Skip to main content
Top

2023 | OriginalPaper | Chapter

Forecasting Price of Small Cardamom in Southern India Using ARIMA Model

Authors : Jagadeesh Babu Myneedi, Nitin Kumar Lautre, Ravikumar Dumpala

Published in: Advances in Industrial and Production Engineering

Publisher: Springer Nature Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Small cardamom is one of the most popular and expensive spices in India. Two top constraints as judged in the year 2019 were labour shortage during production and price fluctuations during the marketing of this crop. This work is an attempt to forecast the price of small cardamom by using its price data from May 2015 to December 2019. It is evident from the data that there is no seasonality in the crop price data during that period. So, Sen’s slope estimator and Mann–Kendall tests are employed to estimate the price trend, and it is found that there is an increasing trend with a magnitude of 0.429. Thus, ARIMA (Autoregressive Integrated Moving Average) model is used to predict the price of the crop for the 2020 period, where it is applied different combinations of (p, d, q) values based on ACF (Auto-Correlation Function) and PACF (Partial Autocorrelation Function) plots. By using standard criteria such as RMSE (Root Mean Square Error), MAPE (Mean Absolute Percentage Error), and MAD (Mean Absolute Deviation), the accuracy of the selected models was assessed. The ARIMA (3,1,3) model performed better in forecasting the prices for small cardamom in southern India. COVID-19 (2019–2020) had a significant impact on the price of small cardamom in southern India, where the price has more fluctuations with a variance of 639,147.93 compared to the forecasted price variance of 65,199.97.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
2.
go back to reference Mohanamani D (2018) Price forecasting of cardamom(large) using ARIMA model. 119(17):2537–2547 Mohanamani D (2018) Price forecasting of cardamom(large) using ARIMA model. 119(17):2537–2547
3.
go back to reference Raj N, Chacko A (2020) Struggle of cardamom growers: local level study in Idukki district of kerala. Int J Multidiscip Res Rev 6(2). www.ijmdrr.com Raj N, Chacko A (2020) Struggle of cardamom growers: local level study in Idukki district of kerala. Int J Multidiscip Res Rev 6(2). www.​ijmdrr.​com
11.
go back to reference Bessler DA (2010) Price forecasting methods and evaluation procedures drought impacts on cattle market integration in the Horn of Africa: a preliminary evaluation using VAR and structural break analysis view project traffic fatalities view project Bessler DA (2010) Price forecasting methods and evaluation procedures drought impacts on cattle market integration in the Horn of Africa: a preliminary evaluation using VAR and structural break analysis view project traffic fatalities view project
12.
go back to reference Nayak RK et al (2021) Indian stock market prediction based on rough set and support vector machine approach. In: Mishra D, Buyya R, Mohapatra P, Patnaik S (eds) Intelligent and cloud computing. smart innovation, systems and technologies 153:345–355. Springer, Singapore Nayak RK et al (2021) Indian stock market prediction based on rough set and support vector machine approach. In: Mishra D, Buyya R, Mohapatra P, Patnaik S (eds) Intelligent and cloud computing. smart innovation, systems and technologies 153:345–355. Springer, Singapore
13.
go back to reference Ticlavilca AM, Feuz DM, Mckee M (2015) Forecasting agricultural commodity prices using multivariate bayesian machine learning regression. 3(1): 10–17 Ticlavilca AM, Feuz DM, Mckee M (2015) Forecasting agricultural commodity prices using multivariate bayesian machine learning regression. 3(1): 10–17
14.
go back to reference Jalikatti VN, Chourad R, Gumgolmath M, Sarfaraz S, Shreya A (2014) Price forecasting of onion in Bijapur market of northern Karnataka using ARIMA technique. Int J Commer Bus Manag 7(1):135–141 Jalikatti VN, Chourad R, Gumgolmath M, Sarfaraz S, Shreya A (2014) Price forecasting of onion in Bijapur market of northern Karnataka using ARIMA technique. Int J Commer Bus Manag 7(1):135–141
15.
go back to reference Darekar AS, Pokharkar VG, Datarkar SB (2016) Onion price forecasting in Kolhapur market of Western Maharashtra using arima technique. 3(12):3364–3368 Darekar AS, Pokharkar VG, Datarkar SB (2016) Onion price forecasting in Kolhapur market of Western Maharashtra using arima technique. 3(12):3364–3368
Metadata
Title
Forecasting Price of Small Cardamom in Southern India Using ARIMA Model
Authors
Jagadeesh Babu Myneedi
Nitin Kumar Lautre
Ravikumar Dumpala
Copyright Year
2023
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-1328-2_4

Premium Partners