Similar Search Results

The stochastic fluctuation of the quantile regression curve

Härdle, Wolfgang (contributor); Song, Song (contributor) - 2008

Persistent link: https://www.econbiz.de/10003693057

Increasing weather risk : fact of fiction?

Wang, Weining; Bobojonov, Ihtiyor B.; Härdle, Wolfgang; … - 2011

It is an undisputed fact that weather risk increases over time due to climate change. However, qualification of this statement with regard to the type of weather risk and geographical location is needed. We investigate the application of novel statistical tools for assessing changes in weather...

Persistent link: https://www.econbiz.de/10009379509

Estimation and testing for varying coefficients in additive models with marginal integration

Yang, Lijian; Härdle, Wolfgang; Park, Byeong U. - 2002

We propose marginal integration estimation and testing methods for the coefficients of varying coefficient multivariate … regression model. Asymptotic distribution theory is developed for the estimation method which enjoys the same rate of convergence … as univariate function estimation. For the test statistic, asymptotic normal theory is established. These theoretical …

Persistent link: https://www.econbiz.de/10009627286

Network quantile autoregression

Zhu, Xuening; Wang, Weining; Wang, Hangsheng; Härdle, … - 2016

connected nodes and node spe- ci c characteristics in a quantile autoregression process. A minimum contrast estimation approach …

Persistent link: https://www.econbiz.de/10011572028

Estimation and testing for varying coefficients in additive models with marginal integration

Yang, Lijian; Park, Byeong U.; Xue, Lan; Härdle, Wolfgang - 2005

Persistent link: https://www.econbiz.de/10003323041

Empirical pricing kernels and investor preferences

Detlefsen, Kai (contributor); Härdle, Wolfgang (contributor) - 2007

This paper analyzes empirical market utility functions and pricing kernels derived from the DAX and DAX option data for three market regimes. A consistent parametric framework of stochastic volatility is used. All empirical market utility functions show a region of risk proclivity that is...

Persistent link: https://www.econbiz.de/10003633572

Value-at-risk and expected shortfall when there is long range dependence

Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2008

portfolio (Bayer, Siemens and Volkswagen). Classical V aR estimation methodology such as exponential moving average (EMA) as …

Persistent link: https://www.econbiz.de/10003636008

Support vector regression based GARCH model with application to forecasting volatility of financial returns

Chen, Shiyi (contributor); Jeong, Kiho (contributor); … - 2008

In recent years support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a moving...

Persistent link: https://www.econbiz.de/10003636113

Numerics of implied binomial trees

Härdle, Wolfgang (contributor); … - 2008

with the estimation from the simulated process, though the BC method shows smaller deviations in case of high interest rate …

Persistent link: https://www.econbiz.de/10003727608

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.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be...

Persistent link: https://www.econbiz.de/10003727640