Verifying the existence of long-memory feature is a crucial activity performed during the
development process of the autoregressive integrated moving average (ARIMA) model. The …

Economic crises cause significant shortages in disposable income and a sharp decline in
the living conditions, affecting healthcare sector, hitting the profitability and sustainability of …

The autoregressive fractional integrated moving average (ARFIMA) has become one of the
popular linear models in time series modeling and forecasting in the past decades. Recent …

The key condition for applying modern portfolio theory is the stock market efficiency. At the
same time, the results of numerous studies show that markets do not always meet the …

В работе проводится анализ влияния параметров модели ARFIMA на точность про‑
гнозирования финансовых временных рядов на примере искусственно …

The objective of this paper is modeling and forecasting the weekly jute prices of Samsi
market in the Malda district of West Bengal in the presence of long memory process. The …

Today's time series analysis is one of the most important statistical methods in forecasting,
and it has been used in many economic, industrial, commercial and science fields, by …

Berinvestasi adalah salah satu cara untuk meningkatkan kesejahteraan dan kekayaan di
masa depan, saham adalah salah satu pilihan investasi yang paling banyak diminati oleh …

This paper explores the application of the ARFIMA fractal model for prediction of the
dynamics of river water pollution based on BOD measure. The study begins by conducting a …

This article takes Shanghai's GDP as the research object and predicts and analyzes the
GDP of Shanghai for the next ten years by comparing two time series models: ARFIMA and …