Abstract
An unrealized gain on a cash flow hedge implies that the price of the underlying hedged item (i.e., commodity price, foreign currency exchange rate, or interest rate) moved in a direction that will negatively affect the firm’s profits after the hedge expires. Prior research shows that unrealized gains/losses on cash flow hedges are negatively associated with future earnings and that investors’ expectations, as reflected in stock prices, do not appear to anticipate this association. We provide further evidence on this mispricing by examining whether financial analysts understand the future earnings effects of cash flow hedges. We find three main results: (1) analysts do not correctly incorporate unrealized cash flow hedging gains and losses into their 2- and 3-year-ahead earnings forecasts, (2) analysts correct their errors after the hedges have largely expired and investors correct their mispricing at this time, and (3) analysts and investors can better process cash-flow-hedge information when managers provide forecasts.
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Notes
In addition, Sect. 2.1 provides additional details on the use of and accounting for cash flow hedges. There we state the necessary conditions under which our hypotheses would hold and empirically test that those conditions hold for our sample firms.
Hirshleifer and Teoh (2003, p. 380) note that investors may incorrectly estimate the value of firms “if hedge profits are marked-to-market whereas the long-term business risk the firm is hedging is not marked-to-market.”
Fischer et al. (2009, pp. 538–542) provide a comprehensive illustration of the accounting for cash flow hedges.
We use the most recent information available in electronic form. Our research design requires 3 years of forward-looking analyst forecasts. Thus, although our sample ends in 2008, we are using information through 2011 in our empirical tests.
Financial firms are eliminated for two reasons. First, Bodnar et al. (1998), Makar et al. (2013), and Campbell (2014) do not include financial firms. Second, financial firms operate in a different regulatory environment compared to nonfinancial firms. Thus the relationship between the level of cash flow hedging gains and losses and analysts’ forecast errors may not be the same for financial and nonfinancial firms. However, all of our inferences are unchanged if we include financial firms in our sample.
This classification is stable over time. For 20 % of our sample, we investigate whether this classification changed in 2008 (the last year our tests examine). Out of 99 firms, the classification changes in only one (1.0 %), and this change was the result of a firm entering into an interest rate hedge for debt it acquired during the second year it appeared in our sample.
Appendix 1 of Campbell (2014) shows this mathematically as long as three assumptions are met. First, the price of the underlying item follows a random walk. We have shown this to be the case in Table 2. Second, the firm must hedge its underlying items on a rolling basis. For a random sample of 20 % of our sample, we find that 99 % hedge the same items in their first and last years in our sample. Since the average expiration of hedge contracts is <1 year, finding similar hedging at intervals of up to 8 years suggests that firms hedge their transactions on a rolling basis. Finally, it must be the case that the cross-sectional variation in the hedge ratio within an industry is relatively constant across short periods (i.e., from t − 1 to t). Although this assumption is not empirically testable due to incomplete firm disclosures, prior theoretical research suggests that firms’ hedge ratios depend on firm-specific and relatively time-invariant factors such as size, risk, and the delta and vega of the manager’s stock and option portfolio (Smith and Stulz 1985; Froot et al. 1993; Geczy et al. 1997).
Managers typically provide their year t + 1 earnings forecast when they announce earnings for year t (i.e., for calendar year-end firms, in January of t + 1) (Anilowski et al. 2007).
All mean values of the continuous variables presented in Table 3 are significantly different from zero at the 0.01 level.
All of these correlations are significant at the 0.01 level.
The variance inflation factors across all of our models were 2.3 or less, suggesting that multicollinearity is not a concern in any of our analyses (Kennedy 2003).
We scale by equity market value to be consistent with our dependent variable ΔEARN, which after being converted to a per share basis and then scaled by price per share is scaled by market value (price per share × number of shares outstanding).
As noted in Sect. 2.2, unrealized cash flow hedge gains/losses capture firm-specific information about the effect of underlying price movements on future profitability. Because we are (at least partly) interested in across-firm variation, we do not include firm fixed effects in our models. Nevertheless, in untabulated results, we estimate all of our models throughout the paper with firm fixed effects in place of industry fixed effects, and all of our results continue to hold.
