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Review of Quantitative Finance and Accounting

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25.10.2017 | Original Research

Managing earnings risk under SFAS 133/IAS 39: the case of cash flow hedges

verfasst von: Dennis Frestad

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 1/2018

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Abstract

Whereas empirical studies suggest that firm hedging is influenced by accounting standards such as SFAS 133 and IAS 39, the nature of earnings risk management remains a puzzle. I develop a model that shows how non-financial firms that prefer predictable earnings jointly optimize their hedging strategy and the choice between fair-value and hedge accounting. I also examine the implications of these decisions for earnings predictability under SFAS 133/IAS 39. In this model, which has two accounting periods, earnings uncertainty arises from economic shocks and accounting mismatches. The specific influence of accounting mismatches is isolated with two benchmarks, one for firm hedging (cash flow hedging) and another for an accounting system that fully complies with the matching principle. In this forward-looking analysis, most firms significantly decrease the hedging of long-term earnings when faced with persistent price dynamics. Under non-persistent price dynamics, the levels of long-term earnings hedging are only slightly reduced. Therefore, the influence of accounting mismatches on firm hedging is highly dependent on the economic environment in which a firm operates, which suggests that the potential influence of accounting on firm hedging may be difficult to identify in archival studies. The analysis also offers a forward-looking perspective on the changing properties of earnings since the late 1970s that supplements the existing body of archival accounting studies. For example, under persistent price dynamics, forward-looking short-term earnings volatility may increase tenfold or more for cash flow hedging under fair-value accounting compared with a perfectly matched accounting system.

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According to Zhang (2009), accounting for derivatives generally depended upon the claimed purpose of derivatives positions prior to 1998. Derivatives held for trading purposes were recognized at fair value on the balance sheet and any unrealized changes in fair value on the income statement. If the claimed purpose was to hedge existing assets/liabilities or forecasted transactions, the accounting rule applied to derivatives would mirror the accounting rule applied to the hedged items. Because most non-financial firms claimed that they held derivatives portfolios for hedging purposes, and the related assets/liabilities or forecast transactions were measured at historical cost, their derivatives portfolios were also measured at historical cost, which was often zero or negligible. Consequently, many derivatives did not influence the income statement before settlement (p. 246).

The mixed attribute problem relates to a long-standing issue in accounting referred to as “the principal concern” and “fundamental problem” of accounting in the classic Paton and Littleton monograph (1940)—matching. The matching principle is the accounting practice whereby expenses are recognized in the same accounting period as are related revenues, and the application of a mixed attribute accounting model can be viewed as a violation of this principle.

Although we do know that earnings variability is considered important by many firms (Glaum and Klöcker 2011; Graham et al. 2005), little is known concerning how firms adapt their hedging strategies under fair-value accounting. Reviewing three empirical studies that attempt to infer the economic effects of accounting standards on the extent of hedging (Richie et al. 2006; Singh 2004; Zhang 2009), Glaum and Klöcker (2011, p. 465) argue, “The results of these studies are not fully conclusive […]” partly because “all three articles rely on archival data, and the methods applied do not allow direct observation or measurement of companies’ hedging behavior.” Glaum and Klöcker’s (2011) own research cannot fill this void, because the nature of this influence is not explored by their binary dependent variables, including the following: (1) whether companies apply hedge accounting and (2) whether hedge accounting rules influence their hedging behavior. In Glaum and Klöcker’s (2011) own words, “the answers to the above questions do not specify how companies’ hedging behavior is altered by the hedge accounting rules” (p. 470). Nevertheless, referring to the results of an undocumented survey (their footnote 15), Glaum and Klöcker contend, “We can generally infer that the accounting rules tend to reduce the level of hedging” (p. 471). Although this insight is important, it is not very precise. In general, the empirical accounting literature on firm hedging has been dominated by survey studies and archival accounting studies with weak or no links to the economic environment in which a firm operates.

If a price shock in the first accounting period is expected to have a large (small) effect on the prices in subsequent accounting periods, the price can be characterized as persistent (non-persistent). With non-persistent prices, price shocks are expected to be transitory.

Some firms extend their hedging activities beyond the next two accounting periods assumed in the model presented (see, for example, Egeland et al. 2013). Consequently, the magnitude of excess earnings volatility induced by accounting mismatch could easily become much worse for a firm with a five-period hedging program than for firms with two-period hedging programs. Nevertheless, a two-period hedging program is still sufficient to uncover important features of excess earnings uncertainty and the behavior of firms concerned with earnings predictability.

OF can be viewed as a two-period analogue to the mean–variance objective function that results when maximizing the expected utility of wealth in one period, i.e., when portfolio returns are normally distributed and utility displays constant absolute risk aversion. This assumption holds for the negative exponential utility function (Pennacchi 2008, p. 14) and is used, for instance, by Anderson and Danthine (1981). In the accounting literature, a similar function is used in a two-period setting by Pirchegger (2006b), who exogenously assumes mean variance preferences defined over the market values of periods one and two. Similar to Pirchegger (2006b), I postulate the objective function OF exogenously because, although the hedgeable and unhedgeable risk factors in my model are bivariately normally distributed by assumption, it does not follow that short- and long-term earnings are normally distributed random variables.

