Advertisement

Review of Accounting Studies

, Volume 20, Issue 2, pp 934–975 | Cite as

Do sophisticated investors use the information provided by the fair value of cash flow hedges?

  • John L. Campbell
  • Jimmy F. Downes
  • William C. SchwartzJr.
Article

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.

Keywords

Analyst forecasts Disclosure Cash flow hedges Other comprehensive income 

JEL Classification

M40 M41 M49 

References

  1. Ajinkya, B. B., & Gift, M. J. (1984). Corporate managers earnings forecasts and symmetrical adjustments of market expectations. Journal of Accounting Research, 22, 425–444.CrossRefGoogle Scholar
  2. Anilowski, C., Feng, M., & Skinner, D. (2007). Does earnings guidance affect market returns? The nature and information content of aggregate earnings guidance. Journal of Accounting and Economics, 44, 36–63.CrossRefGoogle Scholar
  3. Baginski, S. P., Hassell, J. M., & Kimbrough, M. D. (2002). The effect of legal environment on voluntary disclosure: evidence from management earnings forecasts issued in US and Canadian markets. The Accounting Review, 77, 25–50.CrossRefGoogle Scholar
  4. Barth, M., & Hutton, A. (2004). Analyst earnings forecast revisions and the pricing of accruals. Review of Accounting Studies, 9, 59–96.CrossRefGoogle Scholar
  5. Behn, B. K., Choi, J. H., & Kang, T. (2008). Audit quality and properties of analyst earnings forecasts. The Accounting Review, 83, 327–349.CrossRefGoogle Scholar
  6. Bernard, V., & Thomas, J. (1989). Post-earnings-announcement drift: Delayed price response or risk premium? Journal of Accounting Research, 27, 1–36.CrossRefGoogle Scholar
  7. Bernard, V., & Thomas, J. (1990). Evidence that stock prices do not fully reflect the implications of current earnings for future earnings. Journal of Accounting and Economics, 13, 305–340.CrossRefGoogle Scholar
  8. Bernard, V., Thomas, J., & Wahlen, J. (1997). Accounting-based stock price anomalies: separating market inefficiencies from risk. Contemporary Accounting Research, 14, 89–136.CrossRefGoogle Scholar
  9. Bhushan, R. (1989). Collection of information about publicly traded firms: Theory and evidence. Journal of Accounting and Economics, 11, 183–207.CrossRefGoogle Scholar
  10. Bloomfield, R. (2002). The incomplete revelation hypothesis and financial reporting. Accounting Horizons, 16, 233–243.CrossRefGoogle Scholar
  11. Bodnar, G., Hayt, G., & Marston, R. (1998). Wharton survey of financial risk management by US non-financial firms. Financial Management, 27, 70–91.CrossRefGoogle Scholar
  12. Bodnar, G., Hayt, G., Marston, R., & Smithson, C. (1995). Wharton survey of derivatives usage by US non-financial firms. Financial Management, 24, 104–114.CrossRefGoogle Scholar
  13. Bradshaw, M., Sloan, R., & Richardson, S. (2001). Do analysts and auditors use information in accruals? Journal of Accounting Research, 39, 45–74.CrossRefGoogle Scholar
  14. Brown, L. (2001). How important is past analyst forecast accuracy? Financial Analyst Journal, 57(6), 44–49.CrossRefGoogle Scholar
  15. Brown, L., Griffin, P., Hagerman, R., & Zmijewski, M. (1987). Security analyst superiority relative to univariate time-series models in forecasting quarterly earnings. Journal of Accounting and Economics, 9, 61–87.CrossRefGoogle Scholar
  16. Brown, L., & Rozeff, M. (1978). The superiority of analyst forecasts as measures of expectations: evidence from earnings. Journal of Finance, 33, 1–16.CrossRefGoogle Scholar
  17. Campbell, J. L. (2014). The fair value of cash flow hedges, future profitability, and stock returns. Contemporary Accounting Research. doi: 10.1111/1911-3846.12069.Google Scholar
