Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79418
Authors: 
Jordá, Oscar
Liu, Holly
Williams, Jeffrey
Year of Publication: 
2002
Series/Report no.: 
Working Papers, University of California, Davis, Department of Economics 02-4
Abstract: 
This paper contains three useful contributions: (1) it collects a new data-set of electronic transaction data on soybean futures from the Dalian Futures Exchange in China that records, not only the usual elements of each transaction (such as price and size) but also identifies broker and customer identities, variables not usually obtainable; (2) it presents new econometric methods for the analysis of dynamic multivariate count data based on the autoregressive conditional intensity model of Jordà and Marcellino (2000); and (3) together, the new data and econometric methods allow us to investigate, in a manner not available before, the determinants and effects of non-institutional market making (or scalping).
Subjects: 
market making
autoregressive conditional intensity
high-frequency data
JEL: 
G13
G14
C32
Document Type: 
Working Paper

Files in This Item:
File
Size
227.96 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.