IDEAS home Printed from https://ideas.repec.org/a/gam/jijfss/v12y2024i1p11-d1325018.html
   My bibliography  Save this article

Predicting Operating Income via a Generalized Operating-Leverage Model

Author

Listed:
  • Sherwood Lane Lambert

    (College of Business, University of West Florida, Pensacola, FL 32514, USA)

  • Kevin Krieger

    (College of Business, University of West Florida, Pensacola, FL 32514, USA)

  • Nathan Mauck

    (Henry W. Bloch School of Management, University of Missouri-Kansas City, Kansas, MO 64108, USA)

Abstract

We propose a generalized, practitioner-oriented operating-leverage model for predicting operating income using net sales, cost of sales, depreciation, and SG&A. Prior research links operating income directly to these items; hence, our model includes all aggregate revenues and expenses that comprise operating income. Prior research finds that the cost of sales is “much less” sticky than depreciation and SG&A; hence, we use the cost of sales as a proxy for the total variable costs and depreciation and SG&A as proxies for the sticky fixed costs. We introduce a new adjustment to the textbook operating-leverage model so that the ratio of sales to the cost of sales remains constant for the reference and forecast periods. Inspired by prior research, we adjust depreciation and SG&A for cost stickiness. We find that using our generalized operating-leverage model improves the forecast accuracy of next-quarter and next-year operating income predictions compared to predictions made using textbook operating leverage, which is a special case of our model.

Suggested Citation

  • Sherwood Lane Lambert & Kevin Krieger & Nathan Mauck, 2024. "Predicting Operating Income via a Generalized Operating-Leverage Model," IJFS, MDPI, vol. 12(1), pages 1-19, January.
  • Handle: RePEc:gam:jijfss:v:12:y:2024:i:1:p:11-:d:1325018
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7072/12/1/11/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7072/12/1/11/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Huseyin Gulen & Yuhang Xing & Lu Zhang, 2011. "Value versus Growth: Time‐Varying Expected Stock Returns," Financial Management, Financial Management Association International, vol. 40(2), pages 381-407, June.
    2. Alfredo Grau & Araceli Reig, 2021. "Operating leverage and profitability of SMEs: agri-food industry in Europe," Small Business Economics, Springer, vol. 57(1), pages 221-242, June.
    3. Jagjeevan Kanoujiya & Pooja Jain & Souvik Banerjee & Rameesha Kalra & Shailesh Rastogi & Venkata Mrudula Bhimavarapu, 2023. "Impact of Leverage on Valuation of Non-Financial Firms in India under Profitability’s Moderating Effect: Evidence in Scenarios Applying Quantile Regression," JRFM, MDPI, vol. 16(8), pages 1-20, August.
    4. Welch, Pr, 1984. "A Generalized Distributed Lag Model For Predicting Quarterly Earnings," Journal of Accounting Research, Wiley Blackwell, vol. 22(2), pages 744-757.
    5. Abarbanell, JS & Bushee, BJ, 1997. "Fundamental analysis, future earnings, and stock prices," Journal of Accounting Research, Wiley Blackwell, vol. 35(1), pages 1-24.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chi Chen & Li Zhao & Wei Cao & Jiang Bian & Chunxiao Xing, 2020. "Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction," Papers 2002.06878, arXiv.org.
    2. Chahine, Salim & Daher, Mai & Saade, Samer, 2021. "Doing good in periods of high uncertainty: Economic policy uncertainty, corporate social responsibility, and analyst forecast error," Journal of Financial Stability, Elsevier, vol. 56(C).
    3. Kalinowski Sławomir & Puziak Marcin, 2018. "Does a Financial Crisis Affect Operating Risk? Evidence from Polish Listed Companies," Economics and Business Review, Sciendo, vol. 4(1), pages 64-85, April.
    4. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    5. Francesco Campanella & Mario Mustilli & Eugenio D¡¯Angelo, 2016. "Efficient Market Hypothesis and Fundamental Analysis: An Empirical Test in the European Securities Market," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 27-42, February.
    6. Kothari, S. P., 2001. "Capital markets research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 105-231, September.
    7. Jaimin Goh & Jaehong Lee & Wonchang Hur & Yunchang Ju, 2019. "Do Analysts Fully Reflect Information in Patents about Future Earnings?," Sustainability, MDPI, vol. 11(10), pages 1-17, May.
    8. Jacob Thomas & Frank Zhang, 2007. "Tax Expense Surprises and Future Returns," Yale School of Management Working Papers amz2531, Yale School of Management, revised 01 Feb 2008.
    9. Ruey S. Tsay & Yi-Mien Lin & Hsiao-Wen Wang, 2009. "Residual income, non-earnings information, and information content," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 487-511.
    10. Gregory D. Kane & Ryan D. Leece & Frederick M. Richardson & Uma Velury, 2015. "The Impact of Recession on the Value-relevance of Accounting Information," Australian Accounting Review, CPA Australia, vol. 25(2), pages 185-191, June.
    11. Anwer S. Ahmed & Irfan Safdar, 2017. "Evidence on the Presence of Representativeness Bias in Investor Interpretation of Consistency in Sales Growth," Management Science, INFORMS, vol. 63(1), pages 97-113, January.
    12. Zhang, H.S. & Shen, X.Y. & Huang, J.P., 2016. "Pattern of trends in stock markets as revealed by the renormalization method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 340-346.
    13. Rajiv D. Banker & Dmitri Byzalov & Shunlan Fang & Byunghoon Jin, 2020. "Operating asymmetries and non-linear spline correction in discretionary accrual models," Review of Quantitative Finance and Accounting, Springer, vol. 54(3), pages 803-850, April.
    14. Poonawala, Sakina H. & Nagar, Neerav, 2019. "Gross profit manipulation through classification shifting," Journal of Business Research, Elsevier, vol. 94(C), pages 81-88.
    15. Gongmeng Chen & Louis T. W. Cheng & Ning Gao, 2005. "Information Content and Timing of Earnings Announcements," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(1‐2), pages 65-95, January.
    16. Lin Gan & Takahashi Yoshifumi & Nomura Hisako & Yabe Mitsuyasu, 2024. "The short‐ and long‐term impacts of overinvestments on the profitability of agri‐food processing firms in China," Agribusiness, John Wiley & Sons, Ltd., vol. 40(1), pages 227-247, January.
    17. Bianchi, Francesco, 2008. "Rare Events, Financial Crises, and the Cross-Section of Asset Returns," MPRA Paper 20831, University Library of Munich, Germany, revised 01 Jan 2010.
    18. Jamshid Ardalankia & Mohammad Osoolian & Emmanuel Haven & G. Reza Jafari, 2019. "Scaling Features of Price-Volume Cross-Correlation," Papers 1903.01744, arXiv.org, revised Aug 2020.
    19. Ng, Chi Cheong Allen & Shen, Jianfu, 2016. "Screen winners from losers using simple fundamental analysis in the Pacific-Basin stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 159-177.
    20. Jun, So Young & Kim, Dong Sung & Jung, Suk Yoon & Jun, Sang Gyung & Kim, Jong Woo, 2022. "Stock investment strategy combining earnings power index and machine learning," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijfss:v:12:y:2024:i:1:p:11-:d:1325018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.