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How informative is high-frequency data for tail risk estimation and forecasting? An intrinsic time perspectice
Halbleib, Roxana; Dimitriadis, Timo - 2019
This paper proposes a novel and simple approach to compute daily Value at Risk (VaR) and Expected Shortfall (ES) directly from high-frequency data. It assumes that financial logarithm prices are subordinated unifractal processes in the intrinsic time, which stochastically transforms the clock...
Persistent link: https://www.econbiz.de/10012099231
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Value-at-risk and expected shortfall when there is long range dependence
Härdle, Wolfgang Karl; Mungo, Julius - 2008
, we estimate two long memory models, the Fractional Integrated Asymmetric Power-ARCH and the Hyperbolic-GARCH with …
Persistent link: https://www.econbiz.de/10010274140
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Gauging risk with higher moments: Handrails in measuring and optimising conditional value at risk
Bugár, Gyöngyi; Maurer, Raimond H.; Vo, Huy Thanh - 2009
value at risk (CVaR). To be more exact, we attempt to reveal the extent to which the risk given by CVaR can be estimated … different confidence levels for CVaR, and the contribution of the identified factors in explaining CVaR was determined … preferences. In addition, portfolio optimisation was performed in the mean-CVaR framework characterised by using CVaR as a measure …
Persistent link: https://www.econbiz.de/10010275840
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Tail Wags Dog? Time-Varying Information Shares in the Bund Market
Upper, Christian; Werner, Thomas - 2002
The flow of information between futures and spot prices may vary over time, in particular during periods of stress. This article analyses the information content of the Bund Future and German government bonds during 1998 and test whether it is constant over time. The use of high-frequency data...
Persistent link: https://www.econbiz.de/10010295741
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Real-time price discovery in stock, bond and foreign exchange markets
Andersen, Torben G.; Bollerslev, Tim; Diebold, Francis X.; … - 2004
We characterize the response of U.S., German and British stock, bond and foreign exchange markets to real-time U.S. macroeconomic news. Our analysis is based on a unique data set of high-frequency futures returns for each of the markets. We find that news surprises produce conditional mean...
Persistent link: https://www.econbiz.de/10010298290
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Return and Volatility Reactions to Monthly Announcements of Business Cycle Forecasts: An Event Study Based on High-Frequency Data
Steiner, Christian; Groß, Anne; Entorf, Horst - 2009
in a GARCH(1,1)-model, the paper reveals that significant increases in volatility only show up in the presence of …
Persistent link: https://www.econbiz.de/10010298727
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Modeling and Forecasting DAX Index Volatility
Lazarov, Zdravetz - 2004
The recent introduction of the realized variance measure defined as the sum of the squared intra-daily returns stamped on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new directions. First, the realized variance is a much better...
Persistent link: https://www.econbiz.de/10010263102
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Pricing of options under different volatility models
Herzberg, Markus; Sibbertsen, Philipp - 2004
In this paper we compare the price of an option with one year maturity of the German stock index DAX for several volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as the Black-Scholes and Hull-White formulas which...
Persistent link: https://www.econbiz.de/10010296646
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Messung des Marktrisikos mit generalisierter autoregressiver bedingter heteroskedastischer Modellierung der Volatilität: Ein Vergleich univariater und multivariater Konzepte
Krasnosselski, Nikolai; Cremers, Heinz; Sanddorf, Walter - 2014
GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …
Persistent link: https://www.econbiz.de/10010331352
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Asymmetric volatility effects in risk management: An empirical analysis using a stock index futures
Benavides, Guillermo - 2020
In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...
Persistent link: https://www.econbiz.de/10012616403