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21 Table 1. Continued Panel A reports mean coefficient estimates from the crosssectional regression: Ri,t+1 −Rft+1 =Interceptt + qt RDDit + bt BETAit + st log(MKTV)it + ht log(BMRATIO)it + it, where Ri,t+1 denotes the return on stock i for month t+1; Rft+1 is the onemonth Tbill rate; RDDit is the decile rank based on the DD Measure; BETAit is the CAPM beta estimated using five years of data ending the most recent December; MKTVit is the market value of equity; BMRATIOit is the ratio of book value of equity to the market value of equity, where book value is stockholders’ book equity plus deferred taxes minus the book value of preferred stock, and the market value of equity is defined as previously. DD Measure, MKTVit, and BMRATIOit are estimated for the most recent fiscal year ending at least three months prior to month t. Reported coefficients and adjusted R2s are the average values from 420 monthly crosssectional regressions. Twosided FamaMacBeth pvalues are reported in parentheses. Panel B reports descriptive statistics for the AQ factor and the three FamaFrench factors. MktRf is the excess return on the market portfolio. SMB is the return on the size factormimicking portfolio. HML is the return on the booktomarket factormimicking portfolio. The AQ factor is an equallyweighted return on a hedge portfolio that is long(short) the two top(bottom) quintiles of the DD Measure. Panel C reports coefficient estimates for the regression: FRETt = i + i MktRft + si SMBt + hi HMLt + it, where FRETt is the return on the AQ factor for month t and all other variables are as defined above. The regression is based on a series of 420 monthly returns. Twosided pvalues are reported in parentheses. Panel D reports mean coefficient estimates from the stocklevel crosssectional regression: R it −Rfit = Interceptt + b ^ i AQ t AQ + b ^ i MktRf t MktRft + b ^ i SMB t SMB + b ^ i HML t HML + it, where R it is return on stock i for month t; Rfit is the onemonth Tbill rate; and b ^ i AQ, b ^ i MktRf, b ^ i SMB, and b ^ i HML are factor betas estimated using all available returns for stock i (with at least 18 monthly observations) from the timeseries regression Rit −Rfit = i + bi AQ AQt + bi MktRfi MktRft + bi SMB SMBt + bi HML HMLt + it , where all variables are as defined above. Reported coefficients and adjusted R2s are the average values from 420 monthly crosssectional regressions. Twosided FamaMacBeth pvalues adjusted for the Shanken (1992) correction are reported in parentheses. Panel E reports regression coefficients from the portfoliolevel crosssectional regressions based on the fullperiod average excess returns and the fullperiod factor betas: PRETi  Rf =Interceptt + b ^ i AQ AQ + b ^ i MktRf MktRft + b ^ i SMB SMB + b ^ i HML HML + it, where PRETi  Rf is the average excess return on portfolio i calculated using 420 monthly portfolio returns; and b ^ i AQ, b ^ i MktRf, b ^ i SMB, and b ^ i HML are fullperiod factor betas estimated from the regression PRETit  Rft = i + bi AQ AQt + bi MktRfi MktRft + bi SMB SMBt + bi HML HMLt + it , where PRETit is the return on portfolio i for month t and all variables are as defined above. Each regression is based on a series of 420 monthly returns. Twosided FamaMacBeth pvalues adjusted for the Shanken (1992) correction (reported in parentheses) are based on the coefficients obtained by estimating the crosssectional regression monthly. The panel partitions refer to three types of portfolios: (1) “25 B/M and Size Portfolios” are based on quintiles of the booktomarket ratio and size; (2) “100 DD Measure Portfolios” are based on percentiles of the DD Measure; and (3) “64 B/M, Size and DD Measure Portfolios” are based on quartiles of the booktomarket ratio, size, and the DD Measure. The stocks in the portfolios are equally weighted. For each firm and each year t, DD Measure is calculated as the standard deviation of residuals over the [t4, t] period, where residuals are obtained from the following regression estimated crosssectionally for each year and each of the 48 Fama and French (1997) industries: TCAit = t + 0t 1/ATAit + 1t CFOit1 + 2t CFOit + 3t CFOi t+1 + 4t REVit + 5t PPEit + it, where TCAit is total current accruals for year t (estimated using the balance sheet approach: TCAit = CAit  CLit  Cashit + STDEBTit , where CAit is oneyear change in current assets (#4); CLit is oneyear change in current liabilities (#5); Cashit is oneyear change in cash (#1); STDEBTit is oneyear change in debt in current liabilities (#34)); CFOit is cash flow from operations for year t estimated as NIBEit  TAit, where NIBEit is net income before extraordinary items (#18); TAit is total accruals (TAit = TCAit  DEPNit, where DEPNit is depreciation and amortization expense in year t (#14)); REVit is oneyear change in revenues (#12); PPEit is property, plant, and equipment for year t (#7); ATAit is average value of total assets (#6) over years t1, t, and t+1. All variables are scaled by the average value of total assets. At least 20 observations are required for each regression. All numbered items in the description of variables refer to Compustat annual data items. The mean coefficient estimates are based on 420 monthly estimates from the crosssectional regressions. The pvalues are based on the FamaMacBeth tstatistics that
Object Description
Title  Accrual quality and expected returns: the importance of controlling for cash flow shocks 
Author  Ogneva, Maria 
Author email  ogneva@usc.edu 
Degree  Doctor of Philosophy 
Document type  Dissertation 
Degree program  Accounting 
School  Marshall School of Business 
Date defended/completed  20080310 
Date submitted  2008 
Restricted until  Unrestricted 
Date published  20080502 
Advisor (committee chair)  Subramanyam, K.R. 
