Midlands State University Library
Image from Google Jackets

A functional version of the arch model created by Siegfried Hörmann, Lajos Horváth and Ron Reeder

By: Contributor(s): Material type: TextTextSeries: Cambridge: Cambridge University Press, 2013 ; Volume 29, number 2Cambridge: Cambridge University Press, 2013Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISSN:
  • 02664666
Subject(s): LOC classification:
  • HB139.T52 ECO
Online resources: Abstract: Improvements in data acquisition and processing techniques have led to an almost continuous flow of information for financial data. High-resolution tick data are available and can be quite conveniently described by a continuous-time process. It is therefore natural to ask for possible extensions of financial time series models to a functional setup. In this paper we propose a functional version of the popular autoregressive conditional heteroskedasticity model. We will establish conditions for the existence of a strictly stationary solution, derive weak dependence and moment conditions, show consistency of the estimators, and perform a small empirical study demonstrating how our model matches with real data.
Reviews from LibraryThing.com:
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Vol info Copy number Status Notes Date due Barcode
Journal Article Journal Article Main Library - Special Collections HB139.T52 ECO (Browse shelf(Opens below)) Vol. 29, no.2 (pages 267-289) SP17542 Not for loan For In House Use Only

Improvements in data acquisition and processing techniques have led to an almost continuous flow of information for financial data. High-resolution tick data are available and can be quite conveniently described by a continuous-time process. It is therefore natural to ask for possible extensions of financial time series models to a functional setup. In this paper we propose a functional version of the popular autoregressive conditional heteroskedasticity model. We will establish conditions for the existence of a strictly stationary solution, derive weak dependence and moment conditions, show consistency of the estimators, and perform a small empirical study demonstrating how our model matches with real data.

There are no comments on this title.

to post a comment.