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Enron Mail |
Julie,
The introduction looks fine. I have made some cosmetic changes (typos and split infinitives that slipped by). You can safely ignore most o= f=20 them. English is not even my second language. The corrections are in pink. Vince "Julie" <julie@lacima.co.uk< on 08/01/2000 07:43:10 AM To: "VinceJKaminski" <Vince.J.Kaminski@enron.com< cc: =20 Subject: Preface for book Vince, ? Hope you are well. ? We spoke a while ago about who should write the preface for the book, and = =20 you kindly offered that you would provide this.? Is this still possible?? = We=20 realise that you are extremely busy, so Chris and Les went ahead and wrote= =20 something, which is below, and if you want to review, change or re-write?t= he=20 preface, that would be very appreciated.? Let me know what your thoughts a= re. ? Thanks, Julie (we're getting close) ? ?=20 Preface ? ? ? One of our main objectives in writing Energy Derivatives: Pricing and Risk= =20 Management has been to bring together as many of the various approaches fo= r=20 the pricing and risk management energy derivatives as possible, to discuss= =20 in-depth the models, and to show how they relate to each other.? In this = =20 way we hope to help the reader to analyse the different models, price a wid= e =20 range of energy derivatives, or to build a risk management system which use= s=20 a consistent modelling framework.? We believe that for practitioners this= =20 last point is very important and we continue to stress in our articles and= =20 presentations the dangers of having flawed risk management and giving=20 arbitrage opportunities to your competitors by using ad-hoc and inconsiste= nt=20 models for different instruments and markets (see also OTHERS WHO PROPOSE= =20 CONSISTENT MODELS?).? However, it is not our wish to concentrate on one= =20 particular model or models, at the exclusion of the others because we=20 believe that the choice should rest with the user (although it will probab= ly=20 be clear from our discussions the model(s) we prefer).? We therefore try a= nd=20 give as clear account as possible of the advantage and disadvantages of al= l=20 the models so that the reader can make an informed choice as to the models= =20 which best suit their needs. ? In order to meet our objectives the book is divided into 11 chapters.? In= =20 chapter 1 we give an overview of the fundamental principals needed to mode= l=20 and price energy derivatives which will underpin the remainder of the book= .?=20 In addition to introducing the techniques that underlie the Black-Scholes= =20 modelling framework we outline the numerical techniques of trinomial trees= =20 and Monte Carlo simulation for derivative pricing, which are used througho= ut=20 the book. ? In Chapter 2 we discuss the analysis of spot energy prices.? As well as= =20 analysing empirical price movements we propose a number of processes that= =20 can be used to model the prices.? We look at the well-know process of=20 Geometric Brownian Motion as well as mean reversion, stochastic volatility= =20 and jump processes, discussing each and showing how they can be simulated= =20 and their parameters estimated. ? Chapter 3, written by Vince Kaminski, Grant Masson and Ronnie Chahal of=20 Enron Corp., discusses volatility estimation in energy commodity markets.?= =20 This chapter builds on the previous one.? It examines in detail the methods= , =20 merits and pitfalls of the volatility estimation process assuming different= =20 pricing models introduced in chapter 2.? Examples from crude, gas, and=20 electricity markets are used to illustrate the technical and interpretativ= e=20 aspects of calculating volatility. ? Chapter 4 examines forward curves in the energy markets.? Although such= =20 curves are well understood and straight-forward in the most financial =20 markets, the difficulty of storage in many energy markets leads to less wel= l =20 defined curves.? In this chapter we describe forward price bounds for ener= gy=20 prices and the building of forward curves from market instruments.? We =20 outline the three main approaches which have been applied to building=20 forward curves in energy markets; the arbitrage approach, the econometric= =20 approach, and deriving analytical values by modelling underlying stochasti= c=20 factors. ? Chapter 5 presents an overview of structures found in the energy derivativ= e=20 markets and discusses their uses.? Examples of products analysed in this = =20 chapter include a variety of swaps, caps, floors and collars, as well as=20 energy swaptions, compound options, Asian options, barrier options, lookba= ck=20 options, and ladder options. ? Chapter 6 investigates single and multi-factor models of the energy spot= =20 price and the pricing of some standard energy derivatives.? Closed form = =20 solutions for forward prices, forward volatilities, and European option=20 prices both on the spot and forwards are derived and presented for all the= =20 models in this chapter including a three factor, stochastic convenience=20 yield and interest rate model. ? Chapter 7 shows how the prices of path dependent and American style option= s=20 can be evaluated for the models in Chapter 6.? Simulation schemes are =20 developed for the evaluation of European style options and applied to a=20 variety of path dependent options.? In order to price options which=20 incorporate early exercise opportunities, a trinomial tree scheme is=20 developed.? This tree is built to be consistent with the observed forward= =20 curve and can be used to price exotic as well as standard European and=20 American style options. ? Chapter 8 describes a methodology for valuing energy options based on=20 modelling the whole of the market observed forward curve.? The approach=20 results in a multi-factor model that is able to realistically capture the= =20 evolution of a wide range of energy forward curves.? The user defined=20 volatility structures can be of an extremely general form.? Closed-form=20 solutions are developed for pricing standard European options, and efficie= nt=20 Monte Carlo schemes are presented for pricing exotic options.? The chapter= =20 closes with a discussion of the valuation of American style options. ? Chapter 9 focuses on the risk management of energy derivative positions.? = =20 In this chapter we discuss the management of price risk for institutions = =20 that trade options or other derivatives and who are then faced with the=20 problem of managing the risk through time.? We begin with delta hedging a= =20 portfolio containing derivatives and look at extensions to gamma hedging = =01)=20 illustrating the techniques using both spot and forward curve models.? The= =20 general model presented in Chapter 8 is ideally suited to multi-factor=20 hedging of a portfolio of energy derivatives and this is also discussed. ? Chapter 10 examines the key risk management concept of Value at Risk (VaR)= =20 applied to portfolios containing energy derivative products.? After =20 discussing the concept of the measure, we look at how the key inputs =20 (volatilities, covariances, correlations, etc) can be estimated.? We then= =20 compare the fours major methodologies for computing VaR; Delta, Delta-gamm= a,=20 historical simulation and Monte-Carlo simulation, applying each to the sam= e=20 portfolio of energy options.? In this chapter we also look at testing the= =20 VaR estimates for various underlying energy market variables. ? Finally, in Chapter 11 we review modelling approaches to credit risk.? We= =20 look in detail at two quite different approaches, CreditMetrics (J. P. Morg= an=20 (1997)) and CreditRisk+ (Credit Suisse Financial Products (1997)) for whi= ch=20 detailed information is publicly available.? Together these provide an=20 extensive set of tools with which to measure credit risk.? We present=20 numerical examples of applying these techniques to energy derivatives. ? Before we begin we stress that the models and methods we present in this= =20 book are tools which should be used with the benefit of an understanding o= f=20 how both the =01+tool=01, and the market works.? The techniques we descri= be are=20 certainly not =01&magic wands=018 which can be waved at data and risk mana= gement=20 problems to provide instant and perfect solutions.? To quote from the=20 RiskMetrics Technical Document =01&=01( no amount of sophisticated analyti= cs will=20 replace experience and professional judgement in managing risk.=018.? How= ever,=20 the right tools, correctly used make the job a lot easier!
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