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Modifications on Book-Valued Ratios

Author

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  • Catherine Georgiou

    (Department of Economics, Business Division, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece)

Abstract

Purpose: In this paper we try to explain US stock market variations and cash flow fundamentals by employing three different book-valued based ratios. First, we explore the explanatory capacity of the simple book-market ratio on time-varying expected returns, and procced on altering its construction so as to enhance its performance. We then run the extra mile by constructing two new ratios, the book-dividends and book-earnings ratios based on the long-run equilibrium relationships between book, dividends and earnings. Our analysis includes evidence of predictability on dividend and earnings growth rates on the S&P 500 for the most recent sample period 1926-2018. We also investigate the ratios’ forecastability by sub-sampling. Design/methodology/approach: We commence our analysis with the conventional book-market (bm) ratio and by failing to reject the hypothesis of a unit root, we propose the modified book-market (mbm) ratio, whose construction is based on the long-run equilibrium relationship between book (b) and market (m) values. We proceed on associating book values to dividends and earnings series and fix the book-earnings (be) and the dividend-book (db) ratios. We similarly modify be and db, and examine their forecasting performance on returns, dividend and earnings growth. Findings: In-sample evidence suggests that an investor who employs mbm can improve its forecasts by 37% and 41% in the 7- and 10-year return horizon, while the modified dividend-book (mdb) proves even more beneficial by explaining 53% and 59% in similar return horizons. Our modified book-earnings (mbe) has a very good in-sample fit to the earnings growth data unlike the rest of the predictors. With respect to the out-of-sample performance, mbm manages to surpass the simplistic forecast benchmark only at the 10-year horizon by 15% while mdb attains an impressive of 47% and 71% at the 7- and 10-year return horizon. Research limitations/implications: Further research is required so as to solve the earnings puzzle in terms of forecasting along with the necessity to understand the economical sources behind non-stationarity in valuation ratios. Originality/value: We believe that our paper may prove enlightening to investors focused on portfolio allocation and asset pricing and scholars interested in return forecasting, capital budgeting and risk identification.

Suggested Citation

  • Catherine Georgiou, 2022. "Modifications on Book-Valued Ratios," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 15(3), pages 24-37, December.
    • Handle: RePEc:tei:journl:v:15:y:2022:i:3:p:24-37
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    References listed on IDEAS

    as
    1. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    2. repec:bla:jfinan:v:53:y:1998:i:5:p:1563-1587 is not listed on IDEAS
    3. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    4. Polimenis, Vassilis & Neokosmidis, Ioannis M., 2016. "The modified dividend–price ratio," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 31-38.
    5. Kim, Kiwhan & Schmidt, Peter, 1993. "Unit root tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 59(3), pages 287-300, October.
    6. Chen, Long, 2009. "On the reversal of return and dividend growth predictability: A tale of two periods," Journal of Financial Economics, Elsevier, vol. 92(1), pages 128-151, April.
    7. Eugene F. Fama, 2002. "Testing Trade-Off and Pecking Order Predictions About Dividends and Debt," The Review of Financial Studies, Society for Financial Studies, vol. 15(1), pages 1-33, March.
    8. Kothari, S. P. & Shanken, Jay, 1997. "Book-to-market, dividend yield, and expected market returns: A time-series analysis," Journal of Financial Economics, Elsevier, vol. 44(2), pages 169-203, May.
    9. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    10. John Y. Campbell & Robert J. Shiller, 2001. "Valuation Ratios and the Long-Run Stock Market Outlook: An Update," NBER Working Papers 8221, National Bureau of Economic Research, Inc.
    11. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    12. Davis, James L, 1994. "The Cross-Section of Realized Stock Returns: The Pre-COMPUSTAT Evidence," Journal of Finance, American Finance Association, vol. 49(5), pages 1579-1593, December.
    13. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    14. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    15. Garrett, Ian & Priestley, Richard, 2012. "Dividend Growth, Cash Flow, and Discount Rate News," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(5), pages 1003-1028, October.
    16. Chan, Louis K C & Lakonishok, Josef, 1995. "The Behavior of Stock Prices around Institutional Trades," Journal of Finance, American Finance Association, vol. 50(4), pages 1147-1174, September.
    17. Engsted, Tom & Pedersen, Thomas Q., 2010. "The dividend-price ratio does predict dividend growth: International evidence," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 585-605, September.
    18. Vassilis Polimenis & Ioannis Neokosmidis, 2019. "Non-stationary dividend-price ratios," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 552-567, December.
    19. Lettau, Martin & Ludvigson, Sydney C., 2005. "Expected returns and expected dividend growth," Journal of Financial Economics, Elsevier, vol. 76(3), pages 583-626, June.
    20. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    21. John H. Cochrane, 2008. "The Dog That Did Not Bark: A Defense of Return Predictability," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1533-1575, July.
    22. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    23. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
    24. Kothari, S P & Shanken, Jay & Sloan, Richard G, 1995. "Another Look at the Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 50(1), pages 185-224, March.
    25. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    26. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    27. Nelson, Charles R & Kim, Myung J, 1993. "Predictable Stock Returns: The Role of Small Sample Bias," Journal of Finance, American Finance Association, vol. 48(2), pages 641-661, June.
    28. Froot, Kenneth A & Obstfeld, Maurice, 1991. "Intrinsic Bubbles: The Case of Stock Prices," American Economic Review, American Economic Association, vol. 81(5), pages 1189-1214, December.
    29. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    30. Pontiff, Jeffrey & Schall, Lawrence D., 1998. "Book-to-market ratios as predictors of market returns," Journal of Financial Economics, Elsevier, vol. 49(2), pages 141-160, August.
    31. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
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    More about this item

    Keywords

    book-market ratio; modified book-market ratio; book-valued ratios; non-stationary ratios; modified ratios; return predictability;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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