An Analysis On The Link Between Crude Oil And Technology

Yıl 2025, Cilt: 2 Sayı: 1, 59 - 68, 30.06.2025

Mustafa Berk Bacaksız , Şahin Üregil

Öz

This paper examines the relationship between crude oil and technology stock prices particularly focusing on crudeoil’s predictive capabilities using the Long Short Term Memory(LSTM) models. At first we conduct a descriptive analysis byidentifying two distinct trends regarding the correlation between oil and tech stock prices: A strong negative correlation before2016 and a relatively weaker positive correlation after 2016. Wethen develop an LSTM model to forecast technology stock prices based on historical crude oil price data. The performance of the model is evaluated using the Mean Absolute Error (MAE), MeanAbsolute Percentage Error (MAPE) and R2 score. Although it generally shows good forecasting power, the LSTM model struggles during periods of high trade volume and volatility,which introduces outliers and reduces forecast accuracy. Despitethis, the model shows that oil prices can be used as a valuable indicator in predicting trends of the technology sector and possibly with additional enhancements such as more training data and computational power, the forecasting capabilities of such models can be improved even in volatile market conditions.This study also shows us that there is potential benefits in using alternative economic indicators such as oil prices to inform investment strategies in the technology sector.

Anahtar Kelimeler

Time‑Series Analytics; , Feature Engineering , Dynamic Correlation Modeling , Volatility Spillover Algorithms , Big‑Data Financial Analytics , Regime‑Detection Techniques

Kaynakça

• Kocaarslan, B., & Soytaş, U. (2019). Dynamic correlations between oil prices and the stock prices of clean energy and technology firms: The role of the US dollar. Energy Economics, 84, 104502.
• Wen, D., Wang, G.-J., Ma, C., & Wang, Y. (2019). Risk spillovers between oil and stock markets: A VAR for VaR analysis. Energy Economics, 80, 524‑535.
• Ben‑Salha, O., & Mokni, K. (2022). Detrended cross‑correlation analysis in quantiles between oil price and the US stock market. Energy, 242, 122918.
• Managi, S., Yousfi, M., Ben Zaied, Y., Ben Mabrouk, N., & Ben Lahouel, B. (2022). Oil price, US stock market and the US business conditions in the era of COVID‑19 pandemic outbreak. Economic Analysis and Policy, 73, 129‑139.
• Liu, L., Wang, E.-Z., & Lee, C.-C. (2020). Impact of the COVID‑19 pandemic on the crude oil and stock markets in the US: A time‑varying analysis. Energy Research Letters, 1(1), 13154.
• Magazzino, C., Shahbaz, M., & Adamo, M. (2023). On the relationship between oil market and European stock returns. Environmental Science and Pollution Research, 30, 123452‑123465.
• Umar, Z., Mokni, K., Yousfi, M., & Gubareva, M. (2024). Dynamic spillover between oil price shocks and technology stock indices: A country‑level analysis. Research in International Business and Finance, 69, 102231.
• Rath, B. N., & Behera, C. (2024). The interconnectedness between crude oil prices and stock returns in G20 countries. Resources Policy, 91, 104950.
• Sezen, S., Cevik, E. I., Al‑Eisa, E. A., Bugan, M. F., & Destek, M. A. (2025). Investigating the connectedness between oil and stock markets in GCC countries: Evidence from rolling‑window frequency domain causality. Computational Economics. https://doi.org/10.1007/s10614‑025‑10859‑7
• Raheem, I. D. (2022). Different strokes for different folks: The case of oil shocks and emerging equity markets. Energy Economics, 108, 105897.