IDEAS home Printed from https://ideas.repec.org/a/ags/thkase/338429.html
   My bibliography  Save this article

The Information Flow Interpretation of Margin Debt Value Data: Evidence from New York Stock Exchange

Author

Listed:
  • Senarathne, Chamil W.

Abstract

This paper examines the heteroscedasticity in NYSE Composite index returns using margin debt value data from a sampling period of December 1996 to November 2017. Following Lamoureux and Lastrapes (1990), the lagged margin debt value is included in the conditional variance of GARCH and EGARCH models. The results of EGARCH estimates show that the ARCH effect vanishes and the total volatility persistence is most reduced, confirming that the margin debt value is a reflection of time dependence in the rate of new information arrival on stock market borrowing (i.e. margin borrowing). Further, the lagged margin debt value coefficient is negatively and significantly related to conditional volatility. This implies that when the new information pertaining to credit risk flows to the market, the investors adjust the risk downward (i.e. downward revision) as their repose to the flow of new information. However, GARCH estimates have shown to provide a weaker reflection of the effect of information pertaining to stock market borrowing (i.e. margin borrowing) on conditional volatility and therefore had little explanatory power of heteroscedasticity in the stock return data. Overall, the results suggest that the form of persistence of new information arrival on margin debt value data in the conditional volatility is a reflection of ARCH type of residual heteroscedasticity of stock return data of the New York Stock Exchange.

Suggested Citation

  • Senarathne, Chamil W., . "The Information Flow Interpretation of Margin Debt Value Data: Evidence from New York Stock Exchange," Asian Journal of Applied Economics, Kasetsart University, Center for Applied Economics Research, vol. 26(1).
  • Handle: RePEc:ags:thkase:338429
    DOI: 10.22004/ag.econ.338429
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/338429/files/07.Vol26Issue1_p45-70.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.338429?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
    ---><---

    References listed on IDEAS

    as
    1. Li, Chunshuo & Ongena, Steven, 2015. "Bank loan announcements and borrower stock returns before and during the recent financial crisis," Journal of Financial Stability, Elsevier, vol. 21(C), pages 1-12.
    2. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    3. Schwert, C.W., 1989. "Margin Requirements And Stock Volatility," Papers t6, Columbia - Center for Futures Markets.
    4. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-229, March.
    5. Sharpe, Steven A, 1990. "Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized Model of Customer Relationships," Journal of Finance, American Finance Association, vol. 45(4), pages 1069-1087, September.
    6. Hsieh, David A & Miller, Merton H, 1990. "Margin Regulation and Stock Market Volatility," Journal of Finance, American Finance Association, vol. 45(1), pages 3-29, March.
    7. Kumar, Brajesh & Singh, Priyanka & Pandey, Ajay, 2009. "The Dynamic Relationship between Price and Trading Volume:Evidence from Indian Stock Market," IIMA Working Papers WP2009-12-04, Indian Institute of Management Ahmedabad, Research and Publication Department.
    8. Brumm, Johannes & Grill, Michael & Kubler, Felix & Schmedders, Karl, 2015. "Margin regulation and volatility," Journal of Monetary Economics, Elsevier, vol. 75(C), pages 54-68.
    9. Peter Koudijs & Hans-Joachim Voth, 2016. "Leverage and Beliefs: Personal Experience and Risk-Taking in Margin Lending," American Economic Review, American Economic Association, vol. 106(11), pages 3367-3400, November.
    10. Myers, Stewart C. & Majluf, Nicholas S., 1984. "Corporate financing and investment decisions when firms have information that investors do not have," Journal of Financial Economics, Elsevier, vol. 13(2), pages 187-221, June.
    11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    12. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    13. Stewart C. Myers & Nicholas S. Majluf, 1984. "Corporate Financing and Investment Decisions When Firms Have InformationThat Investors Do Not Have," NBER Working Papers 1396, National Bureau of Economic Research, Inc.
    14. 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.
    15. Michael Grill & Karl Schmedders & Felix Kubler & Johannes Brumm, 2012. "Margin Requirements and Asset Prices," 2012 Meeting Papers 533, Society for Economic Dynamics.
    16. Albuquerque, Rui & Ramadorai, Tarun & Watugala, Sumudu W., 2015. "Trade credit and cross-country predictable firm returns," Journal of Financial Economics, Elsevier, vol. 115(3), pages 592-613.
    17. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    18. Ece Oral, 2012. "An empirical analysis of trading volume and return volatility relationship on Istanbul stock exchange national -100 Index," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 2(5), pages 1-9.
    19. Semen Son Turan, 2014. "Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies," Information Management and Business Review, AMH International, vol. 6(6), pages 317-328.
    20. Jones, Charles M. & Lamont, Owen A., 2002. "Short-sale constraints and stock returns," Journal of Financial Economics, Elsevier, vol. 66(2-3), pages 207-239.
    21. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    22. Manish Kumar & M. Thenmozhi, 2012. "Causal effect of volume on stock returns and conditional volatility in developed and emerging market," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 2(4), pages 346-362.
    23. Gebka, Bartosz & Wohar, Mark E., 2013. "Causality between trading volume and returns: Evidence from quantile regressions," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 144-159.
    24. Acharya, Viral V. & Johnson, Timothy C., 2007. "Insider trading in credit derivatives," Journal of Financial Economics, Elsevier, vol. 84(1), pages 110-141, April.
    25. Mohamed Khaled Al-Jafari & Ahmad Tliti, 2013. "An Empirical Investigation of the Relationship between Stock Return and Trading Volume: Evidence from the Jordanian Banking Sector," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 3(3), pages 1-4.
    26. Senarathne, Chamil W & Jayasinghe, Prabhath, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," MPRA Paper 78771, University Library of Munich, Germany, revised 04 Apr 2017.
    27. Hiemstra, Craig & Jones, Jonathan D, 1994. "Testing for Linear and Nonlinear Granger Causality in the Stock Price-Volume Relation," Journal of Finance, American Finance Association, vol. 49(5), pages 1639-1664, December.
    28. C W Senarathne & P Jayasinghe, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," Economic Issues Journal Articles, Economic Issues, vol. 22(1), pages 1-24, March.
    29. Renault, Eric & Werker, Bas J.M., 2011. "Causality effects in return volatility measures with random times," Journal of Econometrics, Elsevier, vol. 160(1), pages 272-279, January.
    30. 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.
    31. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    32. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
    33. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    34. Cem Demiroglu & Christopher M. James, 2010. "The Information Content of Bank Loan Covenants," The Review of Financial Studies, Society for Financial Studies, vol. 23(10), pages 3700-3737, October.
    35. Domian, Dale L. & Racine, Marie D., 2006. "An empirical analysis of margin debt," International Review of Economics & Finance, Elsevier, vol. 15(2), pages 151-163.
    36. 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.
    37. Billett, Matthew T & Flannery, Mark J & Garfinkel, Jon A, 1995. "The Effect of Lender Identity on a Borrowing Firm's Equity Return," Journal of Finance, American Finance Association, vol. 50(2), pages 699-718, June.
    Full references (including those not matched with items on IDEAS)

