Education, Science, Technology, Innovation and Life
Open Access
Sign In

Optimized Pricing Mechanism and Design of Carbon Finance Structured Products

Download as PDF

DOI: 10.23977/ferm.2023.060606 | Downloads: 19 | Views: 516

Author(s)

Zedong Cai 1, Shasha Hu 2, Liangyu Yao 3, Ruyuan Zhang 2

Affiliation(s)

1 School of Finance, Shanghai University of Finance and Economics, Shanghai, China
2 School of Finance, Zhejiang University of Finance and Economics, Hangzhou, China
3 School of Economics and Management, China Jiliang University, Hangzhou, China

Corresponding Author

Zedong Cai

ABSTRACT

Carbon finance play an essential role in the promotion of carbon peaking and carbon neutrality, and one support for the development of carbon finance is the structured deposit launched by banks. This article first examines the pricing rationality of a carbon finance structured deposit by using risk neutrality pricing, GARCH model, Cholesky decomposition, BS Model, Monte Carlo simulation, geometric Brownian motion, Heston model and Merton jump-diffusion model, etc., parameters used for asset pricing are all estimated with reasonable basis. Moreover, this article also optimized its design from the perspectives of increasing market participants and risk diversification. Finally, several enlightenments are summarized and put forward.

KEYWORDS

Carbon Finance, Structured Deposit, Risk Neutrality, Monte Carlo Simulation, Risk Diversification

CITE THIS PAPER

Zedong Cai, Shasha Hu, Liangyu Yao, Ruyuan Zhang, Optimized Pricing Mechanism and Design of Carbon Finance Structured Products. Financial Engineering and Risk Management (2023) Vol. 6: 34-41. DOI: http://dx.doi.org/10.23977/ferm.2023.060606.

REFERENCES

[1] Sun Jiaojiao, Dong Feng. Optimal reduction and equilibrium carbon allowance price for the thermal power industry under China’s peak carbon emissions target [J]. Financial Innovation, 2023, 9(1). 
[2] Qi Shaozhou, Xu Zhenzhen, Yang Zhixuan. China's carbon allowance allocation strategy under the EU carbon border adjustment mechanism: An integrated non-parametric cost frontier approach [J]. Science of the Total Environment, 2022, 831. 
[3] Oluwasegun B. Adekoya. Predicting carbon allowance prices with energy prices: A new approach [J]. Journal of Cleaner Production, 2020 (prepublish). 
[4] Zheng Yan, Zhou Min, Wen Fenghua. Asymmetric effects of oil shocks on carbon allowance price: Evidence from China [J]. Energy Economics, 2021, 97. 
[5] Robert F. Engle. Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation [J]. Econometrica, 1982, 50(4). 
[6] Tim Bollerslev. Generalized autoregressive conditional heteroskedasticity [J]. Journal of Econometrics, 1986, 31(3), 307-327. 
[7] Cecilia Maya. Monte Carlo Option Princing[J]. Lecturas de Economía, 2004, 61(61). 
[8] Steven L. Heston. Invisible Parameters in Option Prices [J]. The Journal of Finance, 1993, 48(3). 
[9] Merton Robert C. Option pricing when underlying stock returns are discontinuous [J]. Journal of Financial Economics, 1976, 3(1-2). 

Downloads: 18124
Visits: 350726

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.