1997 - risk measurement and hedging

8/21/2019 1997 - Risk Measurement and Hedging

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Comments Welcome

Current Version: April 1997

Original Version: March 1996

Risk Measurement and Hedging

Mitchell A. Petersen

J.L. Kellogg Graduate School of Management Northwestern University

Evanston, IL 60208

and

S. Ramu Thiagarajan

J.L. Kellogg Graduate School of Management

Northwestern UniversityEvanston, IL 60208

Abstract

It is difficult to judge the intentions and performance of corporate managers when it comes to their risk

management programs. To evaluate the effectiveness of a risk management program or to test financial

theories of risk management, a firm’s underlying risk exposure must be known. This paper examines a

setting where the firm’s derivative strategies are known and asks how well we can measure the effect of

their hedging program on the firm’s fundamental accounting and market value measures. We study two

gold mining firms which have diametrically opposed policies toward derivatives. American Barrick

aggressively hedges its gold price risk using derivatives; Homestake Mining uses no derivatives. Instead

Homestake Mining uses a combination of operating financial and accounting decisions to manage its risk


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Homestake Mining uses a combination of operating financial and accounting decisions to manage its risk

I: Introduction.

Measuring a firm’s risk exposure and how hedging alters the exposure is the focus of this paper.

We examine a setting in which both the unhedged risk exposure and the effect a hedging program has on

this risk exposure can be estimated. We do this by comparing two companies, which are at opposite ends

of the hedging spectrum, but operate in an industry where measurement of the exposure should be relatively

straightforward. We compare the risk exposure of two firms in the gold mining industry -- American

Barrick which aggressively hedges its gold price risk and Homestake Mining which uses no derivatives to

hedge its gold price risk. By examining the risk exposure of the unhedged and the hedged firm, we can

trace the effects of gold price changes on the different components of the firm’s financial statements as

well as its market values. We chose this experimental design to understand the effects of a risk

management program.

The primary rationale for corporate risk management is that it adds value to the corporation in ways

that shareholders cannot on their own. While the amount of corporate resources devoted to risk

management may make it appear that such an activity adds to shareholder value, risk management does

not add value in the absence of market imperfections (Fite and Pfleiderer, 1994). The literature on risk

management has proceeded along two lines. Assuming that the risk exposure faced by a firm is known, the


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How much a firm should hedge depends upon the firm’s estimate of its risk exposure. Even though the use

of derivatives by corporations is generally preceded by the explanation that the program is designed to

hedge the firm’s risks and not for speculation, distinguishing between the two is difficult without

knowledge of the firm’s risk exposure. The challenge of precisely measuring a non-financial firm’s risk

exposure makes this distinction even more ambiguous. In this paper, we measure the risk exposure of a

gold mining company and examine the effect of hedging on this exposure through the use of a research

design of comparing two companies with well-articulated strategies on hedging.

Much of the necessary data for measuring the firm’s risk exposure is derived from the firm’s

financial statements. The accounting treatment of derivative transactions and their disclosure in financial

reports is still a matter of intense debate. Absence of knowledge about a firm’s underlying risk exposure

makes providing guidelines for accounting treatment more difficult. Part of the difficulty stems from the

absence of a framework for recognition and disclosure of derivative instruments, resulting in different

accounting treatment of economically identical transactions. The absence of consistency in accounting

treatment has resulted in managers basing their hedging decisions on the accounting treatment the hedges

receive. This paper contributes to the general discussion of the different accounting treatments (deferral

hedge accounting versus mark-to-market accounting) by providing empirical evidence on the measurement


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Homestake Mining adjusts its operations such that both cash inflows (sales) and cash outflows (extraction

costs) move with the price of gold. This provides Homestake Mining with some protection from gold price

volatility. Its risk management system also extends to its accounting choices. We present evidence that

Homestake Mining attempts to reduce the volatility of its accounting income through discretionary choices

of accounting methods, estimates, and accruals. An important inference from our paper is that classification

of firms as hedger and non-hedger based on the use of derivatives can be misleading.

The paper is organized as follows. The next section provides a brief review of the tests of risk

management, the motivation for this paper, and the research design employed. In Section III we estimate

the effect of gold prices on the firm’s cashflows and equity values. This is where the direct effect of a

hedging program should be seen. Consistent with intuition we find that the cashflow of the unhedged firm

is dramatically more sensitive to gold prices than the hedge firm. Contrary to our expectations, the equity

returns of both firms are highly sensitive to gold price movements. In fact, we find American Barrick’s (the

hedged firm’s) equity is only marginally less sensitive to changes in gold prices than Homestake Mining’s

(the unhedged firm’s) equity. Differences in leverage and expected growth rates do not fully explain this

finding. We describe the interaction between the firms’ explicit hedging programs or lack thereof and their

discretionary accounting choices in the fourth section. The final section concludes the paper by pointing


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by searching financial databases for keywords such as hedging, swaps, or options. Geczy, Minton and

Schrand (1996) take a sample of S&P 500 firms with foreign exchange rate exposure and classify them as

hedgers based upon finding references to derivative instruments in their financial statements. Hentschel

and Kothari (1997) use a combination of the two selection methods. Comparing the characteristics of

hedgers and non-hedgers is a useful way to explore why firms hedge.

A possible concern with comparing derivative users and nonusers to make inferences about hedging

is that this method has the potential of mis-classifying hedgers as non-hedgers and speculators as hedgers.

As an example of the first case, consider firms in the gold mining industry. Firms in this industry may

borrow gold instead of dollars. A gold loan is economically equivalent to a cash loan plus a series of short

positions in the forward gold market. However, accounting disclosures do not uniformly classify this as a

hedging instrument similar to a forward contract. American Barrick, which used gold loans widely

(especially in the mid and late 80s), initially did not even classify this as a regular loan. It treated this

liability as deferred revenue and then made adjustments to its income statement in future years based on

the delivery of gold to repay the loans. Thus, one firm which uses derivatives (forwards) may be classified1

as a hedger, but another firm which uses gold loans may be classified as a non-hedger. Hentschel and

Kothari’s finding that the volatility of derivative users and nonusers is similar is consistent with this


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It may be equally difficult to distinguish hedgers from speculators. The previous literature has

associated the use of derivatives with hedging. However, derivatives can be used to either lower or raise

a firm’s risk exposure. For example, the finding that more highly levered firms are more likely to hedge

(i.e. use derivatives) can be motivated by the argument that these firms are attempting to lower their

expected costs of financial distress (Haushalter, 1997, and Guay, 1997). Alternatively, we could argue that

these highly levered firms speculate more (i.e. use derivatives) to increase the call option implicit in the

equity of a levered firm. This makes interpreting the empirical results difficult. Therefore the only way to

know whether a firm is hedging or speculating is to know the firm’s underlying risk exposure.

