In this paper, we assess the informational content of daily range, realized variance, realized bipower variation, two time scale realized variance, realized range and implied volatility in daily, weekly, biweekly and monthly out-of-sample Value-at-Risk (VaR) predictions. We use the recently...

Данная часть завершает серию консультационных публикаций Деана Фантаццини на тему «Эконометрический анализ финансовых данных в задачах управления риском». В...

Финансовая эконометрика» - новый и крайне актуальный в прикладном плане раздел эконометрической науки, практически не представленный еще в русскоязычной...

It is widely accepted that some of the most accurate predictions of aggregated asset returns are based on an appropriately specified GARCH process. As the forecast horizon is greater than the frequency of the GARCH model, such predictions either require time-consuming simulations or they can be...

The catastrophic failures of risk management systems in 2008 bring to the forefront the need for accurate and flexible estimators of market risk. Despite advances in the theory and practice of evaluating risk, existing measures are notoriously poor predictors of loss in high-quantile events. To...

The most recent financial crisis unveiled that liquidity risk is far more important and intricate than regulation have conceived. The shift from bank-based to market-based financial systems and from Deferred Net Systems to liquidity-demanding Real-Time Gross Settlement of payments explains some...

Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting...

The purpose of this paper is to investigate the performance of VaR models at measuring risk for WTI oil one-month futures returns. Risk models, ranging from industry standards such as RiskMetrics and historical simulation to conditional extreme value model, are used to calculate commodity market...

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...

This paper calculates option portfolio Value at Risk (VaR) using Monte Carlo simulation under a risk neutral stochastic implied volatility model. Compared to benchmark delta-normal method, the model produces more accurate results by taking into account nonlinearity, passage of time,...