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

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  • 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.

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  • 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(01).
    • Handle: RePEc:ags:thkase:338429
    DOI: 10.22004/ag.econ.338429
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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Michael Grill & Karl Schmedders & Felix Kubler & Johannes Brumm, 2012. "Margin Requirements and Asset Prices," 2012 Meeting Papers 533, Society for Economic Dynamics.
    8. Shen, Dehua & Zhang, Wei & Xiong, Xiong & Li, Xiao & Zhang, Yongjie, 2016. "Trading and non-trading period Internet information flow and intraday return volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 519-524.
    9. 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.
    10. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Brumm, Johannes & Grill, Michael & Kubler, Felix & Schmedders, Karl, 2015. "Margin regulation and volatility," Journal of Monetary Economics, Elsevier, vol. 75(C), pages 54-68.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Peter Fortune, 2001. "Margin lending and stock market volatility," New England Economic Review, Federal Reserve Bank of Boston, pages 3-25.
    22. Zhang, Yongjie & Feng, Lina & Jin, Xi & Shen, Dehua & Xiong, Xiong & Zhang, Wei, 2014. "Internet information arrival and volatility of SME PRICE INDEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 70-74.
    23. 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.
    24. 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.
    25. 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.
    26. Schwert, C.W., 1989. "Margin Requirements And Stock Volatility," Papers t6, Columbia - Center for Futures Markets.
    27. 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.
    28. 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.
    29. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    30. 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.
    31. 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.
    32. Acharya, Viral V. & Johnson, Timothy C., 2007. "Insider trading in credit derivatives," Journal of Financial Economics, Elsevier, vol. 84(1), pages 110-141, April.
    33. 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.
    34. 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.
    35. Chava, Sudheer & Gallmeyer, Michael & Park, Heungju, 2015. "Credit conditions and stock return predictability," Journal of Monetary Economics, Elsevier, vol. 74(C), pages 117-132.
    36. 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.
    37. 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.
    38. 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.
    39. 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.
    40. 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.
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