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Essays on Risk in International Financial Markets

Larsson, Ola LU (2007) In Lund Economic Stuides Number 139.
Abstract (Swedish)
Popular Abstract in Swedish

Denna avhandling behandlar metoder för att modellera risk på de finansiella marknaderna. Avhandlingen består av fyra separata uppsatser och inleds med en introduktion i kapitel ett, medan kapitel två till kapitel 5 består av de fyra uppsatserna.



Den första uppsatsen undersöker implikationerna av att använda olika riskmått inom portföljval. Speciellt undersöks tre olika riskmått: varians, Value at Risk (VaR) and Conditional Value at Risk (CVaR). Först undersöks dessa riskmåtts teoretiska egenskaper med hjälp av stokastisk dominans, där det fastställs att varians and VaR endast är konsistent med stokastisk dominans av första ordningen, medan CVaR är konsistent av andra ordningen.... (More)
Popular Abstract in Swedish

Denna avhandling behandlar metoder för att modellera risk på de finansiella marknaderna. Avhandlingen består av fyra separata uppsatser och inleds med en introduktion i kapitel ett, medan kapitel två till kapitel 5 består av de fyra uppsatserna.



Den första uppsatsen undersöker implikationerna av att använda olika riskmått inom portföljval. Speciellt undersöks tre olika riskmått: varians, Value at Risk (VaR) and Conditional Value at Risk (CVaR). Först undersöks dessa riskmåtts teoretiska egenskaper med hjälp av stokastisk dominans, där det fastställs att varians and VaR endast är konsistent med stokastisk dominans av första ordningen, medan CVaR är konsistent av andra ordningen. I den empiriska delen av uppsatsen undersöks de optimala portföljerna under de olika riskmåtten med hjälp av amerikansk aktiedata. Undersökningen finner att även om VaR och varians har mindre attraktiva teoretiska egenskaper än CVaR är skillnaden mellan de optimala portföljerna små. Vidare genomförs ett test för stokastisk dominans av första och andra ordningen. Testet kan inte påvisa att något riskmått dominerar de övriga.



I avhandlingens andra uppsats undersöks modeller av typen GARCH och stokastisk volatilitet. Framför allt undersöks modellernas förmåga att prognostisera volatilitet och VaR en handelsdag framåt. Resultaten visar att båda modellerna ger dåliga volatilitetsprognoser, med stokastisk volatilitet som något bättre än GARCH. Skillnaden är dock inte signifikant. Vidare visar resultaten att val at fördelning i de respektive modellerna inte har någon betydelse för volatilitetsprognostisering. Modellernas förmåga att prognostisera VaR är generellt tillfredställande, både för GARCH och för stokastisk volatilitet. Modellerna ger ungefär lika bra resultat. Bäst resultat fås för båda modellerna med t-fördelningen och den skeva t-fördelningen.



Den tredje uppsatsen undersöker olika multivariata modeller med avseende på VaR prognostisering. Speciellt fokuserar uppsatsen på copulas. Copulas är funktioner som knyter samman marginalfördelningarna till en multivariat modell. I denna uppsats föreslås ett nytt sätt att modellera tidsvarierande beroende med hjälp av copulas. Vidare undersöks och jämförs tidsvarierande och konstanta copulas med traditionella multivariata modeller. Resultaten visar att copulas kan vara ett värdefullt verktyg inom VaR prognostisering.



I den fjärde uppsatsen undersöks beroendet mellan aktie och obligationsmarknaderna med hjälp av en multivariate regimskiftesmodell. Modellen kan fånga både linjärt och icke-linjärt beroende. Vidare gör modellen möjligt att bestämma om vardera marknaden är i en högvolatilitetsregim eller en lågvolatilitetsregim vid varje tidpunkt. I en bivariat modell ger detta totalt fyra olika regimer. Beroendet mellan aktie och obligationsmarknaderna undersöks i de olika tillstånden med hjälp av data från USA, Storbritannien och Japan. Resultaten visar att beroendet inte är konstant över de olika regimerna. Vidare finner studien att för den amerikanska och den brittiska obligationsmarknaden är beroendet negativt då både obligationsmarknaden och aktiemarknaden är i högvolatilitetstillståndet. (Less)
Abstract
This thesis deals with techniques to model risk in financial markets and consists of four separate essays. The thesis begins with an introduction in chapter one, while chapter two to chapter five contains the four essays.



The first essay examines the implication of using various risk measures for portfolio selection. Specifically, three risk measures are examined: variance, Value at Risk (VaR) and Conditional Value at Risk (CVaR). The theoretical properties of these measures are first examined using the theory of stochastic dominance, and it is established that variance and VaR is only consistent with stochastic dominance of first order, while CVaR is consistent with stochastic dominance of second order. In the empirical... (More)
This thesis deals with techniques to model risk in financial markets and consists of four separate essays. The thesis begins with an introduction in chapter one, while chapter two to chapter five contains the four essays.



The first essay examines the implication of using various risk measures for portfolio selection. Specifically, three risk measures are examined: variance, Value at Risk (VaR) and Conditional Value at Risk (CVaR). The theoretical properties of these measures are first examined using the theory of stochastic dominance, and it is established that variance and VaR is only consistent with stochastic dominance of first order, while CVaR is consistent with stochastic dominance of second order. In the empirical part of the essay, the optimal portfolios under the various risk measures are examined using stock market data from the US. It is found that although VaR and variance have less attractive theoretical properties, in practice, the difference between the measures is small. Furthermore, a test for stochastic dominance of first and second order is employed. The test suggests that none of the risk measures dominates the others.



