DETERMINANTS OF GOLD RETURN IN INDONESIA: EMPIRICAL EVIDENCE OF INFLATION, EXCHANGE RATES, OIL PRICES, CAPITAL MARKET PERFORMANCE, AND WORLD GOLD PRICES

  • Fikri Budi Aulia Faculty of Economics and Business, Janabadra University, Yogyakarta
  • Sutrisno Sutrisno Faculty of Business and Economics, Islamic University of Indonesia, Yogyakarta
  • Zaenal Arifin Faculty of Business and Economics, Islamic University of Indonesia, Yogyakarta

DOI

https://doi.org/10.53625/ijss.v5i6.12986

Keywords

Antam Gold Return, Inflation, Exchange Rate, World Oil, JCI, XAUUSD, OLS, VAR, IRF

Abstract

This study aims to analyze the determinants of gold return in Indonesia using the static approach of Ordinary Least Squares (OLS) and the dynamic approach of Vector Autoregression (VAR) equipped with the Impulse Response Function (IRF). The research variables include inflation (INF), USD/IDR (KURS), world oil prices (OIL), capital market performance proxied by JCI (CMP), and world gold prices (XAUUSD). The data used is in the form of monthly data for the period January 2009-December 2025. Domestic gold returns are measured using Antam gold. The findings show the difference in results between static and dynamic models. In the OLS model, inflation has a significant negative effect on gold returns at a significance level of 10%, while other variables are insignificant. In the VAR model with an optimal lag of 2, the exchange rate has a significant positive effect on lag-2 and oil prices have a significant positive effect on lag-1 on gold returns. IRF analysis shows that capital market performance shocks produce strong but relatively brief negative responses, while exchange rate shocks and XAUUSD produce more persistent positive responses. Inflation shows the relatively longest duration of the response before returning to the initial condition. These results indicate a time-lagged transmission and a response mechanism that is not entirely in line with the view of contemporary direct relationships. The implications of the study confirm the importance of considering market dynamics and transmission channels when evaluating gold as a safe haven and inflation hedge

Downloads

Download data is not yet available.

References

[1] Al-Yahyaee, K., Al-Malki, M., & Man, N. (554, 124350). Gold price forecasting using a wavelet-based neural network model. Physica A: Statistiktical Mechanics and its Applications, 2020.

[2] Alwadeai, A., Vlasova, N., Mareeh, H., & Aljonaid. (2024). Beyond traditional defenses: Unraveling the dynamics of reserves and exchange rate volatility in the face of economic sanctions. Russian Journal of Economics, 10(1),1-19.

[3] Andriyana, Y., Tantular, B., Mindra, J., Nalita, Y., & Falah, A. (2023). Global gold prices forecasting using Bayesian nonparametric quantile generalized additive model. International Journal of Data & Network Science, 7 (3).

[4] Anisa, I., & Darmawan, A. (2018). The Influence of Macroeconomics and World Mining Commodity Prices on the Mining Sector Stock Price Index in Indonesia. Journal of Business Administration (JAB), 56(1), 197–206.

[5] Anusara Sawangchai, Worakamol Wisetsri, & Mohsin Raza. (2021). How macroeconomic indicators influence gold price management. Emerald, 2075–2087.

[6] aletAndrangi. (2003). Are Gold and Platinum Prices Able to Forecast U.S. Macroeconomic Variables?

[7] Batten, J., Ciner, C., & Lucey, B. (2010). The macroeconomic determinants of volatility in precious metals markets. Resources Policy, 35(2), 65-71.

[8] Baur, D., & McDermott, T. (2010). Is gold a safe haven? International evidence. Journal of Banking & Finance, 34(8), 1886-1898.

[9] Baur, D. G., & Lucey, B. M. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. The Financial Review, 45(2), 217-229.

[10] Bampinas, G., & Panagiotidis, T. (2015). On the relationship between oil and gold before and after financial crisis: Linear, nonlinear and time-varying causality testing. . Studies in Nonlinear Dynamics & Econometrics, 19(5), 657–668.

[11] BeckmannJ.,, & Czudaj, R. (2013). Gold and the Dollar: A Volatility Analysis. Resources Policy, Elsevier, Vol.38, No. 4, p 503-513.

[12] Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16–24.