Our sample is comprised of 486 unique firms, and the data is not a balanced panel across all years in the sample. Given the small number of firms and years represented in our sample, it is not clear whether standard errors clustered by firm and year would provide statistically reliable results (Petersen 2009; Gow et al. 2010). Nevertheless, in untabulated results, we estimate all our models with standard errors clustered by firm and year, and all of our results continue to hold.
These coefficients imply that one dollar of unrealized hedging gains translates into reduced earnings of 10.3 and 8.7 cents in years t + 2 and t + 3, respectively. However, these coefficients are based on our multivariate models with a significant number of control variables. If we instead estimate a univariate model (as in Bradshaw et al. 2001), the coefficients on HEDGE for years t + 2 and t + 3 are −2.27 and −1.73, respectively. These coefficients are consistent with findings in Makar et al. (2013) and Campbell (2014) and suggest that firms significantly under-hedge their exposures (i.e., hedge well below 100 % of their future transactions), so that a one dollar gain on a cash flow hedge ultimately translates to lower future profits of more than one dollar.
To do this, we convert the cash flow hedge gain/loss amount reported in Compustat to a per share basis by scaling it by common shares outstanding at time t.
Since we do not know precisely when the current year unrealized cash flow hedge gains and losses affect future earnings, it is difficult to truly isolate an adjusted forecast error. For these tests, we make the assumption that 100 % of the gain/loss in the current year affects earnings in each of the following 3 years. Our focus is on the intuition of whether the adjusted forecast error is larger or smaller than the unadjusted forecast error.
For brevity, we reference the papers that motivate the selection of our control variables and refer readers to those papers for a full description as to how these control variables have been shown to affect analyst forecast errors. We selected these control variables after reviewing the totality of the prior literature on analyst forecasts. One might argue that we should also include the weighted average level of accruals based on recent evidence from Drake and Myers (2011). In untabulated results, we do this, and all of our results throughout the paper are unchanged.
Our inferences are unchanged if we use a fully interacted regression model rather than a partition regression approach.
In untabulated results, we replace the dependent variable of these regressions with management forecast errors (rather than analyst forecast errors). Consistent with management possessing information about the implications of unrealized cash flow hedge gains and losses, we find no association between management forecast errors and HEDGE in any period. However, unlike with analyst forecast errors, data limitations from First Call require that we calculate management forecast errors using a forecasted number from twelve months or less before the actual earnings release date. This restriction undoubtedly improves managers’ forecasting ability for t + 2 and t + 3 because they are making their forecasts at t + 1 and t + 2, respectively. Consequently, these results should be interpreted with caution.
For ease of exposition, we focus our discussion on the case where the firm has a calendar year-end. However, as noted in Table 9, our sample still includes non-calendar-year-end firms. In addition, we focus on analyst corrections of year t + 2 earnings forecasts in this section, but the results are similar if we use t + 3 instead.
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We appreciate helpful comments and suggestions from an anonymous reviewer, Ben Ayers, Linda Bamber, Andy Call, Patricia Dechow, Dan Dhaliwal, Jere Francis, Lisa Hinson, Kelly Huang, Tony Kang, Lian Fen Lee, Sandeep Nabar, Santhosh Ramalingegowda, Bob Resutek, Ben Whipple, and workshop participants at Oklahoma State University and the 2012 American Accounting Association (AAA) Annual Meeting.
Appendices
Appendix 1: Illustration of the implications of cash flow hedge gains/losses for future profitability
This appendix illustrates how cash flow hedge gains/losses provide a signal about future profitability after the hedge has been reclassified into earnings and the firm is fully exposed to the underlying price movements that created the gain or loss. Suppose a firm has revenue of $4 and cost of goods sold (COGS) of $2. Revenue is constant over the next few years, the firm sells only one product, and taxes are ignored. In year t, the firm hedges its inventory costs. After the hedge is in place, the price of inventory goes up by $1, from $2 to $3. Therefore, in year t the firm has a hedge gain of $1 in AOCI. However, because the firm had already purchased its inventory at the “old” price of $2, COGS would be $2 in year t.