  18. Cheng, Q., & Lo, K. (2006). Insider trading and voluntary disclosures. Journal of Accounting Research, 44, 815–848.CrossRefGoogle Scholar
  19. Dechow, P., Hutton, A., & Sloan, R. (2000). The relation between analysts’ forecasts of long-term earnings growth and stock price performance following equity offerings. Contemporary Accounting Research, 17, 1–32.CrossRefGoogle Scholar
  20. Diamond, D., & Verrechia, R. (1991). Disclosure, liquidity, and the cost of capital. Journal of Finance, 46, 1325–1359.CrossRefGoogle Scholar
  21. Drake, M. S., & Myers, L. (2011). Analysts’ accrual-related over-optimism: do analyst characteristics play a role? Review of Accounting Studies, 16, 59–88.CrossRefGoogle Scholar
  22. Fama, E., & French, K. (1995). Size and book-to-market factors in earnings and returns. Journal of Finance, 50, 131–155.CrossRefGoogle Scholar
  23. Fama, E., & French, K. (1997). Industry costs of equity. Journal of Accounting and Economics, 43, 153–193.Google Scholar
  24. FASB. (1999). Statement of financial accounting standards No. 133, accounting for derivative instruments and hedging activities. http://fasb.org/pdf/aop_FAS133.pdf.
  25. FASB. (2009). Current technical plan and project updates. As of September 17, 2009. http://www.fasb.org/jsp/FASB/Page/SectionPage&cid=1218220137074.
  26. FASB. (2011). Accounting standards update 2011-05, comprehensive income (topic 220), presentation of comprehensive income.Google Scholar
  27. Fischer, P., Taylor, W., & Cheng, R. (2009). Advanced Accounting (10th ed.). Mason, OH: South-Western Cengage Learning.Google Scholar
  28. Froot, K., Scharfstein, D., & Stein, J. (1993). Risk management: coordinating corporate investment and financing policies. Journal of Finance, 48, 1629–1658.CrossRefGoogle Scholar
  29. Geczy, C., Minton, B., & Schrand, C. (1997). Why firms use derivatives. Journal of Finance, 52, 1323–1354.CrossRefGoogle Scholar
  30. Gow, I., Ormazabal, G., & Taylor, D. (2010). Correcting for cross-sectional and time-series dependence in accounting research. The Accounting Review, 85, 483–512.CrossRefGoogle Scholar
  31. Hayn, C. (1995). The information content of losses. Journal of Accounting and Economics, 20, 125–153.CrossRefGoogle Scholar
  32. Hirshleifer, D., & Teoh, S. (2003). Limited attention, information disclosure, and financial reporting. Journal of Accounting and Economics, 36, 337–386.CrossRefGoogle Scholar
  33. Hutton, A., Lee, L., & Shu, S. (2012). Do managers always know better? Relative accuracy of management and analyst forecasts. Journal of Accounting Research, 50, 1217–1244.CrossRefGoogle Scholar
  34. Hwang, L., Jan, C., & Basu, S. (1996). Loss firms and analysts’ earnings forecast errors. Journal of Financial Statement Analysis, 1, 18–31.Google Scholar
  35. Jennings, R. (1987). Unsystematic security price movements, management earnings forecasts, and revisions in consensus analyst earnings forecasts. Journal of Accounting Research, 25, 90–110.CrossRefGoogle Scholar
  36. Kennedy, P. (2003). A guide to econometrics (3rd ed.). Cambridge, MA: MIT Press.Google Scholar
  37. Kothari, S. P. (2001). Capital markets research in accounting. Journal of Accounting and Economics, 31, 105–231.CrossRefGoogle Scholar
  38. Kross, W., Ro, B., & Schroeder, D. (1990). Earnings expectations: The analysts’ information advantage. The Accounting Review, 65(2), 461–476. Google Scholar
  39. Lang, M., & Lundholm, R. (1993). Cross-sectional determinants of analyst ratings of corporate disclosures. Journal of Accounting Research, 31, 246–271.CrossRefGoogle Scholar
  40. Lang, M., & Lundholm, R. (1996). Corporate disclosure policy and analyst behavior. The Accounting Review, 71, 467–492.Google Scholar
