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Value Investing and Financial Statement Analysis

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  • Noma, Mikiharu
  • 野間, 幹晴

Abstract

This study investigates whether a simple accounting-based fundamental analysis can outperform the market. In this study, I use a fundamental signal (F_SCORE) to discriminate between eventual winners and losers. F_SCORE is based on a combination of traditional fundamentals such as ROA, cash flow from operations, and operating margin. I demonstrate that the mean return can be increased by at least 7.8% through hedging strategy that buys high F_SCORE firms and that shorts low F_SCORE firms. In particular, an investment strategy that buys high book-to-market (BM) firms with high F_SCORE and shorts low BM firms with low F_SCORE earns a 17.6% annual return. In other words the results are robust across a variety of partitions including size, share price, and trading volume. This study reveals that F_SCORE can predict future earnings. Further, empirical results do not support a risk-based explanation for the investment strategy. Overall, the results of the present study suggest that life cycle hypothesis advocated by Lee and Swaminathan[2000] holds true.

Suggested Citation

  • Noma, Mikiharu & 野間, 幹晴, 2010. "Value Investing and Financial Statement Analysis," Hitotsubashi Journal of commerce and management, Hitotsubashi University, vol. 44(1), pages 29-46, October.
    • Handle: RePEc:hit:hitjcm:v:44:y:2010:i:1:p:29-46
    DOI: 10.15057/18701
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    References listed on IDEAS

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    1. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W, 1994. "Contrarian Investment, Extrapolation, and Risk," Journal of Finance, American Finance Association, vol. 49(5), pages 1541-1578, December.
    2. Guay, W, 2000. "Discussion of value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 43-51.
    3. Frankel, Richard & Lee, Charles M. C., 1998. "Accounting valuation, market expectation, and cross-sectional stock returns," Journal of Accounting and Economics, Elsevier, vol. 25(3), pages 283-319, June.
    4. John M. Griffin & Michael L. Lemmon, 2002. "Book‐to‐Market Equity, Distress Risk, and Stock Returns," Journal of Finance, American Finance Association, vol. 57(5), pages 2317-2336, October.
    5. La Porta, Rafael, et al, 1997. "Good News for Value Stocks: Further Evidence on Market Efficiency," Journal of Finance, American Finance Association, vol. 52(2), pages 859-874, June.
    6. Lev, B & Thiagarajan, Sr, 1993. "Fundamental Information Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 31(2), pages 190-215.
    7. Piotroski, JD, 2000. "Value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 1-41.
    8. Ou, Jane A. & Penman, Stephen H., 1989. "Financial statement analysis and the prediction of stock returns," Journal of Accounting and Economics, Elsevier, vol. 11(4), pages 295-329, November.
    9. repec:bla:jfinan:v:59:y:2004:i:2:p:831-868 is not listed on IDEAS
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    Cited by:

    1. I-Cheng Yeh, 2023. "Synergy frontier of multi-factor stock selection model," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 445-480, March.
    2. I-Cheng Yeh & Yi-Cheng Liu, 2020. "Discovering optimal weights in weighted-scoring stock-picking models: a mixture design approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-28, December.
    3. Ritesh Khatwani & Mahima Mishra & V. V. Ravi Kumar & Janki Mistry & Pradip Kumar Mitra, 2024. "Creating quality portfolios using score-based models: a systematic review," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
    4. Martin Wichlinski & Rajendra Rajaram, 2019. "The Use of RONA/WACC as a Proxy for Investment Quality," Journal of Economics and Behavioral Studies, AMH International, vol. 10(6), pages 177-185.

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