Short-horizon excess returns and exchange rate and interest rate effects

Abstract

We examine the effects of foreign exchange (FX) and interest rate changes on the excess returns of U.S. stocks, for short-horizons of 1 to 40 days. Our new evidence shows a tendency for the volatility of both excess returns and FX rate changes to be negatively related with FX rate and interest rate effects. Both the number of firms with significant FX rate and interest rate effects and the magnitude of their exposures increase with the length of the return horizon. Our finding seems inconsistent with the view that firms hedge effectively at short-return horizons. JEL: F3; G15Keywords: Exchange rate and interest rate effects; smooth transition function; bivariate GJR-GARCH-M; time-varying conditional correlations; Fama-French-Carhart (FFC) factors 2 1 Using a 5% significance level, Jorion (1990) finds that at most, 5.6% of the 287 non-financial U.S. firms in his sample are significantly impacted by FX rate changes whereas, Muller and Verschoor (2006a) find that 29% of the 935 non-financial U.S. firms in their sample are significantly impacted by FX rate changes. 2 He and Ng (1998) find that 26% of non-financial Japanese firms exhibit significant FX rate effects. Similarly, Prasad and Rajan (1995) find that 25% of U.S. industry portfolios exhibit significant FX rate effects.3 frequency compared to prior work. We focus on short-horizon returns since it is often argued that firms are very effective in managing and hedging their short-term exposures (see Booth, 1996;Chow et al., 1997aChow et al., , 1997b. We assume that our return horizons fall within the time period suggested by prior studies. 3 The idea that firms have good hedging skills is often used to explain why one-period returns provide very weak evidence of FX rate and interest rate effects. This explanation seems reasonable since Fortune 500 firms hedge their cash flow exposures over a two-to-four-quarter horizon (see Dolde, 1993), and up to 82% of U.S. firms hedge for an initial maturity of 90 days or less (see Bodnar et al., 1998, pp. 75-77). So the explanation sits well when linked with risk management practice. Correspondingly, long-horizon returns appear to provide stronger evidence of exposure effects relative to one-period returns, due to the increased difficulty firms have in capturing long-term economic exposure (see Booth, 1996). Of course, CAPM estimates of exposure represent residual risk to both firms and investors.We also examine the conditional correlations obtained from the volatility of excess stock returns and the volatility of FX rate changes. This is because the conditional volatility of excess returns and FX rate changes can affect the relation between excess returns and FX rate changes. There is growing support for this view. Bartov et al. (1996), for example, suggest that the volatility of stock returns appears to increase with the volatility of FX rate changes. We statistically test this view using two separate bivariate (asymmetric) GJR-GARCH(1,1) in mean, hereafter, GJR-GARCH-M, that incorporates CAPM. 4 Volatility spillover can a...

Pricing of foreign exchange rate and interest rate risks using short to long horizon returns

“…4 Given the weak evidence for significant exposure betas, it is questionable whether the estimated risk premia are reliable since they are estimated against first-stage exposure betas that are largely insignificant. 5 Second, the tendency for prior studies to use one-period returns to test for risk premia, ignores existing evidence that the magnitude of FX and IR exposure betas increases with the length of the return horizon and that more stocks have exposure betas at longer return horizons Solt 1997a, 1997b;Bodnar and Wong 2003;Joseph, Lambertides, and Savva 2015). This evidence thus provides an interesting setting to test for risk premia.…”

“…8 Furthermore, IR changes are an important component of the model, since IR increases cause firms to reduce investment and borrowing plans (Gertler and Gilchrist 1994;Benito and Young 2007). We follow prior short to long horizon studies and estimate the FX and IR exposure betas (Chow, Lee, and Solt 1997a;1997b;Joseph, Lambertides, and Savva 2015). 9 However, we then sort the exposure betas according to their signs when significant, and estimate the risk premia in line with the Fama-MacBeth approach.…”