© 2000 John Petroff

6)- Using simulations to assess potential default

What would be far more desirable than measuring size of debt, earnings volatility, expense coverage or any other parameter at any given point in time, is to know how likely is a major decline in earning, . The complexity of forecasting earnings and current obligations will be examined in Chapter 12 and Chapter 13. A simpler approach, limited to an evaluation of potential for default, can be conducted on the basis of the financial statements as they are given. The numbers can be entered as is in a spreadsheet, then critical variables can be changed as needed. Most commonly, sales would be modified according to expectations based on economic and industry information. Other key unknowns are prices of essential raw materials, as well as interest rates. Table T-11.2, Table T-11.3 and Table T-11.4 where sales have been modified by 5%, 10% and 15% from the initial values in Table T-11.1 , are examples of such simulation.

An improvement is possible if a probability distribution can be assigned to the likely values of the modified variable. For instance, knowledge of economic conditions and industry circumstances would be indicative of the likelihood of different sales levels. With the probability distribution of sales, a Monte Carlo simulation (discussed in Chapter 5) would generate a probability distribution of earnings from which an expected value can be calculated, and the likelihood of default can be assessed more accurately than on the basis of current financial results alone. Naturally, the quality of the simulation results is entirely dependent on the soundness of the assumptions about the economy, the industry and what management can and will do, which are the subjects of the last four chapters.

See review questions Q-11C6.1 and Q-11C6.2.