An Econophysics Study of the S&P Global Clean Energy Index

Abstract

The study of how financial markets behave continues to be interesting. The existence of more and more data and the development of statistical techniques are some reasons for the increase in research in finance. However, the difficulty in understanding some markets’ behavior is a continuous challenge. In this context, a new research area called Econophysics has emerged, which is constantly increasing in size. We propose in this work to use methodologies related to Econophysics to analyze one stock index composed of firms producing clean energy (S&P Global Clean Energy Index) and compare it with the New York Stock Exchange (NYSE) as a stock market benchmark and with the price of crude oil. In a context where environmental issues are on the agenda, this is an important area of research, because it could help investors to make their decisions. Our results show that the clean energy index seems to have higher time serial dependence than the others, and is less exposed to oil price than the NYSE.

The Co‐Movement between International and Emerging Stock Markets Using ANN and Stepwise Models: Evidence from Selected Indices

“…Reference [15] applied econophysics methodology to analyze one stock index that consists of firms producing clean energy (S&P Global Clean Energy Index). Besides, they compare it with New York Stock Exchange (NYSE) as a stock market benchmark and the price of crude oil.…”

“…Many researchers have studied the prediction of stock markets using different macroeconomic factors and feature issues [14][15][16]. However, few researchers tried to predict the performance of stock markets through the integration between different international and national markets' indices [10,17,18].…”

Are clean energy markets efficient? A multifractal scaling and herding behavior analysis of clean and renewable energy markets before and during the COVID19 pandemic

“…In addition [ 50 ], found unidirectional connectedness from the implied volatility indices to the clean energy stocks. Then again [ 51 ], utilized the quantile regression method and showed decreasing dependence of clean energy indices on oil returns [ 52 ]. used an Econophysics-based DFA approach to study the behavior of three varied indices including the S&P clean energy index.…”

Can International Market Indices Estimate TASI’s Movements? The ARIMA Model

“…In addition, Tissaoui and Azibi [36] studied the predictability of Tadawul index and international indices and found that US volatility risk indices are dominant in forecasting the Saudi stock exchange. Moreover, researchers investigated the relationship between international indices and different variables, including the clean energy index [49] and skew phenomenon [50].…”