We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest cryptocurrencies. Our results show that all employed models make statistically viable...

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and...

"This book focuses on how to generate and extend the practical implications of intelligent systems which the readers can adopt especially in business functions. The book is a blend of balance theory and experimentation, providing a thorough explication of the science of AI along with its...