Research Biotica, Volume 4, Issue 3 : 156-160. Doi : 10.54083/ResBio/4.3.2022/156-160
Research Article

Published on : 21-Sep-2022

Time Series Analysis of Monthly Coffee (Robusta) Prices in India using Box-Jenkins Approach

  • Prema Borkar
  • Gokhale Institute of Politics and Economics (Deemed University), Pune, Maharashtra (411 004), India

Abstract

Robusta coffee is a type of coffee made from the Coffea canephora plant's beans (seeds). It is the world's second most popular coffee, accounting for 43% of global coffee production with arabica constituting the remainder except for the 1.5% constituted by Coffea liberica. The purpose of this study is to focus on predicting monthly coffee prices in India by using the historic time series data. The objective of this paper is to fit an Autoregressive Integrated Moving Average model using Box-Jenkins approach. Numerous fields, including agricultural production, animal husbandry and dairy economics, stock price prediction, etc. depend heavily on forecasting. To choose the best model, Autoregressive (AR), Moving Average (MA), and Autoregressive Integrated Moving Average (ARIMA) processes was used to select the best model for monthly coffee prices in India. This paper discusses ARIMA (p, d, q) time series analysis and its components, ACF, PACF, Normalized BIC, Box-Ljung Q Statistics, and Residual analysis. According to the best fitted model i.e., ARIMA (0,2,1) monthly coffee prices in India is expected to increase to INR 89.35 kg-1 in the month of November 2022. The outcomes are represented numerically and graphically.

Keywords

Autocorrelation function, Box-Jenkins Approach, Coffee Prices, Partial autocorrelation function, Residual Analysis

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