Renewable Energy Financial Modelling: A China Case Study
Karel Janda and
Binyi Zhang ()
No 2019/7, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies
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 (LA-VAR) 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.
Keywords: Renewable energy; Financial modeling; China (search for similar items in EconPapers)
JEL-codes: G15 Q20 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2019-05, Revised 2019-05
New Economics Papers: this item is included in nep-cna, nep-ene, nep-ets, nep-ore and nep-tra
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