FEATURES OF FORECASTING STOCK PRICE CHANGES OF OIL PRODUCTION COMPANIES USING COMBINATIONS OF TREND AND NON-TREND INDICATORS

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Today, a company's share price is influenced by a wide array of factors, ranging from fundamental internal dynamics to political decisions, industry-specific developments, macroeconomic conditions, and global trends. Investors face challenges in selecting an appropriate approach to identifying the target industry and asset, interpreting analysis results, and determining the optimal market entry point. In this context, several pertinent issues emerge regarding forecasting share price changes for oil production companies (BP p.l.c, Chevron p.l.c, Exxon Mobil Corp., Shell p.l.c) on the stock exchange, particularly concerning the use of technical analysis tools like moving averages and oscillators. This study examines the impact of different moving average settings and their combinations on the accuracy of predicting share price movements. Based on these findings, tasks addressed by such indicators are identified, and a systematic approach to selecting technical analysis tools and their configurations is proposed. The paper explores various methods for forming and interpreting signals generated by individual indicators and their combinations, focusing on their implications for forecasting asset price changes. Several criteria are proposed for evaluating the effectiveness of these approaches during the testing phase. The study compares and analyzes the results of multiple forecasting system configurations, identifying the optimal ones according to the selected criteria. Calculations are based on weekly stock data spanning 2000 to 2024, from which the most effective combination of indicators for the forecasting system is determined. Potential areas for optimization and additional tools to enhance the system are also outlined. Finally, the study concludes that the proposed approach to constructing a forecasting system is viable for executing real stock transactions with the selected companies' shares.