文献类型：期刊文献

英文题名：Preferred numbers and the distributions of trade sizes and trading volumes in the Chinese stock market

作者：Mu, G. -H.[1,2,3];Chen, W.[4];Kertesz, J.[3,5];Zhou, W. -X.[1,2,6,7,8]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Sci, Shanghai 200237, Peoples R China;[3]Budapest Univ Technol & Econ, Dept Theoret Phys, H-1117 Budapest, Hungary;[4]Shenzhen Stock Exchange, Shenzhen 518010, Peoples R China;[5]Aalto Univ, Lab Computat Engn, FIN-02150 Espoo, Finland;[6]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China;[7]E China Univ Sci & Technol, Engn Res Ctr Proc Syst Engn, Minist Educ, Shanghai 200237, Peoples R China;[8]Chinese Acad Sci, Res Ctr Fictitious Econ & Data Sci, Beijing 100080, Peoples R China

年份：2009

卷号：68

期号：1

起止页码：145

外文期刊名：EUROPEAN PHYSICAL JOURNAL B

收录：;EI(收录号：20091912068168);WOS:【SSCI(收录号:WOS:000265308800015)，SCI-EXPANDED(收录号:WOS:000265308800015)】；

基金：This work was partly supported by the National Natural Science Foundation of China (Nos. 70501011 and 70502007), the Shanghai Dawn Light Program, the Program for New Century Excellent Talents in University (No. NCET-07-0288), and the China Scholarship Council (No. 2008674017).

语种：英文

外文关键词：Financial markets

摘要：The distributions of trade sizes and trading volumes are investigated based on the limit order book data of 22 liquid Chinese stocks listed on the Shenzhen Stock Exchange in the whole year 2003. We observe that the size distribution of trades for individualstocks exhibits jumps, which is caused by the number preference of traders when placing orders. We analyze the applicability of the "q-Gamma" function for fitting the distribution by the Cram,r-von Mises criterion. The empirical PDFs of tradingvolumes at different timescales Delta t ranging from 1 min to 240 min can be well modeled. The applicability of the q-Gamma functions for multiple trades is restricted to the transaction numbers Delta na parts per thousand currency sign 8. We find that all the PDFs have power-law tails for large volumes. Using careful estimation of the average tail exponents alpha of the distributions of trade sizes and trading volumes, we get alpha > 2, well outside the L,vy regime.