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Financial experts assume that measures the risk of financial asset returns generally have a normal distribution. Reality often shows asset returns are not normally distributed, so that the constraints and make it difficult to estimate the risk of taking the measurements. For it is necessary to...
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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...
Persistent link: https://www.econbiz.de/10013100621
In this paper, we assess the Value at Risk (VaR) prediction accuracy and efficiency of six ARCH-type models, six realized volatility models and two GARCH models augmented with realized volatility regressors. The α-th quantile of the innovation's distribution is estimated with the fully...
Persistent link: https://www.econbiz.de/10013126884
We improve on the Instrumented Principal Component Analysis (IPCA) model developed in Kelly, Pruitt and Su (2019) by providing more efficient Generalized Least Square (GLS) estimators with a closed-form limiting distribution allowing for a more consistent (mis)pricing inference. The IPCA model...
Persistent link: https://www.econbiz.de/10013291474
This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and...
Persistent link: https://www.econbiz.de/10012804913
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...
Persistent link: https://www.econbiz.de/10003891679
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight...
Persistent link: https://www.econbiz.de/10013155427