Our second motivation for a firm-le

Our second motivation for a firm-level return volatility analysis is
rooted in the work of Campbell et al. (2001), who argue that many
investors tend to hold significant individual stocks such that changes
in industry-level and idiosyncratic volatility matter.1 While this fact is
now well understood, the sources of firm-level volatility are relatively
less understood.
The third motivation is that there is lack of knowledge on the
economic significance of the oil price for investors. For example,
Narayan and Sharma (2011) do not show how investors can profit by
using information contained in the oil price. And, while Driesprong
et al. (2008) do, their focus is on the first moment of return. Therefore,
our approach of understanding the role of the oil price on firm return
volatility and subsequently on profitable trading strategies is new.
1.3. Summary
Foreshadowing our main results, we find that the oil price is a
significant determinant of stock return volatility. Generally, the effect
(in terms of sign) of the oil price on stock return volatility is mixed;
but for the bulk of the firms the oil price reduces stock return volatility.
We show that in 13 of the 14 sectors the oil price reduces stock return
volatility. The only exception is banking sector firms, for which the oil
price has a positive effect on stock return volatility. We attribute this
to some of the salient features of banking sector firms, such as the
higher systematic risk of firms in the sector. Our results also reveal
that the oil price has a persistent effect on stock return volatility and
the effect differs by sector. We also find that the oil price affects return
volatility of different sizes of firms differently. Taken together while
our results suggest that the oil price has a heterogeneous effect on
stock return volatility, they also confirm the relevance (at least from a
statistical point of view) of the oil price in influencing stock return
volatility. Motivated by this finding, we then investigate potential economic
gains that investors can make by devising trading strategies
based onmodelswhere the oil price is used to forecast stock return volatility.
We compare trading strategies based on the oil price with those
fromhistorical averages and find on average across all 14 sectors investors
can improve returns by around 5% if theywere to use amodel of the
oil price to forecast firm return variance as opposed to using historical
averages. We also show that the improvements in returns from an oil
price basedmodel are heterogeneous in that investors in certain sectors,
such as financial and manufacturing, can potentially gain by over 11%
while investors in some sectors, such as general services and medical,
gain by less than 1% per annum.
We organise the rest of the paper as follows. In the next section, we
discuss the relationship between the oil price and stock return volatility.
In Section 3,we discuss the empiricalmodel and results. In Section 4, we
provide an explanation for our results. In Section 5, we devise a trading
strategy based on forecasting stock return volatility by utilising information
in the oil price. We compare the profitability of this model
with a historical average based variance forecastmodel. In the final section,
we provide some concluding remarks.
2. Relationship between the oil price and return volatility
Previous studies document various transmission channels through
which the oil price has an impact on certain macro-economic variables,
such as interest rate, money supply, gross domestic product, and
exchange rate (see, for example, Dohner, 1981; Fried and Schultze,
1975; Hotelling, 1931; Mork, 1994; Pierce and Enzler, 1974). According
to Fried and Schultze (1975) and Dohner (1981), thewealth transfer effect
from the oil price rise emphasizes the shift in purchasing power
from oil importing countries to oil exporting countries. As a result,