[ENERGY DERIVATIVE]

by

Acknowledgement

I would take this opportunity to thank my research supervisor, family and friends for their support and guidance without which this research would not have been possible.

DECLARATION

I, [type your full first names and surname here], declare that the contents of this dissertation/thesis represent my own unaided work, and that the dissertation/thesis has not previously been submitted for academic examination towards any qualification. Furthermore, it represents my own opinions and not necessarily those of the University.

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Table of Contents

CHAPTER 1: INTRODUCTION5

Background of the Study5

Thesis Statement7

CHAPTER 2: LITERATURE REVIEW8

Energy products8

Natural Gas8

Oil10

Electricity13

Spreads15

Spark spread15

Characteristics of energy prices17

Distribution17

Spikes18

Mean reversion19

Volatility19

Modeling spot price processes20

Brownian motion21

Geometric Brownian motion22

Regime switching models23

Swings, Recalls, and Nominations24

Swings24

Different types of electricity financial and physical instrument25

Electricity forwards, futures and swaps26

Electricity forwards26

Electricity futures26

Electricity swap28

Electricity options28

Financial derivatives on electricity transmission capacity29

CHAPTER 3: ANALYTICAL STUDY30

Data Analysis30

Seasonality31

Initial Model33

Parameter Estimation35

Ordinary Least Squares Regression35

Spot Prices with Jumps36

Model Specification36

Discussion37

CHAPTER 4: STATISTICAL STUDY41

Formulation of the ES/IS Method for Calculating Conformational Free Energy41

Implicit Continuum Model of Solvent42

CHAPTER 5: CONCLUSION44

REFERENCES45

CHAPTER 1: Introduction

Energy has become one of the most traded commodities after the deregulation in the oil and natural gas industries in the 1980s, followed by the deregulation in the electricity industry in the 1990s. Until then the prices were set by regulators, i.e., governments. Energy prices were relatively stable, but consumers had to pay high premier for inefficient costs, e.g., complex cross-subsidies from areas with surpluses to areas with shortages or inefficient technology. Due to the deregulation a free market with more competitive prices arose that revealed that energy prices are the most volatile among all commodities. This exposed both energy producers and consumers to many financial risks. As the financial risks stem from the different interesting characteristics displayed in price processes of the energy market, we need to account for these characteristics when we are trying to model the consisting price processes. Worth knowing is that it is these characteristics that distinguish the energy market from others. The characteristics that are being referred to are

Spikes;

Mean reversion;

High Volatility.

Background of the Study

It is also important to note that the price distributions portray pronounced skewness and kurtosis. This is helpful when choosing a mathematical model to describe a certain price process. Most common models tend to use the Normal distribution as the underlying distribution, but that leads to erroneous conclusions with respect to energy prices. We thus need to look for models with realistic price distributions that are able to capture the market's characteristics if we want to correctly model the price processes. We also need to distinguish between different products and analyze which characteristics hold for the prices of that particular product. As with all modeling attempts it is very important to closely look at and understand the process that we want to model in order to find the appropriate model. It is well known that the energy market is very complicated and hard to model correctly, referring to the price processes. New models are probably being developed at the very moment that you are reading this ...