[13] Beckmann, J., Berger, T., & Czudaj, R. (2019). Gold price dynamics and the role of uncertainty. Quantitative Finance, 19(4), 663–681.

[14] Blose, L. (2010). Gold prices, cost of carry, and expected inflation. Journal of Economics and Business.

[15] Bouoiyour, J., Selmi, R., & Wohar, M. (2018). Measuring the response of gold prices to uncertainty: An analysis beyond the mean. Economic Modelling, 75, 105–116.

[16] Capie, F., Mills, T., & Wood, G. (2005). Gold as a hedge against the dollar. Journal of International Financial Markets, Institutions and Money, 343-352.

[17] Chuang, O.-C., Gupta, R., Pierdzioch, C., & Shu, B. (2024). Financial Uncertainty and Gold Market Volatility: Evidence from a Generalized Autoregressive Conditional Heteroschedasticity Variant of the Mixed-Data Sampling (GARCH-MIDAS) Approach with Variable Selection. Econometrics, 12 (4), 38.

[18] Chen, P., Miao, X., & Tee, K. (2023). Do gold prices respond more to uncertainty shocks at the zero lower bound? Resources Policy, 86.

[19] Ciner, C., Gurdgiev, C., & Lucey, B. (2013). Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates. International Review of Financial Analysis, 29, 202–211.

[20] Cai, Y., & Sheng, G. (2021). The impact of economic policy uncertainty on gold futures market: Evidence from US and UK.,. Economic Computation and Economic Cybernetics Studies and Research, 55(1), 105–122.

[21] Chang, Y., Ye, Z., & Warren, C. (2024). The reaction of gold to energy and cryptocurrency market uncertainties: Evidence from quantile approaches. Resources Policy, 89.

[22] Devi, B., Reddy, K., & Venkatesan, V. (2021). A comparative study of time series and machine learning models in gold price forecasting. Materials Today: Proceedings, 45(Part 2), 3121–3125.

[23] Das, P., Roy, S., & Rai, B. (2022). Analysis and prediction of gold price using machine learning approaches. International Journal of System Assurance Engineering and Management, 13(Suppl 1), 565–573.

[24] Eichengreen , B., Ferrari Minesso, M., & Mehl, A. (2023). Sanctions and the Exchange Rate in Time. Economic Policy, 38(116), 675-703.

[25] Fuyao LI, & YahuaYin. (2026). Study on the safe-haven and hedging roles of bitcoin, gold, and crude oil on global stock markets in short-term, medium-to-long-term, and shock periods . Elsevier, 472-489.

[26] Frankel, J. (2013). The effect of interest rates on commodity prices. Journal of International Money and Finance, 32, 60-87.

[27] Ghazali, N., Zulkhibri , M., & Osman, N. (2015). A review of the literature on the determinants of gold price. Journal of Economic and Social Thought, 2 (1), 12-20.

[28] Ghazali dkk M.F.,. (2015). Gold as Investment Safe Haven: Evidence from Malaysia. Journal of Economics, Business and Management, Vol.3, No.3, p 322-325.

[29] Ghosh, D., Levin, E., Macmillan, P., & Wright. (2004). Gold as an inflation hedge? Studies in Economics and Finance, 22(1), 1-25.

[30] Gurgul, H., & Lach, L. (2012). The causal link between the Polish stock market and gold prices. Managerial Economics, 11, 47–64.

[31] Hájek, P., & Novotný, J. (2022). Fuzzy rule-based prediction of gold prices using news sentiment analysis. Expert Systems with Applications, 193.

[32] Hood, M., & Malik, F. (2013). The nature of volatility spillover between stock market and gold market. The North American Journal of Economics and Finance, 26, 533–542.

[33] Ibrahim, M. (2012). Financial market risk and gold investment in an emerging market: The case of Malaysia. International Journal of Islamic and Middle Eastern Finance and Management.

[34] Ibrahim H.M. (2014). Financial Market Integration and Gold Prices: Evidence from Malaysia. Economic Modelling, Elsevier, Vol. 43, p. 48-59.

[35] Itskhoki , O., & Mukhin, D. (2025). Sanctions and the Exchange Rate. The Review of Economic Studies.

[36] Jaiswal, S., Srivastava, S., Garg, S., & Singh. (2023). Effect of news headlines on gold price prediction using NLP and deep learning. 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), 781–786.

