Mortgages and Markov chains: a simplified evaluation model
Management Science
WSC '94 Proceedings of the 26th conference on Winter simulation
Experimental designs for system assessment and improvement when noise factors are correlated
WSC '94 Proceedings of the 26th conference on Winter simulation
Design of experiments: robust design: seeking the best of all possible worlds
Proceedings of the 32nd conference on Winter simulation
A decision support methodology for stochastic multi-criteria linear programming using spreadsheets
Decision Support Systems
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We use simple orthogonal and non-orthogonal designs to analyze a multi-tiered model for forecasting performance of a large-scale home mortgage portfolio. The experiments are used to assess the sensitivity of performance to projected changes in economic conditions as well as the sensitivity of the model to coefficients estimated from historical data. Our results attribute the variation in loan performance to variation in individual factors or factor combinations, indicating which are crucial to monitor or forecast accurately. The results are at times counter-intuitive, indicating the benefits of a systematic approach to sensitivity assessment and scenario generation.