Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/45352 
Year of Publication: 
2010
Series/Report no.: 
Discussion Papers in Statistics and Econometrics No. 4/10
Publisher: 
University of Cologne, Seminar of Economic and Social Statistics, Cologne
Abstract: 
This paper investigates a selection of methods disentangling contributions from price jumps to realized variance. Flat prices (consecutively sampled prices in calendar time with the same value) and no trading (no price observation at sampling points), both frequently occurring stylized facts in financial high-frequency datasets, can cause a considerable bias in each considered method. Hence, we propose an approach to robustify those methods so that they can provide undistorted statistical results based on intraday intervals not influenced by flat prices and no trading. The new approach is tested in realistic Monte Carlo experiments and shows to be extraordinary robust against varying levels of flat price and no trading bias. Additionally, we examine the new approach empirically with a dataset of electricity forward contracts traded on the Nord Pool Energy Exchange. We obtain coherent conclusions with respect to predefined qualitative indicators.
Subjects: 
Realized Variance
Zero-Returns
Price Jumps
Robust Estimation
High-Frequency Data
Electricity Forward Contract
JEL: 
C12
C13
C14
G10
Document Type: 
Working Paper

Files in This Item:
File
Size
472.71 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.