We will typically use gamma or generalized Pareto distributions to help us model severity. In operational risk this loss could be the value of customers lost due to a cyber breach, or suppliers failing to deliver critical goods and services resulting in unmet demand, or reputation with investors leading to a flight of capital. In credit this is the unrecoverable face value, accrued interest, and administrative expenses of a defaulted credit instrument such as a loan. Severity is defined as currency based loss. Here we will use a simplified sampling of frequencies of events drawn from a Poisson process similar to the one we used in credit risk measurement. Each transition probability stems from an average hazard rate of defaults in a unit of time and a segment of borrowers. The Poisson process is at the heart of Markov credit risks. Frequency of losses, modeled with a Poisson process. To do this we will start off with modeling potential loss in two dimensions, frequency of loss and severity. Now we need to consider more formally the impact of extreme, but rare events on financial performance. Then there is the probability of contagion that allows one bad market to infect other markets. Rare events can have strong and persistent effects. A common theme runs through this data and outcomes: thick tails, high Value at Risk and Expected Shortfall. Previously we studied the stylized facts of financial variables, market risk, and credit risk. To add insult to injury, employee turnover rates are over 40%. To seemingly top it all off, three VP’s of regional manufacturing have just been indicted for padding vendor accounts for kickbacks. Our major insurance carrier has also just pulled out of underwriting your fire-related losses. Not only that, but recent (5 years ago!) hurricane damage has still not been rectified. Remember that company we just acquired? Not only is customer creditworthiness apt to cost us another $80 million, but our walk-through of distribution, call-center, and production facilities had a raft of negatively impacting issues with health and safety, environmental, and intellectual property all located in places rife with fraud and corruption. 9.6 Now for Something Really Interesting.9.5 Simulate… again until Morale Improves….5.4.2 Try this exervise as we get down to business.
5.4.1 Gee, that’s very nonlinear of you….5.2.6 And now some more about that bond yield.4.3 Getting Caught in the Cross-Current.4.2.2 Now for somthing really interesting…again.
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