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Cash flow duration and market reactions to earnings announcements

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Abstract

This study examines how a stock security’s cash flow duration impacts stock price reactions at earnings announcements. We find that stock price reactions are positively associated with cash flow duration, especially when earnings surprises are negative. Our results imply that long duration creates a leverage effect that magnifies the price reaction around earnings announcements. We further show that the greater stock price reaction for firms with longer cash flow duration could be caused by less accurate analyst forecasts and short-sales constraints. Finally, we find that the effect of cash flow duration generally increases over time, being more notable during financial crisis and less notable when investor sentiment is high.

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Notes

  1. The literature suggests the timing of earnings announcements matters for investor attention and thus stock price reactions. For example, DellaVigna and Pollet (2009) report less immediate response and more drift for earnings announcements made on Friday. Hirshleifer et al. (2009) document an under-reaction to announcements on the days with a number of firms announcing earnings and deHaan et al. (2015) document an under-reaction to announcements that are made post-close versus those that are made pre-open or during regular trading hours. Lyle et al. (2023) find greater abnormal volatility and trading volume in the days following pre-open relative to post-close earnings announcements.

  2. The literature also highlights the importance of disclosure content to earnings announcement reactions. For example, Francis et al (2002) argue that the expansion of concurrent information in earnings announcement press releases explains the over-time increase in the informativeness of earnings announcements. Along the same line, Collins et al. (2009) argue that stronger price reaction to Street earnings (that is, actual earnings reported in I/B/E/S) in comparison to weaker reactions to GAAP earnings can explain the over-time increase in return volatility around earnings announcements. Huang et al (2018) find that earnings press releases that include more quantitative items are associated with stronger price reaction whereas Heitz et al. (2023) show that increased 8-K filings of material information has made the earnings announcement premium disappear in recent years.

  3. We find that low-duration stocks tend to be industrial and manufacturing firms, while high-duration stocks are mainly in the computers, chips, and medical equipment sectors.

  4. Annual earnings forecast has been available since 1978 from I/B/E/S. However, the analyst coverage in the late 1970’s and early 1980’s is generally limited. We use analyst coverage for quarterly earnings throughout the paper.

  5. This is also because Compustat earnings information is largely unavailable for these lowest size-decile firms.

  6. As long as the forecasting horizon is sufficiently long to account for super-normal growth opportunities at the firm and industry levels, the terminal growth rate would be a cross-sectional constant and thus has no material impact on the cross-sectional variation in cash flow duration (Dechow et al. 2004; Weber 2018).

  7. The book value of preferred stock is measured by the redemption value, liquidation value, or par value (in that order).

  8. Based on their sample estimates, Dechow et al. (2004) obtain the AR(1) coefficient of 0.57 for ROE and 0.24 for g whereas Weber (2018) obtain the coefficient of 0.41 for ROE and 0.24 for g.

  9. Specifically, the balance sheet based measure of accruals is computed as ((change in current assets-change in cash holding)-(change in current liabilities-change in debt included in current liabilities-change in income taxes payable)-depreciation and amortization expenses)/average total assets.

  10. Our results do not change if we remove observations with negative cash flow duration from our sample.

  11. When the earnings number in the previous quarter is negative, we use the absolute value of the earnings number as the denominator to compute the growth rate.

  12. We measure short-sale constraints using institutional ownership because institutional ownership data are available in 1980 while stock lending data are not available until 2004.

  13. See “Should we hear from companies more often than four times a year?” by Ellen Simon, July 22, 2005, Associated Press.

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Authors and Affiliations

  1. Department of Finance, Northern Illinois University, 740 Garden Road, DeKalb, IL, 60115, USA

    Wenlian Gao

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  1. Wenlian Gao
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This is a sole-authored paper. The study conception and design, material preparation, data collection and analysis, and writing were done by Wenlian Gao.

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Correspondence to Wenlian Gao.

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Appendix: Correlation Coefficients

Appendix: Correlation Coefficients

 

cfdur

AbsCAR

AbsARET

AbsSUE

Size

Age

RET

Lev

MB

Accrual

IO

Analyst

RDratio

RET_STD

Loss

LTGRFE_3yr

LTGRFE_5yr

IO_R

AbsCAR

0.044

                 

AbsARET

0.045

0.937

                

AbsSUE

−0.153

0.074

0.069

               

Size

0.298

−0.079

−0.056

−0.115

              

Age

−0.084

−0.147

−0.135

−0.021

0.402

             

RET

0.238

0.012

0.009

−0.067

0.068

−0.049

            

Lev

−0.119

−0.074

−0.072

0.084

0.112

0.121

−0.047

           

MB

0.551

0.086

0.089

−0.152

0.234

−0.143

0.324

−0.267

          

Accrual

0.048

0.034

0.036

−0.054

0.019

−0.033

0.022

0.023

0.060

         

IO

0.110

0.078

0.087

−0.020

0.503

0.132

0.026

0.052

0.042

0.072

        

Analyst

0.147

−0.027

−0.008

−0.037

0.631

0.176

−0.034

0.070

0.107

0.048

0.360

       

RDratio

0.307

0.130

0.130

0.034

−0.013

−0.179

0.056

−0.250

0.384

0.045

0.034

0.022

      

RET_STD

0.070

0.321

0.312

0.196

−0.268

−0.302

0.126

−0.106

0.175

0.019

−0.132

−0.110

0.294

     

Loss

0.057

0.087

0.083

0.289

−0.114

−0.118

−0.099

0.012

0.045

−0.025

−0.016

−0.029

0.327

0.260

    

LTGRFE_3yr

0.030

0.037

0.041

0.048

0.069

−0.018

0.036

0.021

0.020

−0.006

0.074

0.098

0.039

0.076

0.030

   

LTGRFE_5yr

0.024

0.022

0.027

0.031

0.088

0.019

0.030

0.028

0.001

−0.008

0.088

0.109

0.033

0.036

0.011

0.694

  

GRFD

0.097

0.042

0.052

0.000

0.207

−0.035

0.025

−0.002

0.120

0.000

0.122

0.268

0.038

0.097

0.000

0.222

0.201

 

IO_R

−0.084

0.017

0.018

0.016

0.000

−0.007

−0.006

0.023

−0.089

−0.007

0.648

0.076

−0.016

−0.047

−0.028

0.038

0.043

0.043

  1. This table presents the correlation coefficients between the variables used in our study. Cfdur is cash flow duration. AbsCAR and AbsARET are the absolute value of abnormal return over the three-day window centered on the earnings announcement date, where the abnormal return is calculated based on DGTW and LM approaches, respectively. AbsSUE is the absolute value of standardized unexpected earnings (SUE). Size is the logarithm of a firm's market capitalization in millions of dollars. Age is the number of years since a firm was listed on CRSP. RET and RET_STD are the stock return and the standard deviation of monthly returns over the previous 12 months. Lev is the debt ratio and MB is the market-to-book ratio. Accrual is the changes in noncash working capital minus depreciation expense, scaled by average total assets for the previous two quarters. IO is the institutional shareholding. Analyst is the number of analysts. RDratio is R&D expenditure over total assets. Loss is a dummy variable that equals 1 if a firm reports negative earnings and 0 otherwise. LTGRFE_3yr and LTGRFE_5yr are 3-year growth rate forecast error and 5-year growth rate forecast error, respectively. GRFD is growth rate forecast dispersion. Sample period is from 1984 to 2018.

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Gao, W. Cash flow duration and market reactions to earnings announcements. Rev Quant Finan Acc (2024). https://doi.org/10.1007/s11156-024-01269-1

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