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SMA Solar Technology
ISIN DE000A0DJ6J9
|WKN A0DJ6J
Market cap (in EUR)
1,801 m
Country
Germany
Sector
Industrials
Dividend yield
1.60%
Overview
Quote
Description
SMA Solar Technology AG engages in the development, production and sale of solar inverters and monitoring systems for solar power systems. It operates its business through the following segments: Residential, Commercial, Utility, Storage, and Digital Energy. The Residential segment caters to global markets for small photovoltaic (PV) systems with and without connection to a smart home solution. The Commercial segment focuses on global markets for medium sized PV systems with and without an energy management solution. The Utility segment covers international PV power plant markets with its powerful string inverters in the sunny-high power product family, and the central inverters in the sunny central product family. The Storage segment consists of system technology for integrating battery-storage systems of all system sizes. The Digital Energy segment comprises of coneva which develops digital energy services for private and business customers; and emerce GmbH that involves in online sales channels for select markets. The company was founded by Reiner Wettlaufer, Peter Drews, Werner Kleinkauf, and Günther Cramer in 1981 and is headquartered in Niestetal, Germany.
Industrials Industrial Manufacturing Electrical Equipment and Power Systems Germany
Chart
Financials
Key metrics
| Market capitalisation, EUR | 1,801 m |
| EPS, EUR | -5.22 |
| P/B ratio | 4.9 |
| P/E ratio | 5.9 |
| Dividend yield | 1.60% |
Income statement (2025)
| Revenue, EUR | 1,516 m |
| Net income, EUR | -181 m |
| Profit margin | -11.95% |
What ETF is SMA Solar Technology in?
There are 5 ETFs which contain SMA Solar Technology. All of these ETFs are listed in the table below. The ETF with the largest weighting of SMA Solar Technology is the iShares Global Clean Energy Transition UCITS ETF USD (Dist).
| ETF | Weight | Investment focus | Fund size (in m EUR) |
|---|---|---|---|
| iShares Global Clean Energy Transition UCITS ETF USD (Dist) | 0.27% | Equity World Utilities Social/Environmental Clean Energy | 2,862 |
| Vanguard ESG Developed Europe All Cap UCITS ETF (EUR) Distributing | 0.01% | Equity Europe Social/Environmental | 34 |
| Vanguard Germany All Cap UCITS ETF (EUR) Distributing | 0.04% | Equity Germany | 259 |
| Vanguard ESG Global All Cap UCITS ETF (USD) Distributing | 0.00% | Equity World Social/Environmental | 508 |
| Amundi MSCI EMU Small Cap ESG Broad Transition UCITS ETF Dist | 0.17% | Equity Europe Small Cap Climate Change | 376 |
Performance
Returns overview
| YTD | +54.88% |
| 1 month | +15.23% |
| 3 months | +43.67% |
| 6 months | +97.46% |
| 1 year | +234.18% |
| 3 years | -46.01% |
| 5 years | +10.09% |
| Since inception (MAX) | +256.04% |
| 2025 | +150.66% |
| 2024 | -77.40% |
| 2023 | -9.64% |
| 2022 | +77.79% |
Monthly returns in a heat map
Risk
Risk metrics in this section:
- Volatility, annualised, measured for 1, 3 and 5 year periods. The annualised volatility reflects the degree of price fluctuations during a one year period. The higher the volatility, the more significantly the price of the asset (stock, ETF, etc.) has changed in the past. Assets with higher volatility are generally considered more risky. We calculate the volatility based on the data for the past 1, 3 and 5 years so that you can see if price fluctuations for the ETF became stronger or weaker over time.
- Return per risk for 1, 3 and 5 year periods. This is the annualised (i.e. converted to a one year period) past return divided by the past annualised volatility. The metric puts the historical return of an asset in relation to its historical risk and gives you a retrospective indication of the degree of price fluctuation you had to bear with in order to obtain the return. We calculate this parameter for 1, 3 and 5 year periods to display its evolution over time.
- Maximum drawdown for a period. This shows the worst possible loss an investor could have suffered during the respective period, by first buying and subsequently selling the asset at the least favourable prices. For example, if there was the following sequence of daily ETF prices: 10€, 5€, 12€, 20€, an investor would have suffered the worst loss by buying for 10€ and subsequently selling for 5€. Therefore in this case the maximum drawdown would be (5€ - 10€)/10€ = -50%.
Risk overview
| Volatility 1 year | 64.44% |
| Volatility 3 years | 63.67% |
| Volatility 5 years | 61.22% |
| Return per risk 1 year | 3.63 |
| Return per risk 3 years | -0.29 |
| Return per risk 5 years | 0.03 |
| Maximum drawdown 1 year | -35.25% |
| Maximum drawdown 3 years | -89.58% |
| Maximum drawdown 5 years | -89.58% |
| Maximum drawdown since inception | -89.58% |
Rolling 1 year volatility
Latest articles
— Data provided by Trackinsight, etfinfo, Xignite Inc., gettex, FactSet and justETF GmbH. Quotes are either real-time (gettex) or 15 minutes delayed stock exchange quotes or NAVs (daily published by the fund provider). By default, ETF returns include dividend payments (if applicable). There is no warranty for completeness, accuracy and correctness for the displayed information.