Besides the industry effect, we also examine whether the size and the degree of international involvement of a company affect its use of foreign exchange risk management products. In Table 4.a, the first
regression is run using USEFX as the dependent variable and LASSETS (log of total corporate assets) as the independent variable. Firm size explains only 2% of the variance and the F-value is not significant. The percentage of foreign income (FINCOME) is used to proxy the degree of international involvement14. The second regression results in Table 4.a show that the degree of international involvement explains 9% of the variance of USEFX, with a F-value highly significant at the 0.0003 level. The coefficient of
FINCOME has a high t-value of 3.75, which is also significant at the 0.0003 level. Such findings indicate that the use of foreign exchange risk management products by a corporation is positively related to its degree of international involvement. As corporations become more internationalized, the amount of foreign currency cash flows passing through the firm increases. There may be more need for the risk management products to hedge the currency exposure15.
To ensure that the international effect is not simply an indirect result of the industry effect, we run another regression including all of the independent variables mentioned above. As shown by the results of Regression 4 in Table 4.a, the two effects seem to be quite independent. When combined, the two explain 23% of the variance of USEFX, which is a significant improvement of the explanatory power. The coefficients of both FINCOME and I6 are still highly significant. The overall equation has a F-value of 4.2, which is significant at the 0.0002 level16.
Thus far, the dependent variable USEFX includes the use of all foreign exchange risk management products. The results may be different if we drop the more popular, simpler products and focus on the more sophisticated, third-generation products. We therefore change the dependent variable to the use of third-generation products (USE3GEN) and return the regressions. Interestingly, the results as shown in Table 4.b are quite similar to those of Table 4.a.
Size, International and Industry Effects on the Use of Individual Products
1 Size Effect 2.55 0.95 0.03 3.1 0.08 (3.69)** (1.77) 2 International Effect 2.61 0.42 0.09 14.1 0.0003 (7.28)** (3.75)** 3 Industry Effect 2.67 0.83 0.93 0.84 0.33 1.52 4.46 0.12 3.2 0.006 (1.94)** (0.50) (0.66) (0.6) (0.22) (0.99) (2.77)** 4 International & 1.31 0.49 0.42 0.59 0.38 0.36 0.74 1.59 3.98 0.22 4.2 0.0002 Industry (0.90) (0.91) (3.39)** (0.37) (0.28) (0.26) (0.48) (1.06) (2.53)**
Furthermore, we want to see how the firm size, the international, and the industry variables affect the use of individual foreign exchange products. A regression is therefore run for each of the 15 products. The results are reported in Table 5. Of the fifteen regressions, only four do not show significant F-values at the 0.05 level. Among these four, three are exchange-traded products (futures, options, and futures options). Though most corporate managers are aware of them, these products are less frequently used than the OTC products. Conversely, high R2s are found in the regressions of the more popular products such as forward contracts and foreign currency swaps.
We apply the F-test in each regression to examine whether or not the coefficients of the six industry dummy variables are the same. The results are shown in the last column of Table 5. Significant industrial variations are found at the 0.05 level of the forward contracts, exchange-traded futures options,
participating forwards, foreign currency warrants, break forwards, and compound options. Significant differences are also seen in the cases of cylinder options and forward exchange agreements at the 0.01 level.
In general, the firm size variable does not show significant effects on the use of individual exchange risk management products. Exceptions are found in the cases of forward contracts, foreign currency swaps, and break forwards. As the firm size increases, the use of forward contracts and foreign currency tends to increase. However, the use of break forwards tends to decrease.
Among the size, international and industry effects, the international effect appears to be the most significant. Of the fifteen products, nine products show highly significant international effects. The products which do not have significant international effects are the three exchange-traded products plus forward rate agreements and hindsight options. As the degree of international involvement increases, corporate use of these exchange risk management products tends to increase. Furthermore, the use cuts across a wide spectrum of foreign exchange products.
Table 5
Firm Size, International, and Industry Effects on Corporate Use of Individual Products
Industry Effect
Types of Products Intercept LASSETS FINCOME I1 I2 I3 I4 I5 I6 R2 ValueF- Sign. of F Significant?
