Abstract
We develop a comprehensive empirical specification that treats risk-management and risk-taking as integrated facets of a financial intermediary’s risk profile. Three main results emerge from a sample of 518 U.S. bank holding companies during 1991–2000: (1) The corporate risk-management theories most consistently supported are those related to financial distress costs and debt holder-related agency costs (with weaker support for the rationales related to managerial contracting costs, firm size, and hedge substitutes); (2) the asymmetric information theory for managing risk is not supported by our sample; (3) a conventional linear model of risk-management adequately explains cross-sectional and time-series variation in the sample. The model’s findings are robust to alternate definitions of the independent variables, major changes in bank regulation, firm-specific fixed effects, nonlinearities and interactions between the independent variables, as well as firm-specific controls for other key risks related to credit quality and operating efficiency.
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Notes
- 1.
There is some discussion in the literature regarding hedging cash flows versus hedging market values of existing and anticipated risk exposures. Our view is that hedging particular exposures of either cash flows or market values will both lead to meaningful impacts on shareholder wealth. Thus, we focus on risk-management’s effects on shareholder value and do not make distinctions between cash flow- and market value-hedging since both forms of risk-management can equally affect total shareholder wealth.
- 2.
See Pagano (1999, 2001) for reviews of the theoretical and empirical literature related to risk-management and risk-taking activities of U.S. commercial banks. Also, see Stulz (1996) and Graham and Rogers (2002) for a discussion of the concepts of a firm’s net risk exposures, integrated risk-management, and their effects on shareholder value.
- 3.
- 4.
For example, one can assume that two similar banks (A and B) both face an increase in demand for fixed rate loans and that both meet this demand by supplying these loans yet they choose to manage the resulting increase in interest rate risk exposure differently. Suppose that bank A immediately sells the fixed rate loans in the secondary market while bank B holds the loans on its balance sheet and then uses derivatives to completely hedge the interest rate risk. The sensitivity to interest rate risk in economic terms is essentially the same for both banks, although they have chosen different ways to manage this risk. In our model, we focus on the economic significance of cross-sectional and time-varying differences in the interest rate risk (and total risk) exposures of U.S. commercial banks and we do not make distinctions between whether the bank used on- or off-balance sheet transactions to manage these exposures. In this sense, our view of risk-management is broader than what is typically defined as hedging in the existing literature (i.e., the explicit use of derivatives). See Stulz (1996) and Meulbroek (2002) for a detailed discussion of a broader definition of risk-management, which is consistent with our perspective.
- 5.
For example, Nance et al. (1993), Mian (1996) and Wall and Pringle (1989) employ binary dependent variables and lack a consistent test of all competing hedging theories. The use of a binary variable is problematic because it does not fully describe the extent of a firm’s hedging activity. When a binary dependent variable is employed, a firm that hedges 1 or 100% of its risk exposure is treated the same in the model. Tufano (1996) attempts to test most (but not all) of the major hedging rationales and uses a continuous variable – an estimated hedge ratio. However, his sample covers a limited number of companies in a relatively small sector of the economy, the North American gold mining industry. Tufano (1996, 1998a) reports empirical results for 48 publicly traded gold mining firms in North America during 1991–1993. Graham and Rogers (2002) focuses on a cross-section of non-financial companies and finds that companies typically hedge to increase the tax benefits related to increased debt capacity and, to a lesser extent, to reduce financial distress costs and take advantage of economies of scale.
- 6.
Additional examples in the banking literature of these focused empirical tests include Galloway et al. (1997) and Cebenoyan et al. (1999) concerning the effect of bank regulation on risk-taking as well as Gorton and Rosen (1995) on the potential agency and contracting problems related to bank riskiness.
- 7.
Note that a related strand of the accounting literature has, rather than using shareholder wealth maximization as the firm’s objective function, focused on analyzing hedging decisions based on managing accounting earnings and book value-based regulatory capital requirements (e.g., see Wolf 2000). Instead, we follow the logic of developing tests where the effect of a bank’s net interest rate risk exposure is measured in terms of its impact on the firm’s stock returns. This is a well-accepted, objective approach that is commonly used in the corporate risk-management literature and therefore we readily adopt it here.
- 8.
As we will discuss later, we also test a short-term interest rate, the three-month U.S. T-bill rate, and find that the long-term rate is statistically more significant than this short-term rate.
