Endogenous informed trading in the presence of trading costs: Theory and evidence |
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| Affiliation: | 1. School of Soil and Water Conservation, Jixian Research Station for Forest Ecosystem, CFERN/CNERN, Beijing Forestry University, Beijing 100083, China;2. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, No. 20, Chegongzhuang West Road, Haidian District, Beijing 100048, China;3. Soil and Water Conservation Monitoring Station of Ningxia Hui Autonomous Region, Yinchuan 750002, China;4. School of Water Resources and Hydropower, Xi''an University of Technology, Xi''an 710048, China;1. College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China;2. State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, PR China;3. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China;1. College of Business, Zayed University, P.O. Box 144534. Abu Dhabi, United Arab Emirates;2. Federal University of Agriculture, Abeokuta, Nigeria;3. ISCAL – Lisbon Accounting and Business School, Instituto Politécnico de Lisboa, Av. Miguel Bombarda, 20, 1069-035 Lisbon, Portugal;4. SOCIUS / CSG - Research in Social Sciences and Management, Rua Miguel Lupi, 20, 1249-078 Lisbon, Portugal |
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| Abstract: | The basic premise of the model we propose is that market frictions (trading costs) force traders with market-wide information to strategically choose which securities to trade in. We study the effect of recognizing trading costs on the choices of informed traders and the resulting statistical properties of security prices. Specifically, we show that (1) stocks with intermediate β's have the least informative prices, even though they are traded by the greatest number of informed traders; (2) for high β securities, the contemporaneous correlation of prices is close to the correlation in fundamental values; (3) a security with a higher β, higher volume of liquidity trading and lower idiosyncratic variance is more likely to lead another security. With market capitalization as a proxy for the level of liquidity trading, these specific predictions of the model on the lead–lag relationship are also shown to be strongly supported by the data. |
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