Neural Finance: Deep Learning Architectures for Predicting Markets and Managing Risk - Softcover

Inhaltsangabe

Reactive Publishing

Unlock the Future of Finance with Deep Learning

In an age where markets move faster than human intuition can follow, Neural Finance delivers a breakthrough roadmap for leveraging deep learning to outpace traditional investment strategies. This comprehensive guide bridges the gap between cutting-edge AI architectures and real-world financial application, offering readers a powerful toolkit to forecast trends, manage risk, and engineer intelligent trading systems.

From convolutional neural networks for time-series analysis to transformer models in portfolio optimization, Johann Strauss demystifies the science behind the models and equips financial professionals, quants, and developers with practical implementation strategies.

Inside this book:

• How to use LSTMs and GRUs for sequential market prediction

• Applying autoencoders for anomaly detection and risk control

• Building reinforcement learning agents for algorithmic trading

• Integrating transformers to interpret macroeconomic signals

• Using real market datasets to train and validate neural models

Whether you’re a financial analyst looking to future-proof your skills, or a data scientist venturing into capital markets, Neural Finance is your definitive guide to mastering AI in the financial arena.

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