Enhancing Financial Predictions Based on Bitcoin Prices Using Big Data and Deep Learning Approach

The increasing adoption of Bitcoin as a digital asset has led to significant interest in accurately predicting its price movements. However, the highly volatile and speculative nature of Bitcoin presents substantial challenges for traditional financial models, which often struggle to capture the complex and nonlinear patterns that influence its price fluctuations. This study proposes a novel approach to enhancing financial predictions related to Bitcoin prices by leveraging the power of big data analytics and deep learning techniques. The integration of large-scale historical market data, social sentiment analysis, blockchain transaction metrics, and macroeconomic indicators allows for a more comprehensive understanding of Bitcoin’s market behavior.To achieve this, deep learning architectures such as Long Short-Term Memory (LSTM) networks and Transformer-based models are employed due to their superior ability to capture long-range dependencies and dynamic trends in time-series data. These models are trained on high-frequency trading data, order book information, real-time market indicators, and sentiment data derived from news sources and social media platforms. By utilizing a data-driven approach, the proposed model aims to improve the robustness and accuracy of Bitcoin price predictions.Extensive experiments and comparative analyses are conducted to evaluate the effectiveness of the deep learning-based framework against traditional statistical models and classical machine learning techniques. The results demonstrate that the proposed approach significantly outperforms conventional methods in terms of predictive accuracy, stability, and generalization capabilities. The findings highlight the potential of deep learning and big data analytics in enhancing cryptocurrency market predictions and risk assessment strategies.The insights derived from this study provide valuable implications for traders, investors, and policymakers seeking to develop more informed trading strategies and risk management frameworks. By harnessing the power of deep learning and big data, this research contributes to the growing field of financial technology and underscores the importance of advanced predictive models in navigating the rapidly evolving cryptocurrency market.