Maturity Transformation and Interest Rate Risk in Large European ...

There are at least three ways that an analyst (say, a regulator) may monitor or assess the interestrate risk of a financial intermediary. Publicly listed banks and insurers disclose measures of thesensitivity of their balance sheets to shifts in the term structure of interest rates, so in the firstinstance an analyst may refer to these disclosures. These self-reported measures have the advantagethat they may take into account the complex structure of the contracts held by an intermediary thatmay not be visible in its financial statements, but such measures also rely on the willingness andability of the intermediary to make an accurate assessment. Furthermore, only one to two measuresare typically disclosed, which cannot be hoped to provide a complete picture of the intermediary’sexposure to interest rate changes.As an alternative, the analyst could use regression analysis to measure the sensitivity of the stockreturn of publicly-listed intermediaries against changes in specific interest rates or against measuresreflecting the shape of the yield curve. The principle paper in this category is Flannery and James(1984a), where the authors find that US banks’ stock returns are sensitive to interest rate changes,and that the degree of sensitivity is correlated with the degree of maturity transformation measuredfrom the nominal contracts on their balance sheets. Flannery and James (1984b) infer the effectivedegree of maturity transformation based on these stock sensitivity measures. Saunders and Yourougou(1990) find that bank stock returns are more sensitive to interest rate changes than the stock returnsof other companies; they also find some evidence to suggest that universal banks would be more robustto interest rate changes due to better diversification. Czaja, Scholz, and Wilkens (2009) measurethe sensitivity of stock returns of German banks and insurers to level, slope and curvature changesin local yield curves, and find that bank and insurer stock returns offer a premium for those banksand insurers with greater sensitivities to the level and curvature factors. English, van den Heuvel,and Zakrajsek (2012) use high-frequency stock and interest rate data around Federal Open MarketCommittee announcements to measure the effect of interest rate level and slope changes in bank stockreturns; studying short time intervals helps to avoid the pollutive effects of unrelated news on stockprices.The analyst could also measure the interest rate sensitivity of each item on the balance sheet, byasking the question “How would the unit prices of the major asset and liability categories change ifinterest rates were different on the valuation date?” This is the approach taken in our paper, andcan be thought of as a ‘prospective’ assessment of interest rate risk, as opposed to the ‘retrospective’assessments following Flannery and James (1984a). The concepts of duration and convexity as measuresof price sensitivity to interest rate changes were introduced by Macaulay (1938), Hicks (1939),Samuelson (1945) and Redington (1952). Houpt and Embersit (1991) propose a duration-based methodfor assessing the interest rate sensitivity of banks’ economic value based on their publicly disclosedbalance sheets. This model has since become known as the Federal Reserve’s Economic Value Model(EVM). Wright and Houpt (1996) evaluate the performance of this simple model for ‘thrift institutions’against a model that uses more detailed private supervisory data, and against the Office for ThiftSupervision’s internal model. Despite the limitations of publicly-available data, the authors find thatthe simple model provides useful information for measuring the sensitivity of banks’ economic valueto interest rate changes; they also find that the biggest limitation of such models are the arbitraryassumptions that have to be made about the behaviour of depositors.Jarrow and van Deventer (1998) offer a no-arbitrage model for determining the economic valueof deposit contract liabilities, and this pricing function could also be used in principle to measure itssensitivity to interest rate changes. O’Brien (2000) also offers such a no-arbitrage model, and furtherestimates its parameters on US bank data, providing detailed sensitivity estimates of the economicvalue of bank liabilities to changes in the short term interest rate. Sierra and Yeager (2004) evaluatethe predictions of the EVM against the actual performance of US community banks, which do nottypically engage in complex derivative transactions, and find that those banks that the EVM identifiesas most sensitive to rising rates show the greatest deterioration in performance in the 1998-2000 periodof rising rates in the US. Sierra (2009) finds that the ‘prospective’ sensitivities of US bank economicvalue to interest rates calculated from the EVM are consistent with the ‘retrospective’ interest ratesensitivities of stock prices discussed above. Entrop, Memmel, Wilkens, and Zeisler (2011) try toproduce a refined EVM model calibrated to German banking data by using repeated observations ofbalance sheets over time. By evaluating their model using private supervisor data, they are able toargue that their model outperforms the EVM, which relies on data at only one point in time. Themost important paper for estimating the sensitivity of US bank balance sheet derivative exposures is2