Title:
Analyzing uncertainty in the price of materials and financial risk management strategies
Analyzing uncertainty in the price of materials and financial risk management strategies
Author(s)
Ilbeigi, Mohammad
Advisor(s)
Castro-Lacouture, Daniel
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Abstract
Significant volatility and unprecedented uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs with regards to proper cost estimating and budgeting of transportation projects. Previous studies indicate that owner organizations often overpay for projects under fixed-price contracts that transfer the material price risk to contractors due to increased risk premiums and hidden contingencies in contractors’ submitted bid prices. A common method widely used by state DOTs for handling the issue of extra risk premiums in submitted bid prices and avoiding overpayment to contractors is to offer price adjustment clauses (PACs) in contracts. A PAC is a risk sharing contractual mechanism that guarantees an adjustment in payment to contractors based on the size and direction of the material price change. Although uncertainty in the price of asphalt cement is a serious challenge for both contractors and state DOTs and many transportation agencies utilize PACs to control consequences of material price volatility, there is little knowledge about analyzing uncertainties in the price of asphalt cement and actual performance of PACs. This dissertation aims to analyze uncertainty in the price of asphalt cement and examine performance of PACs in highway construction projects. After a comprehensive review of the existing body of knowledge about uncertainties in the price of critical materials in transportation projects and PACs, time series analysis is conducted and four univariate time series forecasting models are created to forecast future price of asphalt cement. The results of the time series forecasting show that all four time series models can predict the future values of asphalt cement price with proper accuracy but among the four models, the ARIMA and Holt Exponential Smoothing models are the most accurate prediction models with less than 2% error. Then, ARCH/GARCH time series analysis is conducted to quantify and forecast level of uncertainties in the price of asphalt cement. The results of this step can help transportation agencies systematically measure, analyze and forecast the uncertainties in the price of asphalt cement and implement their risk management strategies at the right time. In next step, impacts of offering PACs on submitted bid prices for major asphalt line items are analyzed using multivariate regression analysis. Finally, effects of offering PACs on dispersion of submitted bid prices and number of bidders are analyzed using system monitoring processes.
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Date Issued
2017-05-11
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Text
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Dissertation