What do price discovery metrics really measure?

A market is typically considered to dominate price discovery if it is the first to reflect new information about the fundamental value. Our simulations indicate that common price discovery metrics – Hasbrouck information share and Harris–McInish–Wood component share – are only consistent with this v...

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Bibliographic Details
Published in:Journal of empirical finance 2013-09, Vol.23, p.68-83
Main Author: Putnin, Talis J
Format: Article
Language:English
Subjects:
Component share
Information
Information leadership share
Information share
Liquidity
Market analysis
Market theory
Price discovery
Prices
Value
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Summary:A market is typically considered to dominate price discovery if it is the first to reflect new information about the fundamental value. Our simulations indicate that common price discovery metrics – Hasbrouck information share and Harris–McInish–Wood component share – are only consistent with this view of price discovery if the price series have equal levels of noise, including microstructure frictions and liquidity. If the noise in the price series differs, the information and component shares measure a combination of leadership in impounding new information and relative avoidance of noise, to varying degrees. A third price discovery metric, the ‘information leadership share’ uses the information share and the component share together to identify the price series that is first to impound new information. This third metric is robust to differences in noise levels and therefore correctly attributes price discovery in a wider range of settings. Using four recent empirical studies of price discovery we show that the choice and interpretation of price discovery metrics can have a substantial impact on conclusions about price discovery. •We use simulations to show what price discovery metrics really measure.•When price channels differ in noise traditional price discovery metrics are biased.•The ‘information leadership share’ is robust to differences in noise levels.•The choice of metric can substantially influence conclusions in empirical research.
ISSN:0927-5398
1879-1727
DOI:10.1016/j.jempfin.2013.05.004