Implications of clean energy, oil and emissions pricing for the GCC energy sector stock
研究了清洁能源、原油和碳排放价格对沙特、阿布扎比和科威特能源股票风险的影响，发现这些外部因素对日收益波动影响不显著，但不同GARCH模型在风险预测上表现各异。
In this study, we analyse the implications of clean energy, oil and emission prices for the energy sector stock in the GCC region. In so doing, we estimate one-day-ahead value at risk (VaR) and the expected shortfall (ES) for Saudi, Abu Dhabi and Kuwaiti energy stock prices over short and long trading positions using three different long memory Autoregressive conditional heteroskedasticity (ARCH)/ Generalized(G)- ARCH models: fractionally integrated asymmetric power ARCH (FIAPARCH), fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) and fractionally integrated hyperbolic generalized autoregressive conditional heteroskedasticity (HYGARCH). In the GARCH model, we employ the three global energy indexes: clean energy production, crude oil and CO2 emission prices as exogenous regressors to consider their impacts on the GCC energy volatilities. Our findings indicate the presence of asymmetry, fat-tails and long memory in the GCC energy price volatilities, and that the three exogenous regressors do not play a significant role in the GCC daily returns volatility. The FIAPARCH produces the most accurate VaR and the expected shortfall for Saudi and Kuwait energy sectors, while HYGARCH performs better for the Abu Dhabi energy index. Our study has profound implications for the clean energy policy, emission pricing and investment strategies entailing energy stock.