The model can easily be extended to account for the possibility that firms might not be indifferent to different splits of a given sum of expected short and long-term earnings. Because this feature is secondary relative to the larger issues modeled, this simplifying assumption is adopted.

Realized hedge ineffectiveness can deviate from prospective hedge ineffectiveness, which suggests that $ \sigma_{{\widetilde{{Earn_{1} }},HA}}^{2} \left( {a_{1}^{DA} ,a_{2}^{DA} ;\Phi } \right) $ and $ \sigma_{{\widetilde{{Earn_{2} }},HA}}^{2} \left( {a_{2}^{DA} ;\Phi } \right) $ of Proposition 5 in most cases should be interpreted as lower bounds on the true earnings variability under hedge accounting. This feature is left unexplored for tractability in this study.

Operating leverage, the ratio of fixed to variable costs, is implicit in this formulation. I will interpret any change in the marginal cost c as being accompanied by an offsetting change in the fixed cost C that maintains the expected prehedge profit unchanged. For the case of µ _Q = 1, the offsetting change in C will be the negative of the change in c, in which case low (high) marginal cost represents high (low) operating leverage.

The link between the AR(1) coefficient, price persistence, and mean reversion illustrated in Table 4 can be shown as follows. Bessembinder et al. (1995, p. 364) define mean reversion “as a percentage change in the date t expectation of the date t + m spot price that is less than the percentage change in the date t spot price” and argue that “an elasticity less than unity implies mean reversion since a component of the spot price shock is temporary, and is expected to be reversed by date t + m.” Consequently, for $ 0 \le Corr\left[ {\tilde{S}_{t + 1} ,E_{t + 1} \left[ {\tilde{S}_{t + 1 + m} } \right]} \right] \le 1 $ and because the partial derivative of $ E_{t + 1} \left[ {\tilde{S}_{t + 1 + m} } \right] $ w.r.t. $ \tilde{S}_{t + 1} $ equals the regression coefficient $ Cov\left[ {\tilde{S}_{t + 1} ,E_{t + 1} \left[ {\tilde{S}_{t + 1 + m} } \right]} \right]/\sigma_{{\tilde{S}_{t + 1} }}^{2} $, mean reversion (one minus elasticity) can be defined as $ {\text{Mean reversion = }}1 - Corr\left[ {\tilde{S}_{t + 1} ,E_{{_{t + 1} }} \left[ {\tilde{S}_{t + 1 + m} } \right]} \right]\frac{{\sigma_{{E_{t + 1} \left[ {\tilde{S}_{t + 1 + m} } \right]}} }}{{\sigma_{{\tilde{S}_{t + 1} }}^{{}} }}\frac{{E_{t} \left[ {\tilde{S}_{t + 1} } \right]\,\,\,\,\,}}{{E_{t} \left[ {\tilde{S}_{t + 1 + m} } \right]}} $. Under the spot and forward price dynamics of Appendix 4 and the restriction $ 0 \le \upvarphi \le 1 $, mean reversion (MR) is therefore given as $ MR = 1 - \upvarphi \frac{{T_{1} + \upvarphi S_{0}^{*} }}{{T_{2} + \upvarphi^{2} S_{0}^{*} }} $ or $ MR = 1 - \upvarphi $, setting $ T_{1} = T_{2} = 1 $ and $ S_{0}^{*} = 0 $ for convenience. Clearly, mean reversion and persistence are two sides of a coin; i.e., a high degree of price persistence implies a low degree of mean reversion and vice versa.

Of course, bias in the forward prices would introduce a real tradeoff between expected earnings and earnings predictability, but this effect is not analyzed in Sect. 3.

EARNVOL1 is the standard deviation of income deflated by total assets, whereas EARNVOL2 is the coefficient of variation of income; see Zhang (2009) for more details (p. 252).

The profit functions of periods one and two under hedge accounting, defined by Eqs. (16) and (17), converge to the profit functions under deferral accounting and cash flow hedging defined by Eq. (3) as $ \sigma_{{\tilde{Q}}} $ approaches zero and hedge effectiveness (HEM) approaches unity under pure hedging strategies. However, the interesting question is how this ratio varies over a wider range of unhedgeable risk.

Three things occur as nonhedgeable risk is gradually introduced in Fig. 5. First, the interaction terms cause the sum of expected earnings to deviate from 0.4 for nonzero price-quantity correlations. This feature is most easily observed in the lower left graph of Fig. 5. Second, hedge effectiveness decreases, causing the gap between OF _DA and OF _DA to increase. This feature is evident in all four graphs of Fig. 5. Third, as the level of unhedgeable risk further increases, some firms hit the lower bar for hedge effectiveness and cannot employ cash flow hedge accounting. The lower the price-quantity correlation and the lower the hedge effectiveness threshold, the smaller this level of unhedgeable risk is.

To some degree, the insights gained could even be important for macro-level (regulatory) analyses that face the risks inherent in employing simplifying assumptions about firms and firm behavior that could, in theory, focus insufficiently on hedging features considered important by firms.

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Titel: Managing earnings risk under SFAS 133/IAS 39: the case of cash flow hedges
verfasst von: Dennis Frestad
Publikationsdatum: 25.10.2017
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 1/2018
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-017-0667-4

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