Monte Carlo scenario generation for retail loan portfolios

Monte Carlo simulation is a common method for studying the volatility of market traded instruments. It is less employed in retail lending, because of the inherent nonlinearities in consumer behavior. In this paper, we leverage the approach of Dual-time Dynamics to separate loan performance dynamics into three components: a maturation function of months-on-books, an exogenous function of calendar date, and a quality function of vintage origination date. Of these three, the exogenous function captures the impacts from the macroeconomic environment. As such, we might naturally want to generate scenarios for the possible futures of these environmental impacts. To generate such scenarios, we must go beyond the random walk methods most commonly applied in the analysis of market-traded instruments. Retail portfolios exhibit autocorrelation structure and variance growth with time that requires more complex modeling than a random walk. This paper describes work using ARMA and ARIMA models for s...

• Type: Journal
• Year: 2010
• Where: JORS
• Authors: J. L. Breeden, D. Ingram
• Keywords: JORS 2010, Monte Carlo, Monte Carlo Simulation, Scenarios