In year t + 1, the firm gets the benefit of the hedge. The firm purchases inventory at the “new” price of $3, but has the offsetting hedge gain of $1 being reclassified into the income statement. Thus, COGS would again be $2.
However, after year t + 1 there is no hedge so, COGS is $3 in years t + 2 and t + 3. Therefore, income is $2 in t and t + 1, but $1 in years t + 2 and t + 3. If analysts fail to anticipate this effect, their forecasts would be correct in year t and t + 1, but incorrect in t + 2.
This scenario is illustrated graphically and through journal entries below:
Appendix 2: Timeline of cash flow hedge reporting, analyst forecasts, and net income
This appendix illustrates the timeline of cash flow hedge reporting, our collection of analyst forecasts, and our predictions for the effects of the gains/losses on the firm’s earnings and analyst forecast errors. We collect the cash flow hedge gain/loss at the end of year t (HEDGE), which reflects the effects of price changes in the firm’s underlying hedged item(s) through the end of year t. This variable is not reported publicly until the release of the year t Form 10-K. We then collect the next month’s mean consensus analyst forecast (to ensure that analysts have had an opportunity to revise their estimates based on the new amount of HEDGE) for the following three year ends (i.e., t + 1, t + 2, and t + 3). Finally, we compare this forecast to the actual earnings for year t + 1, t + 2, and t + 3, to examine whether analysts have fully incorporated the information contained in HEDGE at time t into their first forecasts after the release of the year t Form 10-K.
We expect that, while the hedges in place at time t are protecting the firm’s earnings (i.e., year t + 1), there will be no impact on earnings and thus no penalty for analysts if they fail to incorporate it into their forecasts. However, after the hedges in place at time t fully expire (i.e., year t + 2 and t + 3), there will be predictable forecast errors if analysts fail to incorporate the information into their forecasts. Specifically, a cash flow hedge gain at time t will lead to a negative earnings surprise at time t + 2 and t + 3, while a cash flow hedge loss at time t will lead to a positive earnings surprise at time t + 2 and t + 3.
The top half of this timeline provides the case of any year in the sample (i.e., year t). The bottom half of this timeline provides an illustration using the year t = 2003.
Appendix 3: Examples of management discussion from earnings conference call transcripts
This appendix provides examples of management’s discussion of the impact of hedging on future earnings. To compile these examples, we randomly selected five firms from the top and bottom deciles ranked by the variable HEDGE. We then reviewed the Q4 earnings conference call transcripts for these companies from the period 2002 to 2009. Data was available for nine of the ten firms. Of these nine firms, four (five) were identified as (not) issuing management earnings guidance during our sample period.
We expect that the information environment between managers and analysts is clearer for those firms that provide earnings guidance. Therefore we expect that managers that provide company earnings guidance will be more likely to provide more detailed information regarding the effect of hedging on earnings. Below, we provide the discussion for those firms that do provide earnings guidance. For those firms that do not provide earnings guidance (i.e., Sandisk, Stone Energy, Casella Waste Systems, Lear Corporation, and Community Health Systems), four out of the five provide no discussion of the effect of hedging on earnings. The fifth firm (Casella Waste Systems) provided a vague description of its hedging in response to a direct question from an equity research analyst in 1 out of the 8 years examined. During all other years, there was no mention of hedging. In other words, those firms without management forecast guidance provided significantly less discussion of their hedging activities.
Excerpts from earnings conference call transcripts for firms that provide management earnings guidance
4.1 Southwest Airlines, Q4 2006 conference call
Looking forward, our hedging position is as follows. We’re nearly 95 % hedged for the remainder of 2007 at an average crude oil price of approximately $50 per barrel. And 2008, we’re 65 % hedged at approximately $49 per barrel. 2009 is over 50 % hedged at approximately $51 per barrel. 2010 is over 25 % at approximately $63 a barrel. 2011, about 15 % hedged at $64 a barrel, and 2012 is about 15 % hedged at about $63 a barrel. The estimated fair value of our hedge contract with $1 billion at December 31st, 2006. Excluding fuel, we were very pleased with our unit cost performance.
