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Asset Liability Management using stochastic programming --Mehndi Pirbhai

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Many financial systems in the corporate as well as individual context are underpinned by a cash flow balancing (also called matching) activity. At an individual level typically a young professional may set up savings (assets) after child birth suitably invested in bonds and shares to meet future payment for school fees (liabilities).  At a corporate level many institutions take contributions from working and invest in assets. These assets are pledged to meet the pension liabilities to the individuals during their retirement.  A basic aspect of financial planning encompasses such matching activities of cash flows and is given the generic label: Asset and Liability Management or in short ALM.

In all real-world planning problems, optimum plans cannot be made in a deterministic way since the asset prices and the liabilities are not known with certainty in the future. Under these circumstances optimum allocation models and models of randomness are brought together to compute the possible future prices and liabilities.  This combined paradigm of models is often known as the stochastic optimisation models. Using such SP models, it is possible to compute hedged decisions which may not be the best for any one realisation of the future but is robust in respect of different realisation of the future.

In the finance world, volatility of asset prices and uncertain liabilities clearly lead to possible financial loss or in other words financial risk. Given that, there are various complex financial products being traded in the markets and over-the-counter, not only has it become much harder to assess the potential risks of some of these stand-alone products but also the problem of integrating these risks in the risk management system has arisen.

The new concept of integrated ALM is more focused on integrating the various facets in order to ascertain the uncertainty of the future business environment, and to generate profitable strategies by structuring the assets and liabilities of the business line across a series of alternative future scenarios. In fact, some interesting soft wares are created to cater the need of this niche market.

This white paper sets out to explain ALM.  It discusses why in practice, optimum planning models are used. The development of integrated approach which combines liability models with that of asset allocation decisions incorporating uncertainty and quantification of risk is analyzed.  Brief discussion on various software tools available in the market is included at the end.  This white paper will be of interest to corporate treasurers, to fund managers in the pension & insurance industry, and to analysts who support ALM models in different financial institutions.

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