Although understanding tail behavior of distributions is important in many areas, such as telecommunications network analysis and finance, there is considerable controversy about distinctions between exponential-type and power-type tails. This paper explains why the distinctions are surprisingly difficult for popular methods in the literature, and why particularly large samples are needed for clear discrimination
We address the important question of the extent to which random variables and vectors with truncate...
In many practical situations, we encounter Gaussian distributions, for which the distribution tails ...
The shape of empirical distributions with heavy tails is a recurrent matter of debate. There are cla...
In areas such as financial and insurance risk and communication network design the heaviness of the ...
Heavy-tails are a continual source of excitement and confusion across disciplines as they are repeat...
The aim of this thesis is to show that the use of heavy-tailed distributions in finance is theoretic...
New methods for classifying tails of probability distributions based on data are proposed. Some meth...
This title is written for the numerate nonspecialist, and hopes to serve three purposes. First it ga...
This paper studies analytically and numerically the tail behavior of the symmetric variance-gamma (V...
The aim of this work is to develop a test to distinguish between heavy and super-heavy tailed probab...
There is substantial evidence that many time series associated with financial and insurance claim da...
This monograph is written for the numerate nonspecialist, and hopes to serve three purposes. First i...
Due to its "fat tails", the power law distribution provides an effective model of the tail of stock ...
The concept of heavy- or long-tailed densities (or distributions) has attracted much well-deserved a...
In this Master thesis we will focus on the peculiar statistical properties of heavy tailed distribut...
We address the important question of the extent to which random variables and vectors with truncate...
In many practical situations, we encounter Gaussian distributions, for which the distribution tails ...
The shape of empirical distributions with heavy tails is a recurrent matter of debate. There are cla...
In areas such as financial and insurance risk and communication network design the heaviness of the ...
Heavy-tails are a continual source of excitement and confusion across disciplines as they are repeat...
The aim of this thesis is to show that the use of heavy-tailed distributions in finance is theoretic...
New methods for classifying tails of probability distributions based on data are proposed. Some meth...
This title is written for the numerate nonspecialist, and hopes to serve three purposes. First it ga...
This paper studies analytically and numerically the tail behavior of the symmetric variance-gamma (V...
The aim of this work is to develop a test to distinguish between heavy and super-heavy tailed probab...
There is substantial evidence that many time series associated with financial and insurance claim da...
This monograph is written for the numerate nonspecialist, and hopes to serve three purposes. First i...
Due to its "fat tails", the power law distribution provides an effective model of the tail of stock ...
The concept of heavy- or long-tailed densities (or distributions) has attracted much well-deserved a...
In this Master thesis we will focus on the peculiar statistical properties of heavy tailed distribut...
We address the important question of the extent to which random variables and vectors with truncate...
In many practical situations, we encounter Gaussian distributions, for which the distribution tails ...
The shape of empirical distributions with heavy tails is a recurrent matter of debate. There are cla...