Indian Journal of Finance

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Forecasting Gold Price Using Geometric Random Walk Growth Model


Affiliations
1 Assistant Professor (SS), University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007, Uttarakhand, India
2 Assistant Professor, University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007 Uttarakhand, India
3 Lecturer, University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007, India

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Gold price forecast is important to ascertain the performance of gold as a precious commodity in money and capital markets. This paper addresses the applicability of a geometric random walk model also known as ARIMA(0,1,0) with constant and log transformation as a forecasting tool and analyze the performance of forecast for a short-term and long term horizon. Findings suggest that use of a geometric random walk model to gold price data is valid and comparatively better than other regular ARIMA models. In this study, both in sample and out sample and combined sample forecasts were studied. A forecast for the short-range period is developed and validated through the measures of accuracy of the forecast.

Keywords

ARIMA, Forecasting, Random Walk, Gold Price

C53, G17, E37

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  • Forecasting Gold Price Using Geometric Random Walk Growth Model

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Authors

I. Krishna Murthy
Assistant Professor (SS), University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007, Uttarakhand, India
T. Anupama
Assistant Professor, University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007 Uttarakhand, India
K. Deeppa
Lecturer, University of Petroleum and Energy Studies (UPES), College of Management and Economic Studies, Biholi Campus, Dehradun – 248007, India

Abstract


Gold price forecast is important to ascertain the performance of gold as a precious commodity in money and capital markets. This paper addresses the applicability of a geometric random walk model also known as ARIMA(0,1,0) with constant and log transformation as a forecasting tool and analyze the performance of forecast for a short-term and long term horizon. Findings suggest that use of a geometric random walk model to gold price data is valid and comparatively better than other regular ARIMA models. In this study, both in sample and out sample and combined sample forecasts were studied. A forecast for the short-range period is developed and validated through the measures of accuracy of the forecast.

Keywords


ARIMA, Forecasting, Random Walk, Gold Price

C53, G17, E37