“…Surprisingly, this study finds little support for interest rate risk and credit risk as systematic risk factors for banks. In contrast, Bessler and Kurmann (2014) analyze risk factors for European and US banks and provide significant evidence for the following seven variables: interest rate risk, low and high credit risk, sovereign risk, foreign exchange risk as well as real estate risk and market risk. Overall, the authors conclude that banks' risk factors are multi-faceted and time varying, but generally capture a substantial portion of the variation in bank stock returns.…”
Section: Bank Risk Exposuresmentioning
confidence: 99%
“…However, the risk exposures naturally tilt toward medium-and small-sized banks' exposures. For a detailed analysis of differences in risk exposures of banks in different size categories also seeGandhi and Lustig (2013) as well asBessler and Kurmann (2014). The results are available from the authors upon request.13 We are aware that, besides our long-term interest rate factor, short-term interest rate factors were applied in the literature.…”
“…Surprisingly, this study finds little support for interest rate risk and credit risk as systematic risk factors for banks. In contrast, Bessler and Kurmann (2014) analyze risk factors for European and US banks and provide significant evidence for the following seven variables: interest rate risk, low and high credit risk, sovereign risk, foreign exchange risk as well as real estate risk and market risk. Overall, the authors conclude that banks' risk factors are multi-faceted and time varying, but generally capture a substantial portion of the variation in bank stock returns.…”
Section: Bank Risk Exposuresmentioning
confidence: 99%
“…However, the risk exposures naturally tilt toward medium-and small-sized banks' exposures. For a detailed analysis of differences in risk exposures of banks in different size categories also seeGandhi and Lustig (2013) as well asBessler and Kurmann (2014). The results are available from the authors upon request.13 We are aware that, besides our long-term interest rate factor, short-term interest rate factors were applied in the literature.…”
“…Interest rate risk exposure has been traditionally measured by the coefficients from a two‐factor multiple regression model between equity returns and changes in the market factor and interest rate factor with a fixed maturity (Bessler & Kurmann, 2014; Elyasiani & Mansur, 1998; Elyasiani, Mansur, & Pagano, 2007; Flannery & James, 1984b; Oertmann, Rendu, & Zimmermann, 2000 among others). Banking institutions, however, hold assets and liabilities across a wide spectrum of maturities.…”
Using an extensive global sample, this paper investigates the impact of the term structure of interest rates on bank equity returns.Decomposing the yield curve to its three constituents (level, slope and curvature), the paper evaluates the time-varying sensitivity of the bank's equity returns to these constituents by using a diagonal dynamic conditional correlation multivariate GARCH framework.Evidence reveals that the empirical proxies for the three factors explain the variations in equity returns above and beyond the market-wide effect. More specifically, shocks to the long-term (level) and short-term (slope) factors have a statistically significant impact on equity returns, while those on the medium-term (curvature) factor are less clear-cut. Bank size plays an important role in the sense that exposures are higher for SIFIs and large banks compared to medium and small banks. Moreover, banks exhibit greater sensitivities to all risk factors during the crisis and post-crisis periods compared to the pre-crisis period; though these sensitivities do not differ for market-oriented and bank-oriented financial systems.
“…Akella and Chen (), Song (), Browne, Carson and Hoyt (). Elyasiani, Mansur and Pagano () and Bessler and Kurman () find that various proxies for both market returns and changes in interest rates have significant effects on BHC stock returns, whereas other research has found a market effect but not an interest rate effect (Elyasiani and Mansur ). The BV‐GARCH model used here, thus, includes the following five equations: …”
Section: A Bivariate Garch Model Of Hc Stock Returnsmentioning
confidence: 97%
“…The coefficient on the interest rate factor measures, conditional on market returns, the portfolio's sensitivity to changes in the interest rate environment, which could also be associated with changes in bank and thrift cash flows because of the duration mismatches between their assets and liabilities. As Bessler and Kurman () write, over time different risk factors impact financial insitution stock returns as financial insitutions adopt different strategies for earning profits. Akella and Chen (), Song (), Browne, Carson and Hoyt ().…”
Section: A Bivariate Garch Model Of Hc Stock Returnsmentioning
Using bivariate GARCH models of stock portfolio returns and risk, we find that bank and thrift holding companies that relied the most on Federal Home Loan Bank (FHLB) advances exhibited less total risk and market risk than those that relied on them the least between 2001 and 2012. When we control for differences in holding company size, stock trading volume, residential mortgage lending, and holding company type (bank vs. thrift), the most FHLB‐reliant holding companies sustain the aforesaid risk advantages except during the crisis of 2007–2009, when they exhibit greater idiosyncratic risk. The latter finding suggests that investors perceived the high reliance of the borrowing institutions on advances as a sign of distress. Portfolios that consist of only bank holding companies show qualitatively similar results.
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