Typically, point forecasting methods are compared and assessed by means of an error
measure or scoring function, with the absolute error and the squared error being key …

In this article we present a theoretical review of the existing literature on Value at Risk (VaR)
specifically focussing on the development of new approaches for its estimation. We effect a …

Expected Shortfall (ES) is the average return on a risky asset conditional on the return being
below some quantile of its distribution, namely its Value-at-Risk (VaR). The Basel III Accord …

We study the accuracy of a variety of estimators of asset price variation constructed from
high-frequency data (“realized measures”), and compare them with a simple “realized …

Elicitability and backtesting: Perspectives for banking regulation Page 1 The Annals of Applied
Statistics 2017, Vol. 11, No. 4, 1833–1874 https://doi.org/10.1214/17-AOAS1041 © Institute of …

The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable
outcomes in standard methods for comparing conditional variance forecasts. We motivate …

This paper studies in some detail a class of high‐frequency‐based volatility (HEAVY)
models. These models are direct models of daily asset return volatility based on realised …

We use the information in intraday data to forecast the volatility of crude oil at a horizon of 1–
66 days using a variety of models relying on the decomposition of realized variance in its …

This paper introduces a new class of multivariate volatility models that utilizes high‐
frequency data. We discuss the models' dynamics and highlight their differences from …

This paper addresses the question of the selection of multivariate generalized
autoregressive conditional heteroskedastic (GARCH) models in terms of variance matrix …