Valuation of Guaranteed Maximum Price Contracts in Korea Using the Collar Option Model

Abstract

This study assessed the levels of risk that contractors may be subject to while executing a GMP contract by applying a collar option model to the case study of an apartment project in Korea and identified implications for the application of GMP contracts in Korea. The payoff structure of the GMP contract was defined based on the collar option model and a profit sharing ratio calculated to evaluate the risks involved in GMP contracts. The results showed that an increase in the GMP and a decrease in the expected cost and cost range were accompanied by a decrease in the profit sharing ratio. The proposed valuation model for GMP contracts is expected to help clients and contractors in Korea negotiate reasonable contracts as it enables the contractor to utilize the proposed model as basic data, the client to evaluate the performance of the contractor, and both parties to agree a reasonable profit sharing ratio. Implementing GMP contracts with CMR is likely to have a number of positive effects on the Korean construction market. However, in order to maximize these effects, it is necessary to have the ability to evaluate cost uncertainty. Accordingly, it is very important to analyze the factors that influence cost volatility. In future work, the various factors that have an impact on the GMP must be studied to maximize the positive effects of the framework proposed in this paper. An analysis of the effect of each factor on the change in the GMP will help Korean construction companies who are attempting to introduce GMP contracts to perform their preconstruction services effectively.

Risk management in guaranteed maximum price (GMP) contracts

“…GMP contracts inherit high levels of risks as the GMP level is decided before the design is completed (Chan et al, 2010b). The risk levels in a GMP project increases proportionately to the project cost (Lee et al, 2018).…”

“…, 2010b). The risk levels in a GMP project increases proportionately to the project cost (Lee et al. , 2018).…”