Analysis of historical trends in material production and price volatility

Thesis: S.B., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 42-44).Volatilities generate uncertainties in the market that critically impact the decisions of producers, consumers, and speculators alike. Historical trends in volatility can be studied as a means of better understanding current volatilities and predicting future ones in the industry. This study used the coefficient of variation (CV) as a relative metric to compare the historical production and price volatilities of various materials - 12 metals, cement, and steel - from 1900 through 2015. The long-term (1900-2015) and short-term (1995-2015) volatilities of these materials were quantified, and decades corresponding to periods of warfare and/or economic recession were shown to exhibit highest volatility. To complement the breadth of this approach, aluminum and steel were used as case studies to determine which factors - amongst production, consumption, energy price, and raw material price - drive trends in U.S. material price volatility. Volatility comparison graphs of material price and the factor in question were generated, and the root mean square (RMS) error between the volatilities was taken as a measure of their correlation. Volatilities in both aluminum and steel price were shown to correlate strongest with volatilities in raw material (bauxite and iron ore) price, with volatilities in steel also correlating comparatively with production and consumption dynamics. Overall, this study demonstrated the effectiveness of CV as a quantitative metric to assess historical volatilities and identified key market forces driving these volatilities for the aluminum and steel industries.by Jae Hyun Kim.S.B