors drive price discovery for cross-listed shares? Several significant variables were identified, but the literature assumes that their impact is symmetric throughout the distribution of information shares. Using data from 25 companies listed in the five largest Euro-area stock markets, we examine possible asymmetries using an unconditional quantile regression model, while also expanding the number of possible drivers. We find that liquidity, trading costs, and the probability of informed trading have a higher impact on the middle quantiles compared to the tails, implying that changes in market quality are more important to the price discovery process when the competition among markets is high and less important when informativeness is biased towards one market. Also, we document that price discovery varies with market momentum (mostly positive impact), country risk (mostly negative impact), and financial stress (positive impact), showing a novel ‘flight-to-safety’ effect in price discovery. |
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