Information Environments and High Price Impact Trades: Implication for Volatility and Price Efficiency
57 Pages Posted: 25 Jun 2019
Date Written: June 18, 2019
Using high-frequency transaction and Limit Order Book (LOB) data, we extend the identification dimensions of High Price Impact Trades (HPITs) by using LOB matchedness. HPITs are trades associated with disproportionately large price changes relative to their proportion of volume. We find that a higher presence of HPITs leads to a decline in volatility due to more contrarian trades against uninformed traders, but this decline varies with information environments and liquidity levels. Further, we show that more HPITs lead to higher price efficiency for stocks with greater public disclosure and higher liquidity. Our empirical results provide evidence that HPITs mainly reflect fundamental-based information in a high public information environment, and belief-based information in a low public information environment.
Keywords: Price efficiency, Price discovery, Limit Order Book, Trade size clustering, Stealth trading
JEL Classification: C22, C41, C53, G11
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