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Predict the volatility of Coffee Price using Time Series Models<br />

Wan Fitriah Binti Wan Jusoh<br />

Supervisor: Dr. Hanafi Bin A. Rahim<br />

Bachelor of Science (Financial Mathematics)<br />

School of Informatics and Applied Mathematics<br />

Coffee is actually is very healthy drink and widely used in the world. It is loaded with<br />

antioxidants and beneficial nutrients that can improve your health. The aim of this study<br />

is to analyze the best model to expect the volatility of the coffee price by using the time<br />

series models. The weekly data taken from the US Coffee C Futures Historical Data was<br />

used started from January 4, 1986 until October 1, 2017. The autocorrelation effect was<br />

tested using Durbin Watson test and ARCH effects are exist through the Lagrange<br />

Multiplier test (LM) therefore GARCH (1,1) and EGARCH (1,1) model was applied in this<br />

study. Hence, the empirical results show that EGARCH (1,1) model seems to be better<br />

describing the volatility of the coffee price.<br />

902 | UMT UNDERGRADUATE RESEARCH DAY 2018

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