We construct a Kyle (1985)-type market model in which fast and slow traders are present. We perform numerical calculations after deriving the equilibrium condition, described as a simultaneous equation system. A major finding is that the fast trader, who has an advantage in trade frequency, acts...

This paper examines the short-run weak-form efficiency of equities, using a proprietary data set permitting analysis of orderbook characteristics to measure short-term price predictability. The results show that high levels of algorithmic trader activity in a stock lowers the level of short-run...

This study investigates high-frequency herding behavior in TOPIX 100 index-listed stocks and its impact on stock prices over different time horizons around tick size reduction on the Tokyo Stock Exchange. Our results show that high-frequency herding exists, especially at very short time...

Jumps and cojumps are examined in the covariance matrices of high-frequency financial markets. We propose a new method for identifying intraday volatility jumps in the diffusive covariance matrix of asset pairs. Our method avoids model misspecification errors, is able to identify multiple...

In this paper, the interactions between a large informed trader (IT, for short) and a high-frequency trader (HFT, for short) who can anticipate the former's incoming order are studied in an extended Kyle's model. Equilibria under various specific situations are discussed. We find that, in...

We develop a novel experimental paradigm to study the causal impact of trading algorithms on informational efficiency, liquidity, and welfare. In our design, public information about the asset value is revealed during trading, which gives algorithms a reaction speed advantage. We distinguish...