Locally Time Homogeneous Time Series Modelling

Mstislav Elagin and Vladimir Spokoiny
Additional contact information
Mstislav Elagin: Weierstrass Institute for Applied Analysis and Stochastics
Vladimir Spokoiny: Weierstrass Institute for Applied Analysis and Stochastics

Chapter 17 in Applied Quantitative Finance, 2009, pp 345-361 from Springer

Abstract: Modelling particular features (“stylized facts”) of financial time series such as volatility clustering, heavy tails, asymmetry, etc. is an important task arising in financial engineering. For instance, attempts to model volatility clustering, i.e. the tendency of volatility jumps to appear in groups followed by periods of stability, led to the development of conditional heteroskedastic (CH) models including ARCH by Engle (1982) and GARCH by Bollerslev (1986) as well as their derivatives. The main idea underlying the mentioned methods is that volatility clustering can be modelled globally by a stationary process. The chapter is organized as follows. Section 17.2 is devoted to the formulation of the problem and theoretical introduction. Section 17.3 describes the methods under comparison. In Section 17.4 the procedure for obtaining critical values, essential parameters of the procedures, is given. Section 17.5 shows the application of the adaptive methods to the computation of the value-at-risk.

Keywords: Conditional Variance; Adaptive Method; Parametric Case; Weak Estimate; Volatility Cluster (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-69179-2_17

Ordering information: This item can be ordered from
http://www.springer.com/9783540691792

DOI: 10.1007/978-3-540-69179-2_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().