Dynamic impact of macroeconomic and financial stress factors on Clean Energy Index performance: Evidence from an ARDL analysis
Akshay SAHU et al.
What the paper says
Type of the article: Research ArticleAbstractThe growing importance of renewables in the global push towards low-carbon economies has led to rising investor interest in clean energy stocks; however, their performance remains sensitive to macroeconomic and financial conditions. This study aims to examine the dynamic short-run and long-run impacts of macroeconomic and financial stress factors on clean energy stock returns, proxied by the Clean Edge Green Energy Index. Monthly data covering the period from January 2008 to June 2025 are employed. An autoregressive distributed lag modeling framework is used to capture both short-run dynamics and long-run equilibrium relationships between clean energy stock returns, crude oil prices, exchange-rate, interest rate, and the volatility index. The results confirm the existence of a stable long-run relationship among the variables, as evidenced by the bounds testing approach. In the short run, increases in volatility, exchange-rate appreciation, and rising interest rates exert statistically significant negative effects on clean energy stock returns, while the adjustment toward long-run equilibrium is rapid, with approximately 74% of short-run deviations corrected within one month. In the long run, exchange-rate movements and interest rates continue to impose persistent and economically meaningful adverse effects, whereas crude oil price changes remain statistically insignificant. These findings underscore the importance of macro-financial conditions in shaping clean energy stock performance beyond commodity price dynamics and highlight the role of stable financial environments in supporting long-term investment in renewable energy markets.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.