IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v78y2022icp141-152.html
   My bibliography  Save this article

Measuring volatility persistence in leveraged loan markets in the presence of structural breaks

Author

Listed:
  • Aikins Abakah, Emmanuel Joel
  • Gil-Alana, Luis A.
  • Arthur, Emmanuel Kwesi
  • Tiwari, Aviral Kumar

Abstract

This paper examines volatility persistence in leverage loan market price series for Australia, Canada, Europe, Japan, Singapore, UK and USA in the presence of structural breaks. To the best of our knowledge, this is the first empirical study to examine volatility persistence in the leveraged loan markets. To this end, using fractional integration methods, the results indicate that both absolute and squared returns display long memory features, with orders of integration confirming the long memory hypothesis. However, after accounting for structural breaks, we find a reduction in the degree of persistence in the leveraged loan market. The evidence of persistence in volatility implies that market participants who want to make gains across trading scales need to factor the persistence properties of leveraged loan price series in their valuation and forecasting models since that will help improve long-term volatility market forecasts and optimal hedging decisions.

Suggested Citation

  • Aikins Abakah, Emmanuel Joel & Gil-Alana, Luis A. & Arthur, Emmanuel Kwesi & Tiwari, Aviral Kumar, 2022. "Measuring volatility persistence in leveraged loan markets in the presence of structural breaks," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 141-152.
    • Handle: RePEc:eee:reveco:v:78:y:2022:i:c:p:141-152
    DOI: 10.1016/j.iref.2021.11.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S105905602100246X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.iref.2021.11.016?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. Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016. "Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
    2. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.
    3. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
    4. Gromb, Denis & Vayanos, Dimitri, 2002. "Equilibrium and welfare in markets with financially constrained arbitrageurs," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 361-407.
    5. Carlos González Pedraz, 2019. "Leveraged loans: definition and market development," Economic Bulletin, Banco de España, issue DEC.
    6. Dan Vu Cao, 2010. "Collateral Shortages, Asset Price And Investment Volatility With Heterogeneous Beliefs," 2010 Meeting Papers 1233, Society for Economic Dynamics.
    7. Ana Fostel & John Geanakoplos, 2012. "Tranching, CDS, and Asset Prices: How Financial Innovation Can Cause Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 190-225, January.
    8. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    9. Luis A. Gil‐Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
    10. Markus K. Brunnermeier & Lasse Heje Pedersen, 2009. "Market Liquidity and Funding Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2201-2238, June.
    11. Gil-Alana, Luis A. & Moreno, Antonio, 2012. "Uncovering the US term premium: An alternative route," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1181-1193.
    12. Mirko Abbritti & Luis A. Gil-Alana & Yuliya Lovcha & Antonio Moreno, 2016. "Term Structure Persistence," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 331-352.
    13. Ana Fostel & John Geanakoplos, 2011. "Endogenous Leverage: VaR and Beyond," Cowles Foundation Discussion Papers 1800, Cowles Foundation for Research in Economics, Yale University.
    14. John Geanakoplos & Ana Fostel, 2008. "Leverage Cycles and the Anxious Economy," American Economic Review, American Economic Association, vol. 98(4), pages 1211-1244, September.
    15. Gorton, Gary & Metrick, Andrew, 2012. "Securitized banking and the run on repo," Journal of Financial Economics, Elsevier, vol. 104(3), pages 425-451.
    16. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    17. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2017. "Asymmetric volatility connectedness on the forex market," Journal of International Money and Finance, Elsevier, vol. 77(C), pages 39-56.
    18. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    19. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    20. Jim Armstrong, 2003. "The Syndicated Loan Market: Developments in the North American Context," Staff Working Papers 03-15, Bank of Canada.
    21. Hou, Jie & Perron, Pierre, 2014. "Modified local Whittle estimator for long memory processes in the presence of low frequency (and other) contaminations," Journal of Econometrics, Elsevier, vol. 182(2), pages 309-328.
    22. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    23. Viral V. Acharya & S. Viswanathan, 2011. "Leverage, Moral Hazard, and Liquidity," Journal of Finance, American Finance Association, vol. 66(1), pages 99-138, February.
    24. Luis A. Gil†Alana & Robert Mudida, 2018. "The growth rate series in Kenya: Evidence of non†linearities and factors behind the slow growth," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 23(2), pages 111-121, April.
    25. Berlin, Mitchell & Nini, Greg & Yu, Edison G., 2020. "Concentration of control rights in leveraged loan syndicates," Journal of Financial Economics, Elsevier, vol. 137(1), pages 249-271.
    26. Alexander Rodnyansky & Olivier M. Darmouni, 2017. "The Effects of Quantitative Easing on Bank Lending Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 30(11), pages 3858-3887.
    27. Araújo, Aloísio & Kubler, Felix & Schommer, Susan, 2012. "Regulating collateral-requirements when markets are incomplete," Journal of Economic Theory, Elsevier, vol. 147(2), pages 450-476.
