دانلود رایگان مقاله ارزیابی ارزش به اشتراک گذاری ریسک

Abstract

The allocation of risk among the cooperating parties in a shared project is an important decision. This is especially true in the case of large infrastructure investments. Existing risk allocation methods are either simplistic or do not consider the effect of the agents' pre-existing businesses. In this paper, we model and analyse the effect of risk sharing when two agents want to co-develop an energy infrastructure project in an uncertain environment. The cooperating agents have a pre-existing risky business, and the new common project has a deterministic initial cost but random revenue potential. Our analysis shows that the optimal risk-sharing rule depends not only on the agents' risk aversions but also on the volatility of the common project profit, the volatilities of the agents' pre-existing businesses and the correlation of each agent's pre-existing business with the common project. An illustrative example based on energy infrastructure is used to show the implications of the sharing rule for partners.

5. Conclusions

The exploratory phase of a joint infrastructure project entails uncertainties to cooperating agents with respect to the value of the project and the optimal share of risk. Uncertainty often leads to a deadlock situation in which decision-making stagnates. To address uncertainty in such situations, an approach is required that allows the assessment of the risk and gain of cooperation for each agent. In this paper, we analyse the effect of risk sharing when two risk-averse agents co-develop an energy infrastructure project under uncertain environment. The two agents have background risks from their pre-existing businesses, and the joint project is represented by a risky cash flow. The cooperating partners are risk-averse but need not have the same risk aversion. We assume that the partners will act cooperatively to maximize their joint welfare and there is information symmetry on the common project performance. The models and numerical analyses provide valuable managerial insights.