A second concern with the approach used in existing research is that it treats hedging as a binary

decision. In practice, a firm that hedges a small portion of its risk is closer to a non-hedging firm than to

one that hedges most of its risk. Tufano (1996) and Haushalter (1997) raise this problem and address it by

calculating a continuous hedging variable in their studies. Tufano calculates the change in the value of the

gold mining firm’s derivative portfolio (its delta) from survey data. Higher deltas (i.e. greater sensitivity

of the firm’s derivative portfolio to gold price changes) mean that more of the firm’s risk has been hedged.

Haushalter uses the fraction of the current year’s production which has been hedged with derivatives as a

dependent variable. He shows that the continuous variable contains significantly more information than a


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this is the result of no underlying exposure or because the firm has completely hedged its underlying

exposure, but the transactions did not receive deferral hedge accounting treatment. Current disclosures

often make it difficult to decipher the full nature or extent of a firm's hedging program. 2

It is rarely possible to observe the hedged and the unhedged cash flows for a firm. Thus, we use

a research design which approximates the ideal experiment (see Guay, 1997, for an alternative research

design). The research design in this paper involves the comparison of the risk exposure of two firms in the

gold mining industry: Homestake Mining Inc. and American Barrick. The gold mining industry was chosen

since gold companies are unique in that both the demand for investment capital and the supply of cash

flows from operations depend on a single macro-economic variable -- the price of gold. The value of their

assets and their cashflows fluctuates with the price of gold. Gold is a commodity with little variation in

quality and thus the market for gold is arguably competitive and output is comparable across firms. Being

competitive, the sale price of the product is beyond the control of any individual firm. Finally, the gold

derivative markets are well developed with a variety of different hedging instruments ranging from

forwards and options to spot deferred contracts and gold bullion loans (see Tufano, 1995, for a good

description of hedging instruments used in the gold industry).

The two firms have well articulated hedging strategies which are diametrically opposite. American


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Barrick’s policy to hedge nearly all of its production for the next three years and 50 percent of its

production in years four through six. Among gold mining firms, American Barrick is the most aggressive

in its hedging program and thus it makes a good polar case for our analysis.3

Homestake Mining's approach to hedging lies at the other extreme. Homestake makes it an explicit

corporate policy to hedge little or none of its production. "In order to maintain the maximum upside

potential for gold, ...Homestake does not hedge or use other methods to sell forward its future gold

production. As a result, Homestake's earnings fluctuate with changes in the price of gold along with other

factors including total production costs" Homestake Mining serves as a proxy for the unhedged firm,4

whereas American Barrick serves as a proxy for the hedged firm. The difference between the two should

reflect the effect of hedging.

III: Empirical Relationships: The effect of gold price risk on gold mining firms.

A. Risk Exposure of Operating Cashflow and its Components.

1. Sensitivity of Sales Revenue.

Theory argues that one objective of a hedging program should be the firm’s cashflow (Froot,

Scharfstein, and Stein, 1993 and Lessard, 1990). We start our investigation earlier in the production chain

by examining the risk exposure of the firms’ sales revenue and operating costs. Examining operating


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factor because neither revenues nor costs are correlated with the risk factor. Alternatively it is possible that

both revenues and operating costs are highly correlated with the risk factor, but their difference is not.

Thus, to track the source of or lack of a risk exposure, we begin with the firm’s sales revenue. 5

The sensitivity of the firm’s sales revenue is estimated by regressing the percentage change in sales

revenue from gold on the percentage change in gold prices. Percentage changes are calculated as the6

difference in the natural log of the variable. Gold price changes are based on either year-end figures or the

average of the monthly gold prices obtained from COMEX. The results for both firms are reported in7

Table I. As expected, American Barrick’s sales are essentially independent of the price of gold. The R 2

for the regression is small (0.007) and the slope coefficient is not statistically different from zero (see Table

I -- Panel A). The sensitivity of Homestake Mining’s gold sales is higher, but not one. A 10 percent rise

in the price of gold is associated with only a 3.7 percent rise in Homestake’s sales (Table I -- Panel B) and

the coefficient is not statistically different from zero (R = 0.119).2

The low risk exposure for the unhedged firm is contrary to our intuition that the price of gold is a

significant risk factor facing the gold mining industry. The problem is the way we have estimated the risk

exposure of sales. We measure risk exposure by correlating changes in gold sales revenue with year-end

changes in gold prices. While market prices such as asset and equity values should respond immediately


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throughout the year may respond more slowly to the gold price changes. For example, if the price of gold

rises dramatically in July, only gold sales for the later half of the year will rise. Sales should therefore

depend on the average price of gold and not upon the year-end price of gold. Consequently, instead of

measuring gold price changes based on year-end prices, we calculate the average of the monthly prices and

then calculate the percentage change in this average price.

The risk exposure for Homestake Mining is much more significant when estimated this way. A 10

percent rise in the price of gold is now associated with an 8.9 percent rise in sales revenue (see Table I --

Panel B). A large fraction of the variability in Homestake’s sales revenue is associated with gold prices (R 2

= 0.585). Using average prices, the risk exposure for American Barrick is still essentially zero using (R 2

= 0.024).8

Our estimates of risk exposure thus far have examined only the firm’s gold revenue. American

Barrick is a pure gold mining firm. Homestake Mining has increasingly focused on the gold mining

business, but had interests in lead, silver and uranium mines in the early part of our sample. Since a firm

may choose to be in multiple businesses to lower their risk – as an alternative to hedging with derivatives

– we test the robustness of our results by estimating the sensitivity of Homestake Mining’s total sales

revenue to the price of gold. This enables us to capture the risk exposure of the entire firm as opposed to


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our estimated risk exposure does not change. The coefficient falls from 0.89 from 0.84, but the coefficient

on gold price changes is no longer statistically significant (t=1.2).

2. Sensitivity of Sales Quantity and Average Price Realized

In addition to reporting segmental sales revenue, the annual reports also separately discloses the

components of sales revenue -- sales quantity and the average realized price. For the unhedged firm, sales

revenue will positively covary with gold prices because the price received per ounce of gold changes. In

addition, the firm may increase or decrease gold sales as the price of gold rises by adjusting inventories or

adjusting production schedules. This may either diminish or accentuate the sensitivity of the firm’s sales

revenue to gold price changes since, depending upon management’s expectation of future prices, they may

either raise or lower sales when the gold price increases.

For both American Barrick and Homestake Mining, changes in the physical sales quantity are

uncorrelated with changes in gold prices even after allowing for past prices to affect current production

decisions. This is clear from the regressions reported in Table I. Both firms sell slightly more gold when

prices fall, but the R² never rises above 15 percent and is never statistically different from zero (see Table

I - Panels A and B).

