| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ East Anglia, Sch Econ, Norwich, Norfolk - England
[2] CREATES, London - England
[3] FGV, Sao Paulo Sch Econ, Sao Paulo - Brazil
[4] Univ East Anglia, Norwich Business Sch, Norwich, Norfolk - England
Total Affiliations: 4
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| Document type: | Journal article |
| Source: | JOURNAL OF FINANCIAL ECONOMETRICS; v. 19, n. 5, p. 985-1008, FAL 2021. |
| Web of Science Citations: | 0 |
| Abstract | |
We formulate a continuous-time price discovery model and investigate how the standard price discovery measures vary with respect to the sampling interval. We find that the component share (CS) measure is invariant to the sampling interval, and hence, discrete-sampled prices suffice to identify the continuous-time CS. In contrast, information share (IS) estimates are not comparable across different sampling intervals because the contemporaneous correlation between markets increases in magnitude as the sampling interval grows. We show how to back out the continuous-time IS from discrete-sampled prices under certain assumptions on the contemporaneous correlation. We assess our continuous-time model by comparing the estimates of the (continuous-time) CS and IS at different sampling intervals for 30 stocks in the United States. We find that both price discovery measures are typically stable across the different sampling intervals, suggesting that our continuous-time price discovery model fits the data very well. (AU) | |
| FAPESP's process: | 13/22930-0 - Price discovery in high-dimensional arbitrage portfolios |
| Grantee: | Pedro Luiz Valls Pereira |
| Support Opportunities: | Research Projects - Thematic Grants |