OVERVIEW OF MACHINE LEARNING ALGORITHMS AND THEIR APPLICATION FOR PREDICTION OF CRYPTOCURRENCY PURCHASE PRICES

Abstract

This work provides a comprehensive overview of modern machine learning algorithms and their application in forecasting cryptocurrency purchase prices. The cryptocurrency market is particularly intriguing for investors due to its high volatility, which presents both opportunities for profitable operations and challenges that demand precise predictions to identify advantageous moments for buying and selling. Analyzing price trends and forecasting future changes in the midst of such high market instability poses a real challenge for traders and investors. Machine learning algorithms serve as powerful tools for professionals seeking accurate and well-founded predictions. Regarding examples of machine learning algorithm applications, various fields are explored. Among the diverse algorithms, Autoregressive Integrated Moving Average (ARIMA) stands out as particularly effective for analyzing time series of cryptocurrency prices. ARIMA is a statistical model that combines autoregression, integration, and moving average components. This approach proves valuable for forecasting price trends by considering previous price values and their changes over time. Additionally, regression models such as linear regression or neural networks allow for predicting specific price values over a certain time period. Regression models used to forecast specific values, like linear regression or neural networks, can provide more detailed price forecasts over a specific time period. Neural networks, in particular, can automatically detect complex patterns in data and adapt to changes in market conditions. It’s noteworthy that the utilization of ARIMA and other machine learning algorithms in cryptocurrency market analysis represents a significant step toward understanding and predicting price dynamics. This, in turn, facilitates effective portfolio management and the formulation of well-informed decisions amid financial instability. In conclusion, the integration of ARIMA and various machine learning algorithms into the analysis of the cryptocurrency market is a crucial advancement in comprehending and forecasting price dynamics. This advancement contributes to efficient portfolio management and the ability to make informed decisions in the face of financial instability.