Is Market Trends and Sentiment Affected Stock Price? Evidence from Energy Sector in Indonesia

  • Ayunda Rizqi Oktaviana Universitas Airlangga, Surabaya, Indonesia
  • Anak Agung Gde Satia Utama Universitas Airlangga, Surabaya, Indonesia
Keywords: Market Trend and Sentiment Affected Stock Price, Energy Sector in Indonesia

Abstract

This study investigates the relationship between market trends, market sentiment, and stock prices within the energy sector listed on the Indonesia Stock Exchange (IDX). Grounded in behavioral finance theory which emphasizes the influence of psychological and behavioral factors on financial decision-making this research evaluates how fluctuations in public interest and investor sentiment affect stock price dynamics. The study utilizes secondary data extracted from company annual reports, stock price records, and publicly available financial statements covering the period from 2014 to 2023. The sample includes 22 energy sector companies, selected through purposive sampling based on predefined criteria. To measure market trends, the study employs Google Trends scores, while social media sentiment analysis—using Brandwatch—captures investor sentiment. The regression analysis investigates the influence of both variables on stock prices, incorporating control variables such as company size, debt-to-equity ratio, and dividend payout ratio. The empirical findings reveal that both market trends and investor sentiment exert a significant and positive influence on stock prices in the Indonesian energy sector. The implications of these findings extend to several domains. Investors can integrate trend and sentiment indicators into their analytical frameworks to improve decision-making and anticipate stock movements more effectively. Financial analysts and advisors can adopt these behavioral metrics as complementary tools alongside traditional valuation methods.

Downloads

Download data is not yet available.

References

Ahmed, B. (2020). Understanding the impact of investor sentiment on the price formation process: A review of the conduct of American stock markets. The Journal of Economic Asymmetries, 22, e00172. https://doi.org/10.1016/j.jeca.2020.e00172

Auerbach, A. J., & King, M. A. (n.d.). Taxation, Portfolio Choice, and Debt-Equity Ratios: A General Equilibrium Model.

Bashir, U. (2024). Investor sentiment and stock price crash risk: The mediating role of analyst herding.

Chen, Y., Lin, W., & Wang, J. Z. (2019). A Dual-Attention-Based Stock Price Trend Prediction Model With Dual Features. IEEE Access, 7, 148047–148058. https://doi.org/10.1109/ACCESS.2019.2946223

Chiang, S. L., & Tsai, M. S. (2023). Analyses for the effects of investor sentiment on the price adjustment behaviors for stock market and REIT market. International Review of Economics & Finance, 86, 425–439. https://doi.org/10.1016/j.iref.2023.03.007

Chung, M.-H., & Chang, Y.-K. (2024). Financial Reporting Complexity, Investor Sentiment, and Stock Prices. Finance Research Letters, 62, 105026. https://doi.org/10.1016/j.frl.2024.105026

Fu, J. (2021). Firm-specific investor sentiment and stock price crash risk. Finance Research Letters.

Hart, P. E., & Oulton, N. (1996). Growth and Size of Firms. The Economic Journal, 106(438), 1242. https://doi.org/10.2307/2235518

Herwartz, H., Rengel, M., & Xu, F. (2016). Local Trends in Price‐to‐Dividend Ratios—Assessment, Predictive Value, and Determinants. Journal of Money, Credit and Banking, 48(8), 1655–1690. https://doi.org/10.1111/jmcb.12370

Horobet, A., Vrinceanu, G., Popescu, C., & Belascu, L. (2019). Oil Price and Stock Prices of EU Financial Companies: Evidence from Panel Data Modeling. Energies, 12(21), 4072. https://doi.org/10.3390/en12214072

Jing, N., Wu, Z., & Wang, H. (2021). A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction. Expert Systems with Applications, 178, 115019. https://doi.org/10.1016/j.eswa.2021.115019

Leonardo, M.-P., Carlos Eduardo, C.-M., Ana María, T.-H., José Luis, T.-G., & Campo Elias, L.-R. (2022). Formalization of a new stock trend prediction methodology based on the sector price book value for the Colombian market. Heliyon, 8(4), e09210. https://doi.org/10.1016/j.heliyon.2022.e09210

Li, Y. (2020). Investor Sentiment and Stock Price Premium Validation with Siamese Twins from China.

