76 R.W. Faff, T.J. Brailsford Journal of Energy Finance and Development 4 1999 69–87
ASX 21 industry provides a mixed signal; while it has a large RDRC, this effect will be countered by the positive effect via the inclusion of the Petroleum Products
sub-industry ASX 213. A similar argument applies in the case of the Miscellaneous Industrials ASX 22 because it includes agricultural products, textiles, and fabricated
metal products. Moreover, we are skeptical of any effect revealing itself in relation to the Other Metals industry ASX 2, as it too provides a mixed signal. This industry
has a high RDRC but is also likely to experience an indirect positive sensitivity because oil prices are generally correlated with metals prices.
It is also useful to consider the industries that have a value for the RDRC that is extremely low. One notable case is the ASX 13 Retail industry, which seems to be
consistently low as it relates to ABS 8 Clothing and Footwear, ABS 19 Miscellaneous Manufacturing, and ABS 23 Retail Trade. Another consistent case of low RDRC
is the ASX 11 Engineering industry in relating to ABS 18 Other Machinery and Equipment and ABS 19 Miscellaneous Manufacturing. Accordingly, other things
being equal we predict a negligible role for the oil price factor for these industries. The remaining industries also appear to generally indicate a negligible role for the
oil price factor.
This analysis highlights the importance of conducting the test on industry sectors. The hypothesized differential impact means that aggregate market analysis as pre-
viously conducted in papers such as Jones Kaul, 1996 may mask industry effects. In summary, we predict a positive sensitivity in four oil and oil-related industries
ASX 1, 3, 4, and 5 and a negative sensitivity in four other industries ASX 2, 10, 12, and 14. However, the ability of firms to pass on oil price changes to their customers
and the extent of hedging activity mitigate against finding significant results.
3. Data and research design
3.1. Extra-market oil return sensitivities Consider a two-factor model of the form:
5
R
it
5 a
i
1 b
i
R
mt
1 g
i
OILRAUD
t
1 e
it
1 where R
it
is the return on the ith asset or portfolio in month t, R
mt
is the return on the market index in month t, and OILRAUD
t
is the return on the oil price in month t
expressed in Australian dollars. Following Merton’s 1973 intertemporal CAPM, investors are concerned about
unfavorable shifts in the investment opportunity set over time, in addition to their diversification needs. This feature gives rise to hedging activity, whereby investors
are assumed to be able to construct portfolios that protect against uncertainties in state variables. Oil price risk may be viewed as one such case in which investors seek
to hedge. A further related dimension of risk that is often discussed in a hedging context is foreign exchange risk.
6
This is particularly relevant in the context of oil because it is priced in an international market denominated in U.S. dollars. As a
consequence, we can think of the domestic currency oil price factor as having two
R.W. Faff, T.J. Brailsford Journal of Energy Finance and Development 4 1999 69–87 77
components, namely a a pure oil price factor denominated in U.S. dollars and b an exchange rate factor. Accordingly, consider the following expression for the oil
return in Australian dollars:
OILRAUD
t
5 ln[OILAUD
t
OILAUD
t
2
1
] 2
OILAUD
t
5 OILUSD
t
XRAUDUSD
t
3 where OILAUD
t
is the oil price in month t, expressed in Australian dollars, OILUSD
t
is the oil price in month t, expressed in US dollars, and XRAUDUSD
t
is the AUDUSD exchange rate at t, namely the value of 1 Australian expressed in U.S. dollars.
Upon substitution of Eq. 3 into Eq. 2, we get: OILRAUD
t
5 ln
3
OILUSD
t
XRAUDUSD
t
2
1
OILUSD
t
2
1
XRAUDUSD
t
4
5 ln
3
OILUSD
t
OILUSD
t
2
1
4
1 ln
3
XRAUDUSD
t
2
1
XRAUDUSD
t
4
5 OILRUSD
t
1 ln
3
XRUSDAUD
t
XRUSDAUD
t
2
1
4
4 where XRUSDAUD
t
is the USDAUD exchange rate at t, namely the value of 1 U.S. expressed in Australian dollars, and OILRUSD
t
is the oil price return in month t
, expressed in U.S. dollars. Furthermore, noting that the return from holding U.S. dollars, XR
t
, is defined as follows:
XR
t
5 ln
3
XRUSDAUD
t
XRUSDAUD
t
2
1
4
, 5
the final oil return decomposition becomes: OILRAUD
t
5 OILRUSD
t
1 XR
t
6 A comparison of Eqs. 1 and 6 suggests that the imposed restriction provides a
method of testing the validity of the specification in Eq. 1. The validity of this restriction can be tested by the following model:
R
it
5 a
i
1 b
i
R
mt
1 g
i
OILRUSD
t
1 d
i
XR
t
1 e
it
7 It should be noted that g and d coefficients in Eq. 7 will be equal only if the exchange
rate has absolutely no influence on returns, except for its impact on AUD-denominated oil prices. If the coefficients are not equal, then Eq. 1 is mis-specified.
3.2. Data The data used are continuously compounded monthly returns over the period July
1983 to March 1996, on 24 Australian industry portfolios based on the ASX industry groupings. Returns are calculated from the Price Relatives File of the Centre for
78 R.W. Faff, T.J. Brailsford Journal of Energy Finance and Development 4 1999 69–87
Table 2 Estimation of the Market Model Augmented by an Oil Factor: 1983:07 to 1996:03
ASX Industry a
i
b
i
g
i
w
i a
R
2
DW 1. Gold
2 0.0093
1.3977 0.0759
0.2098 0.571
1.939 21.23
14.19 1.21
2.62 2. Other Metals
2 0.0069
1.3031 2
0.0358 —
0.700 1.778
21.65 18.50
20.84 3. Solid Fuels
0.0031 0.6648
2 0.0117
— 0.427
1.732 0.81
10.47 20.31
4. Oil and Gas 2
0.0048 0.9772
0.2349 0.1891
0.736 2.006
21.27 19.07
7.23 2.35
5. Diversified 0.0052
1.0275 0.1276
— 0.739
1.716 Resources
1.72 20.49
4.21 6. Developers and
2 0.0018
1.0628 2
0.0249 —
0.797 1.927
Contractors 20.67
24.01 20.93
7. Building Materials 0.0011
0.8157 2
0.0033 —
0.767 2.056
0.50 22.07
20.15 8. Alcohol and
0.0065 0.8649
2 0.0197
0.1740 0.498
1.954 Tobacco
1.25 11.99
20.43 2.14
9. Food and 0.0053
0.8029 2
0.0706 —
0.693 1.929
Household Goods 1.96
17.82 22.60
10. Chemicals 0.0082
0.8017 2
0.0424 —
0.619 2.052
2.63 15.31
21.34 11. Engineering
0.0014 0.7511
2 0.0196
— 0.629
1.890 0.47
15.78 20.68
12. Paper and Packaging 0.0029
0.7772 2
0.0884 —
0.678 1.994
1.06 17.04
23.21 13. Retail
0.0006 0.8581
2 0.0439
— 0.696
1.737 0.23
18.20 21.54
14. Transport 2
0.0004 1.1098
2 0.0959
— 0.742
1.734 20.13
20.13 22.88
continued
Research in Finance CRIF at the Australian Graduate School of Management. The proxy for the market portfolio used is a value-weighted domestic index supplied by
CRIF and a value-weighted global index supplied by Morgan Stanley. The oil price data are obtained from Equinet. Of note is that the oil price displayed considerable
volatility over the period, with a major price fall occurring in late 1985 and a major price spike during 1990, around the time of the Gulf War.
4. Results
