4 citations · 4 across the 3 of their papers we have counts for
7 papers
Pricing and hedging of decentralised lending contracts
Lukasz Szpruch, Marc Sabaté Vidales, Tanut Treetanthiploet +1
We study the loan contracts offered by decentralised loan protocols (DLPs) through the lens of financial derivatives. DLPs, which effectively are clearinghouses, facilitate transac…
-Policy Gradient for Online Pricing
Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang
Combining model-based and model-free reinforcement learning approaches, this paper proposes and analyzes an -policy gradient algorithm for the online pricing learning task. The…
Sig-Wasserstein GANs for Time Series Generation
Hao Ni, Lukasz Szpruch, Marc Sabate-Vidales +3
Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we develop high-fidelity t…
Solving path dependent PDEs with LSTM networks and path signatures
Marc Sabate-Vidales, David Šiška, Lukasz Szpruch
Using a combination of recurrent neural networks and signature methods from the rough paths theory we design efficient algorithms for solving parametric families of path dependent…
Robust pricing and hedging via neural SDEs
Patryk Gierjatowicz, Marc Sabate-Vidales, David Šiška +2
Mathematical modelling is ubiquitous in the financial industry and drives key decision processes. Any given model provides only a crude approximation to reality and the risk of usi…
Sig-SDEs model for quantitative finance
Imanol Perez Arribas, Cristopher Salvi, Lukasz Szpruch
Mathematical models, calibrated to data, have become ubiquitous to make key decision processes in modern quantitative finance. In this work, we propose a novel framework for data-d…