IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v50y2016icp224-233.html
   My bibliography  Save this article

Multiscale dependence analysis and portfolio risk modeling for precious metal markets

Author

Listed:
  • He, Kaijian
  • Liu, Youjin
  • Yu, Lean
  • Lai, Kin Keung

Abstract

In this paper, we propose a new Bivariate EMD copula based approach to analyze and model the multiscale dependence structure in the precious metal markets. The proposed model constructs the Copula based dependence structure formulation in the Bivariate Empirical Mode Decomposition (BEMD) transformed multiscale domain. We further propose the BEMD Copula based Portfolio Value at Risk (PVaR) model to estimate the precious metal market risk measure. Empirical studies in the typical precious metal markets have been conducted. We found the evidence of multiscale structure of the time varying dependence structure among precious metal markets. We show that significantly improved portfolio risk forecasting performance could be achieved with the proposed model when the multiscale dependence structure is taken into account during the modeling process.

Suggested Citation

  • He, Kaijian & Liu, Youjin & Yu, Lean & Lai, Kin Keung, 2016. "Multiscale dependence analysis and portfolio risk modeling for precious metal markets," Resources Policy, Elsevier, vol. 50(C), pages 224-233.
  • Handle: RePEc:eee:jrpoli:v:50:y:2016:i:c:p:224-233
    DOI: 10.1016/j.resourpol.2016.09.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420716303130
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2016.09.011?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. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    2. Peter Reinhard Hansen & Allan Timmermann, 2012. "Choice of Sample Split in Out-of-Sample Forecast Evaluation," CREATES Research Papers 2012-43, Department of Economics and Business Economics, Aarhus University.
    3. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    4. Rossen, Anja, 2015. "What are metal prices like? Co-movement, price cycles and long-run trends," Resources Policy, Elsevier, vol. 45(C), pages 255-276.
    5. Sensoy, Ahmet, 2013. "Dynamic relationship between precious metals," Resources Policy, Elsevier, vol. 38(4), pages 504-511.
    6. Wang, Yi-Chiuan & Wu, Jyh-Lin & Lai, Yi-Hao, 2013. "A revisit to the dependence structure between the stock and foreign exchange markets: A dependence-switching copula approach," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1706-1719.
    7. Sukcharoen, Kunlapath & Zohrabyan, Tatevik & Leatham, David & Wu, Ximing, 2014. "Interdependence of oil prices and stock market indices: A copula approach," Energy Economics, Elsevier, vol. 44(C), pages 331-339.
    8. Dirk Baur & Duy Tran, 2014. "The long-run relationship of gold and silver and the influence of bubbles and financial crises," Empirical Economics, Springer, vol. 47(4), pages 1525-1541, December.
    9. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    10. Cheng, Wan-Hsiu & Hung, Jui-Cheng, 2011. "Skewness and leptokurtosis in GARCH-typed VaR estimation of petroleum and metal asset returns," Journal of Empirical Finance, Elsevier, vol. 18(1), pages 160-173, January.
    11. Kaijian He & Kin Keung Lai & Guocheng Xiang, 2012. "Portfolio Value at Risk Estimate for Crude Oil Markets: A Multivariate Wavelet Denoising Approach," Energies, MDPI, vol. 5(4), pages 1-26, April.
    12. Balcilar, Mehmet & Hammoudeh, Shawkat & Asaba, Nwin-Anefo Fru, 2015. "A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 72-89.
    13. Massimiliano Caporin & Angelo Ranaldo & Gabriel G. Velo, 2015. "Precious metals under the microscope: a high-frequency analysis," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 743-759, May.
    14. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    15. Demiralay, Sercan & Ulusoy, Veysel, 2014. "Non-linear volatility dynamics and risk management of precious metals," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 183-202.
    16. Antonakakis, Nikolaos & Kizys, Renatas, 2015. "Dynamic spillovers between commodity and currency markets," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 303-319.
    17. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Downside/upside price spillovers between precious metals: A vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 84-102.
