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Deep Learning in Quantitative Finance
Autor:
Wydawca: John Wiley & Sons
Data wydania: 19.03.2026
Seria: Wiley Finance
Typ okładki:twarda okładka
EAN: 9781119685241
Opis
Opis
The complete and practical guide to one of the hottest topics in quantitative finance
Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning and describes a wide range of applications in mainstream quantitative finance. Inside, you’ll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You’ll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly.
This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You’ll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts.
Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques
Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning
Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website
Introduces the most important software frameworks for applying deep learning within finance
This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.
Producent/osoba odpowiedzialna za bezpieczeństwo produktu
LOGOS EUROPE
contact@logoseurope.eu
Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning and describes a wide range of applications in mainstream quantitative finance. Inside, you’ll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You’ll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly.
This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You’ll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts.
Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques
Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning
Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website
Introduces the most important software frameworks for applying deep learning within finance
This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.
Producent/osoba odpowiedzialna za bezpieczeństwo produktu
LOGOS EUROPE
contact@logoseurope.eu
Szczegóły
Szczegóły
Data wydania: 19.03.2026
Liczba stron: 736
Wymiary: 17.0x24.4
Typ okładki:twarda okładka
Wydawca: John Wiley & Sons
Autor:
Seria: Wiley Finance
Tytuł:Deep Learning in Quantitative Finance
EAN: 9781119685241
Recenzje
Recenzje
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Zamieszczenie recenzji nie wymaga logowania. Sklep nie prowadzi weryfikacji, czy autorzy recenzji nabyli lub użytkowali dany produkt.
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