5 papers
Universal Time Series Generation with Neural Controlled Differential Equations
Torben Berndt, Elyes Farjallah, Leif Seute +3
Recent work on the sequence universality of State Space Models (SSMs) has introduced efficient, maximally expressive continuous-time approaches for time-series modelling. While the…
Fast-Vollib: A Fast Implied Volatility Library for Python with PyTorch, JAX, and CUDA Fused-Kernel Backends
Raeid Saqur
We present fast-vollib, an open-source Python library that provides high-performance European option pricing, implied volatility (IV) computation, and Greeks under the Black-76, Bl…
PIVOT: Bridging Black-Scholes Implied-Volatility and Price Objectives via Differentiable Jäckel Operator
Raeid Saqur, Yannick Limmer, Anastasis Kratsios +2
Modern option-learning systems operate in two coordinates: price space, where markets quote and no-arbitrage constraints are most naturally enforced, and implied volatility (IV) sp…
SANOS Smooth strictly Arbitrage-free Non-parametric Option Surfaces
Hans Buehler, Blanka Horvath, Anastasis Kratsios +2
We present a simple, numerically efficient but highly flexible non-parametric method to construct representations of option price surfaces which are both smooth and strictly arbitr…
Seeking SOTA: Time-Series Forecasting Must Adopt Taxonomy-Specific Evaluation to Dispel Illusory Gains
Raeid Saqur, Christoph Bergmeir, Blanka Horvath +3
We argue that the current practice of evaluating AI/ML time-series forecasting models, predominantly on benchmarks characterized by strong, persistent periodicities and seasonaliti…