Linear and nonlinear interest rate exposure in Spain

Abstract

PurposeThis paper aims to carry out a comprehensive analysis of the influence of interest rate risk on Spanish firms at the industry level.Design/methodology/approachThe methodology employed has its origin in the two‐index linear regression model proposed by Stone. This traditional interest rate exposure model has been extended in this paper to allow for a nonlinear exposure component as well as the presence of asymmetric behaviour in the exposure pattern.FindingsInterest rate exposure is not homogeneous for all the Spanish industries. In line with other markets, highly leveraged industries (construction and real estate), regulated industries (electrical and utilities), and banking industry are the most interest rate sensitive. Nevertheless, the interest rate exposure of Spanish firms also shows some distinctive features due to the peculiar structure of the Spanish market. It is also documented that the classical linear exposure profile prevails over the nonlinear and asymmetric exposure patterns, and that the introduction of the euro seems to have weakened the degree of interest rate risk.Practical implicationsThe evidence presented in this paper can be used as input in decision making by corporate managers, investors, and regulators interested in assessing the impact of interest rate risk at the sector level for hedging, portfolio management, or risk assessment purposes.Originality/valueThis is the first paper which tackles the analysis of the impact of interest rate risk on Spanish firms, taking into account not only the standard linear interest rate exposure profile but also the nonlinear one. The results found in the Spanish case reveal the existence of particularities which might also be present in countries immersed in a process of dramatic economic transformations similar to that experienced by Spain over the past two decades. This is the case of the Central and Eastern European countries which recently joined the European Union.

Linear and nonlinear interest rate sensitivity of Spanish banks

“…This implies that, in general, the linear interest rate exposure of Spanish banks is economically more important than the nonlinear exposure measured using a cubic function. This finding coincides with that reported by Ferrer et al (2010) for the banking sector in an analysis of the interest rate exposure of Spanish firms carried out at the industry level.…”

“…In the same vein, Hallerbach (1994) Following a usual practice in the literature (Flannery and James, 1984;Hirtle, 1997;Benink and Wolff, 2000;Soto et al, 2005;Ferrer et al, 2010), weekly stock returns, adjusted for dividends and stock splits, are employed. The weekly returns are calculated from Wednesday to Wednesday using closing stock prices in order to prevent the possible bias associated to the weekend effect.…”

Exchange Rate and Interest Rate Exposure of UK Industries Using First‐order Autoregressive Exponential GARCH‐in‐mean (EGARCH‐M) Approach

“…Ferrer et al . () and Park and Choi () examined the interest rate exposure of Spanish industry portfolios and US property/liability insurer stock returns respectively. Although they found that more industries were significantly exposed to the long‐term interest rate than the short‐term interest rate, however the exposure coefficients were negative for both interest rate measures.…”

“…The findings indicated that exposure to changes in the long-term interest rates was mostly positive and firms exhibited higher exposure towards the long-term interest rate than the shortterm interest rate. Ferrer et al (2010) and Park and Choi (2011) examined the interest rate exposure of Spanish industry portfolios and US property/ liability insurer stock returns respectively. Although they found that more industries were significantly exposed to the long-term interest rate than the short-term interest rate, however the exposure coefficients were negative for both interest rate measures.…”

Polynomial Regressions and Nonsense Inference

“…In empirical economics, polynomial specifications can be found in many subfields, such as, financial economics [15,16], labor economics [17,18], agricultural economics [19], macroeconomics (exchange rates, [20]) and environmental economics [21,22]. An evocative example can be found in the empirical research dealing with the Kuznets curve and the environmental Kuznets curve; the inverse U-shaped relationship between the variables is typically specified as the dependent variable regressed on the independent and its square (see [23,24]; it is noteworthy that Kuznets' specifications usually employ even-order polynomials).…”