Invited Session Mon.1.H 3027

Monday, 10:30 - 12:00 h, Room: H 3027

Cluster 7: Finance & economics [...]

Applications of stochastic programming to finance and insurance

 

Chair: Giorgio Consigli

 

 

Monday, 10:30 - 10:55 h, Room: H 3027, Talk 1

Andrea Consiglio
Convex lower bounding to generate multi-asset, arbitrage-free, scenario trees

Coauthors: Angelo Carollo, Alessandro Staino

 

Abstract:
Simulation models of economic and financial factors are nowadays widely used to support decisions or to assess risk exposures. An extensive literature on scenarios generation is available whose main aim is to build trees with the least number of nodes, while ensuring a given level of accuracy in describing the joint probability distribution of the process.
There is, however, another important issue that is usually overlooked or, worse, ignored: the no-arbitrage restriction.
A possible solution, relatively to the moment matching approach, is to add the no-arbitrage restriction to the set of equations describing the moments of the multivariate distributions, with the shortcoming, however, of worsening the numerical stability and precision of the solution.
The aim of our analysis is to provide a new solution method for the moment matching model to overcome the limitation raised above. We re-formulate the problem of finding all the solutions of a set of non-linear equations as a global optimization problem. We then focus on new convex lower bounding techniques to provide a more stable and reliable approach to stochastic tree generation.

 

 

Monday, 11:00 - 11:25 h, Room: H 3027, Talk 2

Nalan Gulpinar
Robust investment decisions for asset liability management

Coauthors: Ethem Canakoglu, Dessislava Pachamanova

 

Abstract:
In this paper, we present stochastic and robust models for multi-period Asset Liability Management (ALM) problem. ALM involves the management of risks that arise due to mismatches between the assets and liabilities. Stochastic optimization models focus on finding optimal investment decisions over a set of scenarios for the future returns on the assets and the liabilities of the company. Robust approach is introduced to minimize the risks that arise due to the estimation errors of uncertainty on asset returns and liabilities. Computational experiments using real data are presented to compare the performance of different formalizations of the problem.

 

 

Monday, 11:30 - 11:55 h, Room: H 3027, Talk 3

Giorgio Consigli
Institutional asset-liability management for a large P&C insurance company

Coauthors: Massimo di Tria, Vittorio Moriggia, Davide Musitelli, Angelo Uristani

 

Abstract:
We present an asset-liability manasgement problem for a large insurance company based on a real world development. A 10 year problem is formulated as a stochastic quadratic program with a multicriteria objective function based on short, medium and long term targets.
The investment universe includes fixed-income, real estate and equity investment plus alternative investments such as private equity, renewable energy, infrastructures and commodities with dedicated stochastic models.
Liabilities and insurance reserves are inflation adjusted and the management aims at controlling the risk exposure while achieving short and medium term goals withour jeopardising the long term business sustainability.

 

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