Forward contracts 0.85 0.40 0.08 1.06 1.17 1.22 0.13 0.69 1.05 0.27 6.5 0.0001 Yes (2.19)* (2.39)* (2.04)* (2.36)* (3.23)** (3.36)** (0.31) (1.71) (2.47)** Foreign currency swaps -0.05 -0.72 0.19 -0.53 -0.43 -0.16 -0.27 -0.68 0.42 0.21 4.7 0.0001 No (-0.10) (3.14)** (3.59)** (-0.85) (-0.87) (-0.33) (-0.49) (-1.23) (0.71) Foreign currency futures contracts 0.19 -0.18 0.01 1.01 0.40 0.33 0.34 0.77 0.58 0.06 1.1 0.37 No (0.43) (-0.93) (0.01) (2.00)* (0.98) (0.80) (0.75) (1.70) (1.20) Exchange-traded currency options -0.20 0.14 0.04 0.24 0.23 0.10 -0.05 0.43 0.61 0.08 1.5 0.16 No (-0.60) (0.95) (1.11) (0.62) (0.74) (0.31) (-0.15) (1.24) (1.64) Exchange-traded
futures options -0.12 0.05 0.04 0.10 0.07 -0.10 -0.01 0.43 0.44 0.1 1.8 0.08 Yes (-0.43) (0.48) (0.15) (0.33) (0.29) (-0.01) (-0.04) (1.56) (1.51) Over-the-counter currency options -0.08 0.38 0.18 0.20 0.20 0.24 -0.02 0.04 0.28 0.11 2.1 0.04 No (-0.13) (1.53) (3.12)** (0.29) (0.36) (0.44) (-0.03) (0.06) (0.43) Cylinder options -0.43 0.25 0.12 0.01 0.41 0.19 0.18 0.45 0.99 0.14 2.8 0.01 No (-1.01) (1.34) (2.76)** (0.03) (1.02) (0.48) (0.41) (1.02) (2.11)* Synthetic "homemade" forwards -.10 -0.06 0.11 0.19 0.15 0.31 0.14 0.11 0.73 0.12 2.4 0.02 No (-.27) (-0.35) (3.09)** (0.45) (0.45) (0.90) (0.39) (0.28) (1.83) Synthetic -0.15 -0.02 0.13 0.18 0.13 0.12 0.14 0.10 0.71 0.14 2.7 0.01 No
"homemade" options
(-0.43) (-0.17) (3.64)** (0.44) (0.42) (0.37) (0.39) (0.28) (1.88) Participating
forwards, etc. -0.03 -0.12 0.12 0.05 0.23 -0.04 0.36 0.62 0.56 0.12 2.5 0.01 Yes (-0.09) (-0.72) (3.10)** (0.12) (0.65) (-0.11) (0.93) (1.58) (1.36) Forward exchange agreements, etc. 0.21 -0.03 0.02 -0.21 -0.11 0.02 -0.11 0.25 0.50 0.07 1.4 0.21 No (0.63) (-0.18) (0.50) (-0.56) (-0.39) (0.08) (-0.33) (0.74) (1.40) Foreign currency warrants -0.23 0.13 0.06 -0.07 -0.03 -0.09 0.02 0.11 0.79 0.25 5.7 0.0001 Yes (-1.02) (1.38) (2.62)** (-0.26) (-0.14) (-0.44) (0.10) (0.47) (3.20)**
Break forwards, etc. 0.10 -0.14 0.04 -0.02 0.01 -0.03 0.09 -0.02 0.33 0.12 2.4 0.02 Yes (0.65) (-2.15)* (2.59)** (-0.12) (0.09) (-0.17) (0.56) (-0.15) (1.97)
Compound options -0.04 -0.05 0.07 0.09 -0.03 -0.06 -0.06 -0.04 0.41 0.19 4.1 0.0003 Yes (-0.26) (-0.66) (4.11)** (0.48) (-0.21) (-0.36) (-0.32) (-0.26) (2.20)*
Hindsight/lookback
options, etc. -0.03 0.01 0.01 -0.01 -0.02 0.02 0.01 -0.01 0.18 0.08 1.5 0.17 No (-0.29) (0.17) (1.48) (-0.12) (-0.23) (0.19) (0.03) (-0.10) (1.67)
Notes:
Sample size is 173. The numbers in the parentheses are statistics. *Significant at the 0.05 level.
**Significant at the 0.01 level.
Industry effects are tested to examine whether or not they are significant at the 0.05 level. Dependent variables: Use of individual foreign exchange risk management products.
Notes: Independent variables:
LASSETS Log of total corporate assets FINCOME Percentage of foreign income Industry dummy variables
I1 Mining and construction
I2 Manufacturing (e.g. food, textile, etc.)
I3 Manufacturing (e.g. machinery, electronics, etc.) I4 Transportation and public utilities
I5 Wholesale and retail trade