IDEAS home Printed from https://ideas.repec.org/a/apb/jaterr/2016p118-124.html
   My bibliography  Save this article

Application of soft computing technique in the modelling and prediction of gold and silver rates

Author

Listed:
  • M. Dhiyanji

    (Department of Commerce, Madras University, Chennai, Tamilnadu, India)

  • K. Sundaravadivu

    (Department of Electronics and Instrumentation Engineering, Anna University, Chennai, India)

Abstract

Over the past few years the modelling approach is widely used to discover the complex and dynamic relationship between various profitable variables. This paper focuses on the modeling of gold and silver rates with respect to a certain period of time and also on the prediction of the gold and silver rates. In this paper, with the assistance of Particle Swarm Optimization (PSO) algorithm, the BOX JENKINS and the Auto Regressive Integrated Moving Average(ARIMA) models are developed for the considered economic variables. A comparative study is also presented to assure the model accuracy. Following that, the PSO based KALMAN FILTER DESIGN approach is implemented on the gold and silver rates in order to forecast the market prices. In today's unpredictable world, investors believe that gold can act as a hedge against unexpected disasters, both natural and economical. Therefore forecasting the price of gold has been of highest interest. The major advantage of the proposed PSO based modeling and prediction approach is that, it is a fully automated method which results in higher flexibility and greater accuracy. This study also confirms that the PSO based ARIMA model yields a better result than the PSO based BOX JENKINS model. The proposed PSO based KALMAN FILTER approach also provides better prediction.

Suggested Citation

  • M. Dhiyanji & K. Sundaravadivu, 2016. "Application of soft computing technique in the modelling and prediction of gold and silver rates," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 2(4), pages 118-124.
    • Handle: RePEc:apb:jaterr:2016:p:118-124
    DOI: 10.20474/jater-2.4.3
    as

    Download full text from publisher

    File URL: https://tafpublications.com/platform/Articles/full-jater2.4.3.php
    Download Restriction: no
    File URL: https://tafpublications.com/gip_content/paper/jater-2.4.3.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.20474/jater-2.4.3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Selvanathan, Saroja & Selvanathan, E. A., 1999. "The effect of the price of gold on its production: a time-series analysis," Resources Policy, Elsevier, vol. 25(4), pages 265-275, December.
    2. Shafiee, Shahriar & Topal, Erkan, 2010. "An overview of global gold market and gold price forecasting," Resources Policy, Elsevier, vol. 35(3), pages 178-189, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Maria Immanuvel S & Daniel Lazar, 2022. "Does Volume of Gold Consumption Influence the World Gold Price?," JRFM, MDPI, vol. 15(7), pages 1-14, June.
    2. Ntim, Collins G. & English, John & Nwachukwu, Jacinta & Wang, Yan, 2015. "On the efficiency of the global gold markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 218-236.
    3. Ntantamis, Christos & Zhou, Jun, 2015. "Bull and bear markets in commodity prices and commodity stocks: Is there a relation?," Resources Policy, Elsevier, vol. 43(C), pages 61-81.
    4. Raza, Syed Ali & Masood, Amna & Benkraiem, Ramzi & Urom, Christian, 2023. "Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach," Energy Economics, Elsevier, vol. 120(C).
    5. Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015. "Forecasting the price of gold," Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
    6. Alameer, Zakaria & Elaziz, Mohamed Abd & Ewees, Ahmed A. & Ye, Haiwang & Jianhua, Zhang, 2019. "Forecasting gold price fluctuations using improved multilayer perceptron neural network and whale optimization algorithm," Resources Policy, Elsevier, vol. 61(C), pages 250-260.
    7. Davidson, Sinclair & Faff, Robert & Hillier, David, 2003. "Gold factor exposures in international asset pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 13(3), pages 271-289, July.
    8. Zhang, Guangyong & Jiang, Le & Tian, Lixin & Fu, Min, 2021. "Analysis of the gold fixing price fluctuation in different times based on the directed weighted networks," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    9. Magambo, Isaiah & Dikgang, Johane & Gelo, Dambala & Tregenna, Fiona, 2021. "Environmental and Technical Efficiency in Large Gold Mines in Developing Countries," MPRA Paper 108068, University Library of Munich, Germany.
    10. Aviral K. Tiwari & Claudiu T. Albulescu & Rangan Gupta, 2016. "Time-frequency relationship between US output with commodity and asset prices," Applied Economics, Taylor & Francis Journals, vol. 48(3), pages 227-242, January.
    11. Biswas, Pritam & Sinha, Rabindra Kumar & Sen, Phalguni, 2023. "A review of state-of-the-art techniques for the determination of the optimum cut-off grade of a metalliferous deposit with a bibliometric mapping in a surface mine planning context," Resources Policy, Elsevier, vol. 83(C).
    12. Ewees, Ahmed A. & Elaziz, Mohamed Abd & Alameer, Zakaria & Ye, Haiwang & Jianhua, Zhang, 2020. "Improving multilayer perceptron neural network using chaotic grasshopper optimization algorithm to forecast iron ore price volatility," Resources Policy, Elsevier, vol. 65(C).
    13. Amélie Charles & Olivier Darné & Jae H. Kim, 2014. "Precious metals shine? A market efficiency perspective," Working Papers hal-01010516, HAL.
    14. Aye, Goodness C. & Carcel, Hector & Gil-Alana, Luis A. & Gupta, Rangan, 2017. "Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016," Resources Policy, Elsevier, vol. 54(C), pages 53-57.
    15. Jain, Anshul & Ghosh, Sajal, 2013. "Dynamics of global oil prices, exchange rate and precious metal prices in India," Resources Policy, Elsevier, vol. 38(1), pages 88-93.
    16. Białkowski, Jędrzej & Bohl, Martin T. & Stephan, Patrick M. & Wisniewski, Tomasz P., 2015. "The gold price in times of crisis," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 329-339.
    17. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou, 2021. "Gold Against the Machine," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 5-28, January.
    18. Li, Gang & Li, Yong, 2015. "Forecasting copper futures volatility under model uncertainty," Resources Policy, Elsevier, vol. 46(P2), pages 167-176.
    19. Kuruppuarachchi, Duminda & Lin, Hai & Premachandra, I.M., 2019. "Testing commodity futures market efficiency under time-varying risk premiums and heteroscedastic prices," Economic Modelling, Elsevier, vol. 77(C), pages 92-112.
    20. Zhao, Jue & Hosseini, Shahab & Chen, Qinyang & Jahed Armaghani, Danial, 2023. "Super learner ensemble model: A novel approach for predicting monthly copper price in future," Resources Policy, Elsevier, vol. 85(PB).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:apb:jaterr:2016:p:118-124. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: A/Professor Akbar A. Khatibi (email available below). General contact details of provider: https://tafpublications.com/platform/published_papers/10 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.