Financialization of Agricultural Commodity Markets: Do Financial Data Help to Forecast Agricultural Prices

The dramatic rise in commodity index investment have made many market analysts and researchers believe that commodity markets have undergone a financialization process that forged a closer link between commodity and financial markets. I empirically test whether this hypothesis is true in a forecasting context by using high-frequency financial data to forecast monthly US corn prices. Specific financial series examined include the Baltic Dry Index, the US exchange rate, the Standard and Poor’s 500 market index, the 3-month US Treasury bill interest rate, and crude oil futures prices. Using a recently developed statistical model that deals with mixed-frequency data, I find that while some improvements may be made when including high-frequency financial data in the forecasting model, the improvements in mean-squared prediction error and directional accuracy using such models are minimal, and that models generated from random walk and autoregressive models perform satisfactory well compared to more complicated models.


Issue Date:
2015
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/211626
Total Pages:
30




 Record created 2017-04-01, last modified 2017-04-26

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