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  Econometric Modelling of the Nord Pool System Price
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Ophav

 Ophav:
Fenger, Anders1, Forfatter
Rahbek, Anders2, Vejleder
Tilknytninger:
1Det Samfundsvidenskabelige Fakultet, Københavns Universitet, København, Danmark, diskurs:7001              
2Økonomisk Institut, Det Samfundsvidenskabelige Fakultet, Københavns Universitet, København, Danmark, diskurs:7014              
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Indhold

Ukontrollerede emneord: Nord Pool, Electricity, Econometrics, SDE, Diffusion process, Jump-diffusion process, Ornstein-Uhlenbeck process, Merton process, Maximum Likelihood
 Abstract: The main purpose of the thesis is to model the Nord Pool system price using continuous-time stochastic processes which properly reflect the properties of the system price and to estimate the model on data.
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Bemærkninger:
-
Tilgængelighed:
Offentlig
Mime-type / størrelse:
application/pdf / 2MB
Copyright dato:
2012-02-18
Copyright information:
De fulde rettigheder til dette materiale tilhører forfatteren.
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Basal

Bogmærk denne post: https://diskurs.kb.dk/item/diskurs:24157:1
 Type: Speciale
Alternativ titel: Using Continuous-time Stochastic Processes
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Detaljer

Sprog: English - eng
 Datoer: 2011-09-13
 Sider: -
 Publiceringsinfo: København : Københavns Universitet
 Indholdsfortegnelse: Summary i
Preface v
1 Introduction 1
1.1 Nord Pool Electricity Market . 2
1.2 Literature 3
2 Stochastic Framework 4
2.1 Stochastic Processes 4
2.2 Information over Time . 5
2.3 Marginal Distributions . 7
2.4 Gaussian Distributions . 8
2.5 Time-discretizations 9
2.6 Vector Distributions 10
2.7 Stationarity . 12
2.8 Sample Statistics 13
2.9 References 15
3 Nord Pool System Price 16
3.1 General Properties . 16
3.2 Seasonality . 18
3.3 Price Changes 20
3.4 References 20
4 Diffusion Processes 22
4.1 Itô Processes 22
4.2 Ornstein-Uhlenbeck Process 25
4.3 Cox-Ingersoll-Ross Process . 28
4.4 Black-Scholes-Merton Process . 29
4.5 Modelling of Long Run Trends . 29
4.6 General Ornstein-Uhlenbeck Process . 32
4.7 Seasonal-OU Process 33
4.8 Simulation of Stochastic Processes . 34
4.9 Simulation of OU and CIR Processes . 36
4.10 Simulation of Seasonal-OU Process 38
4.11 References 38
5 MLE of Seasonal-OU Process 40
5.1 What Can Be Estimated? . 40
5.2 Maximum-likelihood Estimation 41
5.3 Seasonal-OU Process 44
5.4 Numerical Optimization 49
5.5 Seasonal-OU Process: Monte Carlo Experiment . 50
5.6 Estimation Results of Seasonal-OU Process 51
5.7 References 58
6 Jump-Diffusion Processes 59
6.1 Jump Processes . 59
6.2 Pure Jump Processes 60
6.3 Simulation of Pure Jump Processes 62
6.4 Merton Process . 65
6.5 OU-Jump Process 66
6.6 Merton & OU-Jump: Simulation . 68
6.7 Merton & OU-Jump: Monte Carlo Experiment 69
6.8 Merton & OU-Jump: Results of Estimation . 71
6.9 References 72
7 Conclusion 73
A Derivations 75
A.1 Factorization of Vector Density 75
A.2 Sample Cumulative Distribution Function 76
A.3 Ornstein-Uhlenbeck Process Derivations . 76
A.4 Black-Scholes-Merton Process Derivations 79
A.5 General OU Process Derivations 81
A.6 Seasonal-OU Process Derivations . 83
A.7 Merton Process: Transition Distribution . 87
A.8 OU-Jump Process: Transition Distribution 88
B Additional Plots & Tables 90
C Source Code 92
Bibliography 98
 Note: -
 Type: Speciale
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