- 9.
Hedge substitutes in our case can include bank-related on-balance sheet activities such as altering the firm’s asset and liability mix in order to reduce risk. Compared to conventional manufacturing and service companies, commercial banks have greater flexibility in employing these on-balance sheet techniques.
- 10.
It should be noted that this strand of the literature treats the variables on the right-hand-side of Equation (45.1) as exogenous and independent of one another when, in reality, most, if not all, of these factors may be inter-dependent. As will be seen in Sect. 45.3.5, our tests differ from the extant literature by allowing for potential interactions between the right-hand-side variables found in Equation (45.1).
- 11.
Recent empirical studies by Geczy et al. (1997) and Schrand (1997) have also provided more formalized tests of the factors describing corporate derivatives usage. Since these papers focus exclusively on derivatives and do not directly investigate the hedging theories described in this paper, we do not summarize their findings here.
- 12.
The interest rate factor was computed in two ways: (1) simply as it is defined above using the ten-year interest rate (i.e., not orthogonalized) and (2) the orthogonalized interest rate, where (per Unal and Kane 1988) the interest rate factor is regressed on the equity market portfolio proxy and the resulting residuals from this regression are used as the second factor in Equation (45.2) rather than the simple non-orthogonalized version of the interest rate factor. We find that the empirical results are qualitatively the same whether the interest rate factor is orthogonalized or non-orthogonalized. Using Occam’s razor, we thus choose to report the simplest estimation method in our Empirical Results section (i.e., we report our results based on the non-orthogonalized interest rate factor since they are simpler to compute and yield the same main results as when the more complicated orthogonalization procedure is employed). The results are essentially the same when either procedure is used because the simple correlation between the market portfolio proxy and the interest rate factor is quite low and thus the two factors in Equation (45.2) are essentially already orthogonalized before even applying an orthogonalization technique.Also, we find that using the simple changes in the three-month T-bill rate provides statistically weaker but qualitatively similar results as those obtained for the ten-year interest rate factor. Thus, we focus our subsequent discussion on the empirical results related to the ten-year Treasury note rather than results based on the three-month T-bill rate.
- 13.
This is done to allow for the interest rate beta to vary over time as well as cross-sectionally. Note that our model is similar to Graham and Rogers’ (2002) approach for estimating interest rate risk except we use stock returns as the dependent variable (versus operating income) because we are interested in studying risk-management’s effects on shareholder value rather than rely on indirect measures of market value such as accounting variables drawn from the firm’s income statement.
- 14.
If equity markets are informationally efficient, then we can interpret this interest rate beta (referred to here as IBETA in its raw form and IRR in its absolute value form) as a summary measure of the sensitivity of the bank’s market value of common equity to changes in interest rates. This measure of interest rate risk is consistent with the corporate risk-management definitions of interest rate risk, hedging, and its net impact on a firm’s market value of equity.
- 15.
We find that our empirical beta estimates are similar when either monthly or daily data are used, albeit the estimates with the monthly data provide more explanatory power in terms of adjusted R 2 statistics. Thus, to conserve space, we report our results from estimates computed using monthly return data.
- 16.
To mitigate the potential downward bias in parameter results caused by using an estimated interest rate risk parameter as a dependent variable, we use a generalized method of moments (GMM) estimator. This nonlinear instrument variables estimation technique explicitly accounts for the errors-in-variables problem that can exist when the dependent variable is estimated via a first-stage set of regressions (see Greene, 1993, and Ferson and Harvey 1991, for more details on this econometric issue).
- 17.
Table 45.1 also contains a description of alternate explanatory variables that are used for robustness testing in a specification referred to as our “Alternative Model” of interest rate risk. This alternative specification is described in detail in the Empirical Results subsection.
- 18.
Note that only hypotheses H2, H7, and H9 presented below might exhibit divergent effects for TOTRISK relative to IRR.
- 19.
Including a dummy variable (denoted TAXDUM) that equals 1 when the firm’s annual net income is above $100,000 provides an alternative way to test this tax influence. This TAXDUM measure of the tax-based incentive to hedge is used as a robustness check in our “Alternative Model” and is similar in spirit to the factors used to simulate the tax-related benefits of corporate hedging in Graham and Smith (1999). This dummy variable attempts to capture the convexity of the BHC’s tax schedule because it is at this low level of net income that the U.S. tax code is most convex. Ideally, a variable measuring tax loss carryforwards and carrybacks would be useful in measuring a firm’s tax convexity. However, these data are not readily available for commercial banks.
