Zelalem Abahana, Matthew Diersen, Jing Li

Statistical Time Series Analysis on Basis and Volume Contracted

Forecasting Models for Forward Contracted Cattle in the United States

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Verlag: LAP Lambert Academic Publishing
• Aufl.
• Seitenzahl: 84
• Englisch
• Abmessung: 220mm
• ISBN-13: 9783847371595
• ISBN-10: 3847371592
• Artikelnr.: 35053955

Autorenporträt

Zelalem G. Abahana, MSc.: Studied economics at South Dakota State University. Visiting scholar and consultant at the United Nations Environment Programme, Geospatial analyst and consultant to German International Development Cooperation-GIZ.