Statistical time series analysis is a powerful method in
characterizing the dynamics of variables in forward contract
markets. Modeling univariate and multivariate time series variables
will enable the modeler to build forecasting models. Variables in a
given forward contract market (for example: basis, volume and
weeks-to-expiration) can have causal relationship with each other
and with their own lagged values. Variables with significant
Granger causality are modeled using vector autoregressive
processes, while variables with insignificant Granger causality are
modeled using autoregressive and moving average processes. Basis
and volume of forward contracted cattle in the United States
exhibit behaviors pertinent to seasonal changes. In this thesis, we
analyzed weekly data on basis, volume and weeks-to-expiration of
forward contracted cattle in the United States. We developed
monthly forecasting models for basis and volume contracted that can
be utilized by farmers and policy makers.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!