activity
20182020
most citedCopula & Marginal Flows: Disentangling the Marginal from its Joint

10 citations · 10 across the 4 of their papers we have counts for

collaborators

8 papers

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 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.LG201910 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

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…