This paper empirically examines limit order revisions and cancellations which contribute to a significant portion of the order activity in many order-driven markets. We document that limit orders are more likely to be revised or cancelled if they are large and near the bid-ask quote. We show that order revisions generate net economic benefits to traders. Our evidence shows strong links between these activities and limit order submission risk using bid-ask spread, volatility and post-event return as proxies. We also find that these activities are less intense when the opportunity cost to monitor a stock is high, such as during lunch hours or when stock volume relative to the entire market is low.

This study employs firm-specific announcements as a proxy for information flows and investigates the information–volatility relation using high-frequency data from the Australian Stock Exchange. Our analysis reveals a positive and significant impact of the arrival rate of the selected news variable on the conditional variance of stock returns, even after controlling for the potential effects of trading volume and high opening volatility. Furthermore, the inclusion of the news variable in the conditional variance equation of the generalized autoregressive conditional heteroscedastic model also reduces volatility persistence, especially with intraday data. Combined with the evidence that news arrivals display a very strong pattern of autocorrelation, our results are consistent with the Mixture of Distribution Hypothesis, which attributes conditional heteroscedasticity of stock returns to time-dependence in the news arrival process.