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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/27131
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| Title: | Modeling Market Microstructure Time Series |
| Authors: | Hasbrouck, Joel |
| Issue Date: | 16-Feb-1996 |
| Series/Report no.: | FIN-95-024 |
| Abstract: | Microstructure data typically consist of trades and bid and offer quotes
for financial securities that are collected at fine sampling intervals
(often within the day). This paper reviews approaches taken to modeling
these data. The emphasis is on the techniques of stationary multivariate
time series analysis: autoregressive and moving average representations
o f standard microstructure models, vector autoregressive estimation,
random-walk decompositions and cointegration. The paper also discusses
the challenges posed by irregular observation frequencies, discreteness
and nonlinearity. |
| URI: | http://hdl.handle.net/2451/27131 |
| Appears in Collections: | Finance Working Papers
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