Univariate Time Series Forecasting of Domestic Gold Prices: Empirical Evidence from SARIMA Modeling and Mann-Kendall Trend Analysis

SURU MUNDA; SANDEEP KUMAR MUND

Univariate Time Series Forecasting of Domestic Gold Prices: Empirical Evidence from SARIMA Modeling and Mann-Kendall Trend Analysis

Author(s)	Dr. SURU MUNDA, Mr. SANDEEP KUMAR MUND
Country	India
Abstract	Gold occupies a distinctive position in India, serving not only as a cultural emblem but also as a reliable financial asset and a barometer of economic conditions. This study analyzes monthly gold price data from January 2011 to February 2026 (182 observations) and generates forecasts up to February 2027 using a Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The results underscore the influence of culturally driven demand, especially during festivals and wedding periods, which produces clear and recurring seasonal fluctuations in prices. The time series initially exhibited non-stationarity; therefore, first-order differencing was applied to achieve stationarity and ensure appropriate model estimation. Seasonal patterns were detected at 12- and 24-month intervals, reflecting consistent annual consumption behavior. Among the models evaluated, SARIMA(0,1,0)(2,0,0)[12] provided the best fit, effectively capturing both the underlying trend and seasonal dynamics compared to non-seasonal alternatives. Diagnostic checks confirmed the model’s reliability, showing no significant autocorrelation in residuals and stable variance. The analysis also revealed a persistent upward trend in gold prices, with an average monthly increase of about INR 249 per 10 grams during the study period. This trend is consistent with broader macroeconomic influences such as currency depreciation, global economic uncertainty, and sustained domestic demand. Forecasts indicate that prices are likely to continue rising, with an estimated increase of around 14% over the projection period. However, the widening forecast intervals highlight growing uncertainty, suggesting the potential impact of unforeseen external factors not accounted for in the model. In conclusion, the study demonstrates the importance of integrating cultural seasonality into financial time series modeling in the Indian context. The findings provide meaningful insights for policymakers, investors, and researchers interested in understanding and predicting commodity price behavior.
Keywords	Gold prices, India, SARIMA model, seasonality, forecasting.
Field	Mathematics > Statistics
Published In	Volume 7, Issue 3, May-June 2026
Published On	2026-05-11

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Univariate Time Series Forecasting of Domestic Gold Prices: Empirical Evidence from SARIMA Modeling and Mann-Kendall Trend Analysis

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