Critical Analysis of Stochastic Optimization Models with Reference to Assets and Liabilities Management

Abstract

Stochastic modelling is a form of financial model that is used to help make investment decisions. This type of modelling forecasts the probability of various outcomes under different conditions, using random variables. Stochastic modelling presents data and predicts outcomes that account for certain levels of unpredictability or randomness. Companies in many industries can employ stochastic modelling to improve their business practices and increase profitability. In the financial services sector, planners, analysts, and portfolio managers use stochastic modelling to manage their assets and liabilities and optimize their portfolios. The purpose of this  research article is to provide a snapshot of the field of Asset Liability Management (ALM) from a theoretical and modelling perspective. Asset-Liability Management has grown considerably complex making use of advanced mathematical techniques and computation. Stochastic programming seems intuitively the best choice out of the available ALM techniques for strategic asset liability management. This approach helps in multi-period investment decisions, portfolio rebalancing and accommodating uncertainty by examining few economic states in he future. This study provides an overview of the evolution of ALM from the idea of asset-liability matching to sophisticated techniques like stochastic programming. This research study has given an insight to the new researchers and ALM practitioners in corporate finance and in other business entities to easily understand the application of the models used in asset liability management.