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5px Helvetica}span.s3 {font: 8.0px Helvetica}The first group of measures focuses on price delay and assess the explanatory power oflagged returns in an extended market model relative to a base model to quantify how speedilyand accurately systematic information is incorporated into prices (Busch & Obernberger,2016). In line with the methodology of Boehmer and Wu (2013) and Philips (2011), Iconstruct two measures using daily stock returns instead of weekly or monthly returns asdaily returns increase the number of observations and diminish potential observation errors.

Unlike the aforementioned authors I use five lagged market returns instead of four laggedreturns for the extended market model to cover all trading days in a week (Busch andObernberger, 2016). In sum, the base market model (2) and extended model (3) estimatedthrough OLS for each firm and each month are as follows:2(,* = ,( + 1(F 2G,* + H(,* (Base model) (3)2(,* = ,( + 1(F 2G,* + 1(I2G,*/IJI>0 + H(,* (Extended market model) (4)where 2(,* is the daily return on stock i, 2G,* is the daily return on the AEX All Share valueweightedindex (a proxy for market return) and 2G,*/I represents the lagged market returns.The key interpretation of both models is that the coefficient for concurrent market return 1(Freflects whether all new information available is incorporated directly into a company’s stockprice. If there is a delay in the incorporation of information into stock prices one observes acoefficient for lagged market returns 1(I that is significantly different from zero in theextended model. In the latter case, the extended model (4) will have higher explanatorypower than the base model (3). The two price delay measures are derived by using theregression estimates of the base and extended model.

The first measure is simply one minusthe ratio of the R2 of the base model over the R2 of the extended market model:

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