Energy trading and risk management : commentary on arbitrage, risk measurement, and hedging strategy
Author(s)
Bibliographic Information
Energy trading and risk management : commentary on arbitrage, risk measurement, and hedging strategy
（Kobe University monograph series in social science research / series editor, Takashi Yanagawa）
Springer, c2022
Available at 1 libraries
Note
Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
Chapter 1. Introduction
Chapter 2. Arbitrage Trading in Energy Market and Risk Measurement
2.1 Background
2.2 Data and Preliminary Analyses
2.3 Trading Strategies
2.4 Simulation Results
2.5 Risk Measurement in Statistical Arbitrage
2.6 Concluding Remarks
Chapter 3. Fuel Markets Connectedness and Fuel Portfolio Risk
3.1 Background
3.2 Data
3.3 Methodology
3.4 Results of Analysis
3.5 Concluding Remarks
Chapter 4. Hedging Strategy with Futures Contracts
4.1 Background
4.2 Data
4.3 Methodology
4.4 Results
4.5 Concluding Remarks
Chapter 5. Investing in a portfolio consisting of energies and related commodities
5.1 Background
5.2 Data
5.3 Methodology
5.4 Results
5.5 Concluding Remarks
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