Practical Applications of Evolutionary Computation to Financial Engineering: Robust Techniques for Forecasting, Trading and Hedging: 11 - Rilegato

Iba, Hitoshi; Aranha, Claus C.

Rilegato

ISBN 10: 3642276474 ISBN 13: 9783642276477

Casa editrice: Springer-Nature New York Inc, 2012

Riassunto

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within.

The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

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Informazioni sull'autore

Hitoshi Iba is a Professor at the Graduate School of Information Science and Technology at the University of Tokyo. From 1990 to 1998, he was a senior researcher at the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He is a founding associate editor of the Journal of Genetic Programming and Evolvable Machines (GPEM) and was a founding associate editor of IEEE Transactions on Evolutionary Computation. He has published more than 100 papers and is a (co-)author of more than 20 books. He is also an underwater naturalist and experienced PADI divemaster, having completed about 1,300 dives. João Eduardo Batista is a postdoctoral researcher at RIKEN-CCS, a leading research center in Japan for computational science and high-performance computing. He graduated with a PhD in Informatics from the Faculty of Sciences at the University of Lisbon in 2024, having researched the application of genetic programming for interpretable feature engineering in remote sensing. Currently, his research topics are attribution in LLMs and LLM optimization, as well as high-performance C code optimization using interpretable machine learning techniques. Jinglue Xu is a researcher at Sakana AI, a Tokyo-based artificial intelligence company focused on generative AI and evolutionary computation. He received his Ph.D. in Information Science and Technology from the University of Tokyo in 2025. His research interests include large language models (LLMs), autonomous agents, evolutionary computation, and AutoML. He has conducted multiple research projects exploring the combination of evolutionary computation, LLMs, and AutoML. Currently, he works at Sakana AI on developing more efficient evolutionary computation methods and their applications to LLMs.

Dalla quarta di copertina

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within.

The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

Dettagli dell'edizione

• Editore: Springer-Nature New York Inc
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 3642276474
• ISBN 13: 9783642276477
• Rilegatura: Copertina rigida
• Numero di pagine: 248
• Contatto del produttore: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Germania