IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v79y2022ics0301420722005529.html
   My bibliography  Save this article

Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine

Author

Listed:
  • Das, Sudeepa
  • Sahu, Tirath Prasad
  • Janghel, Rekh Ram

Abstract

Crude oil price has a large influence on global environment and economy of the country. Similarly, gold price has also impact on economy and it reflects the economy strength of a country. So, the prediction of nonlinear oil and gold prices is the most prominent and arduous factor. In this work, Cluster-based Quasi oppositional based Crow Search Algorithm (CQCSA) optimized Extreme Learning Machine-Fuzzy Inference System (ELMFIS) is proposed for oil and gold price prediction. The consolidation of FIS with ELM is established with benefits of better capability to handle nonlinear data and improved adaptation. The relevant parameters of ELMFIS are elected by CQCSA technique. The CSA algorithm is modified to CQCSA by converting the drawbacks of CSA into the capability to solve a complex problem with high dimension efficiently. The proposed learning algorithm performance is compared with CSA ELMFIS, ELMFIS, ANFIS and ELM models by conceding the performance measures and hypotheses tests. The result suggests that the proposed predictive model can be a promising technique to predict and analysis of oil and gold price.

Suggested Citation

  • Das, Sudeepa & Sahu, Tirath Prasad & Janghel, Rekh Ram, 2022. "Oil and gold price prediction using optimized fuzzy inference system based extreme learning machine," Resources Policy, Elsevier, vol. 79(C).
    • Handle: RePEc:eee:jrpoli:v:79:y:2022:i:c:s0301420722005529
    DOI: 10.1016/j.resourpol.2022.103109
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722005529
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.103109?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dirk G. Baur & Brian M. Lucey, 2010. "Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold," The Financial Review, Eastern Finance Association, vol. 45(2), pages 217-229, May.
    2. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    3. Narayan, Paresh Kumar & Narayan, Seema & Zheng, Xinwei, 2010. "Gold and oil futures markets: Are markets efficient?," Applied Energy, Elsevier, vol. 87(10), pages 3299-3303, October.
    4. Leandro Maciel & Fernando Gomide & Rosangela Ballini, 2016. "Evolving Fuzzy-GARCH Approach for Financial Volatility Modeling and Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 379-398, October.
    5. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    6. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    7. Mensi, Walid & Sensoy, Ahmet & Vo, Xuan Vinh & Kang, Sang Hoon, 2020. "Impact of COVID-19 outbreak on asymmetric multifractality of gold and oil prices," Resources Policy, Elsevier, vol. 69(C).
    8. Ewing, Bradley T. & Malik, Farooq, 2013. "Volatility transmission between gold and oil futures under structural breaks," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 113-121.
    9. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
    10. Baur, Dirk G. & McDermott, Thomas K., 2010. "Is gold a safe haven? International evidence," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1886-1898, August.
    11. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    12. 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.
    13. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
    14. Ghosh, Sajal, 2011. "Examining crude oil price - Exchange rate nexus for India during the period of extreme oil price volatility," Applied Energy, Elsevier, vol. 88(5), pages 1886-1889, May.
    15. Soytas, Ugur & Sari, Ramazan & Hammoudeh, Shawkat & Hacihasanoglu, Erk, 2009. "World oil prices, precious metal prices and macroeconomy in Turkey," Energy Policy, Elsevier, vol. 37(12), pages 5557-5566, December.
    16. Reboredo, Juan C., 2013. "Is gold a hedge or safe haven against oil price movements?," Resources Policy, Elsevier, vol. 38(2), pages 130-137.
    17. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    18. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
    19. Tiwari, Aviral Kumar & Sahadudheen, I., 2015. "Understanding the nexus between oil and gold," Resources Policy, Elsevier, vol. 46(P2), pages 85-91.
    20. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
    21. Chang, Hsiao-Fen & Huang, Liang-Chou & Chin, Ming-Chin, 2013. "Interactive relationships between crude oil prices, gold prices, and the NT–US dollar exchange rate—A Taiwan study," Energy Policy, Elsevier, vol. 63(C), pages 441-448.
    22. Sun, Jingyun & Zhao, Panpan & Sun, Shaolong, 2022. "A new secondary decomposition-reconstruction-ensemble approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 77(C).
    23. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    24. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    25. Salim Lahmiri, 2020. "A predictive system integrating intrinsic mode functions, artificial neural networks, and genetic algorithms for forecasting S&P500 intra‐day data," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(2), pages 55-65, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mao, Qian & Ma, Xinyuan & Sun, Yunpeng, 2023. "Study of impacts of blockchain technology on renewable energy resource findings," Renewable Energy, Elsevier, vol. 211(C), pages 802-808.

