Marked Durations and Their Implications for Market Microstructure
نویسندگان
چکیده
An Autoregressive Conditional Marked Duration (ACMD) model for the analysis of irregularly spaced transactions data is proposed. Based on the Autoregressive Conditional Duration (ACD) model of Engle and Russell (1998), the ACMD model assigns marks to characterize events such as price movements, order arrivals, or quote revisions. By marking tick movements, we study the influence of trade frequency, direction, and size as well as their interactions on price dynamics. We then analyze their effects on volatility as well as the revision of beliefs. Applying the ACMD model with order flow as the marks, estimates for the probability of informed trading are obtained after relaxing several assumptions in the literature. We find that trade frequency has a critical role in price dynamics, while the contribution of volume to the revision of beliefs, volatility, and the probability of informed trading is marginal.
منابع مشابه
Office of Research Transaction-Data Analysis of Marked Durations and Their Implications for Market Microstructure
We propose an Autoregressive Conditional Marked Duration (ACMD) model for the analysis of irregularly spaced transaction data. Based on the Autoregressive Conditional Duration (ACD) model, the ACMD model assigns marks to characterize events such as tick movements and trade directions (buy/sell). Applying the ACMD model to tick movements, we study the influence of trade frequency, direction and ...
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