Abstract
We propose a state-space modeling approach for decomposing trading volume into its liquidity-driven and information-driven components. Using a set of high-frequency S&P 500 stock data, we show that informed trading is linked with a reduction in volatility, illiquidity, and toxicity/adverse selection. We observe that our estimated informed trading component of volume is a statistically significant predictor of one-second stock returns; however, it is not a significant predictor of one-minute stock returns. This disparity is explained by high-frequency trading activity, which eliminates pricing inefficiencies at low latencies.
Original language | English |
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Number of pages | 19 |
Journal | Journal of Financial Markets |
Early online date | 27 Aug 2019 |
DOIs | |
Publication status | E-pub ahead of print - 27 Aug 2019 |
Keywords / Materials (for Non-textual outputs)
- trading volume
- permanent component
- transitory component
- market quality
- time series models
- state-space modeling
- high-frequency trading