Applying Quantum Computing to the Renewable Energy Stock Exchange to Reduce the Risk of Investment

Quantum computers have the potential to outperform classical computers in certain computational tasks. This research study attempts to utilize the quantum mechanics theory applied in the renewable energy stock market. The main quantitative analysis that has been utilized in this research article is a survival function based on Hamiltonian Monte Carlo simulation (HMC) to assess the risk of renewable energy stock investing. The daily data stock price during the period 2020–2023 of eight renewable energy stocks, such as Iberdrola (IBDRY), NextEra Energy (NEE), Vestas Wind (VWDRY), JinkoSolar (JKS), Canadian Solar (CSIQ), Daqo New Energy (DQ), Algonquin Power (AQN), and Clearway Energy (CWEN) is included to predict aversion to risk and make profit from those stocks in the world’s renewable energy stock market. The result from the survival function based on HMC suggests that the investor can hold all-renewable energy stocks in the portfolio for only half a year to one year to make a profit or avoid the risky investment, especially the stocks CSIQ and CWEN, which have performed quite well for investors to make a profit for their investment. If this information has already been confirmed appropriately, then it can be pointed out that the renewable energy stock market has more potential for investors to invest in the stock exchanges to drive sustainable energy development in the future.