research
∙
07/24/2023
Estimation and Inference for Multivariate Continuous-time Autoregressive Processes
The aim of this paper is to develop estimation and inference methods for...
share
research
∙
10/25/2022
The uncertainty of infectious disease outbreaks is underestimated
Uncertainty can be classified as either aleatoric (intrinsic randomness)...
research
∙
07/15/2022
Deep Hedging: Continuous Reinforcement Learning for Hedging of General Portfolios across Multiple Risk Aversions
We present a method for finding optimal hedging policies for arbitrary i...
research
∙
11/15/2021
Deep Hedging: Learning to Remove the Drift under Trading Frictions with Minimal Equivalent Near-Martingale Measures
We present a numerically efficient approach for learning minimal equival...
research
∙
07/12/2021
Unifying the effective reproduction number, incidence, and prevalence under a stochastic age-dependent branching process
Renewal equations are a popular approach used in modelling the number of...
research
∙
03/22/2021
Deep Hedging: Learning Risk-Neutral Implied Volatility Dynamics
We present a numerically efficient approach for learning a risk-neutral ...
research
∙
10/09/2020
Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures
In this paper, we develop a generalized method of moments approach for j...
research
∙
07/13/2020
Feasible Inference for Stochastic Volatility in Brownian Semistationary Processes
This article studies the finite sample behaviour of a number of estimato...
research
∙
09/21/2018
State-dependent Hawkes processes and their application to limit order book modelling
We study statistical aspects of state-dependent Hawkes processes, which ...
research
∙
09/05/2017
