Chevallier | Econometric Analysis of Carbon Markets | Buch | sack.de

Chevallier Econometric Analysis of Carbon Markets



The European Union Emissions Trading Scheme and the Clean Development Mechanism

2012, 217 Seiten, Kartoniert, Previously published in hardcover, Format (B × H): 157 mm x 236 mm, Gewicht: 385 g
ISBN: 978-94-007-9666-9
Verlag: Springer Netherlands


Chevallier Econometric Analysis of Carbon Markets

Through analysis of the European Union Emissions Trading Scheme (EU ETS) and the Clean Development Mechanism (CDM), this book demonstrates how to use a variety of econometric techniques to analyze the evolving and expanding carbon markets sphere, techniques that can be extrapolated to the worldwide marketplace. It features stylized facts about carbon markets from an economics perspective, as well as covering key aspects of pricing strategies, risk and portfolio management.

Zielgruppe


Upper undergraduate


Autoren/Hrsg.


Weitere Infos & Material


1. Introduction to Emissions Trading

1.1 Review of International Climate Policies

1.1.1 From Rio to Durban

1.1.2 The Burgeoning EU CO2 Allowance Trading Market

1.2. Market Design Issues

1.2.1 Initial Allocation Rules

1.2.2 Equilibrium Permits Price

1.2.3 Spatial and Temporal Limits

1.2.4 Safety Valve

1.3. Key Features of the EU Emissions Trading Scheme

1.3.1 Scope and Allocation

1.3.2 Calendar

1.3.3 Penalties

1.3.4 Market Players

1.4 EUA Price Development

1.4.1 Structure and Main Features of EU ETS Contracts

1.4.2 Carbon Price

1.4.3 Descriptive Statistics

2. CO2 Price Fundamentals

2.1 Institutional Decisions

2.1.1 Dummy Variables

2.1.2 Structural Breaks

2.2 Energy Prices

2.2.1 Literature Review

2.2.2 Oil, Natural Gas and Coal
2.2.3 Electricity Variables

2.3 Extreme Weather Events

2.3.1 Relationship Between Temperatures and Carbon Prices

2.3.2 Empirical Application

Appendix: BEKK MGARCH Modeling With CO2 and Energy Prices

Problems

3. Link With The Macroeconomy

3.1 Stock and Bonds Markets

3.1.1 GARCH Modeling of the Carbon Price

3.1.2 Relationship With Stock and Bond Markets

3.2 Macroeconomic, Financial and Commodity Indicators

3.2.1 Extracting Factors Based On Principal Component Analysis

3.2.2 Factor-Augmented VAR Analysis Applied to EUAs

3.3 Industrial Production

3.3.1 Data

3.3.2 Nonlinearity Tests

3.3.3 Self-Exciting Threshold Autoregressive Models

3.3.4 Comparing Smooth Transition and Markov-Switching Autoregressive Models

4. The Clean Development Mechanism

4.1 CERs Contracts and Price Development

4.2 Relationship With EU Emissions Allowances

4.2.1 VAR Analysis
4.2.2 Cointegration

4.3 CERs Price Drivers

4.3.1 Zivot-Andrews Structural Break Test

4.3.2 Regression Analysis

4.4 Arbitrage Strategies: The CER-EUA Spread

4.4.1 Why So Much Interest in this Spread?

4.4.2 Spread Drivers

Appendix: Markov Regime-Switching Modeling With EUAs And CERs

Problems

5. Risk-Hedging Strategies And Portfolio Management

5.1 Risk Factors

5.1.1 Idiosyncratic Risks

5.1.2 Common Risk Factors

5.2 Risk Premia

5.2.1 Theory On Spot-Futures Relationships in Commodity Markets

5.2.2 Bessembinder and Lemmon's (2002) Futures-Spot Structural Model

5.2.3 Empirical Application

5.3 Managing Carbon Price Risk In The Power Sector

5.3.1 Economic Rationale

5.3.2 UK Power Sector

5.3.3 Factors Influencing Fuel-Switching

5.3.4 Econometric Analysis

5.3.5 Empirical Results

5.3.6 Summary
5.4 Portfolio Management

5.4.1 Composition of the Portfolio

5.4.2 Mean-Variance Optimization and the Portfolio Frontier

Appendix: Implied Volatility From Option Pricing

Problems

6. Advanced Topics: Time-To-Maturity and Modeling the Volatility of Carbon Prices

6.1 The Relationship Between Volatility and Time-To-Maturity in Carbon Prices

6.2 Background On the Samuelson Hypothesis

6.3 Data

6.3.1 Daily Frequency

6.3.2 Intraday Frequency

6.4 The 'Net Carry Cost' Approach

6.4.1 Computational Steps

6.4.2 Regression Analysis

6.4.3 Empirical Results

6.5 GARCH Modeling

6.5.1 GARCH Specification

6.5.2 Empirical Results

6.6 Realized Volatility Modeling

6.6.1 Computational Steps

6.6.2 Regression Analysis

6.6.3 Empirical Results

6.6.4 Sensitivity Tests

6.7 Summary

Appendix: Statistical Techniques To Detect Instability In The Volatility Of Carbon Prices

Solutions

Index


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