This book introduces empirical methods for analyzing energy markets. Even beginners in econometrics and mathematical finance must be able to learn how to utilize these methodologies and how to interpret the analysis results. This book provides some example analyses of the North American, European, and Asian energy markets. The reader will experience some theories and practices of energy trading and risk management. This book reveals the characteristics of energy markets using quantitative analyses. Examples include unit root, cointegration, long-term equilibrium, stochastic arbitrage simulation, multivariate generalized autoregressive conditional heteroscedasticity (GARCH) models, exponential GARCH (EGARCH) models, optimal hedge ratio, copula, value-at-risk (VaR), expected shortfall, vector autoregressive (VAR) models, vector moving average (VMA) models, connectedness, and frequency decomposition. This book is suitable for people interested in the empirical study of energy markets and energy trade.
Author(s): Tadahiro Nakajima, Shigeyuki Hamori
Series: Kobe University Monograph Series in Social Science Research
Publisher: Springer
Year: 2022
Language: English
Pages: 144
City: Singapore
Acknowledgements
Contents
About the Authors
List of Figures
List of Tables
1 Preface
References
2 Arbitrage Trading in Energy Markets and Measuring Its Risk
2.1 Introduction
2.2 Data and Preliminary Analyses
2.2.1 Descriptive Statistics
2.2.2 Stationarity and Unit Root Test
2.2.3 Cointegration Test
2.2.4 Long-Term Equilibrium Estimation
2.3 Trading Strategies
2.3.1 Arbitrage Between Own Spot Spread and Future Spread
2.3.2 Statistical Arbitrage
2.4 Simulation Results
2.5 Risk Measurement in Statistical Arbitrage
2.5.1 Value-At-Risk and Expected Shortfall
2.5.2 Copula
2.5.3 Copula Estimation and Risk Measurement
2.6 Concluding Remarks
References
3 Fuel Market Connectedness and Fuel Portfolio Risk
3.1 Introduction
3.2 Data
3.2.1 Crude Oil
3.2.2 Natural Gas
3.3 Methodology
3.3.1 Connectedness Index (Diebold and Yilmaz [4])
3.3.2 Spectral Decomposition (Baruník and Křehlík [1])
3.3.3 EGARCH Volatility Series Estimation
3.4 Analysis Results
3.4.1 Crude Oil
3.4.2 Natural Gas
3.5 Concluding Remarks
References
4 Hedging Strategy with Futures Contracts
4.1 Introduction
4.2 Data
4.3 Optimal Hedge Ratio and Hedge Effectiveness
4.4 Multivariate GARCH Model
4.4.1 Diagonal VECH Model
4.4.2 Diagonal BEKK Model
4.4.3 CCC Model
4.5 Analysis Results
4.5.1 HH Market
4.5.2 NBP Market
4.6 Concluding Remarks
References
5 Market Risk of a Power Generation Business
5.1 Introduction
5.2 Methodology
5.3 Data and Preliminary Analyses
5.3.1 Price Series
5.3.2 Return Series
5.3.3 Volatility Series
5.4 Analysis Results
5.4.1 Return Series
5.4.2 Volatility Series
5.4.3 Risk Measurement
5.5 Concluding Remarks
References
6 Alternative to Postface: Market Risk Transfer in Power Companies
References
Index
