Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31174
Title: How does innovation's tail risk determine marginal tail risk of a stationary financial time series?
Authors: Pan, JZ
Yu, BWT
Pang, WK
Keywords: Risk analysis
Infinite weighted sum
Moving average
Bilinear model
Stochastic difference equation
Tail probability
Vague convergence
Issue Date: 2004
Publisher: Science China Press
Source: Science in China series a - mathematics, 2004, v. 47, no. 3, p. 321-338 How to cite?
Journal: Science in China Series A-Mathematics 
Abstract: We discuss the relationship between the marginal tail risk probability and the innovation's tail risk probability for some stationary financial time series models. We first give the main results on the tail behavior of a class of infinite weighted sums of random variables with heavy-tailed probabilities. And then, the main results are applied to three important types of time series models: infinite order moving averages, the simple bilinear time series and the solutions of stochastic difference equations. The explicit formulas are given to describe how the marginal tail probabilities come from the innovation's tail probabilities for these time series. Our results can be applied to the tail estimation of time series and are useful for risk analysis in finance.
URI: http://hdl.handle.net/10397/31174
ISSN: 1006-9283
DOI: 10.1360/02ys0317
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