This study offers comprehensive coverage of neural network applications in the capital markets, combining the viewpoints of those involved in finance with neural network engineers. The author takes a pragmatic view, treating neural networks as computational equivalents to well-understood, non-parametric inference methods in decision science. He makes comparisons with established techniques where appropriate. The book is based on original papers which represent new and significant research, development and applications in finance and investment.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Based on original papers which represent new and significant research, developments and applications in finance and investment. The author takes a pragmatic view of neural networks, treating them as computationally equivalent to well–understood, non–parametric inference methods in decision science. The author also makes comparisons with established techniques where appropriate.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : Reader's Corner, Inc., Raleigh, NC, Etats-Unis
Hardcover. Etat : As New. Etat de la jaquette : As New. First Edition. This is a fine, as new, hardcover first edition copy in a fine mylar protected DJ, black spine. N° de réf. du vendeur 074369
Quantité disponible : 1 disponible(s)
Vendeur : Better World Books: West, Reno, NV, Etats-Unis
Etat : Very Good. 1st Edition. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 14810093-20
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Vendeur : Cycle Books LA, South el monte, CA, Etats-Unis
Etat : very_good. N° de réf. du vendeur AMTV.0471943649.VG
Quantité disponible : 1 disponible(s)
Vendeur : ThriftBooks-Dallas, Dallas, TX, Etats-Unis
Hardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G0471943649I3N00
Quantité disponible : 1 disponible(s)
Vendeur : medimops, Berlin, Allemagne
Etat : good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present. N° de réf. du vendeur M00471943649-G
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Vendeur : killarneybooks, Inagh, CLARE, Irlande
Hardcover. Etat : Near Fine. Etat de la jaquette : Very Good. 1st Edition. Hardcover, sturdy vinyl boards, xi + 379 pages, NOT ex-library. Book is clean and bright throughout, untanned, with unmarked text, free of inscriptions and stamps, firmly bound. Minor light handling wear only. In a gently used, untorn dust jacket. -- This edited volume provides a foundational technical analysis of the early application of artificial intelligence to financial forecasting and decision-making. Published during a pivotal era for quantitative finance, the work synthesises the research of practitioners and academics seeking to transcend the limitations of linear econometric models. The text addresses the core challenge of the 1990s financial sector: identifying non-linear patterns within the noisy, high-frequency data of global markets. The content is categorised into several critical domains, including stock price prediction, exchange rate modelling, and bond rating. Technical chapters delve into the architecture of multi-layer perceptrons and the mechanics of backpropagation, providing a rigorous framework for training networks to recognise complex market trends. An attention is also given to Arbitrage Pricing Theory (APT) and the use of probabilistic neural networks (PNNs) for asset allocation. A significant portion of the work is dedicated to the practical hurdles of the time, such as data preprocessing, the management of 'overfitting', and the benchmarking of neural network performance against traditional statistical methods like ARIMA and multiple regression. Beyond simple forecasting, the book explores the integration of neural networks into portfolio management and credit risk assessment. It examines hybrid systems that combine neural architectures with genetic algorithms and fuzzy logic to enhance the robustness of trading signals. In a contemporary context, this work remains relevant as a primary record of the origins of modern algorithmic trading and machine learning in finance. It documents the conceptual shift from theory-driven models to data-driven discovery, a transition that underpins today's high-frequency trading environments and AI-led hedge funds. For financial historians and quantitative analysts, this volume offers a deep understanding of the evolution of automated systems and the enduring challenges of modelling market volatility. N° de réf. du vendeur 013221
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Vendeur : The Book Tree, Devizes, WILTS, Royaume-Uni
Hardcover. Etat : Fair. No Jacket. Reading copy with some defects as follows: Black boards with silver titles to spine Bottom of rear board has a fairly large chip and the spine is crushed at the top and bottom. Previous owner's notes on ffep, otherwise internally clean and a good reading copy. No dust jacket. N° de réf. du vendeur 001470887
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