Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5095765 | Journal of Econometrics | 2015 | 26 Pages |
Abstract
We propose to compute the Intraday Value-at-Risk (IVaR) for stocks using real-time transaction data. Tick-by-tick data filtered by price duration are modeled using a two-state asymmetric autoregressive conditional duration (AACD) model, and the IVaR is calculated using Monte Carlo simulation based on the estimated AACD model. Backtesting results for the New York Stock Exchange (NYSE) show that the IVaR calculated using the AACD method outperforms those using the Dionne et al. (2009) and Giot (2005) methods.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Shouwei Liu, Yiu-Kuen Tse,