Measuring private information in a specialist market |
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| Affiliation: | 1. Department of Finance, The University of Arizona, Eller College of Management, Tucson 85721, United States;2. College of Business, University of Michigan-Dearborn, Dearborn, MI 48128, United States;1. Department of Finance, School of Business, University at Albany, State University of New York, Albany, NY, United States;2. Bank of Israel, Israel;3. Bar-Ilan University, Israel;1. Department of Mathematics, Southeast University, Nanjing 210096, PR China;2. School of Mathematical Sciences, Kaili University, Kaili 556011, PR China;1. Department of Economics, Michigan State University, East Lansing, MI 48824-1024, USA;2. Department of Finance, Michigan State University, East Lansing, MI 48824-1024, USA;3. School of Economics and Finance, Queen Mary University of London, UK;4. Rimini Center for Economic Analysis, Italy;5. Department of Economics, Kookmin University, Seoul, Republic of Korea |
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| Abstract: | ![]()
Since the reduced forms of the popular measures of asymmetric information in the price formation process are not nested within larger models we cannot evaluate their fit using standard statistical tools. Furthermore, pairwise correlations amongst the measures are small. We benchmark these measures cross-sectionally to realized specialist loss rates (using alternatively volume and number of trades) in the TORQ data. While five of the six measures are significantly correlated with this benchmark, this is only because they are correlated with the specialist participation rate. We infer that the measures do not measure private information in order flow, even in the setting for which they are designed. |
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