Message-ID: <33344220.1075857010404.JavaMail.evans@thyme> Date: Tue, 15 Feb 2000 03:28:00 -0800 (PST) From: chris_strickland@compuserve.com To: grant_masson@ei.enron.com, vince.kaminski@enron.com Subject: Energy Book Mime-Version: 1.0 Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit X-From: Chris Strickland X-To: Grant Masson , Vince J Kaminski X-cc: X-bcc: X-Folder: \Vincent_Kaminski_Jun2001_9\Notes Folders\Australia X-Origin: Kaminski-V X-FileName: vkamins.nsf Hi Grant, Hope all is well with you. I trust you got my message via the voicemail that Ileft with Vince late Friday afternoon about my inability to travel - I'm trying to rearrange my trip for a couple of week's time when my ear has cleared up, and I look forward to meeting with you one day. I wrote to Vince last week asking for a favour, but I'm not sure ifhe is there in Houston. I know that you guys are probably very busy but I was wondering if you can write a few sentences for me. I'm sending out some sample chapters to the people who responded positively (all of them!) to my request for some feedback on the book. Chapter 1 has an 'overview' of the book with just a couple of sentences on each chapter. Could you please write a sentence or two for your chapter? I'm including what I have already written (although I think it has changed slightly from this version) so that you can see the style. Many thanks and best regards. Chris. 2 Overview of this Book This book aims to provide an in-depth understanding of the pricing and risk management of energy derivatives. In the remainder of this chapter we give an overview of the fundamental principals needed to model and price energy assets, and which underlie the rest of the book. As well as introducing the techniques that underlie the Black-Scholes modelling framework we discuss the numerical techniques of trinomial trees and Monte Carlo simulation for derivative pricing which are used extensively later in the book. In Chapter 2 we analyse spot energy prices. Apart from describing empirical prices we propose a number of processes that can be used to model the prices. We look at the well-know process of GBM as well as mean reversion, stochastic volatility and jump processes, discussing each, and showing how they can be simulated and their parameters estimated. Chapter 3, written by Vince Kaminski and Grant Masson of Enron Capital and Trade . Chapter 4 examines forward curves in the energy markets. Although such curves are well understood and straight forward in the world debt markets the difficulty of storage in many energy markets leads to less well defined curves. What we do in this chapter Chapter 5 presents an overview of the common and not-so-common derivative structures in the energy markets and discusses their uses. Examples of products analysed in this chapter include a variety of swaps, caps, floors and collars, as well as energy swaptions, compound options, Asian (or average rate) options, Barriers, lookbacks, and ladder options. Chapter 6 investigates single and multi-factor models of the energy spot price and the pricing of some standard energy derivatives. Closed form solutions for forward prices, forward volatilities, and European option prices are derived and presented for all the models in this chapter including a three factor stochastic convenience yield and interest rate model with jumps. Chapter 7 shows how the prices of path dependent and American style options can be evaluated for the models in chapter 6. Simulation schemes are developed for the evaluation of European style options and applied to a variety of path dependent options. In order to price options which incorporate early exercise opportunities, a trinomial tree scheme is developed. This tree is built to be consistent with the observed forward curve and can be used to price exotic as well as standard American style options. Chapter 8 develops a new methodology for valuing energy options based on modelling the market observed forward curve. The approach results in a multi-factor model that is able to capture realistically the evolution of a wide range of energy forward curves and where the user defined volatility structures can be of an extremely general form. Closed-form solutions are developed for pricing standard European options and efficient Monte Carlo schemes for exotic options. The chapter finishes with a discussion of the valuation of American style options. Chapter 9 focuses on the risk management of energy derivative positions. In this chapter we discuss the management of price risk for institutions that sell options or other derivatives to a client and who is then faced with the problem of managing the risk through time. We begin with delta hedging a portfolio containing derivatives and look at extensions to gamma hedging - using the models from chapters 5 and 7. The general model of chapter 7 ideally suited to multi-factor hedging and this is also discussed. Chapter 10 looks at the key risk-management concept of Value at Risk applied to portfolios containing energy derivative portfolios. After discussing the concept of the measure, we look at how the key inputs (volatilities, covariances, correlations, etc) can be estimated. We then compare the fours major methodologies for computing VaR; Delta, Delta-gamma, historical simulation and Monte-Carlo simulation. Finally, we look at testing the VaR estimates for various underlying energy market variables.