    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. SENARATHNE W Chamil & JIANGUO Wei, 2018. "Do Investors Mimic Trading Strategies Of Foreign Investors Or The Market: Implications For Capital Asset Pricing," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 13(3), pages 171-205, December.
    2. Senarathne Chamil W. & Šoja Tijana, 2019. "Heteroskedasticity in Excess Bitcoin Return Data: Google Trend vs. Garch Effects," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(3), pages 35-45, September.
    3. Senarathne, Chamil W & Jayasinghe, Prabhath, 2017. "Information Flow Interpretation of Heteroskedasticity for Capital Asset Pricing: An Expectation-based View of Risk," MPRA Paper 78771, University Library of Munich, Germany, revised 04 Apr 2017.
    4. Daouda Lawa tan Toe & Salifou Ouedraogo, 2022. "Dynamic relationship between trading volume, returns and returns volatility: an empirical investigation on the main African’s stock markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(5), pages 429-444, September.
    5. Pramod Kumar Naik & Rangan Gupta & Puja Padhi, 2018. "The Relationship Between Stock Market Volatility And Trading Volume: Evidence From South Africa," Journal of Developing Areas, Tennessee State University, College of Business, vol. 52(1), pages 99-114, January-M.
    6. Madarassy Akin, Rita, 2003. "Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets," Santa Cruz Center for International Economics, Working Paper Series qt1n04g31b, Center for International Economics, UC Santa Cruz.
    7. Madarassy Akin, Rita, 2003. "Maturity Effects in Futures Markets: Evidence from Eleven Financial Futures Markets," Santa Cruz Department of Economics, Working Paper Series qt1n04g31b, Department of Economics, UC Santa Cruz.
    8. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    9. Chen, Gong-meng & Firth, Michael & Rui, Oliver M, 2001. "The Dynamic Relation between Stock Returns, Trading Volume, and Volatility," The Financial Review, Eastern Finance Association, vol. 36(3), pages 153-173, August.
    10. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    11. Semen Son-Turan, 2016. "The Impact of Investor Sentiment on the "Leverage Effect"," International Econometric Review (IER), Econometric Research Association, vol. 8(1), pages 4-18, April.
    12. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Internet, noise trading and commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 82-89.
    13. Georgios Bampinas & Theodore Panagiotidis & Christina Rouska, 2019. "Volatility persistence and asymmetry under the microscope: the role of information demand for gold and oil," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(1), pages 180-197, February.
    14. Loredana Ureche-Rangau & Quiterie de Rorthays, 2009. "More on the volatility-trading volume relationship in emerging markets: The Chinese stock market," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(7), pages 779-799.
    15. Tissaoui, Kais & Ftiti, Zied, 2016. "Liquidity, liquidity risk, and information flow: Lessons from an emerging market," Research in International Business and Finance, Elsevier, vol. 37(C), pages 28-48.
    16. Alizadeh, Amir H. & Tamvakis, Michael, 2016. "Market conditions, trader types and price–volume relation in energy futures markets," Energy Economics, Elsevier, vol. 56(C), pages 134-149.
    17. Zhang, Zuochao & Shen, Dehua, 2024. "Internet stock message boards and the price–volume relationship: Registered users vs non-registered users," Finance Research Letters, Elsevier, vol. 61(C).
    18. Saswat Patra & Malay Bhattacharyya, 2021. "Does volume really matter? A risk management perspective using cross‐country evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 118-135, January.
    19. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    20. Niklas Wagner & Terry Marsh, 2005. "Surprise volume and heteroskedasticity in equity market returns," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 153-168.

    More about this item

    Keywords

    Financial Economics;

    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:ags:thkase:338429. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/darkuth.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.