Stationary Bootstrap Prediction Intervals for GARCH(p,q)
نویسندگان
چکیده
منابع مشابه
Semiparametric Bootstrap Prediction Intervals in time Series
One of the main goals of studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by an autoregressive process. The...
متن کاملBootstrap prediction intervals for autoregressive time series
This paper is concerned with the calculation of interval forecasts for highly-persistent autoregressive (AR) time series using the bootstrap. Three methods are considered for countering the small-sample bias of least squares estimation for processes which have roots close to the unit circle: a bootstrap bias-corrected OLS estimator; the use of the Roy-Fuller estimator in place of OLS; and the u...
متن کاملBootstrap prediction intervals for Markov processes
Given time series data X1, . . . , Xn, the problem of optimal prediction of Xn+1 has been well-studied. The same is not true, however, as regards the problem of constructing a prediction interval with prespecified coverage probability for Xn+1, i.e., turning the point predictor into an interval predictor. In the past, prediction intervals have mainly been constructed for time series that obey a...
متن کاملBootstrap Prediction Intervals for Threshold Autoregressive Models
This paper proposes the use of prediction intervals based on bootstrap for threshold autoregressive models. We consider four bootstrap methods to account for the variability of estimated threshold values, correct the bias of autoregressive coefficients and allow for heterogenous errors. Simulation shows that bootstrap prediction intervals generally perform better than classical prediction inter...
متن کاملOn the Consistency of Sieve Bootstrap Prediction Intervals for Stationary Time Series
In the article, we consider construction of prediction intervals for stationary time series using Bühlmann’s [8], [9] sieve bootstrap approach. Basic theoretical properties concerning consistency are proved. We extend the results obtained earlier by Stine [21], Masarotto and Grigoletto [13] for an autoregressive time series of finite order to the rich class of linear and invertible stationary m...
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: Communications for Statistical Applications and Methods
سال: 2013
ISSN: 2287-7843
DOI: 10.5351/csam.2013.20.1.041