The correlation between gold prices and sales revenue comes solely from the variation in the price


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Homestake Mining we find a text book case of an unhedged firm (see Table I - Panel B). The average sales

price received by Homestake Mining rises and falls one for one with the average price of gold and there

is little unexplained variation in Homestake’s sales price (R² = .977). American Barrick has no risk

exposure if we estimate it using the change in year end prices ( = .122 and t = 0.8). However, if we use

changes in the average gold price as our risk factor, the average sales price for American Barrick increases

3.3 percent for every 10 percent increase in the price of gold. With an R of 40 percent, a large fraction9 2

of this variability is explained by average realized prices. As noted earlier, when we measure risk exposure

relative to the year-end price, American Barrick’s estimated risk exposure was only .112 and not

statistically different from zero.10

The different methods for measuring gold price changes (year-end price or yearly average) give

significantly different estimates of both firms’ risk. This is despite the fact that the correlation between the

two measures is 70 percent. The results suggest that the actual price the gold mining firm receives

fluctuates on a monthly or even a daily basis. Thus, the firm’s true risk exposure is the change in the

average gold price, not the year-end gold price. Hedging with derivatives tied to year-end prices (European

derivatives), such as those used by American Barrick, leaves the firm less than perfectly hedged relative

to the prices which transpired throughout the year. Derivatives which are based on average prices over the


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3. Operating Costs.

Since firms mine gold in a world where gold prices fluctuate, they may change their mining

strategy as a function of the price of gold. Both companies extract gold from multiple mines with different

extraction costs. For example, Homestake Mining’s most efficient mine in 1994 was the David Bell mine

with an extraction cost of $211 dollars per ounce. Its least efficient mine in 1994, the El Hueso mine in

Chile, had an extraction cost of $416 dollars per ounce. As the gold price declines, these firms have the

option of closing down the least efficient mines, reduce the output of these mines, or mine in the lower cost

areas of these mines. This provides gold mining firms with a natural, albeit imperfect, hedge. A natural

hedge such as this one will arise whenever a firm faces an upward sloping cost curve. As gold prices rise,

its marginal and average costs rise, although its average cost rises less than its marginal cost. Thus, its

profi t margin should not be as sensitive as revenues to changes in gold prices. This positive covariance

between extraction costs and gold prices should be less evident for a hedged firm. When gold prices rise,

its marginal revenue per ounce does not increase, and thus its incentive for expanding output in less

efficient mines is diminished.

Since we already know that the ounces sold by both firms are uncorrelated with gold prices, total

costs are a noisy measure of the firm’s cost structure. Consequently, we use the extraction cost per ounce


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Homestake Mining does appear to actively alter its mining, and thus its extraction costs, based on

the price of gold (see Table II). As gold prices rise, its extraction costs also rise as they switch to mining

lower grade ores, which are more costly to extract. A rise of 10 percent in the price of gold during the year,

is associated with a 2.4 percent increase in its extraction costs. As discussed above, altering the firm’s cost

structure takes time. If it takes longer than a year for the firms to adjust its cost structure, then changes in

today’s extraction cost depend not only on the current gold price change but also on the previous year’s

gold price changes. Empirically, we find that it takes up to a full year for Homestake Mining’s production

to fully respond to changes in the price of gold. When we include the gold price change and its two lags,

only the current gold price change and its first lag are statistically different from zero (Table II - Panel B).

The long term adjustment in costs to changes in gold price is sizeable. A 10 percent increase in gold prices

leads to an eventual increase in the average extraction cost of 4.5 percent (using only statistically significant

coefficients). Remember this is the increase in the average cost; the increase in the marginal extraction cost

must be even higher.

The sensitivity of total extraction costs for American Barrick is similar to Homestake Mining (0.36

versus 0.37), but is estimated with very little precision (t=0.6). The R² is tiny (4%). Additional statistical

power would be useful here to determine if the coefficient is truly economically significant, or just big and


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opportunities positively covary with operating cashflows. For example, if the firm has few opportunities

to profitably invest when operating cashflows are low, but many opportunities when operating cashflows

are high, then there is little variability in its net cashflow. For this firm, hedging will not be value

enhancing. To fully describe a firm’s exposure to the risk factor, we must also estimate how its13

investment opportunities covary with the risk factor. This is an empirical challenge since the correct

dependent variable should be desired investment opportunities, not actual investments. Since desired

investment is not observable, the firm’s actual investment expenditure could be used as a proxy for desired

investment.

If the attractiveness of expanding mining capacity rises with the price of gold, we should see more

investing when gold prices rise whether a firm is hedged or not. This statement assumes that firms are able

to fund all of their positive NPV projects. However, if the purpose of hedging is to provide sufficient funds

to finance the firm’s investment opportunities in cash poor states of the world, then assuming unconstrained

availability of funds may be suspect. If we discover that an unhedged firm’s investment expenditure is

uncorrelated with a risk factor, there are two possible explanations. It is possible that investment

opportunities are truly uncorrelated with the risk factor. In this case, we can ignore the investment side of

the hedging question and concentrate on hedging operating cashflow. Alternatively, it is possible that


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opportunities are high when gold prices are low. Such investment opportunities could arise, for example,

from the sale of assets by other (distressed) firms at bargain prices A firm which is not capital constrained

(possibly because it hedged) could therefore profitably acquire assets when gold prices are low and the

industry is in distress (Shleifer and Vishny, 1992).

Whether this is true in the gold industry is an empirical question. Firms in the gold industry are not

highly leveraged on average. Over the 1985 to 1994 period, the average debt to asset ratio (book value of

debt divided by book value of debt plus market value of equity) was 11 percent. The average level of

interest coverage (earnings before interest and taxes plus interest expense divided by interest expense) was

11. However, both variables are highly correlated with the price of gold. The average debt to asset ratio

falls when gold prices rise ( = -0.74) and the average interest coverage rises ( = 0.90). Thus declines in

gold prices could be highly correlated with financial distress in the industry.

To distinguish between the two hypotheses (no risk exposure versus credit constrained investment

decisions), we need to compare an unconstrained firm with a potentially-constrained firm. This is the

advantage of comparing a firm which hedges with derivatives (American Barrick) to one which does not

(Homestake Mining). According to the previous results, when gold prices fall the operating cashflows of

an unhedged and potentially capital constrained firm will fall. This may cause them to cut investment, even


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policy and in fact may be taking cashflow away in exactly the states where the firm values cashflow most

highly – i.e. when it has positive NPV investments.

2. Empirical Estimates of the Investment Risk Exposure.

Gold firms’ investments involve developing new gold deposits (either through exploration or

through acquisition of deposits from other firms) or by extracting gold from the current deposits. All three

forms of investment may take time to adjust to a new environment (different level of gold prices). A run

up in price in the previous year may have prompted a decision to increase production. However, the higher

production may not occur until the following year. Decisions to alter the firms investment in exploration

activities may take even longer. Thus we look for the effect of both current price changes as well as past

price changes.

a. Gold Production.

There is little evidence that either firm alters its production in response to changes in the price of

gold (Table III). Both firms lower production following an increase in the price of gold. However, given

the absence of significance, we cannot reject the null hypothesis that production changes are uncorrelated

with current changes in the price of gold. The problem is not longer lead times for production decisions

versus sales decisions. Past price changes do not significantly raise the explanatory power of the model for


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changes in gold prices is only one year (see Table III — Panel B). Current year changes in the gold price

have a statistically insignificant effect on Homestake Mining’s exploration expense. However, a 10 percent

rise in gold prices this year is followed by a 4.5 percent rise in exploration expenditure the following year

(t = 1.7). For American Barrick, there is no relationship between changes in gold prices and changes in its

exploration expense (Table III — Panel A). Its exploration expense has varied over the sample period by

more than Homestake Mining’s, but the variation has been uncorrelated with changes in the gold price.

c. Gold Reserves

The results thus far suggest that the investment opportunities of a gold mining firm either are

uncorrelated with gold prices (American Barrick) or vary positively with gold prices (Homestake Mining).

