Private Information and High-Frequency Stochastic Volatility
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David L. Kelly
We study the effect of privately informed traders on measured high frequency price changes and trades in asset markets. We use a standard market microstructure framework where exogenous news is captured by signals that informed agents receive. 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. A calibration test of the model shows that the features of the market microstructure, without serially correlated news, accounts qualitatively for the serial correlation in the data, but predicts less persistence than is present in the data.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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- Private Information and High-Frequency Stochastic Volatility
- The ARAR Error Model for Univariate Time Series and Distributed Lag
- Inferring the Forward Looking Equity Risk Premium from Derivative Prices
- An Investigation of Current Account Solvency in Latin America Using Non Linear Nonstationarity Tests
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Artikel in diesem Heft
- Article
- Private Information and High-Frequency Stochastic Volatility
- The ARAR Error Model for Univariate Time Series and Distributed Lag
- Inferring the Forward Looking Equity Risk Premium from Derivative Prices
- An Investigation of Current Account Solvency in Latin America Using Non Linear Nonstationarity Tests
- Switching Regimes in the Term Structure of Interest Rates during U.S. Post-War: A Case for the Lucas Proof Equilibrium?
