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What Explains the Volatility in Pakistan’s Sovereign Bond Yields?

Author

Listed:
  • Mohsin Waheed

    (State Bank of Pakistan)

  • Zulfiqar Hyder

    (State Bank of Pakistan)

Abstract

In this paper, we determine the significant domestic and external drivers of volatility in Pakistan’s sovereign bond yield-to-maturity (YTM) across different tenors. We use a class of volatility models (GARCH, TGARCH, and EGARCH) on daily data starting from January 2019 to October 2022. We find that, in addition to domestic macroeconomic fundamentals, political factors also contribute substantially to the volatility in bond yields. Additionally, we also argue that foreign investors’ risk perception is susceptible to exchange rate depreciation, import cover, and sovereign ratings. On the external side, we find that the general riskiness perception of emerging market bonds as measured by Emerging Market Bond Index Spreads significantly explains the volatility of Pakistan’s sovereign bonds.

Suggested Citation

  • Mohsin Waheed & Zulfiqar Hyder, 2023. "What Explains the Volatility in Pakistan’s Sovereign Bond Yields?," SBP Working Paper Series 112, State Bank of Pakistan, Research Department.
    • Handle: RePEc:sbp:wpaper:112
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    File URL: https://www.sbp.org.pk/publications/wpapers/2023/wp112.pdf
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    References listed on IDEAS

    as
    1. Johri, Alok & Khan, Shahed & Sosa-Padilla, César, 2022. "Interest rate uncertainty and sovereign default risk," Journal of International Economics, Elsevier, vol. 139(C).
    2. Samir Jahjah & Bin Wei & Vivian Zhanwei Yue, 2013. "Exchange Rate Policy and Sovereign Bond Spreads in Developing Countries," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(7), pages 1275-1300, October.
    3. Guglielmo Maria Caporale & Fabio Spagnolo & Nicola Spagnolo, 2018. "Macro news and bond yield spreads in the euro area," The European Journal of Finance, Taylor & Francis Journals, vol. 24(2), pages 114-134, January.
    4. Fang, WenShwo & Miller, Stephen M., 2009. "Modeling the volatility of real GDP growth: The case of Japan revisited," Japan and the World Economy, Elsevier, vol. 21(3), pages 312-324, August.
    5. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    6. Mr. Serhan Cevik & João Tovar Jalles, 2020. "This Changes Everything: Climate Shocks and Sovereign Bonds," IMF Working Papers 2020/079, International Monetary Fund.
    7. 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.
    8. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    9. Balduzzi, Pierluigi & Elton, Edwin J. & Green, T. Clifton, 2001. "Economic News and Bond Prices: Evidence from the U.S. Treasury Market," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(4), pages 523-543, December.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. Otaviano Canuto, 2022. "Quantitative Tightening and Capital Flows to Emerging Markets," Policy notes & Policy briefs 1982, Policy Center for the New South.
    12. Moser, Christoph, 2007. "The Impact of Political Risk on Sovereign Bond Spreads - Evidence from Latin America," Proceedings of the German Development Economics Conference, Göttingen 2007 24, Verein für Socialpolitik, Research Committee Development Economics.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Volatility; Sovereign bonds; Yield; Eurobond; Sukuk; Spreads;
    All these keywords.

    JEL classification:

    • B26 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Financial Economics
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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