activity
20132023
most citedQuant GANs: Deep Generation of Financial Time Series

267 citations · 286 across the 12 of their papers we have counts for

collaborators

13 papers

cs.LG2023★ 1 cited

Sig-Splines: universal approximation and convex calibration of time series generative models

Magnus Wiese, Phillip Murray, Ralf Korn

We propose a novel generative model for multivariate discrete-time time series data. Drawing inspiration from the construction of neural spline flows, our algorithm incorporates li…

q-fin.CP2021

Multi-Asset Spot and Option Market Simulation

Magnus Wiese, Ben Wood, Alexandre Pachoud +4

We construct realistic spot and equity option market simulators for a single underlying on the basis of normalizing flows. We address the high-dimensionality of market observed cal…

cs.LG2021

Estimating the Value-at-Risk by Temporal VAE

Robert Sicks, Stefanie Grimm, Ralf Korn +1

Estimation of the value-at-risk (VaR) of a large portfolio of assets is an important task for financial institutions. As the joint log-returns of asset prices can often be projecte…

q-fin.MF2020

Unifying the theory of storage and the risk premium by an unobservable intrinsic electricity price

Wieger Hinderks, Ralf Korn, Andreas Wagner

In this paper we introduce a new concept for modelling electricity prices through the introduction of an unobservable intrinsic electricity price . We use it to connect the c…

cs.LG2020

A Generalised Linear Model Framework for -Variational Autoencoders based on Exponential Dispersion Families

Robert Sicks, Ralf Korn, Stefanie Schwaar

Although variational autoencoders (VAE) are successfully used to obtain meaningful low-dimensional representations for high-dimensional data, the characterization of critical point…

cs.LG2020★ 2 cited

A lower bound for the ELBO of the Bernoulli Variational Autoencoder

Robert Sicks, Ralf Korn, Stefanie Schwaar

We consider a variational autoencoder (VAE) for binary data. Our main innovations are an interpretable lower bound for its training objective, a modified initialization and archite…

q-fin.RM2019

Transforming public pensions: A mixed scheme with a credit granted by the state

M. Carmen Boado-Penas, Julia Eisenberg, Ralf Korn

Birth rates have dramatically decreased and, with continuous improvements in life expectancy, pension expenditure is on an irreversibly increasing path. This will raise serious con…

stat.ME2019

Machine Learning in Least-Squares Monte Carlo Proxy Modeling of Life Insurance Companies

Anne-Sophie Krah, Zoran Nikolić, Ralf Korn

Under the Solvency II regime, life insurance companies are asked to derive their solvency capital requirements from the full loss distributions over the coming year. Since the indu…

cs.LG2019★ 10 cited

Copula & Marginal Flows: Disentangling the Marginal from its Joint

Magnus Wiese, Robert Knobloch, Ralf Korn

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 modeling or extrapolat…

q-fin.MF2019★ 267 cited

Quant GANs: Deep Generation of Financial Time Series

Magnus Wiese, Robert Knobloch, Ralf Korn +1

Modeling financial time series by stochastic processes is a challenging task and a central area of research in financial mathematics. As an alternative, we introduce Quant GANs, a…

math.OC2019

Optimal inflow control penalizing undersupply in transport systems with uncertain demands

Simone Göttlich, Ralf Korn, Kerstin Lux

We are concerned with optimal control strategies subject to uncertain demands. An Ornstein-Uhlenbeck process describes the uncertain demand. The transport within the supply system…

math.OC2018

Optimal control of electricity input given an uncertain demand

Simone Göttlich, Ralf Korn, Kerstin Lux

We consider the problem of determining an optimal strategy for electricity injection that faces an uncertain power demand stream. This demand stream is modeled via an Ornstein-Uhle…

math.ST2013★ 6 cited

GARCH-extended models: theoretical properties and applications

Giles-Arnaud Nzouankeu Nana, Ralf Korn, Christina Erlwein-Sayer

This paper is concerned with some properties of the generalized GARCH models, obtained by extending GARCH models with exogenous variables, the so-called GARCH extended (GARCHX) mod…