Pricing and Forecasting Carbon Markets
Models and Empirical Analyses
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Article
Intelligent Prediction of Annual CO2 Emissions Under Data Decomposition Mode
CO2 emissions have contributed to global warming and belong to high-noise, non-stationary and nonlinear systems. An accurate prediction method for annual CO2 emissions can improve the effectiveness of emission re...
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Article
Open AccessComplex network analysis of global stock market co-movement during the COVID-19 pandemic based on intraday open-high-low-close data
This study uses complex network analysis to investigate global stock market co-movement during the black swan event of the Coronavirus Disease 2019 (COVID-19) pandemic. We propose a novel method for calculatin...
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Correction to: New theoretical ISM‑K2 Bayesian network model for evaluating vaccination effectiveness
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New theoretical ISM-K2 Bayesian network model for evaluating vaccination effectiveness
Aiming at the difficulty in obtaining a complete Bayesian network (BN) structure directly through search-scoring algorithms, authors attempted to incorporate expert judgment and historical data to construct an...
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Forecasting carbon market volatility with big data
This paper proposes an ensemble forecasting model for carbon market volatility with structural factors and non-structural Baidu search index. Firstly, wavelet analysis is introduced into carbon price denoising...
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On Market Power, Permit Banking Borrowing, and Interactions with the Firm’s Production Market
The carbon trading scheme has been recognized as a cost-saving and effective way to promote carbon emission abatement. This paper constructs an intertemporal carbon market model considering product market and ...
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Bootstrap rolling-window Granger causality dynamics between momentum and sentiment: implications for investors
This paper seeks to examine the unidirectional versus bidirectional Granger causality between investors’ sentiment and momentum strategies. It is based on the full sample Granger causality test and the recent ...
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Article
Forecasting Inflection Points: Hybrid Methods with Multiscale Machine Learning Algorithms
This paper investigates hybrid time series forecasting models, which are based on combinations of ensemble empirical mode decomposition and least squares support vector machines. Several algorithms are conside...
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Measuring the risk of European carbon market: an empirical mode decomposition-based value at risk approach
Unlike common financial markets, the European carbon market is a typically heterogeneous market, characterized by multiple timescales and affected by extreme events. The traditional Value-at-Risk (VaR) with si...
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Including intangible costs into the cost-of-illness approach: a method refinement illustrated based on the PM2.5 economic burden in China
The concentrations of particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) and 10 µm (PM10) is a widespread concern and has been demonstrated for 103 countries. During the past few years, the ex...
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Examining the Factors Affecting Air Pollution Emission Growth in China
In this study, a structural decomposition method was applied to research the factors affecting the changes in air pollution emissions in China. Based on 1995–2009 data from the World IO Database, we combine Ch...
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Erratum to: Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market
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Hilbert Spectra and Empirical Mode Decomposition: A Multiscale Event Analysis Method to Detect the Impact of Economic Crises on the European Carbon Market
Exploring the effect of an economic crisis on the carbon market can be propitious to understand the formation mechanisms of carbon pricing, and prompt the healthy development of the carbon market. Through the ...
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Article
Stimulus Sensitivity of a Spiking Neural Network Model
Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawk...
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Estimation of Lévy-driven Ornstein–Uhlenbeck processes: application to modeling of \(\hbox {CO}_2\) and fuel-switching
This paper proposes an estimation methodology for Lévy-driven Ornstein–Uhlenbeck processes. The estimation unfolds in two steps, with a least-squares method for a subset of parameters in the first stage, and a...
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Electricity-savings pressure and electricity-savings potential among China’s inter-provincial manufacturing sectors
The Inter-Regional Input Output (IRIO) model is developed in 11 manufacturing sectors of China’s 30 provincial-level regions. Against the background of electricity pricing and energy-savings, this paper develo...
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Book
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Chapter
Forecasting Carbon Price with Empirical Mode Decomposition and Least Squares Support Vector Regression
This chapter contains another hybrid model of carbon price forecasting that combines empirical mode decomposition and least squares support vector regression. This multiscale prediction methodology yields accu...
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Chapter
New Perspectives on the Econometrics of Carbon Markets
This chapter provides an accessible introduction to this book. First, we detail the importance of pricing and forecasting carbon market. Second, we review the pricing and forecasting carbon market from the per...
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Examining the Structural Changes of European Carbon Futures Price 2005–2012
This chapter deals with structural breaks detection techniques in the time series of carbon futures. The ICSS is detailed, followed by an event study analysis. Several explanations are advanced as to how and...
