A model robust real options valuation methodology incorporating climate risk

Abstract

Physical climate risk faced by companies is emerging as a significant concern for long term investors, such as sovereign wealth funds. For the mining sector, each physical asset may have a significant financial exposure to extreme climate events such as floods and droughts. Often, these financial risks are difficult to value given the paucity of data on climate extremes, and limited company assessment and disclosure of the associated financial liability. We propose a generalization of the Brennan-Schwartz approach to real option valuation to address this situation. A Poisson point process is used to model arrivals of extreme events that exceed the estimated design return period of the flood/drought mitigation infrastructure at the site. Using techniques from the field of robust performance analysis, we are able to calculate upper and lower bounds over all the probability models within a certain distance from the original model, that address the potential uncertainty of the risk and loss. We suggest two different approaches for mine valuation based on this technique. The first, and more direct approach, calibrates the distance of probability measures from a set of known mine transactions and prices a mine (with currently unknown value) relative to the training set of mines. The second approach uses historical precipitation data from a mine site, to calculate a “worst case” disaster arrival process from the actual physical data, and then the mine is priced using this process. Generalizations to a portfolio of assets are also considered.