2 L. Ballester, R. Ferrer, and C. Gonz ́alez
volatility on the distribution of bank stock returns. The rest of the paper is organised
as follows. Section 2 contains a review of the relevant literature. The methodology
employed and data used are described in Sections 3 and 4, respectively. Section 5
reports the empirical results. Finally, Section 6 concludes.
2 Literature review
The influence of IRR on bank stocks is an issue addressed by a considerable amount
of literature. The bulk of the research has focused on the two-index model postulated
by [18] and several general findings can be stated. First, most of the papers document
a significant negative relationship between interest rate movements and bank stock
returns. This result has been mainly attributed to the typical maturity mismatch be-
tween banks’ assets and liabilities. Banks are normally exposed to a positive duration
gap because the average duration of their assets exceeds the average duration of their
liabilities. Thus, the net interest income and the bank value are negatively affected
by rising interest rates and vice versa. Second, bank stocks tend to be more sensitive
to changes in long-term interest rates than to short-term rates. Third, interest rate
exposure of banks has declined over recent years, probably due to the development
of better systems for managing IRR.
Early studies on bank IRR were based on standard regression techniques under
the restrictive assumptions of linearity, independence and constant conditional vari-
ance of stock returns (see, e.g., [1, 10]). Later on, several studies (see, e.g., [14, 15])
provided evidence against constant conditional variance. A more recent strand of
literature attempts to capture the time-varying nature of the interest rate sensitivity
of bank stock returns by using GARCH-type methodology. Specifically, [17] led the
way in the application of ARCH methodology in banking, showing its suitability for
bank stock analysis. Subsequent studies have used different types of GARCH pro-
cesses to examine interest rate exposure of banks. For example, [5] and [16] have
employed univariate GARCH-M (GARCH in mean) models to examine both the ef-
fect of changes in interest rates and their volatility on bank stock returns, whereas [6]
and [9] have used multivariate GARCH-M models.
3 Methodology
The model proposed can be viewed as an extended version of a univariate
GARCH(1,1)-M model similar to the formulations by [5] and [16]. It is as follows:
Rit=ωi+λiRmt+θiIt+γiloghit+it (1)
hit=α 0 +α 1 ^2 it− 1 +βhit− 1 +δiVCIt− 1 (2)it| (^) t− 1 ∼N( 0 ,hit) (3)
whereRitdenotes the return on banki’s stock in periodt,Rmtthe return on the
market portfolio in periodt,Itthe change in the interest rate in periodt,itan