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**Harvard**

Brodin, E. (2007) *Extreme Value Statistics and Quantile Estimation with Applications in Finance and Insurance*. Göteborg : Chalmers University of Technology (Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, nr: 2577).

** BibTeX **

@book{

Brodin2007,

author={Brodin, Erik},

title={Extreme Value Statistics and Quantile Estimation with Applications in Finance and Insurance},

isbn={978-91-7291-896-2},

abstract={This thesis presents results in Extreme Value
Statistics and quantile estimation. A first part includes a
popular scientific introduction to Extreme Value Statistics and a
review paper on Extreme Value Theory in finance.
Further, we study new non-parametric quantile estimators for
non-extreme quantiles. After concluding that these have the same
asymptotic distribution as sample quantiles, a simulation study
shows that their small sample performance is better in many cases
than that of the sample quantile.
In the part of this thesis dealing with finance we study extreme
dependence between stock market log returns sampled at different
frequencies using the so-called tail dependence function. We also
investigate the "stylized fact" that log returns have Semi-heavy
tails.
The next topic is insurance losses resulting from wind storm
damages in southern Sweden. A detailed statistical analysis
detects a weak trend, that non-extreme quantiles of individual
storms increase with time, but no other trends. We also find
prediction intervals for the sizes of future storm losses using
both a univariate and a bivariate model. One conclusion is that
the major Swedish storm Gudrun was not unlikely to occur.
Finally, we introduce the models used in the insurance application
into risk management in finance.},

publisher={Institutionen för matematiska vetenskaper, matematisk statistik, Chalmers tekniska högskola,},

place={Göteborg},

year={2007},

series={Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no: 2577},

}

** RefWorks **

RT Dissertation/Thesis

SR Print

ID 26358

A1 Brodin, Erik

T1 Extreme Value Statistics and Quantile Estimation with Applications in Finance and Insurance

YR 2007

SN 978-91-7291-896-2

AB This thesis presents results in Extreme Value
Statistics and quantile estimation. A first part includes a
popular scientific introduction to Extreme Value Statistics and a
review paper on Extreme Value Theory in finance.
Further, we study new non-parametric quantile estimators for
non-extreme quantiles. After concluding that these have the same
asymptotic distribution as sample quantiles, a simulation study
shows that their small sample performance is better in many cases
than that of the sample quantile.
In the part of this thesis dealing with finance we study extreme
dependence between stock market log returns sampled at different
frequencies using the so-called tail dependence function. We also
investigate the "stylized fact" that log returns have Semi-heavy
tails.
The next topic is insurance losses resulting from wind storm
damages in southern Sweden. A detailed statistical analysis
detects a weak trend, that non-extreme quantiles of individual
storms increase with time, but no other trends. We also find
prediction intervals for the sizes of future storm losses using
both a univariate and a bivariate model. One conclusion is that
the major Swedish storm Gudrun was not unlikely to occur.
Finally, we introduce the models used in the insurance application
into risk management in finance.

PB Institutionen för matematiska vetenskaper, matematisk statistik, Chalmers tekniska högskola,

T3 Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, no: 2577

LA swe

OL 126