Erhältlich:
Nicht auf Lager
Buch (Softcover): Fachbuch
PyTorch for Quantitative Finance
Applying Deep Learning and Neural SDEs to Algorithmic Trading
Verlag:
Independently Published Unsere-Artikel-Nr.: P35480926
EAN: 9798188445232
Erhältlich:
Nicht auf Lager
Zustellung: Mo, 09.11.2026
Versand: Kostenlos
CHF 56.50
Beschreibung
Reactive Publishing. Bridge the gap between modern deep learning and quantitative finance using PyTorch. PyTorch for Quantitative Finance. provides a rigorous, hands-on guide to building, training, and deploying neural architectures across financial markets. Designed for quantitative analysts, developers, and data scientists, this book moves beyond toy datasets to address the real-world complexities of market microstructure, non-stationary time series, and continuous-time stochastic modeling. Rather than relying on black-box heuristics, you will learn how to integrate deep learning directly with mathematical finance. Discover how to leverage PyTorch to solve high-dimensional partial differential equations (PDEs), construct generative models for market simulation, and design robust algorithmic trading strategies. What You Will Learn: Neural Stochastic Differential Equations (Neural SDEs):. Model continuous-time asset dynamics and latent market trajectories using differentiable SDE solvers in PyTorch. Deep Factor Models & Risk Management:. Construct non-linear factor models to capture complex multi-asset dependencies and tail-risk exposures. Market Simulation with Generative Models:. Use GANs and Variational Autoencoders (VAEs) to generate realistic synthetic financial time series for backtesting. Algorithmic Trading & Execution:. Implement deep reinforcement learning algorithms for optimal execution, portfolio rebalancing, and dynamic hedging. Production-Grade PyTorch Pipelines:. Optimize model performance with custom C extensions, GPU acceleration, and efficient data loaders tailored for high-frequency time series. Whether you are implementing continuous-time models or deploying end-to-end algorithmic execution engines, this book delivers the code, theory, and architecture required to build state-of-the-art quantitative systems.
Spezifikationen
Sprache
- Englisch
Autor
- Alice Schwartz
- Julian K. Mercer
Erscheinungsjahr
- 2026
Format
- Buch (Softcover)
Anzahl Seiten
- 734