In the latter case, a gold mining firm would fit the definition of a firm which is naturally hedged. When

gold prices rise, the firm’s sales revenue and cashflows rise. Just when the firm is generating cashflow

internally, it has investment opportunities to explore for new gold deposits. There is little evidence,

however, that either firm expands the production of current reserves when gold prices rise.

Gold firms can expand their reserves through exploring for gold (and finding it) or through

purchasing reserves from other firms. Increases in the firm’s reserves will include both sources of new

reserves. If a firm is purchasing gold mines or expanding the capacity of its own mines as gold prices rise


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10 percent increase in reserves.14

Our results suggest that the existence of or lack of a derivatives hedging program does not have a

large effect on the firm’s investment activities. A gold hedging program transfers cash from states when

the price of gold rises to states where the price of gold falls. Theoretically this would allow the hedged firm

to make acquisitions (of presumably underpriced properties) when the price of gold is depressed. We find

the opposite. The hedged firm increases its reserves more when gold prices rise then when they fall. In fact,

both firms demonstrate a propensity to invest more when gold prices rise. This relationship is consistent

with a naturally hedged firm. When cashflow from operations is high, so is the firm’s investment

expenditure.

C. Equity Risk Exposure.

1. Expected risk exposure.

Examining the risk exposure of a firm’s asset values is useful first because this is another possible

objective of a risk management program (DeMarzo and Duffie, 1995, Campbell and Kracaw, 1987). Since

the firm’s market value is the discounted value of its future cashflows, we expect the effects of the firm’s

hedging program to appear in its equity returns. Homestake Mining does not hedge with derivatives and

its operating cashflows move with the price of gold. American Barrick is hedged and its operating


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If the price of gold rises by 1 percent, all future expected prices rise by 1 percent. If cashflow is

a simple function of gold prices, then assuming no future growth in production arising from the current

increase in gold prices each year’s cashflow would also rise by 1 percent – as would the value of the firm’s

assets. If the firm hedges, the value of its future cashflows and assets will rise by less than 1 percent. For

example, assume that cashflows are constant across time and the correct discount rate is 14.6 percent. 15

American Barrick hedges 100 percent of its production over the next three years and 50 percent of its

production over years four through six. Thus we can calculate the expected risk exposure of American

Barrick’s assets relative to Homestake Mining’s assets by assuming that the first three years of cashflow

do not change when gold prices change. Cashflows in year four through six are assumed to change half as

much as the change in the price of gold. Based on these assumptions, a 1 percent rise in the price of gold

results in a 0.55 percent increase in the asset value. This hedging strategy would eliminate 45 percent of

the firm’s risk exposure. The remaining risk exposure (55 percent) is also the fraction of firm value

attributable to the unhedged cashflows. The faster the firm is growing, the larger the fraction of the firm’s

value which is unhedged. A high growth firm’s value would thus vary more with gold prices. If cashflows

are growing at 5 percent, for example, the elasticity rises from 0.55 to 0.68.

2. Equity return regressions.


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r r ( r r )

Excess returns are measured as the monthly stock return minus the risk free rate. We use the return on one

month government T-bills as the risk-free rate. The return on gold is the monthly percentage change in the

price of gold. This is the return an investor would earn from holding gold directly. Just as the coefficient

on the market return measures the firm’s sensitivity to market wide or economy wide fluctuations, the

coefficient on gold price changes measures the firm’s sensitivity to gold price changes. Based on the

calculations in the previous section, a hedged firm such as American Barrick should have a significantly

smaller sensitivity to gold prices ( ) than an unhedged firm such as Homestake Mining. If they were2

perfectly hedged, the sensitivity would be zero.

Since Homestake Mining is not exclusively in the gold industry in the early years of our sample,

we need to include the excess return on the other minerals which Homestake Mining produces (lead, silver,

and uranium). If a firm is in multiple businesses then the return on its assets will be a weighted average of

the return on each of its businesses. We do not have market values by business segment. As an

approximation, we use the fraction of sales which come from each of the business units. Thus each risk

factor (lead, gold, silver, and uranium) is multiplied by the fraction of sales from that business unit in the

previous year.


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associated with a 2.1 percent increase in the equity value of Homestake Mining. Whereas, a 1 percent rise

in the price of gold increases the equity value of American Barrick by more than 1.7 percent. If we restrict

our sample to a common time period (March 1987 to December 1995), the difference in the coefficients

is even smaller. The sensitivity of Homestake Mining to gold prices drops to 1.8 which is not statistically

different from the 1.7 estimated for American Barrick (t=0.9) The other advantage of using the common16

time period is Homestake Mining was almost exclusively in gold during this period. If we re-estimate its

risk exposure assuming that it was entirely in gold (i.e. use equation 1), the estimated risk exposure changes

only slightly to 1.7.

Although American Barrick’s hedging program insulates its operating cashflow from fluctuations

in the price of gold, it does not immediately translate into a significantly lower sensitivity of equity returns

to changes in the value of the underlying commodity. If we take our estimate of Homestake Mining’s gold

price , which is 1.8 (and we ignore the effects of leverage until later), based on the calculations in the

previous section we would expect American Barrick’s gold price to be between 1.00 (0.55 * 1.81) and

1.23. Although American Barrick’s hedging program is very aggressive when compared to those of other

firms in the industry, it appears to eliminate a small fraction of the covariance between changes in the value

of the firm’s equity and changes in the price of gold. Bartov and Bodnar (1994) find the opposite result


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CF Revenue Costs ( P C ) Q (3)

Leverage magnifies risk. Thus a firm such as American Barrick may lower its gold price risk by

using derivatives, yet because of higher operating and/or financial leverage its equity may still contain a

significant exposure to gold price risk. When we calculated the effect of hedging on a firm’s measured risk

exposure, we assumed that a 1 percent increase in the price of gold would have the same effect on both

firms’ cashflows. However, this is true only if they have the same operating leverage. Since a firm’s

operating leverage may be part of its risk management strategy (Petersen, 1994), we need to control for

differences in operating leverage.

Costs which do not rise with the price of gold will raise a firm’s operating leverage. If gold prices

lead to higher revenues, but a firm’s total costs do not rise, then a 1 percent increase in the price of gold

will result in a greater than 1 percent rise in cashflows. The amount by which this percentage is greater than

one will be a function of both the degree to which revenues and costs move with gold prices and the firm’s

profit margin. To make this argument concrete, consider the percentage change in a firm’s cashflow as a

function of a 1 percent change in the price of gold. Define cashflow as revenues minus costs, where C is

the firm’s average cost per ounce and P is the firm’s realized price per ounce.