[37] Jeanneret Alexander Dr., & Dr. Dorion Christian. (2018). Are Gold and Platinum Prices Able to Forecast U.S. Macroeconomic Variables? Hec Montreal.

[38] Jin Shang, & ShigeyukiHamori. (2023). Differential Tail Dependence between Crude Oil and Forex Markets in Oil-Importing and Oil-Exporting Countries during Recent Crisis Periods. MDPI, 1 - 24.

[39] Joy, M. (2011). Gold and the US dollar: What’s the 'right' price for gold? Bank for International Settlements. [Working Paper], BIS Working Papers No. 349.

[40] Kabra, G., Inani, S., Nagpal, G., & Vihari, N. (2023). Bibliometric analysis of forecasting gold prices using neural network models: A review and future research agenda. 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 1-6.

[41] Kong, R. (2024). Machine Learning Models for Gold Price Prediction: A Comparative Analysis and Evaluation. Highlights in Business, Economics and Management, 40, 429-435.

[42] Kilimci, Z. (2020). Ensemble regression-based gold price (XAU/USD) prediction. 2020 5th International Conference on Computer Science and Engineering (UBMK), 84-89.

[43] K, P. (2018). Gold Price Forecasting using Support Vector Regression (SVR) and ARIMA. . 2018 International Conference on Inventive Research in Computing Applications (ICIRCA), 1253–1256.

[44] Le, T., & Chang, Y. (2012). Oil price shocks and gold returns. International Economics and Finance Journal.Le dan Chang (2012).

[45] LevinJEric, & E. WrightRobert. (2006). Short-run and Long-run Determinan of the Price of Gold. World Gold Council, 59.

[46] Livieris, I., Pintelas, E., & Pintelas, P. (2020). A CNN–LSTM model for gold price time-series forecasting. Neural Computing and Applications, 32(23), 17351–17360.

[47] Lestari, A., & Hidayat, R. (2023). The Effect of Exchange Rate, Production Volume, and Reference Coal Price on Indonesia's Coal Export Volume for the 2012-2022 Period. Journal of Business Economics and Management, 1(2), 88-97.

[48] LütkepohlH. (2005). New Introduction to Multiple Time Series Analysis. Springer-Verlag. Sims A.C. (1980). Macroeconomics and Reality. Econometrica. Bapak VAR Dunia, 1 - 48.

[49] Maghyereh, A., & Abdoh, H. (2022). Can news-based economic sentiment predict bubbles in precious metal markets? Financial Innovation, 8(1), 35.

[50] Moonis Shakeel, Mustafa Rabbani Raza , Iqbal HawaldarThonse , VaibhavChhabra, & FarrukhZaidiKhurshid. (2023). Is there an intraday volatility spillover between exchange rate, gold and crude oil? Elsevier, Journal of Open Innovation: Technology, Market, and Complexity, 1 - 10.

[51] Muthu, G., S, S., Devi, M., & S, S. (2021). Gold Price Prediction Using Multiple Linear. Regression. Turkish Journal of Computer and Mathematics Education, 12(11), 3737-3741.

[52] Pesaran H., & Shin, Y.M. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 17-29.

[53] Putra, A., & Robiyanto, R. (2019). The effect of commodity price changes and USD/IDR exchange rate on Indonesian mining companies' stock return. Journal of Finance and Banking, 23(1), 97-108.

[54] Pratama, L. P., Yaningwati, F., & Nuzula, N. (2016). The Effect of Benchmark Coal Prices, Rupiah Exchange Rates, and Coal Production on Indonesia's Coal Export Volume (Study on the Coal Mining Sector for the Period 2005-2014), Journal of Business Administration (JAB), 35 (2), 160 - 169.

[55] Pukthuanthong& Roll, R.K.,. (2011). Gold and the Dollar (and Liberty). Journal of Banking & Finance, Elsevier, 2070-2083.

[56] Raza, N., Shahzad, S., Tiwari, A., & Shah. (2016). Asymmetric impact of gold, oil prices and their volatilities on stock prices of emerging markets. Resources Policy, 49, 290–301.

[57] Reboredo, J. C. (2013). Is gold a hedge or safe haven against oil price movements? Resources Policy, 38(2), 130–137.

