Estimating and forecasting the long-memory parameter in the presence of periodicity
Article Abstract:
The Autoregressive Fractionally Integrated Moving Average (ARFIMA) process, a mathematical model which was first introduced in the 1980s, features a long-memory characteristic that is reflected by the hyperbolic delay of its autocorrelation function. The study focuses on modeling long-memory processes with periodicity using Seasonal Autoregressive Fractionally Integrated Moving Average (SARFIMA) processes, which can be used for different seasonal periods.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2007
User Contributions:
Comment about this article or add new information about this topic:
Forecasting volatility
Article Abstract:
The loopholes of several forecasting models and measures for controlling these are presented.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2006
User Contributions:
Comment about this article or add new information about this topic:
- Abstracts: Estimation and testing of time-varying coefficient regression models in the presence of linear restrictions. Analysis of many short time sequences: forecast improvements achieved by shrinkage
- Abstracts: Economic forecasting at high-frequency intervals. Forecasting in the presence of level shifts. Long - Run forecasting in multicointegrated systems
- Abstracts: Level shifts, temporary changes and forecasting. Forecasting international bandwidth capability. Conditional volatility forecasting in dynamic hedging model
- Abstracts: Axiomatic characterizations of the Walras correspondence for generalized economies
- Abstracts: Combination of forecasts using self-organizing algorithms. A note on in-sample and out-of-sample tests for Granger causality