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The effect of operating leverage thus arises from two sources. First, the firm’s ‘profit margin’ ((P-

C)/G) affects the sensitivity of its cashflows to gold price changes. Notice this is a true profit margin only

when P is equal to G (i.e. the firm is unhedged). The higher a firm’s profit margin, the lower its operating

leverage, implying the sensitivity of its cashflow and asset values to gold price changes is lower. In the

extreme case, where its average costs (C) are zero, the sensitivity of a firm’s cashflow to the risk factor

is the same as the sensitivity of its revenues. This is the intuition that is tested in both Tufano (1997) and

Haushalter (1997). Both of these papers use production or extraction costs as a cross sectional proxy for

operating leverage. The higher the costs, the lower the profit margin, and thus the higher the operating

leverage. In neither set of results, however, is this variable statistically significant.

The other dimension of operating leverage, the sensitivity of costs to the risk factor, is also an

important component of operating leverage. The prior empirical work has implicitly assumed that costs are

fixed with respect to the risk factor. Thus they have set C/ G equal to zero. This is not necessarily correct.

In fact, Homestake Mining’s average costs rise with the price of gold (see Table II). The equity regressions

reported in Table IV need to be re-estimated to account for the effect of operating leverage. In the presence

of operating leverage the risk exposure with respect to gold prices ( ) is defined by equation (4). If weGold

assume that the sensitivity of revenues and costs to gold price changes ( P/ G and C/ G) are constant, then


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versus 31 percent) implies that a model which incorporates the effect of operating leverage more accurately

describes the data. Homestake Mining’s sensitivity to gold prices rises with its operating costs and falls

with the price of gold.

For American Barrick, the model which ignores operating leverage fits the data only slightly better

than the model that incorporates operating leverage. However, the average estimated risk exposure of

American Barrick’s equity value falls when we account for operating leverage. Although the decline is not

large, from 1.7 to 1.5, it is consistent with the intuition that hedging reduces a firm’s risk exposure.

4. The Effects of Financial Leverage.

In addition to reducing the costs of financial distress by reducing its operating leverage or by its

use of derivatives, a firm could lower it financial leverage. Thus a firm’s choice of its risk management

strategy and its leverage should be correlated (Hentschel and Kothari, 1997). A firm that hedges with

derivatives, such as American Barrick, can support a higher degree of leverage. This higher leverage will,

in turn, increase the sensitivity of its equity returns to the firm’s underlying risk factors, such as gold prices.

This may partially explain the higher than expected sensitivity of American Barrick’s equity returns to gold

prices. Even if American Barrick’s assets are less sensitive to gold prices than Homestake Mining's (due

to hedging), its equity could still be as sensitive to gold prices as Homestake Mining’s (due to leverage).


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Assets Equity

Equity

Assets DebtDebt

Assets(5)

If we assume that the risk factor sensitivity of both American Barrick and Homestake Mining’s debt is zero

and use the risk factor sensitivity of equity corrected for operating leverage from Table IV we can estimate

the risk factor sensitivities for each firm’s assets. For Homestake Mining, the sensitivity of its assets to gold

is 1.75. American Barrick’s assets are less sensitive to gold prices, 1.25. This is in the range of exposures

which we can expect from hedging. If American Barrick’s long term expected growth rate is 5 percent,

then the above calculations would imply that their hedging program would eliminate about a third of their

risk exposure. This is what we find (1.25 / 1.75 = 0.71).

These results point out the potentially misleading intuition that can arise from classifying firms as

hedgers and non-hedgers based on their use of derivatives. The measured risk exposure of our two firms’

equity are almost identical despite the fact that their use of derivatives are at opposite ends of the spectrum.

However, through a combination of imperfect hedging with derivatives by American Barrick, greater

leverage use by American Barrick, and operational hedging by Homestake mining the impact of the

hedging program can be obscured in the final data. Once these factors are accounted for, the data is


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through deliveries in the spot market, revenue recognition is less discretionary. However, if its20

management feels that GAAP based accounting income is an important metric assessed by the market and

accounting changes are not transparent to all market participants, then one can expect attempts to smooth

operating income. Through adroit choices of accounting techniques, accounting estimates, and discretionary

accruals the management can dampen fluctuations in its operating income arising from gold price changes.

For example, a decrease in income resulting from lower gold prices can be offset, to some extent, by selling

beginning inventory carried on the books at a lower cost (since Homestake uses the LIFO assumption) or

by increasing the estimated useful life of property, plant and equipment resulting in a lower depreciation

expense. Discretionary accruals, such as those relating to law-suits, can also play a role in altering the

income for the period. Due to the conservative nature of accounting standards, unrealized gains are

typically not recognized, whereas unrealized losses are. In order to counter the effect of changing gold

prices, management can engage in both changes in accounting estimates or decisions to engage in

discretionary transactions. Thus management can time the realization of unrealized gains through actions

such as the sale of marketable securities in a year where gold prices have fallen.

To test the hypothesis that discretionary accounting decisions are made to offset fluctuations in the

underlying business, we collected information on accounting choices by reading the footnotes to the two


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are higher for unhedged Homestake Mining. We examine their choices first.

In thirteen of the nineteen years we examine, Homestake Mining’s accounting changes move in

the opposite direction as gold prices. Accounting changes which lower net income are adopted in years

when the price of gold rises. Gold prices increased dramatically in 1980. This was the year Homestake

Mining recognized an $8.1M expense from the settlement of a lawsuit with Westinghouse. They had been

vehemently fighting the suit for several years. They also began amortizing prior service cost for its pension

over 10 years instead of 14 years. This increased the firm’s pension expense and thus decreased its income.

On the other hand, when the price of gold dropped in 1985, Homestake Mining dipped into LIFO layers,

which resulted in the increase of income by $1.7M. They also adopted SFAS 87 early, while at the same

time deciding to terminate a contract for the sale of uranium. Together these actions increased Homestake’s

net income by $11.4M in a year when profits would have been lower due to a lower sales price for its gold.

Similar examples can be found in the other years (See Table V - Panel B).

To test the statistical significance of the negative relation between change in the price of gold and

the income effect of discretionary accounting choices, we estimate an ordered logit model. The dependent

variable is the sign of the accounting change: income increasing, no change, or income decreasing (1,0,-1).

The classification is reported in Table V. We used the percentage change in the average gold price over


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expenses and further increased the loss. In fact, this year qualifies as what is sometimes called a ‘big bath

year’. Under this rubric, the time of operational difficulties arising from production problems / low gold

prices is deemed by the management to be an appropriate time to accrue and recognize other charges,

resulting in a huge loss for this year to be followed by positive income in the following years. Second, even

though the accounting change/accrual and gold prices move in the opposite direction in most years, the

magnitude of such change/accrual does not completely offset the effect of the gold price movements. This

is to be expected, since large changes in reported income resulting from accounting techniques are likely

to make such accrual management more transparent and hence less credible.

