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Time Series Analysis for Coca Cola earnings and Hawaii CO2 mole fraction. These projects were developed during the Master in Business Analytics & Big Data at IE HST.

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Forecasting-Time-Series

1. Modeling Coca-Cola's quarterly's earnings

In this project, I develop linear time series models using the Box-Jenkins methodology, for the quarterly earnings per share of Coca-Cola. I built 5 models in total and compared them in terms of forecasting using both the Recursive Scheme and the Rolling Scheme.

The R code and detailed report of the analysis as well as the data used for this project can be found in the folder 1_Coca_Cola_Earnings.

2. Modeling monthly mean CO2 mole fraction at Mauna Loa Observatory, Hawaii

In this project, I used the Box-Jenkins methodology to find two time-series models analyze monthly mean CO2 mole fraction at Mauna Loa Observatory, Hawaii, with 732 records from March 1958 until February 2019.

The R code and detailed report of the analysis as well as the data used for this project can be found in the folder 2_CO2_Hawaii.

ACF & PACF Forecast

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Time Series Analysis for Coca Cola earnings and Hawaii CO2 mole fraction. These projects were developed during the Master in Business Analytics & Big Data at IE HST.

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