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Economic Scenario Generator

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Economic Scenario Generator
On Constructing a Market Consistent Economic Scenario Generator
Ebba K. Baldvinsdóttir & Lina Palmborg March 4, 2011

Abstract
Recently the insurance industry has started to realise the importance of properly managing options and guarantees embedded in insurance contracts. Interest rates have been low in the last few years, which means that minimum interest rate guarantees have moved from being far out-of-the money to expiring inthe-money. As a result, many insurance companies have experienced solvency problems. Furthermore, insurance rms operating within the European Union will, from the end of 2012, be subject to the Solvency II directive, which places new demands on insurance companies. For example, the valuation of assets and liabilities now needs to be market consistent. One way to accomplish a market consistent valuation is through the use of an economic scenario generator (ESG), which creates stochastic scenarios of future asset returns. In this thesis, we construct an ESG that can be used for a market consistent valuation of guarantees on insurance contracts. Bonds, stocks and real estate are modelled, since a typical insurance company 's portfolio consists of these three assets. The ESG is calibrated to option prices, wherever these are available. An Otherwise the calibration is based on an analysis of historical volatility.

assessment of how well the models capture prices of instruments traded on the market is made, and nally the ESG is used to compute the value of a simple insurance contract with a minimum interest rate guarantee.

Acknowledgements
We would like to thank Handelsbanken Liv for making this thesis possible. Special thanks to Tobias Lindhe, our supervisor at Handelsbanken Liv, and our supervisor Boualem Djehiche at the Division of Mathematical Statistics at KTH for their guidance and support. We would also like to thank Fredrik Bohlin, Maja Ernemo, Rikard Kindell, Björn Laurenzatto and Jonas Nilsson for their helpful feedback



Bibliography: [1] Björk, T. (2009) Press. [2] Black, F & Karasinski, P. (1991) Bond and Option Prices when Short Rates are Lognormal. [3] Black, F & Scholes, M. (1973) The Pricing of Options and Corporate Liabilities. [4] Booth, P. (2001) Unsmoothing Real Estate Returns: How Should it Affect Pension Plan Asset Allocation? Research Paper No 2001.06. [5] Brigo, D. & Mercurio, F. (2010) Heidelberg New York. [6] CEIOPS (2009) Real Estate Finance and Investment. [7] CEIOPS (2009) Summary of Comments on CEIOPS-CP-39/09, Consultation Paper on the Draft L2 Advice on TP - Best Estimate, CEIOPS [8] CEIOPS (2010) QIS5 Risk-Free Interest Rates - Extrapolation Method. [12] European Commission (2010) QIS5 Technical Speci [16] Fleten S.-E. & Lindset, S. (2004) Optimal hedging strategies for multiperiod guarantees in the presence of transaction costs: A stochastic programming approach. [17] Geltner, D. (1993) Estimating Market Values from Appraised Values without Assuming an E cient Market [18] Grosen, A. & Jörgensen, P.L. (2000) Fair valuation of life insurance liabilities. The impact of interest rate guarantees, surrender options and bonus policies. [19] Hull, J. (2009) Options, Futures, and Other Derivatives Pearson Prentice Hall, Upper Saddle River, New Jersey. [20] Hull, J. & White, A. (1990) Pricing Interest Rate Derivative Securities. [21] Hull, J. & White, A. (1993) One-Factor Interest Rate Models and the Valuation of Interest Rate Derivative Securities. [22] Hull, J. & White, A. (1994) Branching Out, Risk [23] Jamshidian, F. (1989) An Exact Bond Option Pricing Formula.

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