A1183
Title: Real options, commodities and natural resources under ambiguity
Authors: Christian Ewald - University of Glasgow (United Kingdom) [presenting]
Yihan Zou - University of Glasgow (United Kingdom)
Ankush Agarwal - Western University Ontario (Canada)
Abstract: The purpose is to explore real options in commodity and natural resource investments when decision-makers face not only risk but also ambiguity uncertainty about model parameters and future dynamics. Robust valuation and optimal timing frameworks are developed based on reflected backward stochastic differential equations (RBSDEs) combined with advanced Monte Carlo methods. In the context of large-scale commodity projects, parameter uncertainty in multi-factor models of spot prices, interest rates, and convenience yields generates a substantial ambiguity premium. Unlike risk, which tends to delay exercise, ambiguity often accelerates investment or harvesting decisions. This is illustrated through applications to aquaculture and forestry. For aquaculture projects, ambiguity in convenience yield estimation leads to earlier optimal harvesting and reduced project value. For forestry, both catastrophe risk, modeled as a Poisson process calibrated with wildfire data, and parameter uncertainty in lumber price dynamics are incorporated. This dual uncertainty reduces lease values and shifts optimal harvesting toward more conservative strategies, though carbon sequestration considerations can offset this effect by delaying harvests. Overall, the results highlight how ambiguity materially alters real options decisions in natural resource sectors and should be accounted for in project evaluation and climate-related risk management.
