Date: September 2011
Creator: Damnjanovic, Ivan & Zhou, Xue
Description: "The main goal of this report is to investigate the impact of commodity price risk on construction cost and the optimal risk hedging of such risks using price adjustment clauses. More specifically, the objective of the report is to develop models that can help highway agencies manage commodity price risks. In this report, weighted least square regression model is used to estimate the risk premium; both univariate and vector time series models are estimated and applied to simulate changes in commodity prices over time, including the effect of correlation; while genetic algorithm is used as a solution approach to a multi-objective optimization formulation. The data set used in this report consists of TxDot bidding data, market-based data including New York Mercantile Exchange (NYMEX) future options data, and Engineering New-Record (ENR) material cost index data. The results of this report suggest that the optimal risk mitigation actions are conditional on owners' risk preferences, correlation among the prices of commodities, and volatility of the market."
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