REAL-TIME CRYPTOCURRENCY ANALYSIS SYSTEM FOR INVESTOR DECISION SUPPORT
Abstract
The exponential growth of the cryptocurrency market over recent decades has posed significant challenges for beginner investors, who frequently struggle with complex and often inaccessible analysis tools. This paper presents the development and implementation of a real-time cryptocurrency analysis system, named SS Innova Crypto Analyzer, aimed at supporting the interpretation of technical information in the cryptocurrency market and contributing to its greater accessibility for retail investors. The system integrates four technical indicators — Relative Strength Index (RSI), Exponential Moving Average (EMA), Moving Average Convergence/Divergence (MACD), and Fibonacci retracement levels within a multi-temporal consensus architecture that simultaneously evaluates five time horizons. In a preliminary backtesting evaluation with four cryptocurrency pairs throughout 2024, the multi-temporal approach increased the average accuracy of directional signals from 58.4% to 64.2%, while reducing the false-positive rate by 11.8 percentage points. The approach generates normalized confidence scores and natural-language recommendations, with the purpose of facilitating the interpretation of technical information by retail investors without specialized backgrounds.
Author Biographies
Bachelor’s degree in Physics from the Institute of Physics at the Federal University of Rio de Janeiro (UFRJ). Master’s degree holder and PhD candidate in Nanotechnology Engineering at COPPE/UFRJ. Works at the intersection of artificial intelligence, nanotechnology, and technologies applied to research, with an interest in developing innovative solutions based on computational modeling, data analysis, and automation. His trajectory includes experience in multidisciplinary contexts, ranging from scientific research to the practical application of technological methods for process optimization and decision-making support.
Bachelor’s degree in Mathematical and Earth Sciences from CCMN/UFRJ and Master’s student in Nanotechnology Engineering at COPPE/UFRJ. Develops activities in the areas of Geographic Information Systems (GIS) and nanotechnology, focusing on the integration of spatial analysis, technology, and applied research. Her work involves the use of geoprocessing tools, data organization and interpretation, as well as an interest in innovative solutions in multidisciplinary contexts.
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