- 20.
Although one might view this variable as endogenous, the level and quality of the bank’s assets and the amount of equity capital on hand at the beginning of each year primarily determine these financial distress variables. Thus, we can consider the financial distress cost proxy as a predetermined variable in our empirical specification.
- 21.
Ideally, one would like to also see if the dollar value of these options is related to a bank’s interest rate risk. However, these data would require the application of an option-pricing model with all the related assumptions such a model requires. After 1991, most firms reported some of the relevant data but the assumptions underlying these dollar estimates are not consistent across firms. Since option grants are typically issued “at the money” (i.e., at approximately the current stock price at the time of issuance), using the number of shares granted scaled by the total number of shares outstanding provides us with an objective, standardized measure of incentive-based compensation. As reported in Table 45.1, we also use an alternative proxy variable (PBONUS), which calculates the percentage of annual cash compensation received in bonus form to provide an alternative standardized measure of the risk-taking incentives of senior management.
- 22.
As noted in Gorton and Rosen (1995) and Spong and Sullivan (1998), among others, the relationship between the level of equity owned by the company’s managers and the degree of risk taken by the firm might be non-monotonic. That is, risk averse managers might take on less risk than is optimal at the firm level when managerial stock ownership is very low (since there is no real incentive to take risk) or very high (because too much of the manager’s wealth is at risk).At moderate levels of ownership, however, managers may take on more risk since their personal incentives may be better aligned with those of outside shareholders. In this case, we expect an inverted U-shaped relationship between risk-taking and equity ownership similar to the one reported in Gorton and Rosen (1995) where both low and high levels of management equity ownership exhibit lower levels of risk-taking than moderate ownership levels. Empirical tests of this alternative hypothesis showed no evidence in support of this non-monotonic relationship. These results (not reported here in order to conserve space) could be due to the more detailed specification of the factors affecting risk-taking in our model.
- 23.
For robustness testing, we use an alternative proxy variable, EQBLOCK, which is computed as the percentage of total shares outstanding held by outside equity “blockholders” (those unaffiliated external investors that own 5% or more of the firm’s common equity). We include only the percentage of shares owned by “true” outside blockholders such as mutual fund companies and exclude any shares owned by “quasi-insiders” such as the bank’s Employee Stock Ownership Plan or relatives/associates of senior bank managers. We make a distinction between these types of groups because quasi-insiders might not be as effective monitors of the firm as true outside blockholders.
- 24.
It should be noted that ASYMINFO and SIZE are most likely inter-related. In our empirical tests discussed later, we accommodate this potential inter-relationship via a full quadratic model of interest rate risk. In addition, both of these variables may also be correlated with moral hazard incentives associated with “too big to fail” (TBTF) policies and mispriced deposit insurance. In effect, the inclusion of these two variables can also help control for risk-increasing incentives related to very large banks that are deemed “TBTF” by regulators.
- 25.
Financial firms with low levels of liquidity face a greater degree of liquidity risk. This risk can be defined as the BHC’s risk of not having sufficient funds on hand to meet depositors’ withdrawal needs. Typically, this risk leads to higher borrowing costs since the BHC is forced to pay a premium to obtain the additional funds on short-term notice in the federal funds market (or at the Fed’s discount window in extreme cases of liquidity needs).
- 26.
Note that when TOTRISK is used as the dependent variable, we must also include our interest rate risk factor, IRR, as a control variable because interest rate risk (along with credit, operating, and liquidity risks) can affect the bank’s overall riskiness.
- 27.
Our definition of OPERISK is noninterest operating expense divided by total revenue and effectively measures operating leverage because OPERISK will be high for banks with a large amount of operating overhead (e.g., due to high fixed operating costs related to an extensive branch network, a large customer support staff, and so forth).
- 28.
It should also be noted that bank-specific fixed effects via a “Fixed Effects” model could be used to incorporate unidentified firm-specific factors that might affect a firm’s interest rate risk exposure. To conserve space, we simply note here that the use of a fixed effects model does not alter the main findings of our basic linear model. That is, allowing for unidentified, firm-specific effects does not improve upon our basic model described later in Equation (45.3).
