Impact of changes in the level, slope and curvature of interest rates on U.S. sector returns: an asymmetric nonlinear cointegration approach

Abstract

This article examines the sensitivity of U.S. sector equity indices to changes in nominal interest rates and in the corresponding principal components (level, slope and curvature of the U.S. yield curve) over the period 1990-2013 using factor models and a nonlinear autoregressive distributed lag (N.A.R.D.L.) approach. Furthermore, for robustness, this research analyses whether the sensitivity of sector stock returns is different depending on the stage of the economy, splitting the whole sample period into two sub-periods: pre-crisis and subprime crisis. In general, the empirical results confirm a substantial exposure to interest rate risk that depends on the model used and the period analysed. In addition, considering the three principal components of the U.S. yield curve, the sensitivity to changes in these components tends to be stronger during the subprime crisis sub-period. Finally, in the N.A.R.D.L. context, about 50% of sectors show long-run relations between sector stock returns and the explanatory factors, mainly during the whole sample and the pre-crisis sub-period. Nevertheless, short-run responses may be mostly shown in the subprime crisis sub-period. Therefore, our results evidence that nominal interest rates and its three components would have asymmetric effects on the U.S. stock returns at sector level, depending on the stage of the economy.

Alternative estimates of the well-known negative relationship between the US interest rate risk and the flow-through capability

“…With respect to IRS, previous literature applies different estimation methods of stock price sensitivity to variations in nominal interest rates. Thus, the bulk of literature has focused on the Stone (1974) two-factor model (Jareño, 2006, and Jareño et al., 2019, among many others):rjt=αj+βj·rmt+γj·Δitu+εjtwhere r jt is the sector j return in time t , β j shows the sensitivity of the sector j to changes in the market return, r mt refers to the stock market return in period t , γ j indicates the sector j return sensitivity to unexpected changes in nominal interest rates, Δ i u t represents unexpected changes in nominal interest rates and ε jt is a random disturbance.…”

“…This two-factor model complements the explanatory power of the CAPM model. Furthermore, some authors (Tessaromatis, 2003; Jareño, 2006; Jareño et al., 2016, 2019; Sevillano and Jareño, 2017) introduce an extension of the Stone (1974) two-factor model. In particular, this model formulates the sector stock returns based on the real interest rate, stock market portfolio return and expected inflation rate.…”

Non-Linear Interdependencies between International Stock Markets: The Polish and Spanish Case

“…This methodology has been used in some previous studies. References [12][13][14] analyze the sensitivity of the Spanish stock market returns to variations in nominal interest rates and their main components (level, slope, and curvature), as well as study the connectedness between Bitcoin and gold price returns using the NARDL approach. Other authors such as References [42][43][44] focus on renewable and environmental sustainability issues to quantify the asymmetric relationship between sustainability-related variables and other macroeconomic variables through the using of the NARDL methodology.…”

“…Thus, to the best of our knowledge, our paper contributes to the previous literature by studying in depth the expected non-linear interdependencies between relevant international stock markets, focusing on the Polish and the Spanish stock market. To that end, this research applies a NARDL approach to estimate both long-and short-run asymmetries ( [12][13][14]45]), not only for the whole sample period, but also for different sub-periods. This methodology allows us to simultaneously check long-and short-run nonlinearities by estimating positive and negative partial sum decompositions of the regressors.…”

“…Second, unlike previous studies that use alternative methodologies to explore the interdependencies between international stock markets, this paper proposes to apply a NARDL methodology. In concrete, unlike most of the previous literature that analyzes the direction of the contagion effect between financial markets by using a GARCH framework, such as [10,11], to the best of our knowledge, our research is the first study that applies the NARDL approach to estimate both long-run and short-run asymmetries [12][13][14] between the Polish and the Spanish stock market returns and some other relevant and international stock market returns. Finally, for robustness, this study compares estimates in different stages of the economy.…”