    18. Crowley Patrick M., 2012. "How Do You Make A Time Series Sing Like a Choir? Extracting Embedded Frequencies from Economic and Financial Time Series using Empirical Mode Decomposition," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(5), pages 1-31, December.
    19. Zhang, Jin-Liang & Zhang, Yue-Jun & Zhang, Lu, 2015. "A novel hybrid method for crude oil price forecasting," Energy Economics, Elsevier, vol. 49(C), pages 649-659.
    20. Aloui, Riadh & Ben Aïssa, Mohamed Safouane & Nguyen, Duc Khuong, 2013. "Conditional dependence structure between oil prices and exchange rates: A copula-GARCH approach," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 719-738.
    21. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    22. Ghorbel, Ahmed & Trabelsi, Abdelwahed, 2014. "Energy portfolio risk management using time-varying extreme value copula methods," Economic Modelling, Elsevier, vol. 38(C), pages 470-485.
    23. Roberts, Mark C., 2009. "Duration and characteristics of metal price cycles," Resources Policy, Elsevier, vol. 34(3), pages 87-102, September.
    24. Ming, Lei & Yang, Shenggang & Cheng, Cheng, 2016. "The double nature of the price of gold—A quantitative analysis based on Ensemble Empirical Mode Decomposition," Resources Policy, Elsevier, vol. 47(C), pages 125-131.
    25. Afanasyev, Dmitriy O. & Fedorova, Elena A., 2016. "The long-term trends on the electricity markets: Comparison of empirical mode and wavelet decompositions," Energy Economics, Elsevier, vol. 56(C), pages 432-442.
    26. Osvaldo C. Silva Filho & Flavio A. Ziegelmann & Michael J. Dueker, 2014. "Assessing dependence between financial market indexes using conditional time-varying copulas: applications to Value at Risk (VaR)," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2155-2170, December.
    27. Chen, Mei-Hsiu, 2010. "Understanding world metals prices--Returns, volatility and diversification," Resources Policy, Elsevier, vol. 35(3), pages 127-140, September.
    28. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    29. 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.
    30. Ahmed A. A. Khalifa & Hong Miao & Sanjay Ramchander, 2011. "Return distributions and volatility forecasting in metal futures markets: Evidence from gold, silver, and copper," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(1), pages 55-80, January.
    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. Zhang, Pinyi & Ci, Bicong, 2020. "Deep belief network for gold price forecasting," Resources Policy, Elsevier, vol. 69(C).
    2. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
    3. Jose Arreola Hernandez & Sang Hoon Kang & Seong-Min Yoon, 2022. "Spillovers and portfolio optimization of precious metals and global/regional equity markets," Applied Economics, Taylor & Francis Journals, vol. 54(20), pages 2320-2342, April.
    4. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    5. Nekhili, Ramzi & Sultan, Jahangir & Mensi, Walid, 2021. "Co-movements among precious metals and implications for portfolio management: A multivariate wavelet-based dynamic analysis," Resources Policy, Elsevier, vol. 74(C).
    6. Ji, Qiang & Geng, Jiang-Bo & Tiwari, Aviral Kumar, 2018. "Information spillovers and connectedness networks in the oil and gas markets," Energy Economics, Elsevier, vol. 75(C), pages 71-84.
    7. Elsayed, Ahmed H. & Naifar, Nader & Nasreen, Samia & Tiwari, Aviral Kumar, 2022. "Dependence structure and dynamic connectedness between green bonds and financial markets: Fresh insights from time-frequency analysis before and during COVID-19 pandemic," Energy Economics, Elsevier, vol. 107(C).
    8. Al-Yahyaee, Khamis Hamed & Rehman, Mobeen Ur & Wanas Al-Jarrah, Idries Mohammad & Mensi, Walid & Vo, Xuan Vinh, 2020. "Co-movements and spillovers between prices of precious metals and non-ferrous metals: A multiscale analysis," Resources Policy, Elsevier, vol. 67(C).
    9. Martha Carpinteyro & Francisco Venegas-Martínez & Alí Aali-Bujari, 2021. "Modeling Precious Metal Returns through Fractional Jump-Diffusion Processes Combined with Markov Regime-Switching Stochastic Volatility," Mathematics, MDPI, vol. 9(4), pages 1-17, February.
    10. Zou, Yingchao & Yu, Lean & Tso, Geoffrey K.F. & He, Kaijian, 2020. "Risk forecasting in the crude oil market: A multiscale Convolutional Neural Network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

