Abstract
Predicting the carbon price accurately can not only promote the sustainability of the carbon market and the price driving mechanism of carbon emissions, but can also help investors avoid market risks and increase returns. However, previous research has only focused on the low-order moment perspective of the returns for predicting the carbon price, while ignoring the shock of extreme events and market asymmetry originating from its pricing factor markets. In this paper, a novel extended higher-order moment multi-factor framework (EHM-APT) was formed to improve the prediction and to capture the driving mechanism of the carbon price. Furthermore, a multi-layer and multi-variable Long Short-Term Memory Network (Multi-LSTM) model was constructed so that the parameters and structure could be determined experimentally for testing the performance of the proposed framework. The results show that the pricing framework considers the shock of extreme events and market asymmetry and can improve the prediction compared with a framework that does not consider the shock of higher-order moment terms. Additionally, the Multi-LSTM model is more competitive for prediction than other benchmark models. This conclusion proves the rationality and accuracy of the proposed framework. The application of the pricing framework encourages investors and financial institutions to pay more attention to the pricing factor of extreme events and market asymmetry for accurate price prediction and investment analysis.
Highlights
Upon signing the Kyoto protocol, the carbon market was formally established in 2005 in an attempt to reduce global greenhouse gas
We developed an extended higher-order moment Multi-factor framework (EHM-arbitrage pricing theory (APT)) for predicting the carbon price by extending the theory of the binary higher-order moment Capital Asset Pricing Model (CAPM) model developed by Fry et al [6] to multivariate factors
As for the EHM-APT framework, we considered the impact of market asymmetry and extreme events that stem from its pricing factor markets on the carbon price compared with the traditional APT model
Summary
Upon signing the Kyoto protocol, the carbon market was formally established in 2005 in an attempt to reduce global greenhouse gas. The carbon market defines virtual carbon emission rights as scarce valuable assets, gives them commodity attributes, and realizes the target of resource allocation and emission reduction through market transaction among reduction entities. The signing of the Paris Agreement in December 2015 further highlights the carbon market’s capital allocation for achieving emission reduction on a global scale [1]. As an emerging policy-based artificial market, the carbon market is characterized by strong sensitivity to policy shocks, especially carbon dioxide (CO2) reduction policies and carbon quota policies [2]. As for the certain pricing framework, the prediction of the carbon price should follow the basic pricing method of general financial assets, and reflect the special driving mechanism of the carbon price
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