Long Run Variance Estimation Using Steep Origin Kernels without Truncation
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Other versions of this item:
- Peter C.B. Phillips & Sainan Jin & Yixiao Sun, 2004. "Long Run Variance Estimation Using Steep Origin Kernels Without Truncation," Yale School of Management Working Papers ysm427, Yale School of Management.
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- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008.
"Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise,"
Econometric Society, vol. 76(6), pages 1481-1536, November.
- Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
- Ole E Barndorff-Nielsen & Peter Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," OFRC Working Papers Series 2006fe05, Oxford Financial Research Centre.
- Peter C.B. Phillips & Yixiao Sun & Sainan Jin, 2005. "Improved HAR Inference," Cowles Foundation Discussion Papers 1513, Cowles Foundation for Research in Economics, Yale University.
More about this item
KeywordsExponentiated kernel; Lag kernel; Long run variance; Optimal exponent; Spectral window; Spectrum;
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2003-10-12 (All new papers)
- NEP-ECM-2003-10-12 (Econometrics)
- NEP-ETS-2003-10-12 (Econometric Time Series)
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