4.2 Delta Airlines, Q4 2002 conference call
For the March 2003 quarter, Delta is 63 % hedged at 70–77 cents per gallon, and for the June quarter, we are 65 % hedged at 75 cents per gallon. For 2003 overall, we have 50 % hedged at 75 cents per gallon. However, the effects of the continued fuel price spikes on the unhedged portion of our fuel purchases could create significant financial pressure in the next several months.
4.3 Energen Corporation, Q4 2004 conference call
With those concepts in mind, and with almost 80 % of our estimated natural gas, oil and NGL production in 2005 already hedged, we have a high level of confidence that our earnings for 2005 can range from $4.25 to $4.45 per diluted share. We are also very encouraged about our prospects for 2006. Today’s prices for natural gas and oil in 2006 are even higher than our internal expectations, with a natural gas strip price for 2006 well above $6 per Mcf and the oil strip price in excess of $44 per barrel. We expect to hedge some of our estimated 2006 production in the coming days and we’re prepared to initiate—as we do that, we’ll be prepared to initiate our 2006 earnings guidance. But clearly, we expect good growth in 2006 from our fundamentally strong business operations.
4.4 Questar Corporation, Q4 2006 conference call
Note that we have now hedged about 73 % of our forecast 2007 natural gas and oil equivalent production. We have taken commodity risk mostly out of the equation. We estimate that a $1 per million BTU change in the average NYMEX price of natural gas will change net income by about $0.11 per diluted share. Similarly, with the correction for oil bases that I just discussed we now estimate that a $10 change in the average comp month NYMEX price of crude oil will move EPS by only $0.05 per share.
Appendix 4: Variable definitions
AUDITOR | Equals 1 if the firm is audited by a Big 4 firm and 0 otherwise (au) |
DEBT/EQUITY | The sum of long-term debt (dltt) and short-term debt (dlc) scaled by the market value of equity (price × csho) at the end of year t |
EARNCHANGE | Change in earnings (ni) from year t to year t + k scaled by stock price (price) at the end of year t |
EARNVOL | The standard deviation of the prior 12 quarters of earnings (niq) divided by the lagged quarterly assets (atq). The prior 12 quarterly earnings ends at the fourth quarter of year t |
FERROR | Realized earnings in year t + k minus first mean consensus analyst forecast of earnings for year t + k following year t’s filing of the 10-K, scaled by price at the end of year t. See Appendix 2 for exact details on the timing of variables used in the paper |
GROSS PROFIT | Gross profit for the year t (gp) |
HEDGE | The amount of unrealized cash flow hedging gains and losses recorded in AOCI (aocidergl) at the end of year t, scaled by market value (price × csho) in year t − 1 |
HORIZON | Number of days from analyst earnings forecast (statpers) to year t + k fiscal period end (fpedats) |
LEVERAGE | Total liabilities (lt) in year t scaled by total assets (at) in year t |
LMVAL | Log of market value (price × csho) at the end of year t |
LOSS | Equals 1 if a firm has a loss in year t + k and 0 otherwise |
MANAGEFOR | Equals 1 if management issues earnings forecasts for year t + 1 within the first 3 months of the year and 0 otherwise. Variable only equals 1 if management’s forecast is issued before the mean consensus analyst forecast is tabulated |
MARKET VALUE | Close price (price) in year t times total shares outstanding (csho) at the end of year t |
MKBK | Market-to-book ratio measured at the end of year t |
NET INCOME | Net income (ni) for the year t |
NUMANALYSTS | The number of analysts used to calculate the mean consensus forecast for the year t + k |
ROA | Net income (ni) scaled by total assets (at) at the end of year t |
SALES | Sales (sale) for the year t |
SURPRISE | Net income (ni) in year t minus net income in year t − 1 scaled by price in year t − 1 |
TOTAL ASSETS | Total assets (at) at the end of year t |
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Campbell, J.L., Downes, J.F. & Schwartz, W.C. Do sophisticated investors use the information provided by the fair value of cash flow hedges?. Rev Account Stud 20, 934–975 (2015). https://doi.org/10.1007/s11142-015-9318-y
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DOI: https://doi.org/10.1007/s11142-015-9318-y