Federal Home Loan Bank Advances and Bank and Thrift Holding Company Risk: Evidence from the Stock Market

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.     

Real-Estate Risk Effects on Financial Institutions’ Stock Return Distribution: a Bivariate GARCH Analysis

This paper examines two relationships using the bivariate generalized autoregressive conditionally heteroskedastic (GARCH) methodology. First, the relationship between equity returns of commercial banks, savings and loans (S&Ls) and life insurance companies (LICs), and those of the real-estate investment trusts (REITs), a proxy for the real-estate sector performance. Second, the relationship between conditional volatilities of the stock returns of these financial intermediaries (FIs) and that of REITs. The former relationship allows the spillover of returns between the real-estate and the financial intermediation sector to be analyzed. The latter allows an investigation of the prevalence, direction and strength of inter-sectoral risk transmission to be carried out. Several interesting results are obtained. First, the equity returns of the FIs considered follow a GARCH process and should be modeled accordingly. Second, as found in the literature, returns on REITs should be modeled using the Fama-French multiple factor model. However, this model has to be extended to incorporate a GARCH error structure. Third, all FI returns considered are highly sensitive to REIT returns and the effects are both statistically and economically significant. This is an indication that shocks to REITs returns spillover to the former markets. Fourth, spillover of increased volatility in the real-estate sector to S&Ls and LICs is significant but not to commercial banks.     

Convergence and risk-return linkages across financial service firms

We examine the risk and return linkages across US commercial banks, securities firms, and life insurance companies during the 1991–2001 period. After controlling for changes in the broader stock market, interest rates, and foreign currency values, we find that return and risk interdependencies across these financial firms are significant and size-varying; larger institutions display stronger volatility transmission linkages, while smaller ones exhibit more prominent return-related linkages. The tighter link in risk among large financial institutions (FIs) suggests stronger convergence, employment of common models of risk measurement and risk management, and more intense inter-industry competition, particularly between large banks and large securities firms, compared to smaller institutions. Lack of risk spillover among smaller FIs confirms the intuition that they typically assume more localized and idiosyncratic risk. The co-movement of stock returns among smaller FIs has been helped by the effects of locally based factors, such as economic conditions and state regulations, on all such institutions, and a less diversified product set. Differences in spillover patterns between large and smaller institutions have implications on investment choices and mergers and acquisitions in the industry. Introduction of the Gramm-Leach-Bliley Act (1999) has had dissimilar effects on the riskiness of large versus smaller life insurance and securities firms, and an insignificant effect on commercial banks.     

Institutional Ownership Stability and Risk Taking: Evidence From the Life–Health Insurance Industry

We investigate the relationship between risk taking of life–health (LH) insurers and stability of their institutional ownership within a simultaneous equation system model. Three main results are obtained. First, stable institutional ownership of is associated with lower total risk of LH insurers, supporting the prudent‐man law hypothesis. Second, when investors are sorted in terms of stringency of the prudent‐man restrictions, their negative effect on risk holds for all, except insurance companies, as owners of LH insurers. Third, large institutional owners do not raise the riskiness of the investee‐firms, as proposed by the large shareholder hypothesis. Regulatory implications are drawn.     

Institutional Ownership,Diversification, and Riskiness of Bank Holding Companies

We examine the relationship among the level and stability of institutional ownership, diversification, and riskiness of publicly traded bank holding companies. We find that large and stable institutional ownership is associated with a higher (lower) level of geographic, revenue, and nontraditional banking (asset) diversification and lower risk, suggesting that institutional investors are prudent and favor risk‐reducing diversification strategies. The association between institutional ownership level and diversification is more pronounced under deregulation and during the crisis, suggesting a substitution effect between regulation and market discipline, and a greater level of monitoring and/or advising by institutional investors during the crisis, respectively.     

Measuring technical and scale inefficiencies in the beer industry: Nonparametric and parametric evidence

Two alternative approaches of efficiency measurement, nonparametric and statistical, are employed to calculate three types of efficiency indexes for the U.S. beer industry over the period 1950–1986. The results indicate that the beer industry was operating at a high level of pure technical efficiency over that period. The mean value of this efficiency measure is 93.7 percent based on the nonparametric approach and 87.5 percent based on the statistical approach. The two approaches yield dissimilar values and sources for overall technical inefficiency. The overall technical efficiency index computed under the nonparametric approach stands at 91.10 percent and the observed inefficiency is found to be more due to pure technical inefficiency than to scale inefficiency. Using the statistical approach, the beer industry is found to be less overall technically efficient (68.42 percent) than indicated by the nonparametric methodology and the observed inefficiency is found to be primarily contributed to by scale inefficiency.     

The Association Between Market and Exchange Rate Risks and Accounting Variables: A GARCH Model of the Japanese Banking Institutions

This study has two purposes. First, it estimates the market, interest rate, and exchange rate sensitivities (betas) of the Japanese banking institutions. Second, it investigates the relationship between the market-based measures of risk and accounting-based financial ratios. We extend the literature in three important ways. First, we employ a multi-factor GARCH model to estimate the betas. This framework incorporates non-linearities in the bank stock return modeling and allows for time-varying risk premia. Second, we investigate the determinants of market and exchange rate risk in terms of bank financial ratios. To this end, we regress the beta measures derived from the GARCH model against the corporate decision variables to determine the direction and the magnitude of the impact of the latter on the market and exchange rate risk exposures. Third, by using data on the Japanese banking institutions, we provide a comparison of the bank interest rate and exchange rate sensitivities and the strength of the links between the risk measure and the corporate decision variables between the U.S. and the Japanese banking institutions. This comparison sheds light on the robustness of the results concerning interest rate and exchange rate risk, and their determinants, across the two countries. Several interesting results are obtained. First, empirical results indicate that interest rate is only occasionally significant while market and exchange rate variables are significant for all the banks in the sample. Second, market and exchange rate risk measures do impound information in the financial ratios with the explanatory power of the market beta model being higher than that of the exchange rate beta model. Third, the association of the market-based risk measures and the financial ratios is weaker for the Japanese banks than those found for their U.S. counterparts in the existing literature.JEL Classification: G21, F37     

Interest Rate Risk and Equity Values of Life Insurance Companies: A GARCH–M Model

The importance of managerial decisions related to interest‐sensitive cash flows has received considerable attention in the insurance literature. Consistent with the interest‐sensitive nature of insurer assets and liabilities, empirical research has shown that insurer insolvency is significantly related to interest rate volatility. We investigate the interest rate sensitivity of monthly stock returns of life insurers based on a generalized autoregressive conditionally heteroskedastic in the mean (GARCH–M) model. We examine three different portfolios (equally weighted, risk‐based, and size‐based) with binary variables to explicitly account for varying interest rate strategies adopted by the Federal Reserve System. Results based on data for the period 1975 through 2000 indicate that life insurer equity values are sensitive to long‐term interest rates and that interest sensitivity varies across subperiods and across risk‐based and size‐based portfolios. The results complement insolvency research that links insurer financial performance to changes in interest rates.