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Chen, Ying; Härdle, Wolfgang; Pigorsch, Uta - 2009

With the recent availability of high-frequency Financial data the long range dependence of volatility regained researchers' interest and has lead to the consideration of long memory models for realized volatility. The long range diagnosis of volatility, however, is usually stated for long sample...

Persistent link: https://www.econbiz.de/10003796151

Nonparametric autoregression with multiplicative volatility and additive mean

Yang, Lijian; Härdle, Wolfgang; Nielsen, Jens Perch - 1998

For over a decade, nonparametric modelling has been successfully applied to study nonlinear structures in financial time series. It is well known that the usual nonparametric models often have less than satisfactory performance when dealing with more than one lag. When the mean has an additive...

Persistent link: https://www.econbiz.de/10009578559

Implied market price of weather risk

Härdle, Wolfgang; López Cabrera, Brenda - 2009

Weather influences our daily lives and choices and has an enormous impact on cooperate revenues and earnings. Weather derivatives differ from most derivatives in that the underlying weather cannot be traded and their market is relatively illiquid. The weather derivative market is therefore...

Persistent link: https://www.econbiz.de/10003796146

Pricing of Asian temperature risk

Benth, Fred Espen; Härdle, Wolfgang; Cabrera, Brenda López - 2009

variation is calibrated with a combination of a fourier truncated series with a GARCH model and with a local linear regression …

Persistent link: https://www.econbiz.de/10003893132

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

Kernel regression smoothing of time series

Härdle, Wolfgang; Vieu, Philippe - 1990

Persistent link: https://www.econbiz.de/10000800790

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

Time series modelling with semiparametric factor dynamics

Borak, Szymon; Härdle, Wolfgang; Mammen, Enno; Park, … - 2007

High-dimensional regression problems which reveal dynamic behavior are typically analyzed by time propagation of a few number of factors. The inference on the whole system is then based on the low-dimensional time series analysis. Such highdimensional problems occur frequently in many different...

Persistent link: https://www.econbiz.de/10003633687

Long memory persistence in the factor of Implied volatility dynamics

Härdle, Wolfgang (contributor); Mungo, Julius (contributor) - 2007

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small number of factors. Such dimension reduction is...

Persistent link: https://www.econbiz.de/10003633787

Adaptive pointwise estimation in time-inhomogeneous time-series models

Čížek, Pavel (contributor); Härdle, Wolfgang (contributor) - 2008

-coefficient parametric models, such as AR or GARCH, whose coefficients may arbitrarily vary with time. Global parametric, smooth transition … the particular case of GARCH estimation, the proposed method is applied to stock-index series and is shown to outperform … the standard parametric GARCH model. -- adaptive pointwise estimation ; autoregressive models ; conditional …

Persistent link: https://www.econbiz.de/10003635965