Improving on daily measures of price discovery
Gustavo Fruet Dias,
Marcelo Fernandes () and
Cristina Mabel Scherrer
No 444, Textos para discussão from FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil)
We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily VECM regressions as standard in the literature. We show that our estimator is not only consistent, but also outperforms the standard daily VECM in finite samples. We illustrate our theoretical findings by studying the price discovery process of 10 actively traded stocks in the U.S. from 2007 to 2013.
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