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Long memory persistence in the factor of Implied volatility dynamics
Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2007
Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small … long time, affecting significantly stock prices. For appropriate representation of the series dynamics and the possibility …. -- Implied Volatility ; Dynamic Semiparametric Factor Modeling ; Long Memory ; Fractional Integrated Volatility Models …
Persistent link: https://www.econbiz.de/10003633787
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Value-at-risk and expected shortfall when there is long range dependence
Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2008
Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...
Persistent link: https://www.econbiz.de/10003636008
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A generalized ARFIMA process with Markov-switching fractional differencing parameter
Tsay, Wen-jen (contributor); Härdle, Wolfgang (contributor) - 2007
We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...
Persistent link: https://www.econbiz.de/10003633683
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Measuring and modeling risk using high-frequency data
Härdle, Wolfgang (contributor);  … - 2008
Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management … ; realized betas ; volatility modeling …
Persistent link: https://www.econbiz.de/10003727640
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Combination of multivariate volatility forecasts
Amendola, Alessandra; Storti, Giuseppe - 2009
This paper proposes a novel approach to the combination of conditional covariance matrix forecasts based on the use of the Generalized Method of Moments (GMM). It is shown how the procedure can be generalized to deal with large dimensional systems by means of a two-step strategy. The finite...
Persistent link: https://www.econbiz.de/10003796201
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Prognose mit nichtparametrischen Verfahren
Härdle, Wolfgang; Schulz, Rainer; Wang, Weining - 2010
Persistent link: https://www.econbiz.de/10008663388
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On the appropriateness of inappropriate VaR models
Härdle, Wolfgang (contributor);  … - 2006
The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index,...
Persistent link: https://www.econbiz.de/10003324192
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Varying coefficient GARCH versus local constant volatility modeling : comparison of the predictive power
Polzehl, Jörg (contributor);  … - 2006
Persistent link: https://www.econbiz.de/10003324453
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Capturing common components in high-frequency financial time series : a multivariate stochastic multiplicative error model
Hautsch, Nikolaus (contributor) - 2007
We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics …) common factor dynamics as well as idiosyncratic effects in the processes of high-frequency return volatilities, trade sizes … and intensities are driven by idiosyncratic dynamics as well as a highly persistent common factor capturing most causal …
Persistent link: https://www.econbiz.de/10003634717
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Modelling high-frequency volatility and liquidity using multiplicative error models
Hautsch, Nikolaus (contributor);  … - 2008
In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as trading costs in an electronic limit order book market. Using data from the Australian Stock Exchange we model 1-min squared mid-quote returns, average trade sizes, number of...
Persistent link: https://www.econbiz.de/10003727673