In the second essay the forecasting performance of GARCH and stochastic volatility models is examined and compared. The results for volatility forecasting is generally quite disappointing, with no model passing the tests for complete unbiased forecasts. The stochastic volatility model delivers in general slightly better forecasts compared to the GARCH model, but the difference is not significant. Moreover, the choice of distribution seems to be unimportant. The VaR forecasts are in general quite satisfying, both for the GARCH model and for the stochastic volatility model. The models are about equally good. Best results are obtained with the student t distribution and skewed student t distribution.



The third essay examines various multivariate models for forecasting purposes. A special interest is taken in copulas. Copulas are functions that tie marginal distributions together into a multivariate model. In this essay a new way to incorporate time varying dependence in copulas is suggested and evaluated. Furthermore, alternative time varying as well as constant copulas are also examined, as well as traditional multivariate models. The results suggest that copulas are a valuable tool for VaR forecasting.



In the fourth essay, the non-linear dependence between stocks and bonds is examined using a multivariate regime switching model. With the model, each market can, at each point in time, being characterized as being in a high volatility state and in a low volatility state. In a bivariate setting, this corresponds to four separate states. The dependence between the stock market and the bond market is examined across the different states using data from the US, the UK and Japan. It is found for all markets that the dependence is not constant across the regimes. Furthermore, for the US and the UK bond market, it is found that when both the stock market and the bond market are in the high volatility state, the dependence is negative. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Knif, Johan, Svenska handelshögskolan
organization
publishing date
type
Thesis
publication status
published
subject
keywords
volatility, Value at Risk, copulas, Economics, econometrics, economic theory, economic systems, economic policy, Nationalekonomi, ekonometri, ekonomisk teori, ekonomiska system, ekonomisk politik, Financial science, Finansiering
in
Lund Economic Stuides
volume
Number 139
pages
94 pages
publisher
Department of Economics, Lund Universtiy
defense location
Ekonomihögskolan Tycho Brahes väg 1 Lund
defense date
2007-01-25 10:15
ISSN
0460-0029
language
English
LU publication?
yes
id
f86ed554-afad-4803-a177-cd4f4f12e15f (old id 547815)
date added to LUP
2007-09-27 11:40:30
date last changed
2016-09-19 08:44:57
@phdthesis{f86ed554-afad-4803-a177-cd4f4f12e15f,
  abstract     = {This thesis deals with techniques to model risk in financial markets and consists of four separate essays. The thesis begins with an introduction in chapter one, while chapter two to chapter five contains the four essays.<br/><br>
<br/><br>
The first essay examines the implication of using various risk measures for portfolio selection. Specifically, three risk measures are examined: variance, Value at Risk (VaR) and Conditional Value at Risk (CVaR). The theoretical properties of these measures are first examined using the theory of stochastic dominance, and it is established that variance and VaR is only consistent with stochastic dominance of first order, while CVaR is consistent with stochastic dominance of second order. In the empirical part of the essay, the optimal portfolios under the various risk measures are examined using stock market data from the US. It is found that although VaR and variance have less attractive theoretical properties, in practice, the difference between the measures is small. Furthermore, a test for stochastic dominance of first and second order is employed. The test suggests that none of the risk measures dominates the others.<br/><br>
<br/><br>
In the second essay the forecasting performance of GARCH and stochastic volatility models is examined and compared. The results for volatility forecasting is generally quite disappointing, with no model passing the tests for complete unbiased forecasts. The stochastic volatility model delivers in general slightly better forecasts compared to the GARCH model, but the difference is not significant. Moreover, the choice of distribution seems to be unimportant. The VaR forecasts are in general quite satisfying, both for the GARCH model and for the stochastic volatility model. The models are about equally good. Best results are obtained with the student t distribution and skewed student t distribution.<br/><br>
<br/><br>
The third essay examines various multivariate models for forecasting purposes. A special interest is taken in copulas. Copulas are functions that tie marginal distributions together into a multivariate model. In this essay a new way to incorporate time varying dependence in copulas is suggested and evaluated. Furthermore, alternative time varying as well as constant copulas are also examined, as well as traditional multivariate models. The results suggest that copulas are a valuable tool for VaR forecasting.<br/><br>
<br/><br>
In the fourth essay, the non-linear dependence between stocks and bonds is examined using a multivariate regime switching model. With the model, each market can, at each point in time, being characterized as being in a high volatility state and in a low volatility state. In a bivariate setting, this corresponds to four separate states. The dependence between the stock market and the bond market is examined across the different states using data from the US, the UK and Japan. It is found for all markets that the dependence is not constant across the regimes. Furthermore, for the US and the UK bond market, it is found that when both the stock market and the bond market are in the high volatility state, the dependence is negative.},
  author       = {Larsson, Ola},
  issn         = {0460-0029},
  keyword      = {volatility,Value at Risk,copulas,Economics,econometrics,economic theory,economic systems,economic policy,Nationalekonomi,ekonometri,ekonomisk teori,ekonomiska system,ekonomisk politik,Financial science,Finansiering},
  language     = {eng},
  pages        = {94},
  publisher    = {Department of Economics, Lund Universtiy},
  school       = {Lund University},
  series       = {Lund Economic Stuides},
  title        = {Essays on Risk in International Financial Markets},
  volume       = {Number 139},
  year         = {2007},
}