ScholarLens Back to search
2019•International Journal of Applied Mathematics & Statistics/International journal of applied mathematics and statisticsOpen access

Forecasting Gold Price: An Application of Auto Regressive Integrated Moving Average Model

M. O. Faruk, Md. Moyazzem Hossain

Open full text 0 citations

Abstract

In recent years, the trend of the global gold price has attracted a lot of attention and the price of gold has terrifying spike compared to historical trend. In this paper, an attempt has been made to develop a model for forecasting the gold price. The sample data of gold price (in USD per ounce) were taken from January, 1950 to January, 2018. This paper uses the Box-Jenkin's Auto Regressive Integrated Moving Average (ARIMA) methodology for building the forecasting model. Results advocate that ARIMA(1,1,2)(1,1,2)12 is the most suitable model to be used for predicting the gold price.

About this research paper

What this paper is about

In recent years, the trend of the global gold price has attracted a lot of attention and the price of gold has terrifying spike compared to historical trend. In this paper, an attempt has been made to develop a model for forecasting the gold price. The sample data of gold price (in USD per ounce) were taken from January, 1950 to January, 2018. This paper uses the Box-Jenkin's Auto Regressive Integrated Moving Average (ARIMA) methodology for building the forecasting model. Results advocate that ARIMA(1,1,2)(1,1,2)12 is the most suitable model to be used for predicting the gold price.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In recent years, the trend of the global gold price has attracted a lot of attention and the price of gold has terrifying spike compared to historical trend. In this paper, an attempt has been made to develop a model for forecasting the gold price. The sample data of gold price (in USD per ounce) were taken from January, 1950 to January, 2018. This paper uses the Box-Jenkin's Auto Regressive Integrated Moving Average (ARIMA) methodology for building the forecasting model. Results advocate that ARIMA(1,1,2)(1,1,2)12 is the most suitable model to be used for predicting the gold price.

Key concepts: Autoregressive integrated moving average, Fluid ounce (US), Econometrics, Moving average, Autoregressive model, Gold as an investment, Sample (material), Economics

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
Forecasting Gold Price: An Application of Auto Regressive Integrated Moving Average Model — Research Paper | ScholarLens