    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. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    2. Bao, Dun, 2020. "Dynamics and correlation of platinum-group metals spot prices," Resources Policy, Elsevier, vol. 68(C).
    3. Reboredo, Juan C. & Ugolini, Andrea, 2015. "Downside/upside price spillovers between precious metals: A vine copula approach," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 84-102.
    4. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Maitra, Debasish & Al-Jarrah, Idries Mohammad Wanas, 2019. "Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach," Resources Policy, Elsevier, vol. 64(C).
    5. Bhatia, Vaneet & Das, Debojyoti & Tiwari, Aviral Kumar & Shahbaz, Muhammad & Hasim, Haslifah M., 2018. "Do precious metal spot prices influence each other? Evidence from a nonparametric causality-in-quantiles approach," Resources Policy, Elsevier, vol. 55(C), pages 244-252.
    6. Vasyl Golosnoy & Anja Rossen, 2018. "Modeling dynamics of metal price series via state space approach with two common factors," Empirical Economics, Springer, vol. 54(4), pages 1477-1501, June.
    7. Jiang, Kunliang & Ye, Wuyi, 2022. "Does the asymmetric dependence volatility affect risk spillovers between the crude oil market and BRICS stock markets?," Economic Modelling, Elsevier, vol. 117(C).
    8. Su, Chi-Wei & Wang, Xiao-Qing & Zhu, Haotian & Tao, Ran & Moldovan, Nicoleta-Claudia & Lobonţ, Oana-Ramona, 2020. "Testing for multiple bubbles in the copper price: Periodically collapsing behavior," Resources Policy, Elsevier, vol. 65(C).
    9. Dutta, Anupam, 2018. "A note on the implied volatility spillovers between gold and silver markets," Resources Policy, Elsevier, vol. 55(C), pages 192-195.
    10. Albulescu, Claudiu Tiberiu & Aubin, Christian & Goyeau, Daniel & Tiwari, Aviral Kumar, 2018. "Extreme co-movements and dependencies among major international exchange rates: A copula approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 56-69.
    11. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2017. "Price forecasting in the precious metal market: A multivariate EMD denoising approach," Resources Policy, Elsevier, vol. 54(C), pages 9-24.
    12. Nekhili, Ramzi & Sultan, Jahangir & Mensi, Walid, 2021. "Co-movements among precious metals and implications for portfolio management: A multivariate wavelet-based dynamic analysis," Resources Policy, Elsevier, vol. 74(C).
    13. Vêlayoudom Marimoutou & Manel Soury, 2015. "Energy Markets and CO2 Emissions: Analysis by Stochastic Copula Autoregressive Model," AMSE Working Papers 1520, Aix-Marseille School of Economics, France.
    14. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    15. Uddin, Gazi Salah & Shahzad, Syed Jawad Hussain & Boako, Gideon & Hernandez, Jose Areola & Lucey, Brian M., 2019. "Heterogeneous interconnections between precious metals: Evidence from asymmetric and frequency-domain spillover analysis," Resources Policy, Elsevier, vol. 64(C).
    16. Karanasos, Menelaos & Menla Ali, Faek & Margaronis, Zannis & Nath, Rajat, 2018. "Modelling time varying volatility spillovers and conditional correlations across commodity metal futures," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 246-256.
    17. Emmanuel Afuecheta & Saralees Nadarajah & Stephen Chan, 2021. "A Statistical Analysis of Global Economies Using Time Varying Copulas," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1167-1194, December.
    18. Guo, Yanfeng & Wen, Xiaoqian & Wu, Yanrui & Guo, Xiumei, 2016. "How is China's coke price related with the world oil price? The role of extreme movements," Economic Modelling, Elsevier, vol. 58(C), pages 22-33.
    19. Balcilar, Mehmet & Ozdemir, Zeynel Abidin, 2019. "The volatility effect on precious metals price returns in a stochastic volatility in mean model with time-varying parameters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    20. Berna Kirkulak-Uludag & Zorikto Lkhamazhapov, 2017. "Volatility Dynamics of Precious Metals: Evidence from Russia," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(4), pages 300-317, August.

    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:50:y:2016:i:c:p:224-233. 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.