4 presents the econometric methodologies used to test the multi-factor model. Section 5 discusses the data. Section 6 reports the empirical results. Concluding
comments are offered in Section 7.
2. Literature review
Previous studies on interest rate and exchange rate sensitivities in bank stock returns include the works of Choi et al. 1992 and Wetmore and Brick 1994,
1998. These authors apply a three-index model market, interest rate, and exchange rate factors to the bank stock returns under the assumption of constant variance
error terms. Consequently, a simple regression technique such as OLS or GLS can be employed to test whether the slope coefficients are significant different from zero
and that allows them to answer whether the bank stock returns are sensitive to those risk factors. To test the stabalities of estimated slope coefficients, they divide
the full sample into several sub-samples based on pre-specified structure breaks. Then, they run separate regressions within the sub-samples and conduct the tests.
What they find in their studies is that the coefficients of market risk, interest rate risk, and exchange rate risk are time dependent and differ by bank type. These
studies mainly focus on the sensitivities of beta risks and do not consider asset pricing tests.
Many studies have provided strong evidence against constancy of the conditional variance of asset returns and in favor of time-varying risk premia when ARCH-type
model is employed. Thus, it is unwise if researchers continue to assume constant volatility. Song 1994 is the first study to use the ARCH-type model in banking.
He finds that ARCH-type modeling is the appropriate framework in analyzing bank stock returns based on Hansen’s 1982 test of overidentifying restrictions.
According to his results, both market and interest rate risk measures i.e., betas of banks do change significantly over time and they are also priced in bank stocks.
However, he does not consider the exchange rate risk. In addition, although GMM estimator is robust but, in general, it is not efficient. Flannery et al. 1997 is
another study applying ARCH-type modeling strategy in banking. Specifically they apply a two-factor GARCH model originally developed by Engle et al. 1990 to
price both US bank and non-bank stock portfolios. They find that both market and interest rate risks are time-varying and significantly priced in the non-bank stock
portfolio, but only the market risk is priced in the bank stock portfolios. One drawback in their study is the two-step procedure used in estimating and testing a
two-factor GARCH model. As pointed out by Ng et al. 1992, the two-step estimation procedure maintains consistency of the parameters of interest but it
sacrifices the efficiency. Also, they do not consider exchange rate risk. Given the lack of study of exchange rate risk pricing and the previous inconclusive results of
interest rate risk pricing in bank stock returns, it is the purpose of this paper trying to provide more convincing evidence concerning the pricing of bank stock returns
by estimating and testing both unconditional and conditional three-factor asset pricing models utilizing three different econometric methodologies, namely NLSUR
via GMM, pricing kernel, and MGARCH-M.
3. The theoretical motivation
