Deep Learning Models for Forecasting Financial Markets: and Blockchain Validation of Transactions

This book offers a comprehensive exploration of how artificial intelligence and distributed ledger technology are reshaping modern finance. The book delves into advanced neural network architectures-such as LSTM, CNN, and Transformer models-for predicting market trends, price movements, and trading signals with high precision. It also investigates how blockchain enhances transactional transparency, immutability, and security in financial ecosystems. By merging predictive analytics with decentralized validation, the text presents a novel framework for building trust-driven, data-intelligent financial infrastructures. Practical case studies, algorithmic models, and implementation guidelines make this resource valuable for data scientists, economists, fintech developers, and policy analysts seeking to understand the synergy between AI-driven forecasting and blockchain-based integrity systems.