Finally, it is not possible to label discretionary action taken by the management, such as the sale

of marketable securities or writing down of investment, as being exclusively governed by the motive to

smooth the effects of gold prices on income. The sale of marketable securities can be motivated by the

desire to raise cash when gold prices fall instead of or in addition to the desire to smooth income. We do

not find strong evidence to support this alternative explanation. Homestake Mining does not cut its

investment when gold prices fall (as we would expect if it is cash constrained), nor does American Barrick

appear to invest more as gold prices fall (as we would expect if its hedging program eliminated cash

constraints faced by unhedged firms). A more direct test, however, is to categorize the accounting choices


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gold falls. However, the magnitude of the coefficient in the ordered logit is 56 percent smaller and is not

statistically significant (p=0.16). The evidence supports the hypothesis that these accounting changes are

motivated by the desire to smooth income opposed to generate cashflow.

The predominantly negative relation between the gold price change and the accounting

choice/discretionary accrual in Homestake Mining is striking when compared to a similar analysis for

American Barrick (Table V -- Panel A). American Barrick, the hedged firm, does not appear to engage in

any form of accounting choice/discretionary accrual to smooth its income. For most of the years in our

sample period (7 out of 11), American Barrick made no changes in its accounting policy which were

disclosed in the footnotes. In the years where there are changes, they do not tend to increase income as gold

prices fall. If anything, they do the opposite. American Barrick appears more likely to increase income in

years when gold prices rise than lower income. As a hedged firm — and given the results of the previous

section — the American Barrick’s managers have less need to smooth out the effects of changes in gold

prices on the firm’s performance.

The evidence from the manager’s choice of discretionary accruals or accounting estimates/methods

is consistent with the manager’s desire to hedge accounting income. Firms which explicitly hedge, such

as American Barrick, need to make few discretionary adjustments to its accounts. Its accounting income


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We find that the risk exposure of the two firms’ equity to gold prices is almost identical. Given only near

term cashflows can be hedged, it is not surprising that American Barrick’s shareholders bear gold price

risk. However, the amount by which American Barrick’s hedging program reduces this risk is quite low.

This finding highlights a significant hurdle facing empirical tests of risk management theory. The

available tools which firms have for pursuing risk management objectives are multi-dimensional. Firms

can alter the primitive risks they face through a wide array of methods. Risk management can be pursued

through the operations of the firm, through the financial structure of the firm, through the firm’s accounting

choices, or through the use of derivatives. We document evidence of all of these approaches among two

firms that we study.

Homestake Mining has avoided the use of derivatives to limit their exposure to fluctuations in the

price of gold. Instead they have used changes in operational decisions and accounting choices to limit their

risk exposure. Homestake Mining’s revenues move one for one with the price of gold. However, their

average costs also rise and fall with gold prices, thus eliminating a portion of their risk exposure through

operating decisions. During the early part of our sample, they were also in other industries which reduced

their risk exposure to gold price risk.

We also find evidence that accounting choice can be used as another form of risk management.


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Finally our results highlight the diversity of risk management objectives that a firm may pursue.

The theoretical literature on risk management has provided justifications for hedging asset values,

cashflow, or net cashflow (operating cashflow minus desired investment expenditure). Since the different

approaches to risk management (operational structure, financial structure, and derivative use) can target

different pieces of a firm(cashflow, accounting income, or equity values), this provides a rich context for

testing the theory.

The final implication of our findings is that tests of theoretical foundations for risk management

need to focus less on why firms hedge or not, and more on their choice of methods. Previous findings that

the risk reduction from hedging is small (Hentschel and Kothari, 1997, Guay, 1997) suggest that firms may

not just be hedging, they may also be speculating. Alternatively, it suggests that firms which do not use

derivatives are hedging through alternative means. This is exactly what we find. The question which needs

to be asked is why firms choose their particular method of risk management. Careful measurement and

comparison of firm’s risk exposure and its approach to altering that exposure is the first step.


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ln( PQ )P

ln( PGold

) ln( QManager s estimate

) (6)

Appendix I: Estimating Conditional versus Unconditional Risk Exposures.

The estimated risk exposure of American Barrick’s sales revenue differs when it is estimated

directly using sales revenue ( =.225 and t=0.4) or indirectly using the average realized price ( =0.331 and

t=2.2), especially given the first coefficient is not statistically different from zero (Table I -- Panel A). A

similar comparison can be made for Homestake Mining (Table I -- Panel B). Which method is correct

depends on what one considers as conditioning information. Expected sales revenue will depend upon both

the expected price of gold and the expected amount of gold to be sold. Therefore an assumption about the

expected quantity of gold to be sold throughout the year must be made. Sitting at January 1st, managers

consider the risk exposure of their sales revenue (PQ) over the next year. The managers have some

expectation of the quantity of gold they intend to sell (Q ).Manager’s estimate

In the sales revenue regression, we have assumed that the expected change in the unit sales is equal

to the sample average over the period. In this case, the expected change in quantity variable is absorbed

into the constant term, and we have the sales revenue regression reported in the top rows of Table I. This

is a lower bound on the amount of information the managers have. Since they are aware of changes in the


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when measuring a firm’s risk exposure. The more volatile the variability in unit sales, the more variability

there will be in dollar sales. If this is predominantly noise (i.e. the manager’s have good information about

unit sales over the coming year), then this should be filtered out before estimating the firm’s risk exposure.

During the entire sample period, the volatility of unit output was small relative to the volatility of gold

prices. Thus the unconditional (0.89) and conditional (1.00) estimates are similar for Homestake Mining

(see Table I). However, during the later half of our sample (1986-1994) gold prices were less volatile

relative to unit output. In this period, the difference between the unconditional (0.68, t=1.4) and the

conditional estimates (1.01, t=15.6) is larger (regression not reported). Filtering out noise will be most

valuable when the variability of gold prices is small relative to the volatility of unit output (the signal to

noise ratio is small).


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References

Bartov, Eli and Gordon M. Bodnar, 1994, Firm Valuation, Earnings Expectations, and the Exchange-Rate

Exposure Effect, Journal of Finance 44, 1755-1786.

Campbell, Tim S. and William A. Kracaw, 1987, Optimal Managerial Incentive Contracts and the Value

of Corporate Insurance, Journal of Financial and Quantitative Analysis 22, 315-328.

DeMarzo, Peter M., and Darrell Duffie, 1995, Corporate Incentives for Hedging and Hedge Accounting,

Review of Financial Studies 8, 743-771.

Fite, David and Paul Pfleiderer, 1995, Should Firms Use Derivatives to Hedge Risk? in William Beaver and George Parks Risk Management: Problems and Solutions (McGraw Hill, New York, NY).

Francis, Jennifer and Jens Stephan, 1990, Characteristics of Hedging firms: An empirical examination, in

Robert J. Schwartz and Clifford W. Smith, Jr, Eds. Advanced Strategies in Financial Risk Management

(New York Institute of Finance, Englewood Cliffs, NJ)

Froot, Kenneth A., David S. Scharfstein and Jeremy C. Stein, 1993, Risk Management: Coordinating

corporate investment and financing policies, The Journal of Finance 5, 1629-1658.

