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ARIMA Model – Vietnam’s GDP Forecasting
2021Gross Domestic Product (GDP) is the value of all the finished goods and services produced within the country in a specific time period. It is a common indicator used to measure a nation’s economic growth. In this paper, the authors used the Box-Jenkins method to build an Auto Regressive Integrated Moving Average (ARIMA) which is suitable for Vietnam’s ...
Lê Thị Thúy Hằng +1 more
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ARIMA Modelling and Forecasting
2020The Auto-Regressive Integrated Moving Average (ARIMA) model is the general class of models for modelling and forecasting a time series. It consists of the AR, MA and ARMA models. In this chapter, we will discuss each of these models in turn before summarising the steps for ARIMA modelling. We conclude this chapter with a numerical example.
Timina Liu, Shuangzhe Liu, Lei Shi
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Forecasting stock index returns using ARIMA-SVM, ARIMA-ANN, and ARIMA-random forest hybrid models
International Journal of Banking, Accounting and Finance, 2014The purpose of this paper is to develop and identify the best hybrid model to predict stock index returns. We develop three different hybrid models combining linear ARIMA and non-linear models such as support vector machines (SVM), artificial neural network (ANN) and random forest (RF) models to predict the stock index returns. The performance of ARIMA-
Manish Kumar, M. Thenmozhi
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2004
In this chapter we will deal with classic, linear time series analysis. At first we will define the general linear process.
Jürgen Franke +2 more
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In this chapter we will deal with classic, linear time series analysis. At first we will define the general linear process.
Jürgen Franke +2 more
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Forecasting: Arima or Kalman Models
IFAC Proceedings Volumes, 1985Abstract In this article we have compared two of the currently most interesting quantitative models in forecasting applied to the socio-econcmic field, i.e. the ARIMA model and the Kalman filter. The comparison has been based on three fundamental points of view: model adequacy, identification procedure and forecasting function. We have identified two
J. Dekleva, N. Rožić
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ARIMA Forecasting Models in Inventory Control
Journal of the Operational Research Society, 1982In many industrial inventory control systems the policy of reordering and at what level depends crucially on the statistical properties of the random sum of a sequence of sales demands over the lead time. Current practice has conveniently assumed that the sales demands are independent.
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Forecasting Irish inflation using ARIMA models [PDF]
, 1998 This paper outlines the practical steps which need to be undertaken to use autoregressive integrated moving average (ARIMA) time series models for forecasting Irish inflation. A framework for ARIMA forecasting is drawn up. It considers two alternative approaches to the issue of identifying ARIMA models - the Box Jenkins approach and the objective ...
Meyler, Aidan +2 more
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Prediction Intervals for ARIMA Models
1997The problem of constructing prediction intervals for linear time series (ARIMA) models is examined. The aim is to find prediction intervals which incorporate an allowance for sampling error associated with parameter estimates. The effect of constraints on parameters arising from stationarity and invertibility conditions is also incorporated.
Snyder, R. D. +5 more
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Applied Mechanics and Materials, 2013
It is often the case that managers and social scientists are called to deal with time series. Time series analysis usually involves a study of the components of the time series and finding models that permit statistical inferences and predictions. ARIMA models are, in theory, the most general class of models for forecasting a time series.
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It is often the case that managers and social scientists are called to deal with time series. Time series analysis usually involves a study of the components of the time series and finding models that permit statistical inferences and predictions. ARIMA models are, in theory, the most general class of models for forecasting a time series.
openaire +1 more source