1 |
Allen, D., Ng, K. H. and Peiris, S. (2012). Estimating and simulatingWeibull models of risk or price durations: an application to ACD models, North American Journal of Economics and Finance, 25, 214-224.
|
2 |
Allen, D., Ng, K. H. and Peiris, S. (2013). The efficient modelling of high frequency transaction data: a new application of estimating functions in financial economics, Economics Letters, 120, 117-122.
DOI
|
3 |
Bauwens, L. and Giot, P. (2003). Asymmetric ACD models: Introducing price information in ACD models, Empirical Economics, 28, 709-731.
DOI
|
4 |
Bauwens, L. and Hautsch, N. (2009). Modelling Financial High Frequency Data Using Point Processes, Handbook of Financial Time Series, Springer.
|
5 |
Engle, R. F. (2000). The econometrics of ultra-high-frequency data, Econometrica, 68, 1-22.
DOI
|
6 |
Engle, R. F. and Russell, J. R. (1997). Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model, Journal of Empirical Finance, 4, 187-212.
DOI
|
7 |
Engle, R. F. and Russell, J. R. (1998). Autoregressive conditional duration: a new model for irregularly spaced transaction data, Econometrica, 66, 1127-1162.
DOI
|
8 |
Godambe, V. P. (1985). The foundation of finite sample estimation in stochastic processes, Biometrika, 72, 419-428.
DOI
|
9 |
Jo, S. P. (2010). A study on determinants of volatility in intra-day stock return: an application of UHFGARCH-Leverage model, M.A thesis, Hanyang University.
|
10 |
Park, S. N. and Kim, Y. J. (2014). Bayesian forecasting with nonlinear autoregressive conditional duration models, Journal of Industrial Economics and Business, 27, 1-33.
|
11 |
Tsay, R. S. (2010). Analysis of Financial Time Series, Third Ed. Wiley, New York.
|