IDEAS home Printed from https://ideas.repec.org/a/seg/012016/v2y2017i2p141-148.html
   My bibliography  Save this article

A New Empirical Investigation Of The Platinum Spot Returns

Author

Listed:
  • Simone Kruse

    (University of Mannheim)

  • Thomas Tischer

    (Deutsche Bundesbank)

  • Timo Wittig

    (University of Bayreuth)

Abstract

The global platinum market has been in downturn and unstable for five consecutive years, and thus market participants are demanding effective quantitative risk management tools. Since platinum is so widely used and serves as an important investment vehicle, the importance of risk management of platinum spot returns cannot be understated. In this paper, we take advantage of a very popular econometric model, the generalized autoregressive conditional heteroscedasticity (GARCH) model, for platinum returns. We received two important findings by using the conventional GARCH models in explain daily platinum spot returns. First, it is crucial to introduce heavy-tailed distribution to explain conditional heavy tails; and second, the NRIG distribution performs better than the most widely-used heavy-tailed distribution, the Student’s t distribution.

Suggested Citation

  • Simone Kruse & Thomas Tischer & Timo Wittig, 2017. "A New Empirical Investigation Of The Platinum Spot Returns," Journal of Smart Economic Growth, , vol. 2(2), pages 141-148, September.
    • Handle: RePEc:seg:012016:v:2:y:2017:i:2:p:141-148
    as

    Download full text from publisher

    File URL: https://jseg.ro/index.php/jseg/article/view/21/21
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guo, Zi-Yi, 2017. "Models with Short-Term Variations and Long-Term Dynamics in Risk Management of Commodity Derivatives," EconStor Preprints 167619, ZBW - Leibniz Information Centre for Economics.
    2. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2012. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(2), pages 207-218.
    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. McCown, James Ross & Shaw, Ron, 2017. "Investment potential and risk hedging characteristics of platinum group metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 328-337.
    5. Klein, Tony, 2017. "Dynamic correlation of precious metals and flight-to-quality in developed markets," Finance Research Letters, Elsevier, vol. 23(C), pages 283-290.
    6. Zi-Yi Guo & Yangxiaoteng Luo, 2017. "Dynamic Stochastic Factors, Risk Management and the Energy Futures," International Business Research, Canadian Center of Science and Education, vol. 10(9), pages 50-59, September.
    7. Su, Jung-Bin & Hung, Jui-Cheng, 2011. "Empirical analysis of jump dynamics, heavy-tails and skewness on value-at-risk estimation," Economic Modelling, Elsevier, vol. 28(3), pages 1117-1130, May.
    8. Zi-Yi Guo, 2017. "A Stochastic Factor Model for Risk Management of Commodity Derivatives," Proceedings of Economics and Finance Conferences 4507452, International Institute of Social and Economic Sciences.
    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. Andrew Maree & Peter Card & Paul Kidman, 2017. "Heavy-tailed distribution, GARCH models and the silver returns," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 7(2), pages 1351-1351.

    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. Ahmed, Walid M.A., 2018. "On the interdependence of natural gas and stock markets under structural breaks," The Quarterly Review of Economics and Finance, Elsevier, vol. 67(C), pages 149-161.
    2. Gavriilidis, Konstantinos & Kambouroudis, Dimos S. & Tsakou, Katerina & Tsouknidis, Dimitris A., 2018. "Volatility forecasting across tanker freight rates: The role of oil price shocks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 376-391.
    3. Talbi, Marwa & de Peretti, Christian & Belkacem, Lotfi, 2020. "Dynamics and causality in distribution between spot and future precious metals: A copula approach," Resources Policy, Elsevier, vol. 66(C).
    4. Malinda & Maya & Jo-Hui & Chen, 2022. "Testing for the Long Memory and Multiple Structural Breaks in Consumer ETFs," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 12(6), pages 1-6.
    5. Yoon Hong & Ji-chul Lee & Guoping Ding, 2017. "Volatility Clustering, New Heavy-Tailed Distribution and the Stock Market Returns in South Korea," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 6(3), pages 164-169, September.
    6. Andrew Maree & Peter Card & Paul Kidman, 2017. "Heavy-tailed distribution, GARCH models and the silver returns," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 7(2), pages 1351-1351.
    7. 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.
    8. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    9. Naeem, Muhammad Abubakr & Hasan, Mudassar & Arif, Muhammad & Suleman, Muhammad Tahir & Kang, Sang Hoon, 2022. "Oil and gold as a hedge and safe-haven for metals and agricultural commodities with portfolio implications," Energy Economics, Elsevier, vol. 105(C).
    10. Gil-Alana, Luis A. & Tripathy, Trilochan, 2014. "Modelling volatility persistence and asymmetry: A Study on selected Indian non-ferrous metals markets," Resources Policy, Elsevier, vol. 41(C), pages 31-39.
    11. Luu Duc Huynh, Toan, 2020. "The effect of uncertainty on the precious metals market: New insights from Transfer Entropy and Neural Network VAR," Resources Policy, Elsevier, vol. 66(C).
    12. Su, Jung-Bin, 2014. "Empirical analysis of long memory, leverage, and distribution effects for stock market risk estimates," The North American Journal of Economics and Finance, Elsevier, vol. 30(C), pages 1-39.
    13. Mensi, Walid & Nekhili, Ramzi & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Oil and precious metals: Volatility transmission, hedging, and safe haven analysis from the Asian crisis to the COVID-19 crisis," Economic Analysis and Policy, Elsevier, vol. 71(C), pages 73-96.
    14. 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.
    15. Hasan, Md. Bokhtiar & Hassan, M. Kabir & Rashid, Md. Mamunur & Alhenawi, Yasser, 2021. "Are safe haven assets really safe during the 2008 global financial crisis and COVID-19 pandemic?," Global Finance Journal, Elsevier, vol. 50(C).
    16. Mokni, Khaled & Al-Shboul, Mohammed & Assaf, Ata, 2021. "Economic policy uncertainty and dynamic spillover among precious metals under market conditions: Does COVID-19 have any effects?," Resources Policy, Elsevier, vol. 74(C).
    17. Ramzi Nekhili & Jahangir Sultan, 2020. "Jump Driven Risk Model Performance in Cryptocurrency Market," IJFS, MDPI, vol. 8(2), pages 1-18, April.
    18. Hussain Shahzad, Syed Jawad & Bouri, Elie & Roubaud, David & Kristoufek, Ladislav, 2020. "Safe haven, hedge and diversification for G7 stock markets: Gold versus bitcoin," Economic Modelling, Elsevier, vol. 87(C), pages 212-224.
    19. 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).
    20. Bentes, Sónia R., 2022. "On the stylized facts of precious metals’ volatility: A comparative analysis of pre- and during COVID-19 crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).

    More about this item

    Keywords

    GARCH model; fat tails; platinum spot returns;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    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:seg:012016:v:2:y:2017:i:2:p:141-148. 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: Radu Lixandroiu (email available below). General contact details of provider: .

    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.