{"repo":"jialuechen/torchquant","free":true,"listed":false,"github":"https://github.com/jialuechen/torchquant","clone":"git clone https://github.com/jialuechen/torchquant.git","description":"PyTorch for Quantitative Finance : Refine Derivatives Hedging and Pricing with Architecture Alightment in Operators","language":"Python","stars":194,"topics":["quantitative-finance","risk-management","pytorch","numerical-methods","quantlib","automatic-differentiation","derivatives-pricing","deep-learning"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"TorchQuant is a high-performance, differentiable quantitative finance library built on top of PyTorch's automatic differentiation and GPU acceleration. It provides comprehensive tools for derivatives pricing, risk management, and stochastic model calibration. The core innovation in this pytorch extension library is to delicately convert various exotic characteristics into corresponding deep learing mechanisms (see the below table). More kinds of derivatives will be supported as the library grows. Financial Instruments and Deep Mechanisms Analogy (Partial Examples) This table outlines the analogy between financial instruments and neural network components, reflecting how structural and functional characteristics of financial derivatives can inspire the design of all the pricing components in TorchQuant. Financial Instrument / Attribute Core Feature / Description Analogous Neural Network Mechanism Analogy Explanation ---------------------------------------- -------------------------------------------------------- ----------------------------------------------------- -------------------------------------------------------------------------------------- European Option Call: max(S − K, 0); Put: max(K − S, 0) ReLU Activation occurs when input exceeds or falls below a threshold Softplus Option Proxy Smooth version of option payoff Softplus Activation Function Provides smooth derivatives, suitable for differentiable training American Option Early exercise right; optimal stopping str","default_branch":null,"files":null,"tree":[],"storefront":"/r/jialuechen","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/jialuechen/torchquant/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}