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Learning, noise traders, the volatility and the level of bond spreads

Listed author(s):
  • Peter Benczur

    ()

    (Central Bank of Hungary)

According to various studies, sovereign bond spreads often deviate from any "sensible" perception of default risk. It is usually attributed to behavioral effects (overreaction) or illiquidity. The former explanation imposes some irrationality or bounded rationality on investors; while the latter usually relies on some informational asymmetry or thin markets. The paper presents a different source of liquidity risk: in a Diamond-Dybvig type model, where agents face a liquidity risk (becoming more risk-averse early consumers), changes in the speed of public learning about default risk may increase bond spreads. This effect operates through a link between future volatility and current levels: increased expected future price volatility (a volatility effect) leads to lower prices today (a level effect). Under reasonable parameter values, accelerated information revelation may increase spreads by 50%. I also compare the welfare of the issuer and investors under different speeds of learning: revealing information may be good or bad for the issuer (issue prices may increase or decrease), and also for the investors (ex ante utility might be higher or lower).

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File URL: http://econ.core.hu/doc/dp/dp/benczur.pdf
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Paper provided by Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences in its series IEHAS Discussion Papers with number 0114.

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Length: 27 pages
Date of creation: 2001
Handle: RePEc:has:discpr:0114
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  1. Krebs, Tom, 1999. "Information and asset prices in complete markets exchange economies," Economics Letters, Elsevier, vol. 65(1), pages 75-83, October.
  2. Grossman, Sanford J & Miller, Merton H, 1988. " Liquidity and Market Structure," Journal of Finance, American Finance Association, vol. 43(3), pages 617-637, July.
  3. Harvey, Campbell R & Huang, Roger D, 1991. "Volatility in the Foreign Currency Futures Market," Review of Financial Studies, Society for Financial Studies, vol. 4(3), pages 543-569.
  4. Redding, Lee S., 1999. "Negative nominal interest rates and the liquidity premium," Economics Letters, Elsevier, vol. 62(2), pages 213-216, February.
  5. Jones, Charles M. & Kaul, Gautam & Lipson, Marc L., 1994. "Information, trading, and volatility," Journal of Financial Economics, Elsevier, vol. 36(1), pages 127-154, August.
  6. Douglas W. Diamond & Philip H. Dybvig, 2000. "Bank runs, deposit insurance, and liquidity," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 14-23.
  7. Cassano, Mark A., 1999. "Learning and mean reversion in asset returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(4), pages 529-545.
  8. Ederington, Louis H & Lee, Jae Ha, 1993. " How Markets Process Information: News Releases and Volatility," Journal of Finance, American Finance Association, vol. 48(4), pages 1161-1191, September.
  9. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
  10. Amihud, Yakov & Mendelson, Haim, 1991. " Liquidity, Maturity, and the Yields on U.S. Treasury Securities," Journal of Finance, American Finance Association, vol. 46(4), pages 1411-1425, September.
  11. Hirshleifer, Jack, 1971. "The Private and Social Value of Information and the Reward to Inventive Activity," American Economic Review, American Economic Association, vol. 61(4), pages 561-574, September.
  12. LeRoy, Stephen F & Porter, Richard D, 1981. "The Present-Value Relation: Tests Based on Implied Variance Bounds," Econometrica, Econometric Society, vol. 49(3), pages 555-574, May.
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