Bootstrap prediction intervals for autoregressive conditional duration models
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Publication:5107501
DOI10.1080/00949655.2019.1644513OpenAlexW2963124514MaRDI QIDQ5107501
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Publication date: 27 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2019.1644513
maximum likelihood estimationACD modelsquasi-maximum likelihood estimationconditional least squaresre-sampling
Cites Work
- Unnamed Item
- On Fréchet autoregressive conditional duration models
- Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions
- Bootstrap prediction for returns and volatilities in GARCH models
- The Birnbaum-Saunders autoregressive conditional duration model
- Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market
- Bootstrap procedures under some non-i.i.d. models
- Bootstrapping regression models
- Efficiency and robustness in resampling
- Bootstrap methods: another look at the jackknife
- Sieve bootstrap for time series
- Bootstrapping forecast intervals in ARCH models
- A generalized least squares estimation method for the autoregressive conditional duration model
- Capturing common components in high-frequency financial time series: a multivariate stochastic multiplicative error model
- Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes
- Bootstrap Prediction Intervals for Autoregression
- On a measure of lack of fit in time series models
- Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
- Bootstrap predictive inference for ARIMA processes
- GARCH Models
- Inverse Gaussian Distribution for Modeling Conditional Durations in Finance
- A nonlinear autoregressive conditional duration model with applications to financial transaction data