Model risk is if the model used is not appropriate. For eg using a binomial distribution for mortality instead of a normal distribution (okay not the best example)
Hope this illustrates random fluctuations risks:
Suppose investment returns in the past 12 months were
10%, 10%, -25%, 10%, 10%, ...., 10%
What would be an appropriate estimate of future investment returns?
One approach, take the average including the -25%.
Another approach would be take the average but ignore the -25%. This would be reasonable because the -25% for that month would have been due to a one-off factor (not likely to occur again/ cannot be predicted with any certainty) and not an indicator of future trend in investment return.
Now finally, suppose you had extended this investigation to the last 120 months and if the investment returns were still 10% except that one -25%, it would not make a big difference whether or not you included or ignored the -25% investment return in working out the average as an estimate. The average would still be 10% or close to it.
If this does still not help, then it may be a bit too late to try and understand it. Good luck anyway.
Last edited by a moderator: Sep 23, 2009