    28. Emmanuel Joel Aikins Abakah & Paul Alagidede & Lord Mensah & Kwaku Ohene-Asare, 2018. "Non-linear approach to Random Walk Test in selected African countries," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 14(3), pages 362-376, April.
    29. Luiz Renato Lima & Zhijie Xiao, 2010. "Is there long memory in financial time series?," Applied Financial Economics, Taylor & Francis Journals, vol. 20(6), pages 487-500.
    30. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    31. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    32. Adrian, Tobias & Shin, Hyun Song, 2010. "Liquidity and leverage," Journal of Financial Intermediation, Elsevier, vol. 19(3), pages 418-437, July.
    33. Gil-Alana, Luis Alberiko & Abakah, Emmanuel Joel Aikins & Rojo, María Fátima Romero, 2020. "Cryptocurrencies and stock market indices. Are they related?," Research in International Business and Finance, Elsevier, vol. 51(C).
    34. John Geanakoplos, 2009. "The Leverage Cycle," Cowles Foundation Discussion Papers 1715, Cowles Foundation for Research in Economics, Yale University.
    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. Abakah, Emmanuel Joel Aikins & Nasreen, Samia & Tiwari, Aviral Kumar & Lee, Chien-Chiang, 2023. "U.S. leveraged loan and debt markets: Implications for optimal portfolio and hedging," International Review of Financial Analysis, Elsevier, vol. 87(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. Fostel, Ana & Geanakoplos, John, 2012. "Why does bad news increase volatility and decrease leverage?," Journal of Economic Theory, Elsevier, vol. 147(2), pages 501-525.
    2. Ana Fostel & John Geanakoplos, 2012. "Tranching, CDS, and Asset Prices: How Financial Innovation Can Cause Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 190-225, January.
    3. Abakah, Emmanuel Joel Aikins & Gil-Alana, Luis Alberiko & Madigu, Godfrey & Romero-Rojo, Fatima, 2020. "Volatility persistence in cryptocurrency markets under structural breaks," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 680-691.
    4. Abakah, Emmanuel Joel Aikins & Caporale, Guglielmo Maria & Gil-Alana, Luis Alberiko, 2021. "Economic policy uncertainty: Persistence and cross-country linkages," Research in International Business and Finance, Elsevier, vol. 58(C).
    5. Feixue Gong & Gregory Phelan, 2020. "Debt collateralization, capital structure, and maximal leverage," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 70(2), pages 579-605, September.
    6. Cipriani, Marco & Fostel, Ana & Houser, Daniel, 2021. "Leverage and asset prices: An experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 183(C), pages 700-717.
    7. Gregory Phelan, 2017. "Collateralized borrowing and increasing risk," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 63(2), pages 471-502, February.
    8. Karlis, Alexandros & Galanis, Girogos & Terovitis, Spyridon & Turner, Matthew, 2017. "Heterogeneity and Clustering of Defaults," Economic Research Papers 270011, University of Warwick - Department of Economics.
    9. Aikins Abakah, Emmanuel Joel & Gil-Alana, Luis A. & Tripathy, Trilochan, 2022. "Stochastic structure of metal prices: Evidence from fractional integration non-linearities and breaks," Resources Policy, Elsevier, vol. 78(C).
    10. A. K. Karlis & G. Galanis & S. Terovitis & M. S. Turner, 2021. "Heterogeneity and clustering of defaults," Quantitative Finance, Taylor & Francis Journals, vol. 21(9), pages 1533-1549, September.
    11. Wei Xiong, 2013. "Bubbles, Crises, and Heterogeneous Beliefs," NBER Working Papers 18905, National Bureau of Economic Research, Inc.
    12. Tobias Adrian & Emanuel Moench & Hyun Song Shin, 2013. "Dynamic Leverage Asset Pricing," Staff Reports 625, Federal Reserve Bank of New York.
    13. Ana Fostel & John Geanakoplos, 2013. "Leverage and Default in Binomial Economies: A Complete Characterization," Working Papers 2013-16, The George Washington University, Institute for International Economic Policy.
    14. Nicole Boyson & Jean Helwege & Jan Jindra, 2014. "Crises, Liquidity Shocks, and Fire Sales at Commercial Banks," Financial Management, Financial Management Association International, vol. 43(4), pages 857-884, December.
    15. Istiak, Khandokar & Serletis, Apostolos, 2020. "Risk, uncertainty, and leverage," Economic Modelling, Elsevier, vol. 91(C), pages 257-273.
    16. Adrian, Tobias & Borowiecki, Karol Jan & Tepper, Alexander, 2022. "A leverage-based measure of financial stability," Journal of Financial Intermediation, Elsevier, vol. 51(C).
    17. Christian Laux & Thomas Rauter, 2017. "Procyclicality of U.S. Bank Leverage," Journal of Accounting Research, Wiley Blackwell, vol. 55(2), pages 237-273, May.
    18. Aye, Goodness C. & Carcel, Hector & Gil-Alana, Luis A. & Gupta, Rangan, 2017. "Does gold act as a hedge against inflation in the UK? Evidence from a fractional cointegration approach over 1257 to 2016," Resources Policy, Elsevier, vol. 54(C), pages 53-57.
    19. Brunnermeier, Markus K. & Oehmke, Martin, 2013. "Bubbles, Financial Crises, and Systemic Risk," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1221-1288, Elsevier.
    20. Markus Brunnermeier & Simon Rother & Isabel Schnabel & Itay Goldstein, 2020. "Asset Price Bubbles and Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 33(9), pages 4272-4317.

    More about this item

    Keywords

    Leverage loan indices; Persistence; Volatility; Fractional integration;
    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
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

    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:eee:reveco:v:78:y:2022:i:c:p:141-152. 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/620165 .

    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.