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). App...
Saved in:
Main Authors: | TAY, Anthony S., TING, Christopher, TSE, Yiu Kuen, Warachka, Mitchell |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2004
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/lkcsb_research/2373 https://ink.library.smu.edu.sg/context/lkcsb_research/article/3372/viewcontent/TransactionDataAnalMarkedDurations_2004_wp.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Using high-frequency transaction data to estimate the probability of informed trading
by: TAY, Anthony S., et al.
Published: (2009) -
Modeling transaction data of trade direction and estimation of probability of informed trading
by: TAY, Anthony S., et al.
Published: (2007) -
Using High-Frequency Transaction Data to Estimate the Probability of Informed Trading
by: Tay, Anthony S., et al.
Published: (2009) -
Intraday periodicity adjustments of transaction duration and their effects on high-frequency volatility estimation
by: TSE, Yiu Kuen, et al.
Published: (2014) -
Estimation of Monthly Volatility: An Empirical Comparison of Realized Volatility, GARCH and ACD-ICV Methods
by: LIU, Shouwei, et al.
Published: (2013)