This paper proposes a means to determine whether a a calculated VaR is "too large" and give a definition of this term within the context.
The authors put forward a means of Euler capital allocation where the probability level is adjusted such that the total capital is equal to the reference quantile-based capital level.
The authors propose four new nonparametric estimators of static CoVar and compare their performance in simulation studies.
This paper investigates the statistical problem of estimating the capture ratio based on a finite number of observations of a fund’s returns.
Test for fractional degree stochastic dominance with applications to stock preferences for China and the United States
This paper develops the test statistics for fractional degree stochastic dominance and introduces a bootstrap method for determining the critical values of the tests.
This study aims to test the sufficiency of the solvency capital requirement approach for calculating operational risk using the standard formula as defined in Solvency II.
Synthetic data made with machine learning will struggle to capture the caprice of financial markets
Traditionally quants have learnt to pick data apart. Soon they might spend more time making it up
In this paper, we refer to the axiomatic theory of risk and investigate the problem of formal verification of the expected shortfall (ES) model based on a sample ES. Recognizing the infeasibility of parametric methods, they explore the bootstrap…
David Hand shines a light on dark data and the dangers of distortion by absence
This paper investigates the effects of window-size selection on various models for value-at-risk (VaR) forecasting using high-performance computing.
Academics claim Vasicek model’s underestimation tendency can be slashed to near-zero