Search Results - "Wiese, Magnus"

Quant GANs: deep generation of financial time series by Wiese, Magnus, Knobloch, Robert, Korn, Ralf, Kretschmer, Peter

“…Modeling financial time series by stochastic processes is a challenging task and a central area of research in financial mathematics. As an alternative, we…”
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Sig‐Wasserstein GANs for conditional time series generation by Liao, Shujian, Ni, Hao, Sabate‐Vidales, Marc, Szpruch, Lukasz, Wiese, Magnus, Xiao, Baoren

“…Abstract Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high‐dimensional probability measures…”
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Risk-Neutral Market Simulation by Wiese, Magnus, Murray, Phillip

“…AAAI 2022 Workshop on AI in Financial Services: Adaptiveness, Resilience & Governance We develop a risk-neutral spot and equity option market simulator for a…”
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Signature Trading: A Path-Dependent Extension of the Mean-Variance Framework with Exogenous Signals by Futter, Owen, Horvath, Blanka, Wiese, Magnus

“…In this article we introduce a portfolio optimisation framework, in which the use of rough path signatures (Lyons, 1998) provides a novel method of…”
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Sig-Splines: universal approximation and convex calibration of time series generative models by Wiese, Magnus, Murray, Phillip, Korn, Ralf

“…We propose a novel generative model for multivariate discrete-time time series data. Drawing inspiration from the construction of neural spline flows, our…”
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Copula & Marginal Flows: Disentangling the Marginal from its Joint by Wiese, Magnus, Knobloch, Robert, Korn, Ralf

“…Deep generative networks such as GANs and normalizing flows flourish in the context of high-dimensional tasks such as image generation. However, so far exact…”
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Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions by Murray, Phillip, Wood, Ben, Buehler, Hans, Wiese, Magnus, Pakkanen, Mikko S

“…We present a method for finding optimal hedging policies for arbitrary initial portfolios and market states. We develop a novel actor-critic algorithm for…”
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Multi-Asset Spot and Option Market Simulation by Wiese, Magnus, Wood, Ben, Pachoud, Alexandre, Korn, Ralf, Buehler, Hans, Murray, Phillip, Bai, Lianjun

“…We construct realistic spot and equity option market simulators for a single underlying on the basis of normalizing flows. We address the high-dimensionality…”
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Sig-Wasserstein GANs for Time Series Generation by Ni, Hao, Szpruch, Lukasz, Sabate-Vidales, Marc, Xiao, Baoren, Wiese, Magnus, Liao, Shujian

“…Synthetic data is an emerging technology that can significantly accelerate the development and deployment of AI machine learning pipelines. In this work, we…”
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Quant GANs: Deep Generation of Financial Time Series by Wiese, Magnus, Knobloch, Robert, Korn, Ralf, Kretschmer, Peter

“…Quantitative Finance, 2020 Modeling financial time series by stochastic processes is a challenging task and a central area of research in financial…”
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Deep Hedging: Learning to Simulate Equity Option Markets by Wiese, Magnus, Bai, Lianjun, Wood, Ben, Buehler, Hans

“…NeurIPS 2019 Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy We construct realistic equity option…”
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Conditional Sig-Wasserstein GANs for Time Series Generation by Liao, Shujian, Ni, Hao, Szpruch, Lukasz, Wiese, Magnus, Sabate-Vidales, Marc, Xiao, Baoren

“…Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high dimensional probability measures. However,…”
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