Estimation of mis-specified long memory models
نویسندگان
چکیده
منابع مشابه
Issues in the Estimation of Mis-Specified Models of Fractionally Integrated Processes†
In this paper we quantify the impact of model mis-specification on the properties of parameter estimators applied to fractionally integrated processes. We demonstrate the asymptotic equivalence of four alternative parametric methods: frequency domain maximum likelihood, Whittle estimation, time domain maximum likelihood and conditional sum of squares. We show that all four estimators converge t...
متن کاملIndirect Estimation of Long Memory Volatility Models
An indirect estimator is proposed for two long memory volatility models; the fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and the long memory stochastic volatility (LMSV) model. The small sample properties of the indirect estimator are compared to the small sample properties of conventional maximum likelihood estimators. It is found that the ...
متن کاملSemiparametric Estimation of Long-memory Models
This article revises semiparametric methods of inference on different aspects of long memory time series. The main focus is on estimation of the memory parameter of linear models, analyzing bandwidth choice, bias reduction techniques and robustness properties of different estimates, with some emphasis on nonstationarity and trending behaviors. These techniques extend naturally to multivariate s...
متن کاملThe Estimation of Misspecied Long Memory Models
We consider time series that, possibly after integer di¤erencing or integrating or other detrending, are covariance stationary with spectral density that is regularly varying near zero frequency, and unspeci ed elsewhere. This semiparametric framework includes series with short, long and negative memory. We establish consistency of the popular log-periodogram memory estimate that, conventionall...
متن کاملQuasi-Maximum Likelihood Estimation of Long-Memory Stochastic Volatility Models*
We analyze finite sample properties of the quasi-maximum likelihood estimators of longmemory stochastic volatility models. The estimates are done in the time domain using autoregressive and moving average in the state space representation. The results are compared with usual estimators of the long-memory parameter.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Econometrics
سال: 2006
ISSN: 0304-4076
DOI: 10.1016/j.jeconom.2005.06.024