@article{Etienne:211626,
      recid = {211626},
      author = {Etienne, Xiaoli},
      title = {Financialization of Agricultural Commodity Markets: Do  Financial Data Help to Forecast Agricultural Prices},
      address = {2015},
      number = {1008-2016-80342},
      pages = {30},
      year = {2015},
      abstract = {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.},
      url = {http://ageconsearch.umn.edu/record/211626},
      doi = {https://doi.org/10.22004/ag.econ.211626},
}