Artikel

Temporal aggregation and long memory for asset price volatility

The effects of temporal aggregation and choice of sampling frequency are of great interest in modeling the dynamics of asset price volatility. We show how the squared low-frequency returns can be expressed in terms of the temporal aggregation of a high-frequency series. Based on the theory of temporal aggregation, we provide the link between the spectral density function of the squared low-frequency returns and that of the squared high-frequency returns. Furthermore, we analyze the properties of the spectral density function of realized volatility series, constructed from squared returns with different frequencies under temporal aggregation. Our theoretical results allow us to explain some findings reported recently and uncover new features of volatility in financial market indices. The theoretical findings are illustrated via the analysis of both low-frequency daily Standard and Poor's 500 (S&P 500) returns from 1928 to 2011 and high-frequency 1-min S&P 500 returns from 1986 to 2007.

Language
Englisch

Bibliographic citation
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 8 ; Pages: 1-18 ; Basel: MDPI

Classification
Wirtschaft
Subject
long memory
random level shifts
semiparametric estimators
stochastic volatility
temporal aggregation

Event
Geistige Schöpfung
(who)
Perron, Pierre
Shi, Wendong
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2020

DOI
doi:10.3390/jrfm13080182
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Perron, Pierre
  • Shi, Wendong
  • MDPI

Time of origin

  • 2020

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