July 22nd, 2007, 12:10 am
Assuming a 100% chance of default if the collateral drops below the loan value, then you want the probability that the commodity's value drops below the required level during the term of the loan. You can model this using techniques in stochastic calculus, models from options theory, or Monte Carlo sims of random walks. (you may need to resort to simulations if you need to model changes in the default level of collateral in response to payments on the loan.)But for simple situations in which: 1) you're willing to ignore the time-value-of-money for the collateral (i.e., that the amount of required collateral needs to grow during the life of the loan), 2) have a low chance of default and 3) involve commodities that you are willing to assume follow a normal distribution for price changes, you get a good first approximation by using volatility on the loan duration as your sigma and looking at the probability of the distribution being below the required level on the maturity date of the loan. This will slightly underestimate the probability of default because it will miss events in which the value of the commodities dropped below the default threshold but then rebounded. (Of course, one could say that this model overestimates chance of default because you wouldn't necessary expect 100% of borrows to default the instant the security deposit drops a penny below the required level -- some percentage of borrowers would make their margin calls.)