Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/203226 
Title: 

Renewable energy financial modelling: A China case study

The document was removed on behalf of the author(s)/ the editor(s).

Year of Publication: 
2019
Series/Report no.: 
IES Working Paper No. 07/2019
Publisher: 
Charles University in Prague, Institute of Economic Studies (IES), Prague
Abstract: 
In this paper, we analyse the dynamic relationship among the Chinese renewable energy stock prices, the U.S renewable energy stock prices, oil prices and technology stock prices. We apply a four-variable Lag Augmented Vector Autoregressive (LAVAR) model to study the return interactions among the variables. Moreover, we also use Generalized Autoregressive Conditional Heteroskedasticity (GARCH) models to study the dynamic conditional volatility of the Chinese renewable energy stock prices. The empirical results indicate that both return and conditional volatility of the Chinese renewable energy stock prices can be explained by past movements of the U.S renewable energy stock prices and technology stock prices. In addition, we find significant evidence to support the existence of the GARCH effects in the Chinese renewable energy stock prices. However, only weak statistical evidence reveals the significance of the leverage effects in the Chinese renewable energy stock market.
Subjects: 
Renewable energy
Financial modeling
China
JEL: 
Q20
G15
Document Type: 
Working Paper

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The document was removed on behalf of the author(s)/ the editor(s) on: June 15, 2020


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