Machine Learning and AI in Finance - Softcover

Softcover

ISBN 10: 0367703335 ISBN 13: 9780367703332

Verlag: Routledge, 2023

Inhaltsangabe

The significant amount of information available in any field requires a systematic and analytical approach to select the most critical information and anticipate major events. During the last decade, the world has witnessed a rapid expansion of applications of artificial intelligence (AI) and machine learning (ML) algorithms to an increasingly broad range of financial markets and problems. Machine learning and AI algorithms facilitate this process understanding, modelling and forecasting the behaviour of the most relevant financial variables.

The main contribution of this book is the presentation of new theoretical and applied AI perspectives to find solutions to unsolved finance questions. This volume proposes an optimal model for the volatility smile, for modelling high-frequency liquidity demand and supply and for the simulation of market microstructure features. Other new AI developments explored in this book includes building a universal model for a large number of stocks, developing predictive models based on the average price of the crowd, forecasting the stock price using the attention mechanism in a neural network, clustering multivariate time series into different market states, proposing a multivariate distance nonlinear causality test and filtering out false investment strategies with an unsupervised learning algorithm.

Machine Learning and AI in Finance explores the most recent advances in the application of innovative machine learning and artificial intelligence models to predict financial time series, to simulate the structure of the financial markets, to explore nonlinear causality models, to test investment strategies and to price financial options.

The chapters in this book were originally published as a special issue of the Quantitative Finance journal.

Über diesen Titel

Über die Autorin bzw. den Autor

Germán G. Creamer is Associate Professor at Stevens Institute of Technology. He is also a visiting scholar at Stern School of Business, NYU; Adjunct Associate Professor, Columbia University and former Senior Manager, American Express.

Gary Kazantsev

is the Head of Quant Technology Strategy, Office of the CTO at Bloomberg L. P., New York, USA.

Tomaso Aste

is Professor of Complexity Science, Department of Computer Science, University College London, UK.

Details zur Ausgabe

• Verlag: Routledge
• Erscheinungsdatum: 2023
• Sprache: Englisch
• ISBN 10: 0367703335
• ISBN 13: 9780367703332
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 130
• Herausgeber: Creamer German, Kazantsev Gary, Aste Tomaso
• Kontakt zum Hersteller: BOOKS etc..; cs@booksetc.co.uk; ; BOOKS etc.; Aldershot; Vereinigtes Königreich
• Verantwortliche Person: as - Schwabe GmbH; https://www.as-schwabe.de/; ; Merkurstra�e 10; Eutingen im G�u; 72184; Deutschland