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