Private Information and High-Frequency Stochastic Volatility

Abstract

We study the effect of privately informed traders on measured price changes and trades in asset markets. In the model exogenous news is captured by signals that informed agents receive. Agents trade anonymously through a market specialist, who does not receive a signal. We show that the entry and exit of informed traders following the arrival of news accounts for high-frequency serial correlation in squared price changes (stochastic volatility) and trades. Because the bid-ask spread of the market specialist tends to shrink as individuals trade and reveal their information, the model also accounts for the empirical observation that high-frequency serial correlation is more pronounced in trades than in squared price changes. * We thank

On the Correlation Structure of Microstructure Noise: A Financial Economic Approach

“…41 Kelly and Steigerwald (2004) take this a step further by linking information persistence and frequency with the difference between prices and trades in the decay rate of autocorrelations. deviation of the bias is large relative to the IV suggests that the learning rate itself may have fluctuated considerably around its increasing trend.…”

Information-based trading, price impact of trades, and trade autocorrelation

“…Because the price impact of a trade is measured by the size of the marketmakerÕs quote revision, the EKO model establishes a direct theoretical link between the price impact of trades and the probability of informationbased trading (PIN). Kelly and Steigerwald (2001) consider a variant of Easley and OÕHara (1992) model and show that the entry and exit of informed traders in response to the random arrival of private information implies that trades are serially correlated. Given that informed traders are trading in the current period, they are likely to trade in the 7 Hasbrouck (1988) holds that the information content of a trade can be measured by the permanent or ultimate price impact of the unexpected component of the trade.…”

“…5 Covrig and Ng (2004) find that institutional trading produces greater clustering of trades than individual investor trading during periods of high information flow. In addition, Kelly and Steigerwald (2001) predict that the size of serial correlation in trade direction increases with the probability of informed-based trading.…”

Volatility clustering and the bid–ask spread: Exchange rate behavior in early Renaissance Florence

“…Several market microstructure models (e.g., Admati and Pfleiderer, 1988;Easley et al, 1997;Kelly and Steigerwald, 2004), however, offer plausible interpretations. These models assume asymmetric information and are concerned with how prices incorporate information using some type of trading scheme.…”