CONFIDENCE BANDS IN NONPARAMETRIC TIME SERIES REGRESSION
By Zhibiao Zhao, Wei Biao Wu. 2008
81 citations recorded by the source corpus.
We consider nonparametric estimation of mean regression and conditional variance (or volatility) functions in nonlinear stochastic regression models. Simultaneous confidence bands are constructed and the coverage probabilities are shown to be asymptotically correct. The imposed dependence structure allows applications in many linear and nonlinear auto-regressive processes. The results are applied to the S&P 500 Index data.
Subfields: Finance, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/3aa30d09dbe2fe8ef52f83365afcbf75b8c86add
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Per Aslak Mykland
- Lan Zhang
- Asger Lunde
- P. R. Hansen
- Yacine Aït-Sahalia
- Shuzhuan Zheng
- Wolfgang Karl Härdle
- David Degras
In Statistics and Probability
- Lijian Yang
- Wolfgang Karl Härdle
- Lan Zhang
- Shuzhuan Zheng
- Per Aslak Mykland
- David Degras
- Shujie Ma
- Hua Liang
Citations in the corpus
- A Smooth Simultaneous Confidence Corridor for the Mean of Sparse Functional Data (2014, background): “Nonparametric time series with specific dependence structures were considered in Zhao and Wu (2008).”
- A Confidence Corridor for Sparse Longitudinal Data Curves (2011, background): “Nonparametric time series with specific dependence structures are considered in Zhao and Wu (2008).”
- Inference for volatility-type objects and implications for hedging (2008, background): “An approach to simultaneous intervals based on strong approximation can be found in Fan and Wang (2008) and Zhao and Wu (2008).”
- Simultaneous confidence bands for nonparametric regression with functional data (2009, background): “The case of a random design is studied in Zhao and Wu (2008).”