Geczy, Christopher, Bernadette A. Minton and Catherine Schrand, 1996, Why Firms Use Currency

Derivatives, forthcoming Journal of Finance.

Guay, Wayne R., 1997, The Impact of Derivatives on Firm Risk: An Empirical Examination of New

Derivative Users, University of Rochester working paper.

Haushalter, David G., 1997, The Role of Corporate Hedging: Evidence from Oil and Gas Producers,University of Oregon working paper.

Hentschel, Ludger and S.P. Kothari, 1997, Are Corporations Reducing or Taking Risks with Derivatives?


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Shleifer, Andre and Robert Vishny, 1992, Liquidation Values and Debt Capacity: A Market Equilibrium

Approach, Journal of Finance 47, 1342-1366.

Smith, Clifford and Rene Stulz, 1985, The Determinants of Firms' Hedging Policies, The Journal of

Financial and Quantitative Analysis 28, 391-405.

Tufano, Peter, 1995, American Barrick Resources Corporation: Managing Gold Price Risk in Scott Mason,

Robert Merton, Andre Perold, and Peter Tufano, Eds. Cases in Financial Engineering (Prentice Hall,

Englewood Cliffs, NJ), pp 609-644.

Tufano, Peter, 1996, Who Manages Risk? An Empirical Examination of Risk Management Practices in the

Gold Mining Industry, Journal of Finance 51, 1097-1137.

Tufano, Peter, 1997, The Determinants of Stock Price Exposure: Financial Engineering and the Gold

Mining Industry, Harvard Business School working paper.


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Table I: Sensitivity of Sales Revenue and Components to Gold Prices

Panel A: Hedged Firm – American Barrick (1986-1994)

Dependent Variable Intercept Gold Price Gold Price R Model

Change (%) Change (%)t t-1

2

Sales Revenue 0.365 0.095 0.007 Year end1

(0.054) (0.424)

Sales Revenue 0.359 0.072 0.207 0.041 Year end1

(0.059) (0.453) (0.453)

Sales Revenue 0.361 0.225 0.024 Average1

(0.055) (0.544)

Sales Quantity 0.352 -0.027 0.001 Year end1

(0.054) (0.423)

Sales Quantity 0.354 -0.017 -0.089 0.007 Year end1

(0.055) (0.458) (0.457)

Sales Quantity 0.354 -0.107 0.005 Average1

(0.055) (0.545)

Average Price ($/oz) 0.013 0.122 0.091 Year end

(0.019) (0.146)

Average Price ($/oz) 0.005 0.090 0.297 0.622 Year end

(0.013) (0.102) (0.102)

5

Average Price ($/oz) 0.008 0.331 0.400 Average(0.015) (0.153)

10


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Table I (Continued)

Panel B: Unhedged Firm – Homestake Mining (1976-1994)

Dependent Variable Intercept Gold Price Gold Price R Gold

Change (%) Change (%) Pricet t-1

2

Sales Revenue 0.073 0.368 0.119 Year end

(0.063) (0.242)

Sales Revenue 0.055 0.192 0.687 0.539 Year end

(0.047) (0.187) (0.180)

1

Sales Revenue -0.052 0.886 0.585 Average

(0.043) (0.181)

1

Sales Quantity 0.055 -0.242 0.113 Year end

(0.043) (0.165)

Sales Quantity 0.054 -0.257 0.058 0.119 Year end

(0.044) (0.175) (0.169)

Sales Quantity 0.048 -0.112 0.020 Average

(0.045) (0.188)

Average Price ($/oz) 0.018 0.611 0.432 Year end

(0.044) (0.170)

1

Average Price ($/oz) 0.001 0.449 0.629 0.895 Year end

(0.020) (0.078) (0.075)

1 1

Average Price ($/oz) 0.004 0.998 0.977 Average(0.009) (0.038)

1

Notes:


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Table II: Sensitivity of Operating Costs to Gold Prices


Dependent Intercept Gold Price Gold Price Gold Price R Model

Variable Change (%) Change Changet t-1(%) (%)

t-2

2

Unit Costs -0.034 0.199 0.022 Year end

(0.065) (0.508)

Unit Costs -0.046 0.149 0.466 0.138 Year end

(0.067) (0.518) (0.517)

Unit Costs -0.039 0.527 0.370 0.669 0.351 Year end

(0.064) (0.574) (0.498) (0.523)

Unit Costs -0.038 0.360 0.042 Average

(0.065) (0.649)

Panel B: Unhedged Firm – Homestake Mining (1978-1994)


Variable Change (%) Change Changet t-1(%) (%)

t-2

2

Unit Costs 0.036 0.237 0.281 Year end

(0.028) (0.103)

5

Unit Costs 0.021 0.162 0.296 0.651 Year end

(0.020) (0.075) (0.075)

5 1

Unit Costs 0.015 0.197 0.256 0.129 0.720 Year end

(0.019) (0.072) (0.073) (0.072)

5 1


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Table III: Sensitivity of Investment Decisions to Gold Prices



Variable Change (%) Change (%) Change (%)t t-1 t-2

2

Gold 0.337 -0.244 0.081 Year end

Production (0.040) (0.312)

1

Gold 0.338 -0.241 -0.031 0.082 Year end

Production (0.044) (0.339) (0.338)

1

Gold 0.336 -0.332 -0.008 -0.162 0.113 Year end

Production (0.048) (0.425) (0.369) (0.388)

Exploration 0.035 0.879 0.038 Year end

Expenditure (0.184) (1.559)

Exploration 0.036 0.913 -1.062 0.115 Year end

Expenditure (0.197) (1.599) (1.367)

Exploration 0.045 1.219 -1.180 0.519 0.126 Year endExpenditure (0.214) (2.025) (1.525) (1.823)

Gold 0.302 1.127 0.160 Year end

Reserves (0.125) (0.978)

5

Gold 0.254 0.919 1.917 0.617 Year end

(0.093) (0.717) (0.717)

5

Reserves

5

Gold 0.270 1.743 1.707 1.461 0.851 Year end (0.571) (0.495) (0.521)

1 5Reserves (0.064)

1 5


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Table III (Continued)

Panel B: Unhedged Firm -- Homestake Mining (1976-1994)


Variable Change (%) Change (%) Change (%)t t-1 t-2

2

Gold 0.070 -0.173 0.103 Year end

Production (0.032) (0.124)

5

Gold 0.070 -0.177 0.016 0.104 Year end

Production (0.033) (0.132) (0.127)

5

Gold 0.078 -0.237 0.074 -0.195 0.224 Year end

Production (0.034) (0.137) (0.138) (0.133)

5

Exploration 0.072 0.182 0.025 Year end

Expenditure (0.072) (0.278)

Exploration 0.059 0.065 0.454 0.179 Year end

Expenditure (0.068) (0.271) (0.261)

10

Exploration 0.029 0.127 0.481 0.185 0.266 Year endExpenditure (0.071) (0.283) (0.286) (0.275)

Gold 0.054 -0.196 0.089 Year end

Reserves (0.039) (0.151)

