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Econometric Models for Oil Price Forecasting: A Critical Survey

Frey, Giliola; Manera, Matteo; Markandya, Anil; Scarpa, … - In: CESifo Forum 10 (2009) 1, pp. 29-44

Persistent link: https://www.econbiz.de/10005013101

Risk Modeling and Management: An Overview

Chang, Chia-Lin; Allen, David E.; McAleer, Michael; … - Department of Economics and Finance, College of … - 2013

The papers in this special issue of Mathematics and Computers in Simulation are substantially revised versions of the papers that were presented at the 2011 Madrid International Conference on “Risk Modeling and Management” (RMM2011). The papers cover the following topics: currency hedging...

Persistent link: https://www.econbiz.de/10010907434

An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange

Bucevska, Vesna - In: Business Systems Research 4 (2013) 1, pp. 49-64

VaR estimation in emerging financial markets. Methods/Approach: Using the daily returns of the Macedonian stock exchange … estimation of VaR is related to the chosen GARCH model. The obtained findings bear important implications regarding VaR … estimation in turbulent times that have to be addressed by investors in emerging capital markets. …

Persistent link: https://www.econbiz.de/10011019968

Accurate Value-at-Risk forecast with the (good old) normal-GARCH model

Hartz, Christoph; Mittnik, Stefan; Paolella, Marc S. - Center for Financial Studies - 2006

A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and,...

Persistent link: https://www.econbiz.de/10010958670

Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates

Siburg, Karl Friedrich; Stoimenov, Pavel; Weiß, Gregor N.F. - In: Journal of Banking & Finance 54 (2015) C, pp. 129-140

We propose to forecast the Value-at-Risk of bivariate portfolios using copulas which are calibrated on the basis of nonparametric sample estimates of the coefficient of lower tail dependence. We compare our proposed method to a conventional copula-GARCH model where the parameter of a Clayton...

Persistent link: https://www.econbiz.de/10011264647

Portfolio Value at Risk Based on Independent Components Analysis

Chen, Ying; Härdle, Wolfgang; Spokoiny, Vladimir - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2005

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A...

Persistent link: https://www.econbiz.de/10005207944

Structural breaks and financial risk management

Valentinyi-Endrész, Marianna - Magyar Nemzeti Bank (MNB) - 2004

rolling-window estimation and out-of-sample forecast the SB models seem to perform slightly better. However the results are …

Persistent link: https://www.econbiz.de/10005357941

Quantile Regression in Risk Calibration

Chao, Shih-Kang; Härdle, Wolfgang Karl; Wang, Weining - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2012

elements of CoVaR estimation are two levels of quantile regression: one on market risk factors; another on individual risk …

Persistent link: https://www.econbiz.de/10009651900

Quantile Forecasts of Financial Returns Using Realized GARCH Models

Watanabe, Toshiaki - Institute of Economic Research, Hitotsubashi University - 2011

This article applies the realized GARCH model, which incorporates the GARCH model with realized volatility (RV), to quantile forecasts of financial returns such as Value-at-Risk and expected shortfall. This model has certain advantages in the application to quantile forecasts because it can...

Persistent link: https://www.econbiz.de/10009209768

Backtesting Value-at-Risk using Forecasts for Multiple Horizons, a Comment on the Forecast Rationality Tests of A.J. Patton and A. Timmermann

Hoogerheide, Lennart F.; Ravazzolo, Francesco; Dijk, … - Tinbergen Institute - 2011

Patton and Timmermann (2011, 'Forecast Rationality Tests Based on Multi-Horizon Bounds', <I>Journal of Business & Economic Statistics</I>, forthcoming) propose a set of useful tests for forecast rationality or optimality under squared error loss, including an easily implemented test based on a...</i>

Persistent link: https://www.econbiz.de/10009322510