- 29.
A highest-level bank holding company is an entity that is not owned or controlled by any other organization. Its activities are restricted by regulatory agencies as well as by federal and state laws. However, a highest-level BHC can clearly own other lower-level BHCs that, in turn, can own one or more commercial banks. The highest-level BHC can also engage in some nonbank financial activities such as securities brokerage, mutual fund management, and some forms of securities underwriting. By focusing our analysis on highest-level BHCs, we can take into account the impact of these nontraditional bank activities on the BHC’s risk-taking and risk-management behavior.
- 30.
Data limitations, particularly for management compensation data such as stock option grants, prohibit us from extending the analysis to time periods earlier than 1991. Reporting changes related to executive compensation and the concomitant hand-collection of these data precluded us from extending the analysis for more than the 1991–2000 period.
- 31.
We do not include a measure of foreign exchange rate risk in our analysis because the sample of banks employed here operates primarily domestic-oriented businesses. Less than 15% of the observations in this sample have a non-zero exposure to foreign exchange rate risk (as measured by the gross notional value of the firm’s foreign exchange futures/forwards/swaps). We also estimated Equation (45.2) with a trade-weighted U.S. dollar index as an additional independent variable to act as another check on the relevance of foreign currency risk but found that this variable was not a significant factor affecting the vast majority of banks in our sample. A separate analysis of exchange rate risk for the relatively small subset noted above is therefore beyond the scope of this paper.
- 32.
As Froot and Stein (1998) demonstrate, a zero interest rate parameter is typically sub-optimal when the firm faces convex external financing costs. In addition, firms may want to deviate from a zero interest rate parameter when manager-owner agency problems exist. As discussed in Tufano (1998b), hedging can reduce the number of times the firm enters the capital markets and therefore reduces the amount of monitoring performed by external investors. Utility-maximizing managers may therefore have an incentive to hedge more in order to obscure their consumption of perquisites or creation of other agency costs (to the detriment of the firm’s shareholders). In addition, as noted in Pennacchi (1987), among others, the potential mispricing of FDIC deposit insurance may create incentives to take on more risk (and therefore hedge less). To the extent that these problems are mitigated by the banking industry’s frequent (i.e., daily) entrance into the capital markets, the use of a zero interest rate parameter can be viewed as an appropriate benchmark for gauging the relative degree of the financial institution’s hedging activity vis-à-vis its peers.
- 33.
Other important empirical papers related to this study are Schrand (1997) on derivatives usage, Amihud and Lev (1981), Gorton and Rosen (1995), Houston and James (1995), Morck et al. (1988), Crawford et al. (1995), and Hubbard and Palia (1995) on management ownership and compensation issues, as well as Galloway et al. (1997) and Cebenoyan, et al. (1999) on bank risk-taking, and Angbazo (1997) on bank profitability and off-balance sheet activities.
- 34.
The stochastic disturbance term and parameters have been omitted from the following equations to streamline notation. In addition, the y-th year subscripts have been dropped from the right-hand-side variables.
- 35.
As noted earlier, when TOTRISK N, y is used as the dependent variable, the IRR N, y variable is included as an independent variable to control for the BHC’s interest rate risk exposure.
- 36.
The ASYMINFO variable is not replaced in Equation (45.4) because we do not have a suitable alternative for this asymmetric information proxy variable. Admittedly, finding a good proxy for the level of asymmetric information within a BHC is the most difficult aspect of estimating a model such as the one described by Equations (45.3) and (45.4) since information asymmetries are naturally difficult to quantify. One obvious alternative would be to use the bank’s SIZE variable but this variable is needed to control for size-related corporate risk-management effects. It is also highly correlated with the REVENUE variable specified in Equation (45.4) and thus the inclusion of both SIZE and REVENUE would introduce a high degree of multi-colinearity into the model. Interestingly, when we simply drop the ASYMINFO variable from Equation (45.4) and allow SIZE to proxy for both size-related and asymmetric information effects, the parameter estimates for the other independent variables remain relatively unchanged. This suggests that our model is robust to using SIZE as an alternative proxy for information asymmetries.
- 37.
