Stochastic Optimization in Insurance Stochastic Optimization in Insurance
SpringerBriefs in Quantitative Finance

Stochastic Optimization in Insurance

A Dynamic Programming Approach

    • €42.99
    • €42.99

Publisher Description

The main purpose of the book is to show how a viscosity approach can be used to tackle control problems in insurance. The problems covered are the maximization of survival probability as well as the maximization of dividends in the classical collective risk model. The authors consider the possibility of controlling the risk process by reinsurance as well as by investments. They show that optimal value functions are characterized as either the unique or the smallest viscosity solution of the associated Hamilton-Jacobi-Bellman equation; they also study the structure of the optimal strategies and show how to find them.

The viscosity approach was widely used in control problems related to mathematical finance but until quite recently it was not used to solve control problems related to actuarial mathematical science. This book is designed to familiarize the reader on how to use this approach. The intended audience is graduate students as well as researchers in this area.

GENRE
Science & Nature
RELEASED
2014
19 June
LANGUAGE
EN
English
LENGTH
156
Pages
PUBLISHER
Springer New York
PROVIDER INFO
Springer Science & Business Media LLC
SIZE
3.9
MB
Gaussian Process Models for Quantitative Finance Gaussian Process Models for Quantitative Finance
2025
Saddlepoint Approximation Methods in Financial Engineering Saddlepoint Approximation Methods in Financial Engineering
2018
Enlargement of Filtration with Finance in View Enlargement of Filtration with Finance in View
2017
Fourier-Malliavin Volatility Estimation Fourier-Malliavin Volatility Estimation
2017
Contagion! Systemic Risk in Financial Networks Contagion! Systemic Risk in Financial Networks
2016
Electricity Derivatives Electricity Derivatives
2015