Showing 1 - 10 of 19,911
The CCC-GARCH model, and its dynamic correlation extensions, form the most important model class for multivariate asset returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of Gaussianity. This paper considers the so-called...
Persistent link: https://www.econbiz.de/10014236254
We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an international equity portfolio. According to the risk...
Persistent link: https://www.econbiz.de/10010407672
Risk estimation or volatility estimation at financial markets, particularly stock exchange markets, is complex issue of great importance to theorists and practitioners. Models used to estimate volatility forecasts are translated into better pricing of stocks and better risk management. The aim...
Persistent link: https://www.econbiz.de/10011901688
In this study we consider the risk estimation as a stochastic process based on the Sample Quantile Process (SQP) - which is a generalization of the Value-at-Risk calculated on a rolling sample. Using SQP's, we are able to show and quantify the pro-cyclicality of the current way financial...
Persistent link: https://www.econbiz.de/10012919289
. Two approaches based on the extreme value theory were compared: Block Maxima and the Peaks Over Threshold. Forecasts were …
Persistent link: https://www.econbiz.de/10012302139
This paper presents the first methodological proposal of estimation of the VaR. Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a simple backtesting methodology by...
Persistent link: https://www.econbiz.de/10011811561
We propose a heterogeneous autoregressive (HAR) model with time-varying parameters in the form of a local linear random forest. In contrast to conventional random forests that approximate the volatility nonparametrically using local averaging, the building blocks of our forest are HAR panel...
Persistent link: https://www.econbiz.de/10013404288
This study aimed to predict the JKII (Jakarta Islamic Index) price as a price index of sharia stocks and predict the loss risk. This study uses geometric Brownian motion (GBM) and Value at Risk (VaR; with the Monte Carlo Simulation approach) on the daily closing price of JKII from 1 August...
Persistent link: https://www.econbiz.de/10012800645
We document a substantial increase in downside risk to US economic growth over the last 30 years. By modelling secular trends and cyclical changes of the predictive density of GDP growth, we find an accelerating decline in the skewness of the conditional distributions, with significant,...
Persistent link: https://www.econbiz.de/10013226483
Standard realized volatility (RV) measures estimate the latent volatility of an asset price using high frequency data with no reference to how or where the estimate will subsequently be used. This paper presents methods for “tailoring” the estimate of volatility to the application in which...
Persistent link: https://www.econbiz.de/10014255167