There are not 5,180 observations (i.e., 518 ×10 years) because all banks do not have data for all 10 years.
- 38.
- 39.
To conserve space, these statistics are not reported in the tables.
- 40.
To conserve space, these statistics are not reported in the tables noted above.
References
Allayannis, G. and J. P. Weston. 2001. “The use of foreign currency derivatives and financial market value.” Review of Financial Studies 14, 243–276.
Amihud, Y. and B. Lev. 1981. “Risk reduction as a managerial motive for conglomerate mergers.” Bell Journal of Economics 12, 605–617.
Angbazo, L. 1997. “Commercial bank net interest margins, default risk, interest-rate risk, and off-balance-sheet banking.” Journal of Banking and Finance 21, 55–87.
Berkman, H. and M. E. Bradbury. 1996. “Empirical evidence on the corporate use of derivatives.” Financial Management 25, 5–13.
Blair, R. D. and A. A. Heggestad. 1978. “Bank portfolio regulation and the probability of failure.” Journal of Money, Credit, and Banking 10, 88–93.
Bodnar, G. M., G. S. Hayt, and R. C. Marston. 1996. “1995 Wharton Survey of derivatives usage by US non-financial firms.” Financial Management 25, 142.
Brewer, E., W. E. Jackson, and J. T. Moser. 1996. “Alligators in the swamp: The impact of derivatives on the financial performance of depository institutions.” Journal of Money, Credit, and Banking 28, 482–497.
Campbell, T. S. and W. A. Kracaw. 1990. “Corporate risk-management and the incentive effects of debt.” Journal of Finance 45, 1673–1686.
Campbell, T. S. and W. A. Kracaw. 1990b. “A comment on bank funding risks, risk aversion, and the choice of futures hedging instrument.” Journal of Finance 45, 1705–1707.
Cebenoyan, A. S., E. S. Cooperman, and C. A. Register. 1999. “Ownership structure, charter value, and risk-taking behavior for thrifts.” Financial Management 28(1), 43–60.
Copeland, T. and M. Copeland. 1999. “Managing corporate FX risk: a value-maximizing approach.” Financial Management 28(3), 68–75.
Crawford, A. J., J. R. Ezzell, and J. A. Miles. 1995. “Bank CEO pay-performance relations and the effects of deregulation.” Journal of Business 68, 231–256.
Culp, C. L., D. Furbush, and B. T. Kavanagh. 1994. “Structured debt and corporate risk-management.” Journal of Applied Corporate Finance Fall 7(3), 73–84.
Cummins, J. D., R. D. Phillips, and S. D. Smith. 1998. “The rise of risk-management.” Economic Review, Federal Reserve Bank of Atlanta 83, 30–40.
DeMarzo, P. and D. Duffie. 1995. “Corporate incentives for hedging and hedge accounting.” Review of Financial Studies 8, 743–772.
Demsetz, R. S. and P. E. Strahan. 1995. “Historical patterns and recent changes in the relationship between bank holding company size and risk.” FRBNY Economic Policy Review 1(2), 13–26.
Deshmukh, S. D., S. I. Greenbaum, and G. Kanatas. 1983. “Interest rate uncertainty and the financial intermediary’s choice of exposure.” Journal of Finance 38, 141–147.
Diamond, D. W. 1984. “Financial intermediation and delegated monitoring.” Review of Economic Studies 51, 393–414.
Ferson, W. E. and C. R. Harvey. 1991. “The variation of economic risk premiums.” Journal of Political Economy 99, 385–415.
Flannery, M. J. and C. M. James. 1984. “The effect of interest rate changes on the common stock returns of financial institutions.” Journal of Finance 39, 1141–1153.
Froot, K. A. and J. C. Stein. 1998. “Risk management, capital budgeting, and capital structure policy for financial institutions: An integrated approach.” Journal of Financial Economics 47, 55–82.
Froot, K. A., D. S. Scharfstein, and J. C. Stein. 1993. Risk-management: Coordinating corporate investment and financing policies, Journal of Finance 48, 1629–1658.
Galloway, T. M., W. B. Lee, and D. M. Roden. 1997. “Banks’ changing incentives and opportunities for risk taking.” Journal of Banking and Finance 21, 509–527.
