3 papers
q-fin.RM2022
Volatility Sensitive Bayesian Estimation of Portfolio VaR and CVaR
Taras Bodnar, Vilhelm Niklasson, Erik Thorsén
In this paper, a new way to integrate volatility information for estimating value at risk (VaR) and conditional value at risk (CVaR) of a portfolio is suggested. The new method is…
cs.CV2021
Automatic deforestation detectors based on frequentist statistics and their extensions for other spatial objects
Jesper Muren, Vilhelm Niklasson, Dmitry Otryakhin +1
This paper is devoted to the problem of detection of forest and non-forest areas on Earth images. We propose two statistical methods to tackle this problem: one based on multiple h…
q-fin.PM2020
Bayesian Quantile-Based Portfolio Selection
Taras Bodnar, Mathias Lindholm, Vilhelm Niklasson +1
We study the optimal portfolio allocation problem from a Bayesian perspective using value at risk (VaR) and conditional value at risk (CVaR) as risk measures. By applying the poste…