scholarly journals Stochastic Optimization in Asset & Liability Management: A Model for Non-Maturing Accounts

2000 ◽  
pp. 67-101 ◽  
Author(s):  
Karl Frauendorfer ◽  
Michael Schürle
Keyword(s):  
Stochastic Optimization ◽  
Asset Liability Management ◽  
Liability Management

A MODEL FOR THE OPTIMAL ASSET-LIABILITY MANAGEMENT FOR INSURANCE COMPANIES

2003 ◽  
Vol 06 (03) ◽  
pp. 277-299 ◽  
Author(s):  
S. SBARAGLIA ◽  
M. PAPI ◽  
M. BRIANI ◽  
M. BERNASCHI ◽  
F. GOZZI
Keyword(s):  
Stochastic Optimization ◽  
Utility Function ◽  
Discrete Time ◽  
Optimization Problem ◽  
Insurance Companies ◽  
Asset Liability Management ◽  
Liability Management ◽  
Stochastic Optimization Problem ◽  
The Right ◽  
To Receive

This paper is devoted to the formulation of a model for the optimal asset-liability management for insurance companies. We focus on a typical guaranteed investment contract, by which the holder has the right to receive after T years a return that cannot be lower than a minimum predefined rate rg. We take account of the rules that usually are imposed to insurance companies in the management of this funds as reserves and solvency margin. We formulate the problem as a stochastic optimization problem in a discrete time setting comparing this approach with the so-called hedging approach. The utility function to maximize depends on various parameters including specific goals of the company management. Some preliminary numerical results are reported to ease the comparison between the two approaches.

scholarly journals Stratified filtered sampling in stochastic optimization

2000 ◽  
Vol 4 (1) ◽  
pp. 17-38 ◽  
Author(s):  
Robert Rush ◽  
John M. Mulvey ◽  
John E. Mitchell ◽  
Thomas R. Willemain
Keyword(s):  
Pilot Study ◽  
Stochastic Optimization ◽  
Optimization Model ◽  
Stratified Sampling ◽  
Sampling Plan ◽  
Insurance Company ◽  
Decision Strategy ◽  
Asset Liability Management ◽  
Liability Management

We develop a methodology for evaluating a decision strategy generated by a stochastic optimization model. The methodology is based on a pilot study in which we estimate the distribution of performance associated with the strategy, and define an appropriate stratified sampling plan. An algorithm we call filtered search allows us to implement this plan efficiently. We demonstrate the approach's advantages with a problem in asset / liability management for an insurance company.

scholarly journals Asset–liability modelling in the quantum era

2021 ◽  
Vol 26 ◽  
Author(s):  
T. Berry ◽  
J. Sharpe
Keyword(s):  
Quantum Mechanics ◽  
Quantum Computer ◽  
Quantum Algorithm ◽  
Capital Requirements ◽  
Quantum Computers ◽  
Investment Management ◽  
Asset Liability Management ◽  
Liability Management ◽  
Insight Into ◽  
Current Practices

Abstract This paper introduces and demonstrates the use of quantum computers for asset–liability management (ALM). A summary of historical and current practices in ALM used by actuaries is given showing how the challenges have previously been met. We give an insight into what ALM may be like in the immediate future demonstrating how quantum computers can be used for ALM. A quantum algorithm for optimising ALM calculations is presented and tested using a quantum computer. We conclude that the discovery of the strange world of quantum mechanics has the potential to create investment management efficiencies. This in turn may lead to lower capital requirements for shareholders and lower premiums and higher insured retirement incomes for policyholders.

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