INVL Renewable Energy Fund I raised an additional EUR 18.3 million from investors
- Bias Rating
-10% Center
- Reliability
N/AN/A
- Policy Leaning
-90% Very Liberal
- Politician Portrayal
N/A
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The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.
Sentiments
N/A
- Liberal
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Center
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Conservative
-100%
Liberal
100%
Conservative
Contributing sentiments towards policy:
68% :Renewable energy is an attractive asset class from an environmental, economic and energy independence perspective.66% : The money raised from investors will be used to develop renewable energy facilities in the European Union, currently focusing on the Romanian and Polish markets where the fund's managers see big growth potential.
62% : Investing in the fund provides investors with a chance to contribute significantly to the growth of renewable energy, to diversify their assets geographically, and to earn an attractive return," says Liudas Liutkevičius, the managing partner of the INVL Renewable Energy Fund I.
62% : Poland and Romania have a need for new electricity generation capacity due to specifics of the production balance in those markets, and their governments are supporting the development of renewable energy.
60% : The fund's total investments in renewable energy projects Romania could reach about EUR 350 million.
56% : It invests in early- and mid-stage renewable energy projects (solar and wind), including the construction of new power plants, the development and/or acquisition of the infrastructure necessary for the operation of power plants, and effective management of existing power plants in the European Union and member states of the European Economic Area.
*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.