| Summary/Abstract |
The considerable amount of required infrastructure and renewable energy investments expected in the forthcoming years also implies an increasingly relevant contribution of private and institutional investors. In this context, especially regulatory and policy risks have been shown to play a major role for investors when evaluating investments in renewable energy and should thus also be taken into account in risk assessment and when deriving risk-return profiles. In this paper, we provide a stochastic model framework to quantify policy risks associated with renewable energy investments (e.g. a retrospective reduction of a feed-in tariff), thereby also taking into account energy price risk, resource risk, and inflation risk. The model is illustrated by means of simulations and scenario analyses, and it makes use of expert estimates and fuzzy set theory for quantifying policy risks. Our numerical results for a portfolio of onshore wind farms in Germany and France show that policy risk can strongly impact risk-return profiles, and that cross-country diversification effects can considerably decrease the overall risk for investors.
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