Explanation:
There are very few historical observations on which to base our estimates. A model is only as good as the input data. Due to a lack of credible historical data on extreme events (some of which have never occurred but can still occur), practitioners formulate assumptions. Unfortunately, some of the assumptions are normally out of sync with the reality, meaning the resulting estimates are also unreliable. For example, an incorrect assumption regarding the distribution of a certain phenomenon might correctly model central observations but fail to come up with reliable estimates of extreme observations.
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Q.2176 Modeling extreme events in various fields, particularly in finance and risk management, often presents a significant challenge. This difficulty arises primarily due to certain factors that hinder the effective modeling of these events. What is the primary reason why modeling extreme events is typically difficult and problematic?
A
A lack of models that can estimate the effects of certain extreme but possible events.
B
A lack of qualified personnel to oversee the modeling process.
C
A lack of credible, reliable input data.
D
The fact that extreme event modeling requires a considerable investment of time and expertise.