  41. Makar, S., Wang, L., & Alam, P. (2013). The mixed attribute model in SFAS 133 cash flow hedge accounting: implications for market pricing. Review of Accounting Studies, 18, 66–94.CrossRefGoogle Scholar
  42. Minton, B., & Schrand, C. (1999). The impact of cash flow volatility on discretionary investment and the costs of debt and equity financing. Journal of Financial Economics, 45, 423–460.CrossRefGoogle Scholar
  43. Petersen, M. A. (2009). Estimating standard errors in finance panel data sets: comparing approaches. Review of Financial Studies, 22, 435–480.CrossRefGoogle Scholar
  44. Rees, L., & Shane, P. (2012). Academic research and standard setting: the case of other comprehensive income. Accounting Horizons, 26, 789–815.CrossRefGoogle Scholar
  45. Ruland, W. (1978). The accuracy of forecasts by management and by financial analysts. The Accounting Review, 53, 439–447.Google Scholar
  46. Schrand, C. (1997). The association between stock-price interest rate sensitivity and disclosures about derivative instruments. The Accounting Review, 72, 87–109.Google Scholar
  47. SEC. (2008). Report and recommendations pursuant to Section 133 of the Emergency Economic Stabilization Act of 2008: Study on mark-to-market accounting. http://www.sec.gov/news/studies/2008/marktomarket123008.pdf.
  48. Shane, P., & Brous, P. (2001). Investor and (value line) analyst underreaction to information about future earnings: The corrective role of non-earnings-surprise information. Journal of Accounting Research, 39, 387–404.CrossRefGoogle Scholar
  49. Shleifer, A., & Vishny, R. W. (1989). Management entrenchment: the case of manager-specific investments. Journal of Financial Economics, 25, 123–139.CrossRefGoogle Scholar
  50. Shumway, T. (1997). The deslisting bias in CRSP data. Journal of Finance, 52, 327–340.CrossRefGoogle Scholar
  51. Skinner, D. (1994). Why firms voluntarily disclose bad news. Journal of Accounting Research, 32, 38–60.CrossRefGoogle Scholar
  52. Sloan, R. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings? The Accounting Review, 71, 289–315.Google Scholar
  53. Smith, C. W., & Stulz, R. (1985). The determinants of firms’ hedging policies. Journal of Financial and Quantitative Analysis, 20, 391–405.CrossRefGoogle Scholar
  54. Smithson, C., Smith, C., & Wilford, D. (1995). Managing financial risk: a guide to derivatives products, financial engineering and value maximization. New York: Irwin Professional.Google Scholar
  55. Stulz, R. (1990). Rethinking risk management. Journal of Applied Corporate Finance, 9, 8–24.CrossRefGoogle Scholar
  56. Teoh, S., & Wong, T. (2002). Why new issues and high-accrual firms underperform: the role of analysts’ credulity. Review of Financial Studies, 15, 869–900.CrossRefGoogle Scholar
  57. Waymire, G. (1986). Additional evidence on the accuracy of analyst forecasts before and after voluntary management earnings forecasts. The Accounting Review, 61, 129–142.Google Scholar
  58. White, H. (1980). A heteroskedasticity–consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817–838.CrossRefGoogle Scholar
  59. Wong, M. H. F. (2001). The association between SFAS No. 119 derivatives disclosures and the foreign exchange risk exposure of manufacturing firms. Journal of Accounting Research, 38, 387–417.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • John L. Campbell
    • 1
  • Jimmy F. Downes
    • 2
  • William C. SchwartzJr.
    • 3
  1. 1.J.M. Tull School of Accounting, Terry College of BusinessUniversity of GeorgiaAthensUSA
  2. 2.School of Accountancy, College of Business AdministrationUniversity of Nebraska-LincolnLincolnUSA
  3. 3.Department of Accounting, Spears College of BusinessOklahoma State UniversityStillwaterUSA

Personalised recommendations