Gold 0.052 -0.215 0.073 0.102 Year end

(0.040) (0.160) (0.154)Reserves

Gold 0.077 -0.285 0.082 -0.218 0.240 Year end

Reserves (0 039) (0 154) (0 155) (0 150)

10 10


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Table IV: Sensitivity of Equity Returns to Gold Price Changes

Panel A: Hedged Firm – American Barrick

Independent Variable Intercept Market Return Gold Return R Estimation2

Dates

% in Gold Prices 0.024 1.076 1.651 0.295 8703-95121

(0.009) (0.239) (0.276)

1 1

% in Gold Prices 0.026 1.080 1.492 0.271 8703-9512

* G / (P - C) (0.009) (0.244) (0.266)

1 1 1

Panel B: Unhedged Firm – Homestake Mining

Independent Variable Intercept Market Return Gold Return R Estimation2

Dates

% in Gold Prices 0.005 0.952 2.078 0.487 7601-9512

(0.005) (0.126) (0.156)

1 1

% in Gold Prices 0.006 0.870 1.811 0.310 8703-9512

(0.009) (0.225) (0.277)

1 1

% in Gold Prices 0.004 0.855 1.821 0.363 8703-9512

* G / (P - C) (0.008) (0.213) (0.246)

1 1

Notes:

The table contains coefficient estimates for the regression of the excess equity return on the excess

value weighted equity market return, the excess gold return and in the case of Homestake Mining the excess

return on lead, uranium, and silver. The excess return on the metal prices was multiplied by the fraction of the


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1986 is the first year for which we were able to secure American Barrick’s annual report and thus we only have its realized prices back to 1984.21

42

Table V: Hedging of Accounting Income through Discretionary Accruals and Accounting Choices

Panel A: Hedged Firm -- American Barrick

Year Change in Gold Price Accountings Effect on Details of Accounting Choice, Discretionary Accruals and Changes in Estimates

Realized COMEX Income Cashflow

Price Average

1984 N/A -14.8% Negative Posit ive • Wrote down petroleum and natural gas inves tment. P rovis ion for losses amounted to21

$10.1M

1985 -7.0 -11.5% Zero Zero • Changed the method of accounting of depreciation from unit of production to straight line

with no material changes in the financial statement.

1986 4.4% 14.6% Zero Zero • No significant changes

1987 13.0% 19.7% Positive Zero • Changed method of depreciation from 3-20 years to 5-25 years for buildings. This

increased its reported income.

1988 6.2% -3.5% Zero Zero • No significant changes

1989 -2.3% -13.1% Zero Zero • No significant changes

1990 0.2% 0.5% Positive Zero • Changed the estimate of useful life on mining equipment from 3-10 to 3-15

• Changed the method of accounting for mineral exploration expense. This increased

income by $1.4M and decreased PPE by 34.9M and retained earnings by $30.9M

1991 0.2% -6.0% Zero Zero • No significant changes

1992 -3.7% -4.6% Zero Zero • No significant changes

1993 -3.1% 6.3% Zero Zero • No significant changes

1994 -1.7% 4.8% Zero Zero • No significant changes


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43

Table V (continued)

Panel B: Unhedged Firm -- Homestake Mining

Year Change in Gold Price Accountings Effect on Details of Accounting Choice, Discretionary Accruals and Changes in Estimates

Realized COMEX Income CashflowPrice Average

1976 -27.1% -25.5% Positive Negative • Dipped into LIFO layers increasing income by 4¢/share

• Included unrealized holding gains on marketable securities in net income

• Decreased the minimum period for recognition of prior service pension costs from 13 to

14 years.

1977 16.8% 18.7% Zero Zero • No significant changes

1978 26.6% 27.6% Negative Positive • Recognized permanent impairment in the value of investments

1979 46.6% 48.9% Negative Negative • Recognized losses on metal trading activities.

1980 69.0% 63.5% Negative Negative • Settled lawsuit in December taking a charge of $8.1M

• Changed assumption for recognition of prior service cost to 10 years from 14 years

1981 -28.7% -28.6% Positive Zero • Changed assumption for recognition of prior service cost from 10 years to 10-30 years

1982 -6.2% -19.3% Zero Zero • No changes

1983 12.0% 9.8% Negative Zero • Changed useful life of equipment to 5-20 years from 8-20 years

1984 -15.8% -14.8% Positive Zero • Used pooling method of accounting for acquisition of Felmont Oil Corp acquired in June

1984. This increased net income and revenues by inclusion of Felmont’s operations prior

to acquisition

1985 -12.7% -11.5% Positive Positive • LIFO liquidations which increase income by $1.74M• Early adopted SFAS 87 which increased income by 3.5M.

• Adopted an early retirement program which decreased income by 3M.

• Ea rly termination of uranium sales contract raised income by $19.2M. Offset $10M of

increase in income by a write down of uranium assets


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44

1986 13.5% 14.6% Negat ive Negative • Changed the method of deprecia tion for a particular mine from the " tons milled" bas is to

"recoverable ounces" basis resulting in a charge of $4.4M

• Incurred shut-down expenses on lead business $5.7M.

1987 20.5% 19.7% Positive Zero • Sale of interests in affiliates included in "total revenues". This increased sales by

$146.3M.• Changed estimates of useful life from 5-8 to 5-10 years

1988 -2.3% -3.5% Positive Zero • Early Adoption of SFAS 96 resulting in a $3.1M increase.

1989 -13.5% -13.1% Positive Posit ive • Income f rom discontinued operations (sale of oil bus iness) amounts to $34.2m aris ing

from sale of oil and gas p roperties.

1990 0.3% 0.5% Negative Positive • Wrote off uranium investment. Lowered income by $9.6M

• Changed pension investment rate of return assumption from 8.0% to 8.5%.

1991 -5.9% -6.0% Negative Zero • Changed estimates of useful life from 5-10 to 3-10.

• Ea rly adopted SFAS 106 relating to accrual of post-retirement health benefits which

increased the loss by $28.8M

• Wrote down exploration properties due to lack of sufficient gold

1992 -7.7% -4.6% Negative Zero • Wrote down mining properties based on low gold prices in the amount of $130M

• Used the pooling method of accounting for acquisition of International Corona which

increased income marginally.

1993 3.1% 6.3% Net Negative • LIFO liquidation resulting in a pre-tax profit of $5.2M (NI 52.5M)

Negat ive • Offered early retirement program and undertook some restructuring which increased

expenses by $7.5M

1994 6.7% 4.8% Positive Positive • Recognized income from sale of stock by subsidiary resulting in additional income of

$11.2M

• Sale of investments resulting in a pre-tax gain of $15.2M.

Notes:

Change in the gold price is the percent change in the price received for the firm’s gold during the year. The COMEX average is the percent

change in the average of month end gold prices on the COMEX. Percent changes are calculated as the difference in the log prices. We obtained the

detai l of accounting choices by reading the annual reports and their footnotes each year. The net effect, on income, of the accounting changes and

discretionary accruals made during the year is also provided.

1997 - risk measurement and hedging

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