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Price discovery in a continuous-time setting

Dias, Gustavo F., Fernandes, Marcelo and Scherrer, Cristina M. ORCID: 0000-0002-7935-5378 (2021) Price discovery in a continuous-time setting. Journal of Financial Econometrics, 19 (5). 985 - 1008. ISSN 1479-8409

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Identification Number: 10.1093/jjfinec/nbz030

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.

Item Type: Article
Additional Information: © 2020 The Author(s)
Divisions: Finance
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
JEL classification: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation
C - Mathematical and Quantitative Methods > C3 - Econometric Methods: Multiple; Simultaneous Equation Models; Multiple Variables; Endogenous Regressors > C32 - Time-Series Models
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation
G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency; Event Studies
Date Deposited: 08 Oct 2024 09:09
Last Modified: 26 Nov 2024 23:21
URI: http://eprints.lse.ac.uk/id/eprint/125646

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