TY - JOUR
T1 - Institutional trading and Abel Noser data
AU - Hu, Gang
AU - Jo, Koren M.
AU - Wang, Yi Alex
AU - Xie, Jing
N1 - We thank the editor (Stuart L. Gillan) and the referee for their detailed comments that helped us improve the paper significantly. For helpful discussions, we thank Amber Anand, Eli Bartov, Ekkehart Boehmer, Thomas Chemmanur, Agnes Cheng, Zhi Da, Ilia Dichev, Fangjian Fu, Tyler Henry, Dashan Huang, Pankaj Jain, Michael Jung, Byoung Kang, Bin Ke, Jennifer Koski, Weikai Li, JC Lin, Andy Puckett, Zhen Shi, Wanshan Song, Chester Spatt, Jun Tu, John Wei, Russ Wermers, Franco Wong, Yong Yu, and participants at AsianFA 2018 Conference in Tokyo, 2018 JAAF Conference in Jeju and seminars at Chinese University of Hong Kong Shenzhen, Hong Kong Polytechnic University, and Singapore Management University. Hu thanks Ani Chitaley, Peter Lert, Mark Matthews, and other former colleagues at Fidelity Management & Research Company's Global Equity Trading group for introducing him into the world of institutional trading, and their instrumental help in obtaining Abel Noser data for academic research. Hu also thanks Abel Noser, especially Gene Noser and Jamie Noser, for generously providing their institutional trading data, and Siu Chang, Allison Keane, Judy Maiorca, Bruce Stewart, John Thomas, and Marsha Tracer at or formerly at Abel Noser for excellent technical assistance and answering numerous data questions over the years. Hu acknowledges support from the National Natural Science Foundation of China (NSFC No. 71471130). All remaining errors or omissions are our own.
PY - 2018/10
Y1 - 2018/10
N2 - We survey the growing academic literature using Abel Noser data, including 55 publications thus far. We analyze publication patterns to explore how the availability of a specialized microstructure dataset propagates across different areas within finance and into other disciplines such as accounting. Of note, we identify corporate finance and accounting as the most under-researched areas that offer promising opportunities for future academic research using the data. To provide guidance for researchers interested in using Abel Noser data, we analyze institutional trading using transaction-level data spanning more than 12 years and covering 233 million transactions with $37 trillion traded. We provide background information on the origin and history of the data, offer suggestions for cleaning and using the data, and discuss (dis)advantages of Abel Noser compared to other data sources for institutional trading. We also document two simple facts: 1) institutional trade sizes decline dramatically over time, rendering trade size-based inferences of institutional trades problematic; 2) we estimate that Abel Noser data cover 12% of CRSP volume over our sample period and 15% for 1999–2005, significantly higher than the estimate in Puckett and Yan (2011) for 1999–2005: 8%, a widely quoted number in the literature. This background should prove useful for researchers seeking to address a number of as yet unexplored issues, especially in corporate finance and accounting research.
AB - We survey the growing academic literature using Abel Noser data, including 55 publications thus far. We analyze publication patterns to explore how the availability of a specialized microstructure dataset propagates across different areas within finance and into other disciplines such as accounting. Of note, we identify corporate finance and accounting as the most under-researched areas that offer promising opportunities for future academic research using the data. To provide guidance for researchers interested in using Abel Noser data, we analyze institutional trading using transaction-level data spanning more than 12 years and covering 233 million transactions with $37 trillion traded. We provide background information on the origin and history of the data, offer suggestions for cleaning and using the data, and discuss (dis)advantages of Abel Noser compared to other data sources for institutional trading. We also document two simple facts: 1) institutional trade sizes decline dramatically over time, rendering trade size-based inferences of institutional trades problematic; 2) we estimate that Abel Noser data cover 12% of CRSP volume over our sample period and 15% for 1999–2005, significantly higher than the estimate in Puckett and Yan (2011) for 1999–2005: 8%, a widely quoted number in the literature. This background should prove useful for researchers seeking to address a number of as yet unexplored issues, especially in corporate finance and accounting research.
KW - Abel Noser
KW - Accounting
KW - ANcerno
KW - Corporate Finance
KW - Institutional Investor
KW - Investments
KW - Market Microstructure
KW - Trading
UR - http://www.scopus.com/inward/record.url?scp=85054083488&partnerID=8YFLogxK
U2 - 10.1016/j.jcorpfin.2018.08.005
DO - 10.1016/j.jcorpfin.2018.08.005
M3 - Journal article
AN - SCOPUS:85054083488
SN - 0929-1199
VL - 52
SP - 143
EP - 167
JO - Journal of Corporate Finance
JF - Journal of Corporate Finance
ER -