This study yields a contribution to a better understanding of the interest rate sensitivity of real estate and should enable a more sophisticated interest rate risk management, especially for insurance companies and pension funds. This is achieved by modelling the whole life of a typical but...

We model the dynamics of asset prices and associated derivatives by consideration of the dynamics of the conditional probability density process for the value of an asset at some specified time in the future. In the case where the asset is driven by Brownian motion, an associated "master...

We study discretizations of polynomial processes using finite state Markov processes satisfying suitable moment matching conditions. The states of these Markov processes together with their transition probabilities can be interpreted as Markov cubature rules. The polynomial property allows us to...

We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. The model learns the features necessary for an effective low-dimensional representation, overcoming the curse...

We provide a general valuation approach for capital budgeting decisions involving the modularization of a system. Within the framework developed by Baldwin and Clark (2000), we implement an approach using a numerical procedure based on the Least Squares Monte Carlo method proposed by Longstaff...

We propose a technique to avoid spurious detections of jumps in high-frequency data via an explicit thresholding on available test statistics. We prove that it eliminates asymptotically all spurious detections. Monte Carlo results show that it performs also well in finite samples. In Dow Jones...

The present article deals with intra-horizon risk in models with jumps. Our general understanding of intra-horizon risk is along the lines of the approach taken in [BRSW04], [Ro08], [BMK09], [BP10], and [LV19]. In particular, we believe that quantifying market risk by strictly relying on...

Risk transfer is a key risk and capital management tool for insurance companies. Transferring risk between insurers is used to mitigate risk and manage capital re- quirements. We investigate risk transfer in the context of a network environment of insurers and consider capital costs and capital...

We use BERT, an AI-based algorithm for language understanding, to decipher regulatory climate-risk disclosures and measure their impact on the credit default swap (CDS) market. Risk disclosures can either increase or decrease credit spreads, depending on whether disclosure reveals new risks or...

The forward-looking nature of option market data allows one to derive economically-based and model-free risk measures. This article proposes an extensive analysis of the performances of option-implied VaR and CVaR, and compare them with classical risk measures for the S&P500 Index. Delivering...