A Baysian Model of Intraday Specialist Pricing
We develop and test a model of intraday price formation based on an explicit description of a representative market maker whose beliefs evolve according to Bayes’ rule. We derive an estimating equation where the weight the market maker places on the order flow as an information signal can be recovered from the parameter estimates. This weight is a natural measure of information asymmetry since it is the ratio of the quality of private information to the quality of public information. The model is interesting for other reasons as well. First, the model encompasses several other models of intraday price formation. Second, the error term arises endogenously and possesses a natural economic interpretation. Third, the model permits us to partially distinguish the price effects of information asymmetry and inventory control by market makers. Fourth, the model provides a method to assess the implicit costs of trading. We show that there are substantial non-linearities in pricing that may reflect the way in which large blocks are traded in the upstairs market. We estimate the model with a new data set obtained from a NYSE specialist. The data set comprises almost 75,000 records for most of the year 1987 and is o independent interest given the paucity of inventory data. The results provide strong support of information asymmetries, as perceived by the market.
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Web page: http://finance.wharton.upenn.edu/weiss/
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