Modeling Nonlinearities and Asymmetries in Asset Pricing

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Title: Modeling Nonlinearities and Asymmetries in Asset Pricing
Author: Kulp-Tåg, Sofie
Other contributor: Svenska handelshögskolan, Institutionen för finansiell ekonomi och ekonomisk statistik, finansiell ekonomi
Swedish School of Economics and Business Administration, Department of Finance and Statistics, Finance
Publisher: Svenska handelshögskolan
Date: 2008-06-02
Language: en
Belongs to series: Economics and Society - 179
ISBN: 978-951-555-986-9
ISSN: 0424-7256
Thesis level: Doctoral thesis
Abstract: Financial time series tend to behave in a manner that is not directly drawn from a normal distribution. Asymmetries and nonlinearities are usually seen and these characteristics need to be taken into account. To make forecasts and predictions of future return and risk is rather complicated. The existing models for predicting risk are of help to a certain degree, but the complexity in financial time series data makes it difficult. The introduction of nonlinearities and asymmetries for the purpose of better models and forecasts regarding both mean and variance is supported by the essays in this dissertation. Linear and nonlinear models are consequently introduced in this dissertation. The advantages of nonlinear models are that they can take into account asymmetries. Asymmetric patterns usually mean that large negative returns appear more often than positive returns of the same magnitude. This goes hand in hand with the fact that negative returns are associated with higher risk than in the case where positive returns of the same magnitude are observed. The reason why these models are of high importance lies in the ability to make the best possible estimations and predictions of future returns and for predicting risk.
Subject: asymmetry
conditional variance
nordic stock markets
parameter stability
exponential garch
asymmetric volatility
piecewise regression
arch effects
Rights: Publikationen är skyddad av upphovsrätten. Den får läsas och skrivas ut för personligt bruk. Användning i kommersiellt syfte är förbjuden.

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