Li, Y., Bu, H., Li, J., & Wu, J. (2020). The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning. International Journal of Forecasting, 36(4), 1541–1562. https://doi.org/10.1016/j.ijforecast.2020.05.001

Monirul Islam, Md., Sohag, K., Mamman, S. O., & Herdhayinta, H. (2023). Response of Indonesian mineral supply to global renewable energy generation: Analysis based on gravity model approach. Geoscience Frontiers, 101658. https://doi.org/10.1016/j.gsf.2023.101658

Olivia, S., & Gibson, J. (2008). Household Energy Demand and the Equity and Efficiency Aspects of Subsidy Reform in Indonesia. The Energy Journal, 29(1), 21–40. https://doi.org/10.5547/ISSN0195-6574-EJ-Vol29-No1-2

Omar, H. M., Yahya, A., & Mohammed, S. M. (2025). Data Analysis Approaches for Apple Stock Price Prediction and Financial Risk Management. Danadyaksa: Post Modern Economy Journal, 3(1), 32–43. https://doi.org/10.69965/danadyaksa.v3i1.193

Phuong, L. C. M. (2021). Investor sentiment by relative strength index and stock return: Empirical evidence on Vietnam’s stock market. Accounting, 451–456. https://doi.org/10.5267/j.ac.2020.11.006

Qian, B., & Tan, Y. (2024). Firm-specific investor sentiment and stock price informativeness. Finance Research Letters, 66, 105680. https://doi.org/10.1016/j.frl.2024.105680

Raihan, A., Pavel, M. I., Muhtasim, D. A., Farhana, S., Faruk, O., & Paul, A. (2023). The role of renewable energy use, technological innovation, and forest cover toward green development: Evidence from Indonesia. Innovation and Green Development, 2(1), 100035. https://doi.org/10.1016/j.igd.2023.100035

Wah, B., & Qian, M. (n.d.). Constrained Formulations and Algorithms for Stock-Price Predictions Using Recurrent FIR Neural Networks.

Wen, M., Li, P., Zhang, L., & Chen, Y. (2019). Stock Market Trend Prediction Using High-Order Information of Time Series. IEEE Access, 7, 28299–28308. https://doi.org/10.1109/ACCESS.2019.2901842

Widya Yudha, S., & Tjahjono, B. (2019). Stakeholder Mapping and Analysis of the Renewable Energy Industry in Indonesia. Energies, 12(4), 602. https://doi.org/10.3390/en12040602

Xie, W., Zhang, H., Guo, J., & He, M. (2022). Does a national industrial policy promote financial market stability? A study based on stock price crash risk. China Journal of Accounting Research, 15(4), 100269. https://doi.org/10.1016/j.cjar.2022.100269

Yilmaz, E. S., Ozpolat, A., & Destek, M. A. (2022). Do Twitter sentiments really effective on energy stocks? Evidence from the intercompany dependency. Environmental Science and Pollution Research, 29(52), 78757–78767. https://doi.org/10.1007/s11356-022-21269-9

Zhong, Z., Wu, Q., & Wang, M. (2024). Does the U.S.-China trade war stop? A novel event study on fake news and stock price in China. Finance Research Letters, 66, 105702. https://doi.org/10.1016/j.frl.2024.105702

Zhu, B., & Niu, F. (2016). Investor sentiment, accounting information and stock price: Evidence from China. Pacific-Basin Finance Journal, 38, 125–134. https://doi.org/10.1016/j.pacfin.2016.03.010

Published
2025-09-27
How to Cite
Oktaviana, A., & Satia Utama, A. A. G. (2025). Is Market Trends and Sentiment Affected Stock Price? Evidence from Energy Sector in Indonesia. Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE), 8(3), 11829-11840. https://doi.org/10.31538/iijse.v8i3.7501