IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202161.html

Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios

Author

Listed:
  • Afees A. Salisu

    (Centre for Econometric & Allied Research, University of Ibadan, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Christian Pierdzioch

    (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • David Gabauer

    (Data Analysis Systems, Software Competence Center Hagenberg, Hagenberg, Austria)

Abstract

We examine the predictive value of risk perceptions as measured in terms of the gold-to-silver and gold-to-platinum price ratios for stock-market tail risks and their connectedness in eight major industrialized economies using monthly data for the period 1916:02-2020:10 and 1968:01-2020:10, where we use four variants of the popular Conditional Autoregressive Value at Risk (CAViaR) framework to estimate the tail risks for both 1% and 5% VaRs. Our findings for the short sample period show that the gold-to-silver price ratio resembles the gold-to-platinum price ratios in that it is a useful proxy for global risk. Our findings for the long sample period show, despite some heterogeneity across economies, that the gold-to-silver price ratio often helps to out-of-sample forecast for both 1% and 5% stock market tail risks, particularly when a forecaster suffers a higher loss from underestimation of tail risks than from a corresponding overestimation of the same absolute size. We also find that using the gold-to-silver price ratio for forecasting the total connectedness of stock markets is beneficial for an investor who suffers a higher loss from an underestimation of total connectedness (i.e., an investor who otherwise would overestimate the benefits from portfolio diversification) than from a comparable overestimation.

Suggested Citation

  • Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:202161
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Kyriazis, Nikolaos & Corbet, Shaen, 2024. "Evaluating the dynamic connectedness of financial assets and bank indices during black-swan events: A Quantile-VAR approach," Energy Economics, Elsevier, vol. 131(C).
    3. Demirer, Riza & Gabauer, David & Gupta, Rangan & Nielsen, Joshua, 2024. "Gold, platinum and the predictability of bubbles in global stock markets," Resources Policy, Elsevier, vol. 90(C).
    4. Zhang, Yi & Zhou, Long & Wu, Baoxiu & Liu, Fang, 2024. "Tail risk transmission from the United States to emerging stock Markets: Empirical evidence from multivariate quantile analysis," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
    5. Riza Demirer & David Gabauer & Rangan Gupta & Joshua Nielsen, 2023. "Gold-to-Platinum Price Ratio and the Predictability of Bubbles in Financial Markets," Working Papers 202317, University of Pretoria, Department of Economics.
    6. Kyriazis, Nikolaos A. & Papadamou, Stephanos & Tzeremes, Panayiotis, 2023. "Are benchmark stock indices, precious metals or cryptocurrencies efficient hedges against crises?," Economic Modelling, Elsevier, vol. 128(C).
    7. Wang, Jiashun & Wang, Jiqian & Ma, Feng, 2024. "International commodity market and stock volatility predictability: Evidence from G7 countries," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 62-71.
    8. Choi, Insu & Kim, Woo Chang, 2023. "Estimating Historical Downside Risks of Global Financial Market Indices via Inflation Rate-Adjusted Dependence Graphs," Research in International Business and Finance, Elsevier, vol. 66(C).
    9. Sobti, Neharika, 2025. "What triggers intraday price jumps and co-jumps in gold?," International Review of Financial Analysis, Elsevier, vol. 105(C).
    10. Kejin Wu & Sayar Karmakar & Rangan Gupta & Christian Pierdzioch, 2023. "Climate Risks and Stock Market Volatility Over a Century in an Emerging Market Economy: The Case of South Africa," Working Papers 202326, University of Pretoria, Department of Economics.
    11. İhsan Erdem Kayral & Melike Aktaş Bozkurt & Sahar Loukil & Ahmed Jeribi, 2025. "Market Resilience Unveiled: Insights from Quantile Time Frequency Connectedness into Emerging Countries Stock Indices," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(2), pages 7781-7815, June.

    More about this item

    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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:pre:wpaper:202161. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.