Все науки. №2, 2024. Международный научный журнал - страница 18

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UDK: 510.9

Abstract. This article explores the development of advanced price action prediction algorithms using Python. The study focuses on employing machine learning techniques to forecast future price movements in financial markets. Through extensive backtesting and evaluation, the effectiveness of these algorithms is assessed. The implementation is carried out in Python, utilizing popular libraries such as Pandas, NumPy, and Scikit-learn. The research aims to contribute to the field of algorithmic trading by providing insights into the design and performance of predictive models for price action.

Keywords: Algorithmic trading, Price action prediction, Machine learning, Python, Financial markets.

In the rapidly evolving landscape of financial markets, algorithmic trading has gained prominence. This section discusses the significance of price action prediction algorithms and their role in facilitating informed trading decisions. It also outlines the objectives of the study, emphasizing the need for accurate and reliable forecasting models. The introduction provides a contextual background on algorithmic trading and the challenges associated with predicting price movements.