    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. Kanjilal, Kakali & Ghosh, Sajal, 2017. "Dynamics of crude oil and gold price post 2008 global financial crisis – New evidence from threshold vector error-correction model," Resources Policy, Elsevier, vol. 52(C), pages 358-365.
    2. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    3. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    4. Liu, Min & Lee, Chien-Chiang, 2022. "Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS," Resources Policy, Elsevier, vol. 76(C).
    5. Wang, Xinya & Lucey, Brian & Huang, Shupei, 2022. "Can gold hedge against oil price movements: Evidence from GARCH-EVT wavelet modeling," Journal of Commodity Markets, Elsevier, vol. 27(C).
    6. İrfan Civcir & Uğur Akkoç, 2021. "Dynamic volatility linkages and hedging between commodities and sectoral stock returns in Turkey: Evidence from SVAR‐cDCC‐GARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1978-1992, April.
    7. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan & Gkillas, Konstantinos, 2020. "Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model," Energy Economics, Elsevier, vol. 88(C).
    8. Mehmet Balcilar & Zeynel Abidin Ozdemir & Muhammad Shahbaz & Serkan Gunes, 2017. "Does Inflation Cause Gold Prices? Evidence from G7 Countries," Working Papers 15-31, Eastern Mediterranean University, Department of Economics.
    9. Mehmet Balcilar & Zeynel Abidin Ozdemir & Muhammad Shahbaz & Serkan Gunes, 2018. "Does inflation cause gold market price changes? evidence on the G7 countries from the tests of nonparametric quantile causality in mean and variance," Applied Economics, Taylor & Francis Journals, vol. 50(17), pages 1891-1909, April.
    10. O'Connor, Fergal A. & Lucey, Brian M. & Batten, Jonathan A. & Baur, Dirk G., 2015. "The financial economics of gold — A survey," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 186-205.
    11. Raggad, Bechir & Bouri, Elie, 2023. "Gold and crude oil: A time-varying causality across various market conditions," Resources Policy, Elsevier, vol. 86(PA).
    12. Shahbaz, Muhammad & Balcilar, Mehmet & Abidin Ozdemir, Zeynel, 2017. "Does oil predict gold? A nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 52(C), pages 257-265.
    13. Dutta, Anupam & Bouri, Elie & Roubaud, David, 2019. "Nonlinear relationships amongst the implied volatilities of crude oil and precious metals," Resources Policy, Elsevier, vol. 61(C), pages 473-478.
    14. Singhal, Shelly & Choudhary, Sangita & Biswal, Pratap Chandra, 2019. "Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico," Resources Policy, Elsevier, vol. 60(C), pages 255-261.
    15. Semei Coronado & Rebeca Jim'enez-Rodr'iguez & Omar Rojas, 2015. "An empirical analysis of the relationships between crude oil, gold and stock markets," Papers 1510.07599, arXiv.org, revised May 2016.
    16. Muhammad Shafiullah & Sajid M. Chaudhry & Muhammad Shahbaz & Juan C. Reboredo, 2021. "Quantile causality and dependence between crude oil and precious metal prices," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6264-6280, October.
    17. Mohamed Arbi Madani & Zied Ftiti, 2019. "The Generalisation of the DMCA Coefficient to Serve Distinguishing Between Hedge and Safe Haven Capabilities of the Gold," Papers 1912.12590, arXiv.org.
    18. Walid Chkili, 2015. "Gold–oil prices co-movements and portfolio diversification implications," Economics Bulletin, AccessEcon, vol. 35(4), pages 2832-2845.
    19. Mishra, Aswini Kumar & Ghate, Kshitish & Renganathan, Jayashree & Kennet, Joushita J. & Rajderkar, Nilay Pradeep, 2022. "Rolling, recursive evolving and asymmetric causality between crude oil and gold prices: Evidence from an emerging market," Resources Policy, Elsevier, vol. 75(C).
    20. Golitsis, Petros & Gkasis, Pavlos & Bellos, Sotirios K., 2022. "Dynamic spillovers and linkages between gold, crude oil, S&P 500, and other economic and financial variables. Evidence from the USA," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).

    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:eee:jrpoli:v:79:y:2022:i:c:s0301420722005529. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.