[58] Sjaastad. (2008). The price of gold and the exchange rates: Once again. Elsevier, 296.

[59] Sari, R., Hammoudeh, S., & Soytas, U. (2010). Dynamics of oil prices, precious metal prices, and exchange rates. Energy Economics, 32(2), 351-362.

[60] Shafiee, S., & Topal, E. (2010). An overview of global gold market and gold price forecasting. Resources Policy, 35(3), 178-189.

[61] Septiawan, D., Topowijono, & Sulasmi, A. (2016). The Influence of World Oil Prices, Inflation, and Exchange Rates on Indonesia's Economic Growth (Study in 2007 - 2014). Journal of Business Administration, 40(2), 130-138.

[62] Sari, R., & Nugroho, B. (2024). The impact of oil price fluctuations on mining sector stock returns: Evidence from Indonesia. International Journal of Energy Economics and Policy, 14(2), 112-120.

[63] Sari, N., & Abundanti, N. (2016). The effect of deposits, ROA, inflation and SBI interest rates on credit disbursement at commercial banks. E-Journal of Management of Udayana University, 5(11), 7158–7186.

[64] Setyowibowo, S., As'ad, M., Sujito, S., & Farida. (2022). Forecasting of Daily Gold Price using ARIMA-GARCH Hybrid Model. Journal of Development Economics, 20(1), 1-9.

[65] Shelly Singhal, Sangita Choudhary, & PratapBiswalChandra. (2019). Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico. Elsevier, 255-261.

[66] Suhartono, & Suman, A. (2019). Analysis of the Transmission of International Gold Prices to Domestic Gold Prices. Journal of Development Economics, 17(1), 1-13.

[67] Sugiyono. (2019). Quantitative, Qualitative, and R&D Research Methods. Alphabet. Bandung.

[68] Trivedi, S., Singh, T., & Bisht, K. (2022). Gold Price Forecasting using ARIMA with Step-wise Selection. SSRN Electronic Journal.

[69] Tully, E., & Lucey, B. (2007). A power GARCH examination of the gold market. Research in International Business and Finance, 21(2), 316-325.

[70] Wang, J., Chen, Z., & Li, Z. (2024). Forecasting gold price using a novel hybrid model with variational mode decomposition and deep learning. Resources Policy, 88, 104468.

[71] Wang, Y., & Lin, T. (2023). A Novel Deterministic Probabilistic Forecasting Framework for Gold Price with a New Pandemic Index Based on Quantile Regression Deep Learning and Multi-Objective Optimization. Mathematics, 12(1), 29.

[72] Wang, K., & Chueh, Y. (2013). Dynamic transmission effects between the interest rate, the US dollar, and gold prices. Economic Modelling, 30, 292-298.

[73] Widijatmoko, A., & Anggraeni, M. (2023). The Effect of Gold Prices, World Oil Prices, and Palm Oil Prices on Stock Prices for the 2019 – 2022 Period. Journal of Economics, Management and Accounting Research, 2(1), 16–26.

[74] Worthington, A., & Pahlavani, M. (2007). Worthington, A. C., & Pahlavani, M. Gold investment as an inflationary hedge: Cointegration evidence with allowance for endogenous structural breaks. Applied Financial Economics Letters, 3(4), 259–262.

[75] Yang, M., Wang, R., & Zeng, Z. (2024). Improved prediction of global gold prices: An innovative Hurst-reconfiguration-based machine learning approach. Resources Policy, 88, 104430.

[76] You, W., Guo, Y., & Peng, C. (2023). Twitter sentiment, economic policy uncertainty, and gold price forecasting. International Review of Economics & Finance, 83, 678–693.

[77] Zhang, L., Wang, L., Ji, Y., & Pan, Z. (2025). Forecasting gold volatility in an uncertain environment: The roles of large and small shock sizes. Journal of Forecasting, 44(4), 1478–1500.

[78] Zhou, Y., Han, L., & Yin, L. (2018). Is the relationship between gold and the U.S. dollar always negative? The role of macroeconomic uncertainty. Applied Economics, 50(4), 354–370.

[79] Zhang, Y., & Wei, Y. (2010). The crude oil market and the gold market: Evidence for cointegration, causality and price discovery. Resources Policy, 35(3), 168-177

30-04-2026