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Are the forecast errors of stock prices related to the degree of accounting conservatism?

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  • Chen-Yin Kuo

Abstract

Instead of existing research studying the relation between forecast errors and either of two accounting-conservatism forms (unconditional, conditional) respectively, this paper studies the relation between forecast errors and two forms simultaneously, and finds that the relation varies across industries. For large industries, when a firm adopts higher unconditional conservatism and lower conditional conservatism, forecast errors are smaller. Small industries show that a firm with lower unconditional conservatism and higher conditional conservatism has smaller forecast errors. These findings imply that forecast errors and accounting conservatism appear to be related. This information could be of interest to both investors and firm managers. JEL classification numbers: C32, G30Keywords: Accounting conservatism; Unconditional conservatism; Conditional conservatism; Forecast errors; Stock prices

Suggested Citation

  • Chen-Yin Kuo, 2018. "Are the forecast errors of stock prices related to the degree of accounting conservatism?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 8(6), pages 1-9.
    • Handle: RePEc:spt:apfiba:v:8:y:2018:i:6:f:8_6_9
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    1. Westerlund, Joakim & Narayan, Paresh Kumar & Zheng, Xinwei, 2015. "Testing for stock return predictability in a large Chinese panel," Emerging Markets Review, Elsevier, vol. 24(C), pages 81-100.
    2. Joakim Westerlund & Paresh Narayan, 2015. "Testing for Predictability in Conditionally Heteroskedastic Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 342-375.
    3. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    4. Westerlund, Joakim & Narayan, Paresh Kumar, 2012. "Does the choice of estimator matter when forecasting returns?," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2632-2640.
    5. Narayan, Paresh Kumar & Ahmed, Huson Ali & Sharma, Susan Sunila & K.P., Prabheesh, 2014. "How profitable is the Indian stock market?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 44-61.
    6. 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.
    7. Narayan, Paresh Kumar & Bannigidadmath, Deepa, 2015. "Are Indian stock returns predictable?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 506-531.
    8. Byungcherl Charlie Sohn, 2012. "Analyst forecast, accounting conservatism and the related valuation implications," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 52, pages 311-341, October.
    9. Gupta, Rangan & Modise, Mampho P., 2013. "Macroeconomic Variables and South African Stock Return Predictability," Economic Modelling, Elsevier, vol. 30(C), pages 612-622.
    10. Khan, Mozaffar & Watts, Ross L., 2009. "Estimation and empirical properties of a firm-year measure of accounting conservatism," Journal of Accounting and Economics, Elsevier, vol. 48(2-3), pages 132-150, December.
    11. Deepa & Paresh K Narayan, "undated". "Are Indian Stock Returns Predictable?," Working Papers 2015_07, Deakin University, Department of Economics.
    12. Lin, Fengyi & Wu, Chung-Min & Fang, Tzu-Yi & Wun, Jheng-Ci, 2014. "The relations among accounting conservatism, institutional investors and earnings manipulation," Economic Modelling, Elsevier, vol. 37(C), pages 164-174.
    13. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    14. Narayan, Paresh Kumar & Narayan, Seema & Thuraisamy, Kannan Sivananthan, 2014. "Can institutions and macroeconomic factors predict stock returns in emerging markets?," Emerging Markets Review, Elsevier, vol. 19(C), pages 77-95.
    15. David Ashton & Pengguo Wang, 2013. "Valuation Weights, Linear Dynamics and Accounting Conservatism: An Empirical Analysis," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 40(1-2), pages 1-25, January.
    16. Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
    17. repec:zbw:bofrdp:2013_008 is not listed on IDEAS
    18. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    19. Narayan, Paresh Kumar & Narayan, Seema & Westerlund, Joakim, 2015. "Do order imbalances predict Chinese stock returns? New evidence from intraday data," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 136-151.
    20. Gupta, Rangan & Modise, Mampho P., 2012. "South African stock return predictability in the context data mining: The role of financial variables and international stock returns," Economic Modelling, Elsevier, vol. 29(3), pages 908-916.
    21. Kousenidis, Dimitrios V. & Ladas, Anestis C. & Negakis, Christos I., 2009. "Value relevance of conservative and non-conservative accounting information," The International Journal of Accounting, Elsevier, vol. 44(3), pages 219-238, September.
    22. Joakim Westerlund & Paresh K Narayan & Xinwei Zheng, "undated". "Testing For Stock Return Predictability In A Large Chinese Panel," Working Papers 2015_11, Deakin University, Department of Economics.
    23. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    24. Tswei, Keshin, 2013. "Is transaction price more value relevant compared to accounting information? An investigation of a time-series approach," Pacific-Basin Finance Journal, Elsevier, vol. 21(1), pages 1062-1078.
    25. Kuo, Chen-Yin, 2016. "Does the vector error correction model perform better than others in forecasting stock price? An application of residual income valuation theory," Economic Modelling, Elsevier, vol. 52(PB), pages 772-789.
    26. Narayan, Paresh Kumar & Sharma, Susan Sunila & Thuraisamy, Kannan S., 2015. "Can governance quality predict stock market returns? New global evidence," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 367-380.
    27. Elgers, Pieter & Murray, Dennis, 1992. "The relative and complementary performance of analyst and security-price-based measures of expected earnings," Journal of Accounting and Economics, Elsevier, vol. 15(2-3), pages 303-316, August.
    28. Yan-Leung Cheung & Yin-Wong Cheung & Alan T. K. Wan, 2009. "A high-low model of daily stock price ranges," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(2), pages 103-119.
    29. Basu, Sudipta, 1997. "The conservatism principle and the asymmetric timeliness of earnings," Journal of Accounting and Economics, Elsevier, vol. 24(1), pages 3-37, December.
    30. Granger, Clive W J, 1986. "Developments in the Study of Cointegrated Economic Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 213-228, August.
    31. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
    32. Givoly, Dan & Hayn, Carla, 2000. "The changing time-series properties of earnings, cash flows and accruals: Has financial reporting become more conservative?," Journal of Accounting and Economics, Elsevier, vol. 29(3), pages 287-320, June.
    33. Johansen, Søren & Juselius, Katarina, 1992. "Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 211-244.
    34. García Lara, Juan Manuel & García Osma, Beatriz & Penalva, Fernando, 2016. "Accounting conservatism and firm investment efficiency," Journal of Accounting and Economics, Elsevier, vol. 61(1), pages 221-238.
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    More about this item

    Keywords

    accounting conservatism; unconditional conservatism; conditional conservatism; forecast errors; stock prices;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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