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 …

The interest in forecasting the Value at Risk (VaR) has been growing over the last two
decades, due to the practical relevance of this risk measure for financial and insurance …

In this paper, we examined the asymmetric dynamics and causality of technological
progress––proxied by green technology innovation––on both consumption-based carbon …

Recently, advances in time-varying quantile modeling have proven effective in financial
Value-at-Risk forecasting. Some well-known dynamic conditional autoregressive quantile …

The propagation of tail risks poses a significant threat to global financial stability. Although a
growing body of literature studies tail connectedness across global stock markets, little …

This paper employs a combination of the Copula-CoVaR approach and the ARMA-GARCH-
skewed Student-t model to investigate the tail dependence structure and extreme risk …

This work investigates the performance of different models of value at risk. We include
several methods (parametric, historical simulation, Monte Carlo, and extreme value theory) …

Since the pioneering work by Tong (1978, 1983), threshold time series modelling and its
applications have become increasingly important for research in economics and finance. A …

This paper proposes value‐at risk (VaR) estimation methods that are a synthesis of
conditional autoregressive value at risk (CAViaR) time series models and implied volatility …

Some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models are
proposed that incorporate intra-day price ranges. Model estimation is performed using a …