Message-ID: <30381563.1075856493877.JavaMail.evans@thyme> Date: Tue, 11 Jul 2000 07:55:00 -0700 (PDT) From: vince.kaminski@enron.com To: vkaminski@aol.com Subject: Re: EFA meetings Mime-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit X-From: Vince J Kaminski X-To: Vkaminski@aol.com X-cc: X-bcc: X-Folder: \Vincent_Kaminski_Jun2001_3\Notes Folders\Sent X-Origin: Kaminski-V X-FileName: vkamins.nsf ---------------------- Forwarded by Vince J Kaminski/HOU/ECT on 07/11/2000 02:59 PM --------------------------- Tom Arnold on 07/11/2000 12:32:27 PM To: Vince.J.Kaminski@enron.com cc: Subject: Re: EFA meetings Hey Vince, Thanks for your reply. I'll see what becomes of the session and keep you informed. As to the paper, Tim Crack and I have a revised version of the paper I gave you. We have since found out that by using certainty equivalence, our model is more robust. For example, if one has an asset pricing model that incorporates mean, variance, and skewness (Harvey and Siddique, JF June, 2000) and a binomial model that incorporates mean, variance, and skewness (Johnson, Paulukiewicz, and Mehta, RQFA, 1997), our model allows you to price options under the real world measure. The benefit is that one can take all of the model parameters from historical data that is non-risk neutralized. From a pricing perspective, there isn't a tremendous benefit in a mean-variance world (variance stays the same in risk neutral or risky measure). However,in the mean-variance-skewness world, there is a benefit because we do not believe (although we're still hunting down an appropriate cite) skewness is the same under risk-neutral and risky measure. Given we can only measure the skewness in our risky world, our model becomes much more significant. I would certainly appreciate comments on the version of the paper you have and would also pass on the new version of the paper if you would like to see it. Thanks again, Tom