By Gautam Mitra, Katharina Schwaiger
Fresh years have proven a rise in improvement and attractiveness of quantitative equipment for asset and legal responsibility administration innovations. This booklet offers cutting-edge quantitative determination types for 3 sectors: pension cash, insurance firms and banks, considering new laws and the industries dangers.
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Extra resources for Asset and Liability Management Handbook
Stacy, M. Sylvanus, A. L. Turner, K. Watanabe and W. T. Ziemba. ‘The Russell-Yasuda Kasai model: An asset/liability model for a Japanese insurance company using multistage stochastic programming’. Interfaces, 24(1):29–49, 1994. Consigli, G. and M. A. H. Dempster. ‘Dynamic stochastic programming for asset-liability management’. Annals of Operations Research, 81:131–162, 1998. , F. Cocco and S. A. Zenios. ‘The Prometeia model for managing insurance policies with guarantees’. Handbook of Asset and Liability Management, Handbooks of Finance.
15 Asset-Liability Management in Defined Contribution Pensions: A Stochastic Model with Reference to Auto Choice Portfolios in the New Pension System in India Hira Sadhak and Steward Doss In this chapter we examine the implication of asset liability management (ALM) in a defined contribution pension plan where investment risks are transferred to the members of the fund. An ALM model has been developed with the help of Monte Carlo simulation, and future liability and cash flow have been projected, which can guide the fund managers to design an appropriate asset allocation and reallocation strategy for managing an auto choice life-cycle fund under the investment regulation norms.
We present a generic ALM problem cast as an LDI, which we represent through a family of four decision models: a deterministic linear programming model, a two-stage stochastic programming (SP) model incorporating uncertainty, a chance-constrained SP model and an integrated chance-constrained SP model. In the deterministic model, we study the relationship between PV01 matching and the required funding. In the model, we have two sources of randomness: liabilities and interest rates. We generate interest rate scenarios using the Cox, Ingersoll and Ross model and investigate the relationship between funding requirements and minimize the absolute deviation of the present value matching of the assets and liabilities over time.
Asset and Liability Management Handbook by Gautam Mitra, Katharina Schwaiger