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Using Econometric Models to Manage the Price Risk of Cocoa Beans: A Case from India

Author

Listed:
  • Kepulaje Abhaya Kumar

    (Department of Business Administration, Mangalore Institute of Technology & Engineering, Mangalore 574225, India)

  • Cristi Spulbar

    (Faculty of Economics and Business Administration, University of Craiova, 200585 Craiova, Romania)

  • Prakash Pinto

    (Department of Business Administration, St. Joseph Engineering College, Mangalore 575028, India)

  • Iqbal Thonse Hawaldar

    (Department of Accounting & Finance, College of Business Administration, Kingdom University, Sanad 40434, Bahrain)

  • Ramona Birau

    (Doctoral School of Economic Sciences, University of Craiova, 200585 Craiova, Romania)

  • Jyeshtaraja Joisa

    (Department of Business Administration, Mangalore Institute of Technology & Engineering, Mangalore 574225, India)

Abstract

This study aims at developing econometric models to manage the price risk of Dry and Wet Cocoa beans with the help of ARIMA (Autoregressive Integrated Moving Average) and VAR (Vector Auto Regressive). The monthly price of Cocoa beans is collected for the period starting from April 2009 to March 2020 from the office of CAMPCO Limited, Mangalore, and the ICE Cocoa futures price from the website of investing.com. The augmented dickey fuller test is used to test the stationarity of the series. The ACF and PACF correlograms are used to identify the tentative ARIMA model. Akaike information criterion (AIC) and Schwarz criterion (SBIC), Sigma square, and adjusted R 2 are used to decide on the optional AR and MA terms for the models. Durbin–Watson statistics and correlograms of the residuals are used to decide on the model’s goodness of fit. Identified optimal models were ARIMA (1, 1, 0) for the Dry Cocoa beans price series and ARIMA (1, 1, 2) for the Wet Cocoa beans price series. The multivariate VAR (1) model found that the US and London Cocoa futures prices traded on the ICE platform will influence the price of Dry Cocoa in India. This study will be helpful to forecast the price of Cocoa beans to manage the price risk, precisely for Cocoa traders, Chocolate manufacturers, Cocoa growers, and the government for planning and decision-making purposes.

Suggested Citation

  • Kepulaje Abhaya Kumar & Cristi Spulbar & Prakash Pinto & Iqbal Thonse Hawaldar & Ramona Birau & Jyeshtaraja Joisa, 2022. "Using Econometric Models to Manage the Price Risk of Cocoa Beans: A Case from India," Risks, MDPI, vol. 10(6), pages 1-18, June.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:6:p:115-:d:829932
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    References listed on IDEAS

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    1. repec:cup:cbooks:9781107034662 is not listed on IDEAS
    2. Buhl, Hans Ulrich & Strauß, Sofie & Wiesent, Julia, 2011. "The impact of commodity price risk management on the profits of a company," Resources Policy, Elsevier, vol. 36(4), pages 346-353.
    3. Michael T. Chng, 2004. "A model of price discovery and market design: Theory and empirical evidence," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(12), pages 1107-1146, December.
    4. Adusei Jumah, 2001. "The effects of dollar-sterling exchange rate volatility on futures markets for coffee and cocoa," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 28(3), pages 307-328, October.
    5. Abhaya K. Kumar & Prakash Pinto & Iqbal Thonse Hawaldar & Cristi Spulbar & Ramona Birau & Minea Elena Loredana, 2021. "Forecasting Areca Nut Market Prices Using The Arima Model: A Case Study Of India," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 2, pages 4-18, April.
    6. Brooks,Chris, 2014. "Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9781107661455, December.
    7. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    8. Taghizadeh-Hesary, Farhad & Rasoulinezhad, Ehsan & Yoshino, Naoyuki, 2019. "Energy and Food Security: Linkages through Price Volatility," Energy Policy, Elsevier, vol. 128(C), pages 796-806.
    9. Durdana Qaiser Gillani & Syed Ahmad Saad Gillani & Muhammad Zahid Naeem & Cristi Spulbar & Elizabeth Coker-Farrell & Abdullah Ejaz & Ramona Birau, 2021. "The Nexus between Sustainable Economic Development and Government Health Expenditure in Asian Countries Based on Ecological Footprint Consumption," Sustainability, MDPI, vol. 13(12), pages 1-15, June.
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    Cited by:

    1. Juan D. Borrero & Jesus Mariscal, 2022. "Predicting Time SeriesUsing an Automatic New Algorithm of the Kalman Filter," Mathematics, MDPI, vol. 10(16), pages 1-13, August.

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