Geczy, C., B. M. Minton, and C. Schrand. 1997. “Why firms use currency derivatives.” Journal of Finance 52, 1323–1354.
Gorton, G. and R. Rosen. 1995. “Corporate control, portfolio choice, and the decline of banking.” Journal of Finance 50, 1377–1420.
Graham, J. R. and D. A. Rogers. 2002. “Do firms hedge in response to tax incentives?” Journal of Finance 57, 815–839.
Graham, J. R. and C. W. Smith Jr. 1999. “Tax incentives to hedge.” Journal of Finance 54, 2241–2262.
Greene, W. H. 1993. Econometric analysis, Macmillan, New York), pp. 370–381.
Hamada, R. S. 1972. “The effect of the firm’s capital structure on the systematic risk of common stocks.” Journal of Finance 27, 435–452.
Haushalter, G. D. 2000. “Financing policy, basis risk, and corporate hedging: Evidence from oil and gas producers.” Journal of Finance 55, 107–152.
Hausman, J. 1978. “Specification tests in econometrics.” Econometrica 46, 1251–1271.
Hirtle, B. 1997. “Derivatives, portfolio composition and bank holding company interest rate risk exposure.” Journal of Financial Services Research 12, 243–276.
Houston, J. F. and C. James. 1995. “CEO compensation and bank risk: Is compensation in banking structured to promote risk taking?” Journal of Monetary Economics 36, 405–431.
Howton, S. and S. Perfect. 1998. “Currency and interest-rate derivatives use in U.S. firms.” Financial Management 27(4), 111–121.
Hubbard, R. G. and D. Palia. 1995. “Executive pay and performance: Evidence from the U.S. banking industry.” Journal of Financial Economics 39, 105–130.
Hughes, J., W. Lang, L. J. Mester, and C-G. Moon. 1996. “Efficient banking under interstate branching.” Journal of Money, Credit, and Banking 28, 1045–1071.
Hughes, J., W. Lang, G. -G. Moon, and M. S. Pagano. 2006. Managerial incentives and the efficiency of capital structure in U.S. commercial banking, Rutgers University, Working Paper.
Kashyap, A. and J. C. Stein. 1995. “The impact of monetary policy on bank balance sheets.” Carnegie-Rochester Conference Series on Public Policy 42, 151–195.
Keeley, M. C. 1990. “Deposit insurance, risk, and market power in banking.” American Economic Review 80, 1183–1200.
Keeton, W. R. and C. S. Morris. 1987. “‘Why do banks’ loan losses differ?’ Federal Reserve Bank of Kansas City.” Economic Review, May, 3–21.
Leland, H. E. and D. H. Pyle. 1977. “Informational asymmetries, financial structure, and financial intermediation.” Journal of Finance 32, 371–387.
Lin, C. M. and S. D. Smith. 2007. “Hedging, financing, and investment decisions: A simultaneous equations framework.” Financial Review 42, 191–209.
Mian, S. L. 1996. “Evidence on corporate hedging policy.” Journal of Financial and Quantitative Analysis 31, 419–439.
Meulbroek, L. K. 2002. “A senior manager’s guide to integrated risk management.” Journal of Applied Corporate Finance 14, 56–70.
Modigliani, F. and M. H. Miller. 1958. “The cost of capital, corporation finance, and the theory of investment.” American Economic Review 48, 261–297.
Morck, R., A. Shleifer, and R. W. Vishny. 1988. “Management ownership and market valuation: an empirical analysis.” Journal of Financial Economics 20, 293–315.
Nance, D. R., C. W. Smith Jr., and C. W. Smithson. 1993. “On the determinants of corporate hedging.” Journal of Finance 48, 267–284.
Newey, W. and K. West. 1987. “A simple positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix.” Econometrica 55, 703–708.
Niehans, J. 1978. A theory of money, Johns Hopkins, Baltimore, MD, pp. 166–182.
Pagano, M. S. 1999. An empirical investigation of the rationales for risk-taking and risk-management behavior in the U.S. banking industry, Unpublished dissertation, Rutgers University.
Pagano, M. S. 2001. “How theories of financial intermediation and corporate risk-management influence bank risk-taking.” Financial Markets, Institutions, and Instruments 10, 277–323.
Pennacchi, G. G. 1987. “A reexamination of the over- (or under-) pricing of deposit insurance.” Journal of Money, Credit, and Banking 19, 340–360.
