Multiple regression model for cotton price returns: Analysis of the impact of weather, oil price return, and China’s economy

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School of Business | Bachelor's thesis
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Date

2018

Department

Mikkelin kampus

Major/Subject

Mcode

Degree programme

(Mikkeli) Bachelor’s Program in International Business

Language

en

Pages

42

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Abstract

Objectives The study aims at determining the relationship between cotton price return and oil price return, China’s economy, and weather condition, particularly the monsoon season. Furthermore, the study attempts to conduct a multiple regression model to estimate the cotton price return based on oil price return, difference of precipitation in China, India, USA, China’s interest rate, China’s import, and monsoon. Summary A multiple regression model is conducted for 263 samples of cotton spot price and independent variables: oil spot price, China’s import, China’s interest rate, precipitation in USA, China, India, and monsoon period, which are all recorded as monthly data from February of 1994 to December of 2015. The assumption pre-tests for multiple regression model are conducted. Based on the assumption test result, the input set of data can be considered valid for conducting multiple regression model. Conclusions The empirical results reaffirm the negative relationship between cotton price return and two other variables: China’s interest rate, and the change in China’s import level and positive relationship between cotton price return and oil price return. The model offers inconclusive conclusion for the relationship of cotton price return and monsoon period.

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Thesis advisor

Hearn, Bruce

Keywords

cotton price, cotton return, multiple regression, China's economy, monsoon

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https://urn.fi/URN:NBN:fi:aalto-201809105083

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[kand] Kauppakorkeakoulu / BIZ (Open Access)