LOG IN⠴ݱâ

  • ȸ¿ø´ÔÀÇ ¾ÆÀ̵ð¿Í Æнº¿öµå¸¦ ÀÔ·ÂÇØ ÁÖ¼¼¿ä.
  • ȸ¿øÀÌ ¾Æ´Ï½Ã¸é ¾Æ·¡ [ȸ¿ø°¡ÀÔ]À» ´­·¯ ȸ¿ø°¡ÀÔÀ» ÇØÁֽñ⠹ٶø´Ï´Ù.

¾ÆÀ̵ð ÀúÀå

   

¾ÆÀ̵ð Áߺ¹°Ë»ç⠴ݱâ

HONGGIDONG ˼
»ç¿ë °¡´ÉÇÑ È¸¿ø ¾ÆÀ̵ð ÀÔ´Ï´Ù.

E-mail Áߺ¹È®ÀÎ⠴ݱâ

honggildong@naver.com ˼
»ç¿ë °¡´ÉÇÑ E-mail ÁÖ¼Ò ÀÔ´Ï´Ù.

¿ìÆí¹øÈ£ °Ë»ö⠴ݱâ

°Ë»ö

SEARCH⠴ݱâ

ºñ¹Ð¹øÈ£ ã±â

¾ÆÀ̵ð

¼º¸í

E-mail

ÇмúÀÚ·á °Ë»ö

The determinants of bank loan recovery rates

  • Hinh Khieu University of Southern Indiana
  • Donald Mullineaux University of Kentucky
  • Ha-Chin Yi Texas State University
While there is a very large literature on the determinants of default on various debt instruments, relatively little is known about the factors which influence recoveries on bank loans in the default state. The issue has taken on heightened importance since Basel II permits banks to determine required capital holdings by using model-based estimates of ¡°loss given default¡± which depends on the recovery rate. We measure recoveries using the ¡°Ultimate Recovery Database¡± supplied by Moody¡¯s and model the recovery rate as a function of variables reflecting loan and borrower characteristics, industry and macroeconomic conditions, and several recovery process variables. We find that loan characteristics, such as the presence of certain types of collateral, are significant determinants of recovery rates, whereas many of the borrower characteristics before default generally are not. Industry and macroeconomic conditions also are relevant, as are certain process factors such as prepackaged bankruptcies. Since trading prices on loans approximately 30 days after default are often used by practitioners (and in some academic studies) as proxies for the recovery rate, we examine whether this proxy provides a rational estimate of actual recoveries. We find that the process that drives the 30-day trading price after default differs significantly from the actual settlement recovery process.

  • Hinh Khieu
  • Donald Mullineaux
  • Ha-Chin Yi
While there is a very large literature on the determinants of default on various debt instruments, relatively little is known about the factors which influence recoveries on bank loans in the default state. The issue has taken on heightened importance since Basel II permits banks to determine required capital holdings by using model-based estimates of ¡°loss given default¡± which depends on the recovery rate. We measure recoveries using the ¡°Ultimate Recovery Database¡± supplied by Moody¡¯s and model the recovery rate as a function of variables reflecting loan and borrower characteristics, industry and macroeconomic conditions, and several recovery process variables. We find that loan characteristics, such as the presence of certain types of collateral, are significant determinants of recovery rates, whereas many of the borrower characteristics before default generally are not. Industry and macroeconomic conditions also are relevant, as are certain process factors such as prepackaged bankruptcies. Since trading prices on loans approximately 30 days after default are often used by practitioners (and in some academic studies) as proxies for the recovery rate, we examine whether this proxy provides a rational estimate of actual recoveries. We find that the process that drives the 30-day trading price after default differs significantly from the actual settlement recovery process.