Saunders, A. 1997. Financial institutions management: a modern perspective, Irwin/McGraw-Hill, New York, NY, pp. 330–331.
Saunders, A., E. Strock, and N. G. Travlos. 1990. “Ownership structure, deregulation, and bank risk taking.” Journal of Finance 45, 643–654.
Schrand, C. M. 1997. “The association between stock-price interest rate sensitivity and disclosures about derivatives instruments.” The Accounting Review 72, 87–109.
Schrand, C. M. and H. Unal. 1998. “Hedging and coordinated risk-management: Evidence from thrift conversions.” Journal of Finance 53, 979–1014.
Shapiro, A. C. and S. Titman. 1985. “An integrated approach to corporate risk-management.” Midland Corporate Finance Journal 3, 41–56.
Sinkey, J. F., Jr. and D. Carter. 1994. “The derivatives activities of U.S. commercial banks,” in The declining role of banking, Papers and proceedings of the 30th annual conference on bank structure and regulation, Federal Reserve Board of Chicago, pp. 165–185.
Smith, C. W., Jr. 1995. “Corporate risk management: Theory and practice.” Journal of Derivatives 2, 21–30.
Smith, C. W., Jr. and R. M. Stulz. 1985. “The determinants of firms’ hedging policies.” Journal of Financial and Quantitative Analysis 20, 391–405.
Smith, C. W., Jr. and R. L. Watts. 1992. “The investment opportunity set and corporate financing, dividend, and compensation policies.” Journal of Financial Economics 32, 263–292.
Spong, K. R. and R. J. Sullivan. 1998. “How does ownership structure and manager wealth influence risk?” Financial Industry Perspectives, Federal Reserve Bank of K.C., pp. 15–40.
Stein, J. C. 1998. “An adverse-selection model of bank asset and liability management with implications for the transmission of monetary policy.” RAND Journal of Economics 29, 466–486.
Stulz, R. M. 1984. “Optimal hedging policies.” Journal of Financial and Quantitative Analysis 19, 127–140.
Stulz, R. M. 1990. “Managerial discretion and optimal financing policies.” Journal of Financial Economics 26, 3–27.
Stulz, R. M. 1996. “Rethinking risk-management,” Journal of Applied Corporate Finance 9, 8–24.
Tufano, P. 1996. “Who manages risk? An empirical examination of risk-management practices in the gold mining industry.” Journal of Finance 51, 1097–1137.
Tufano, P. 1996b. “How financial engineering can advance corporate strategy.” Harvard Business Review 74, 136–140.
Tufano, P. 1998a. “The determinants of stock price exposure: financial engineering and the gold mining industry.” Journal of Finance 53, 1015–1052.
Tufano, P. 1998b. “Agency costs of corporate risk-management.” Financial Management 27, 67–77.
Unal, H. and E. J. Kane. 1988. “Two approaches to assessing the interest rate sensitivity of deposit institution equity returns.” Research in Finance 7, 113–137.
Wall, L. D. and J. J. Pringle. 1989. “Alternative explanations of interest rate swaps: A theoretical and empirical analysis.” Financial Management 18, 59–73.
Wolf, R. 2000. “Is there a place for balance-sheet ratios in the management of interest rate risk?” Bank Accounting and Finance 14(1), 21–26.
Acknowledgments
The author wishes to thank Joe Hughes, Oded Palmon, Bob Patrick, and especially Ivan Brick, for helpful comments that greatly improved this paper. The author has also benefited from comments by Fernando Alvarez, Bob Cangemi, Robert DeYoung, Larry Fisher, Bill Lang, C.F. Lee, Ben Sopranzetti, and Kenneth Spong, as well as from participants of the FMA International Conference, Chicago Risk Management Conference, New England Doctoral Students Conference, and Eastern Finance Association Conference. Scott Williams also provided capable research assistance. This research was based on my dissertation at Rutgers University and was partially supported by the New Jersey Center for Research in Financial Services.
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Pagano, M.S. (2010). An Empirical Investigation of the Rationales for Integrated Risk-Management Behavior. In: Lee, CF., Lee, A.C., Lee, J. (eds) Handbook of Quantitative Finance and Risk Management. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77117-5_45
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