Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data

Posted: 3 Mar 2010

See all articles by Yacine Ait-Sahalia

Yacine Ait-Sahalia

Princeton University - Department of Economics; National Bureau of Economic Research (NBER)

Jean Jacod

Université Paris VI Pierre et Marie Curie

Multiple version iconThere are 3 versions of this paper

Date Written: January 29, 2010

Abstract

This paper describes a simple yet powerful methodology to decompose asset returns sampled at high frequency into their base components (continuous, small jumps, large jumps), determine the relative magnitude of the components, and analyze the finer characteristics of these components such as the degree of activity of the jumps. We extend the existing theory to incorporate to effect of market microstructure noise on the test statistics, apply the methodology to high frequency individual stock returns, transactions and quotes, stock index returns and compare the qualitative features of the estimated process for these different data and discuss the economic implications of the results.

Keywords: Continuous-time models, semimartingales, jumps, volatility, spectrum, high frequency financial returns, market microstructure noise

JEL Classification: G11

Suggested Citation

Ait-Sahalia, Yacine and Jacod, Jean, Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data (January 29, 2010). AFA 2011 Denver Meetings Paper. Available at SSRN: https://ssrn.com/abstract=1562624 or http://dx.doi.org/10.2139/ssrn.1562624

Yacine Ait-Sahalia (Contact Author)

Princeton University - Department of Economics ( email )

Fisher Hall
Princeton, NJ 08544
United States
609-258-4015 (Phone)
609-258-5398 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jean Jacod

Université Paris VI Pierre et Marie Curie ( email )

4, Place Jussieu, B.P. 169
Laboratoire de Probabilites
F-75252-Paris Cedex 05
France
01 44 27 53 21 (Phone)

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