|
|
Enron Mail |
Comments from Rick Jones on the credit reserve model. Anita Dupont is setti=
ng=20 up a meet with Rick Jones to discuss these. Vince & Bill - if you want to= =20 join the meeting, please let me or Anita know. Regards, Krishna. ---------------------- Forwarded by Pinnamaneni Krishnarao/HOU/ECT on=20 04/11/2001 09:04 AM --------------------------- Richard B Jones@EES 04/10/2001 04:16 PM To: Pinnamaneni Krishnarao/HOU/ECT@ECT cc: =20 Subject: Credit Risk Model Comments - at this point. ---------------------- Forwarded by Richard B Jones/HOU/EES on 04/10/2001= =20 04:16 PM --------------------------- Richard B Jones 03/23/2001 05:53 PM To: Cheryl Lipshutz/HOU/EES@EES, Trushar Patel/Corp/Enron@Enron,=20 michelle.wenz@enron.com, Gayle Muench/ENRON@enronXgate, Jeremy=20 Blachman/HOU/EES@EES cc: =20 Subject: Credit Risk Model Comments - at this point. Hi everyone, I have run the model and, along with the contract briefs I have some=20 questions & ideas. I was hoping to talk to each of you so I could avoid=20 writing this detailed, one-sided e-mail, but with our schedules being so=20 exclusive, this will have to do for now. Every deal has its own model because of the commodity deal structure=20 complexity. So no aggregate results can be obtained without having the mode= ls=20 for each contract. However, the JC Penny=01,s version can serve as a testin= g=20 platform for some of the items I am mentioning below. I have not talked to= =20 the people in research who are the most knowledgeable about the model, so= =20 some of these comments may be mute points. I plan to do that went I get bac= k.=20 1) Since the credit risk is developed for a time period, it makes sense to= =20 regularly update the commodity data (and credit rating if its chaged) and= =20 re-run the model for the time remaining. I would expect this is done alrea= dy. 2) The default probabilities seem not to change. That is, if the input cred= it=20 rating is E1, then the E1 default probability curve is used for the contrac= t=20 period. For annual accounting that seems OK, but in MTM, it seems to me tha= t=20 the credit analysis needs to take into consideration the credit rating=20 transition probabilities. That is, the credit implications of companies=20 changing their credit rating during the contract period. with some=20 constraints imposed by actually slow credits appear to change would give a= =20 more realistic view of our credit risk in the MTM world. 3) Are all "defaults" created equal to us? Look at OC. It seems to me that= =20 the data used to develop the default probabilities are over different=20 business segments and are OK ----for that range of companies. However, we a= re=20 dealing with specific types of firms where "default" may not mean we do not= =20 get paid. Sure we still have some credit risk, but it=01,s not like Montgom= ery=20 Ward=01,s where the lights are being turned off for good. Energy is so=20 fundamental for a company=01,s success and default actions can be used as a= way=20 to save a company albeit in a different form. So financial default does no= t=20 neccesarily mean default for EES commodity payments totally. 4) A while back someone said to me that may, maybe the people who reach for= a=20 life preserver are more likely to live than those that don=01,t. By that I = mean=20 that, perhaps our use of these default probabilities actually overstates th= e=20 credit risk in that if a company has at least enough proactive vision to=20 contract EES, then they are more likely to improve that one that doesn=01,t= .=20 This is a type of behavioral variable that the data doesn=01,t consider. Th= is=20 would be a useful MBA project to examine these types of corporate variables= =20 and compare it to their credit rating forward curve. 5) This leads me to something I hope we can acomplish in the special financ= e=20 team. The contract briefs are, to me, the begimnning of this exercise. If = we=20 can combine our customers into "exposure group portfolios" (for lack of a= =20 better term), where a group has similar "risk characteristics" beyind the= =20 current parameter set, that we define, then this offers a potential to shop= =20 some of these exposure to specialized insurance markets. 6) A technical point. Monte Carlo simulations are numerical experiments.=20 Besides the model assumptions, numerical experiments have three inherent=20 error attributes; the number of trials, numerical roundoff, and random numb= er=20 generator randomness statistical properties. The first two are not a proble= m=20 in this application but the last one could be. Has anyone examined the effe= ct=20 of using different random number generators on Enron=01,s aggregate credit = risk? 7) There is one last point here. For most of the above points, the "improve= d"=20 analysis could make the credit risk be higher.=20 Rick=20
|