In this paper, we provide new empirical evidence of the relative usefulness of interval (density) and point forecasts of asset-return volatility, in the context of financial risk management using high frequency data. In our evaluation we use both statistical criteria (i.e., accuracy of...

This study extends the Diebold-Yilmaz Connectedness Index (DYCI) methodology and, based on forecast error covariance decompositions, derives a network risk model for a portfolio of assets. As a normalized measure of the sum of variance contributions, system-wide connectedness averages out the...

We present a computationally tractable method for simulating arbitrage free implied volatility surfaces. We illustrate how our method may be combined with a factor model for the implied volatility surface to generate dynamic scenarios for arbitrage-free implied volatility surfaces. Our approach...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

Given the increasing interest in cryptocurrencies shown by investors and researchers, and the importance of the potential loss scenarios resulting from investment/trading activities, this research provides market operators with a dynamic overview on the short-term portfolio tail risk...

1 Introduction -- 2 Motivation -- Part I MEASURES -- 3 Basic Terms and Notation -- 4 Historical Value-at-Risk -- 5 Sensitivities -- 6 Stress Tests -- 7 Analytical Value-at-Risk -- 8 Expected Shortfall -- 9 Model Choices -- 10 A Monte Carlo Modi cation -- 11 Support Measures -- Part II OPERATIONS...

The study provides evidence in favour of the price range as a proxy estimator of volatility in financial time series, in the cases that either intra-day datasets are unavailable or they are available at a low sampling frequency.A stochastic differential equation with time varying volatility of...

This article considers risk measures constructed under a discrete mixture-of-normal distribution on the innovations of a GARCH model with time-varying volatility. The authors use an approach based on a continuous empirical characteristic function to estimate the parameters of the model using...

In this paper, we explore the use of Independent Component Analysis (ICA) from the field of signal processing to model and estimate the dynamics of multivariate volatilities of financial asset returns in the GARCH framework. The resulting ICA-GARCH approach is shown to provide a computationally...