楼主: stiwen
2048 1

[CFA] 2 materials for Nonlife Actuarial Science [推广有奖]

  • 1关注
  • 0粉丝

高级会员

已卖:1007份资源

博士生

1%

还不是VIP/贵宾

-

威望
0
论坛币
1077 个
通用积分
79.9439
学术水平
1 点
热心指数
2 点
信用等级
0 点
经验
4115 点
帖子
147
精华
0
在线时间
222 小时
注册时间
2008-3-7
最后登录
2025-11-14

楼主
stiwen 发表于 2010-1-22 20:57:59 |AI写论文

+2 论坛币
k人 参与回答

经管之家送您一份

应届毕业生专属福利!

求职就业群
赵安豆老师微信:zhaoandou666

经管之家联合CDA

送您一个全额奖学金名额~ !

感谢您参与论坛问题回答

经管之家送您两个论坛币!

+2 论坛币
One is for claim reserving ,the other one for nonlife insurance mathematics.
Below is the related preface of the book:

To the outside world, insurance mathematics does not appear as a challenging
topic. In fact, everyone has to deal with matters of insurance at various
times of one’s life. Hence this is quite an interesting perception of a field
which constitutes one of the bases of modern society. There is no doubt that
modern economies and states would not function without institutions which
guarantee reimbursement to the individual, the company or the organization
for its losses, which may occur due to natural or man-made catastrophes,
fires, floods, accidents, riots, etc. The idea of insurance is part of our civilized
world. It is based on the mutual trust of the insurer and the insured.
It was realized early on that this mutual trust must be based on science,
not on belief and speculation. In the 20th century the necessary tools for
dealing with matters of insurance were developed. These consist of probability
theory, statistics and stochastic processes. The Swedish mathematicians
Filip Lundberg and Harald Cram´er were pioneers in these areas. They realized
in the first half of the 20th century that the theory of stochastic processes provides
the most appropriate framework for modeling the claims arriving in an
insurance business. Nowadays, the Cram´er-Lundberg model is one of the backbones
of non-life insurance mathematics. It has been modified and extended
in very different directions and, moreover, has motivated research in various
other fields of applied probability theory, such as queuing theory, branching
processes, renewal theory, reliability, dam and storage models, extreme value
theory, and stochastic networks.
The aim of this book is to bring some of the standard stochastic models
of non-life insurance mathematics to the attention of a wide audience which,
hopefully, will include actuaries and also other applied scientists. The primary
objective of this book is to provide the undergraduate actuarial student with
an introduction to non-life insurance mathematics. I used parts of this text in
the course on basic non-life insurance for 3rd year mathematics students at the
Laboratory of Actuarial Mathematics of the University of Copenhagen. But
I am convinced that the content of this book will also be of interest to others
who have a background on probability theory and stochastic processes and
would like to learn about applied stochastic processes. Insurance mathematics
is a part of applied probability theory. Moreover, its mathematical tools are
also used in other applied areas (usually under different names).
The idea of writing this book came in the spring of 2002, when I taught
basic non-life insurance mathematics at the University of Copenhagen. My
handwritten notes were not very much appreciated by the students, and so I
decided to come up with some lecture notes for the next course given in spring,
2003. This book is an extended version of those notes and the associated
weekly exercises. I have also added quite a few computer graphics to the
text. Graphs help one to understand and digest the theory much easier than
formulae and proofs. In particular, computer simulations illustrate where the
limits of the theory actually are.
二维码

扫码加我 拉你入群

请注明:姓名-公司-职位

以便审核进群资格,未注明则拒绝

关键词:Actuarial Materials material Nonlife Science Science Actuarial Materials Nonlife

沙发
stiwen(未真实交易用户) 发表于 2010-1-22 21:13:47
Non-Life Insurance
Mathematics:  An Introduction with the Poisson Process

Thomas Mikosch
Second Edition
ISBN 978-3-540-88232-9
Springer-Verlag Berlin Heidelberg 2009

您需要登录后才可以回帖 登录 | 我要注册

本版微信群
jg-xs1
拉您进交流群
GMT+8, 2026-1-3 00:12