The Pictet Cleaner Planet ETF (PCLN) is dedicated to fostering a healthier environment by investing worldwide in companies actively driving the transition towards a more sustainable and ecologically mindful global economy. It adheres to rigorous Environmental, Social, and Governance (ESG) standards, specifically seeking out firms committed to superior ESG performance and responsibly exercising shareholder voting rights. The investment process starts with a distinctive thematic screening method that narrows down the universe of potential investments. Eligible companies must demonstrate a positive influence in critical areas such as renewable energy development, pollution control, advanced water technologies, sustainable agricultural practices, efficient waste management, and initiatives supporting a circular economy. Following this initial filter, the second stage employs a three-phase assessment: (I) evaluating companies for their alignment with the fund's themes, market liquidity, and volatility; (II) conducting a thorough fundamental analysis of their business quality, management effectiveness, financial strength, and overall sustainability; and (III) determining portfolio weightings based on extensive research insights, the fund manager's conviction, and various risk considerations. The fund strictly avoids investments in companies involved in controversial weaponry, thermal coal, or those with severe breaches of the UN Global Compact principles.
+17.2%
2025-11-13low 23.72 · high 33.662026-11-13
Performance
1M
3M
YTD
1Y
3Y ann.
5Y ann.
PCLN
-3.3%
-9.1%
+15.7%
+17.3%
—
—
Active Equity average (3 funds)
-6.5%
-8.3%
+17.2%
+18.5%
—
—
Insider activity in the holdings
Open-market insider buying across this fund’s holdings over 90 days, weighted by holding weight: +$17.6M net.
Fund facts, prices, performance and distributions: our market-data vendor. Holdings: the vendor and SEC Form N-PORT. Insider and Congress data: InsiderBuying. Last updated Nov 13, 2026. This is historical data, not investment advice. Report a data error