Advisor (committee member) 
Beatty, Randolph DeFond, Mark Hann, Rebecca Jones, Christopher S. 
Abstract  Francis, LaFond, Olsson, and Schipper (2005) document that accrual quality is inversely related to the cost of equity capital. However, Core, Guay, and Verdi (2007) find no association between accrual quality and future stock returns and conclude that there is no evidence that the stock market prices accrual quality. I hypothesize that Core et al. 's result arises because poor accrual quality firms experience negative cash flow shocks in the future, which results in negative returns that offset the higher expected returns for such firms. Consistent with this prediction, I find a significant negative association between realized returns and accrual quality after controlling for cash flow shocks, either by including proxies for future cash flow shocks in asset pricing regressions or by using an accrual quality measure that is less correlated with future cash flow shocks. This result is robust to properly specified and standard asset pricing tests. Overall, this paper adds to the growing literature suggesting that accrual quality is linked to the cost of capital. 
Keyword  accounting quality; cash flow shocks 
Language  English 
Part of collection  University of Southern California dissertations and theses 
Publisher (of the original version)  University of Southern California 
Place of publication (of the original version)  Los Angeles, California 
Publisher (of the digital version)  University of Southern California. Libraries 
Type  texts 
Legacy record ID  uscthesesm1219 
Contributing entity  University of Southern California 
Rights  Ogneva, Maria 
Repository name  Libraries, University of Southern California 
Repository address  Los Angeles, California 
Repository email  cisadmin@lib.usc.edu 
Filename  etdOgneva22080502 
Archival file  uscthesesreloadpub_Volume14/etdOgneva22080502.pdf 
Description
Title  Page 29 
Contributing entity  University of Southern California 
Repository email  cisadmin@lib.usc.edu 
Full text  21 Table 1. Continued Panel A reports mean coefficient estimates from the crosssectional regression: Ri,t+1 −Rft+1 =Interceptt + qt RDDit + bt BETAit + st log(MKTV)it + ht log(BMRATIO)it + it, where Ri,t+1 denotes the return on stock i for month t+1; Rft+1 is the onemonth Tbill rate; RDDit is the decile rank based on the DD Measure; BETAit is the CAPM beta estimated using five years of data ending the most recent December; MKTVit is the market value of equity; BMRATIOit is the ratio of book value of equity to the market value of equity, where book value is stockholders’ book equity plus deferred taxes minus the book value of preferred stock, and the market value of equity is defined as previously. DD Measure, MKTVit, and BMRATIOit are estimated for the most recent fiscal year ending at least three months prior to month t. Reported coefficients and adjusted R2s are the average values from 420 monthly crosssectional regressions. Twosided FamaMacBeth pvalues are reported in parentheses. Panel B reports descriptive statistics for the AQ factor and the three FamaFrench factors. MktRf is the excess return on the market portfolio. SMB is the return on the size factormimicking portfolio. HML is the return on the booktomarket factormimicking portfolio. The AQ factor is an equallyweighted return on a hedge portfolio that is long(short) the two top(bottom) quintiles of the DD Measure. Panel C reports coefficient estimates for the regression: FRETt = i + i MktRft + si SMBt + hi HMLt + it, where FRETt is the return on the AQ factor for month t and all other variables are as defined above. The regression is based on a series of 420 monthly returns. Twosided pvalues are reported in parentheses. Panel D reports mean coefficient estimates from the stocklevel crosssectional regression: R it −Rfit = Interceptt + b ^ i AQ t AQ + b ^ i MktRf t MktRft + b ^ i SMB t SMB + b ^ i HML t HML + it, where R it is return on stock i for month t; Rfit is the onemonth Tbill rate; and b ^ i AQ, b ^ i MktRf, b ^ i SMB, and b ^ i HML are factor betas estimated using all available returns for stock i (with at least 18 monthly observations) from the timeseries regression Rit −Rfit = i + bi AQ AQt + bi MktRfi MktRft + bi SMB SMBt + bi HML HMLt + it , where all variables are as defined above. Reported coefficients and adjusted R2s are the average values from 420 monthly crosssectional regressions. Twosided FamaMacBeth pvalues adjusted for the Shanken (1992) correction are reported in parentheses. Panel E reports regression coefficients from the portfoliolevel crosssectional regressions based on the fullperiod average excess returns and the fullperiod factor betas: PRETi  Rf =Interceptt + b ^ i AQ AQ + b ^ i MktRf MktRft + b ^ i SMB SMB + b ^ i HML HML + it, where PRETi  Rf is the average excess return on portfolio i calculated using 420 monthly portfolio returns; and b ^ i AQ, b ^ i MktRf, b ^ i SMB, and b ^ i HML are fullperiod factor betas estimated from the regression PRETit  Rft = i + bi AQ AQt + bi MktRfi MktRft + bi SMB SMBt + bi HML HMLt + it , where PRETit is the return on portfolio i for month t and all variables are as defined above. Each regression is based on a series of 420 monthly returns. Twosided FamaMacBeth pvalues adjusted for the Shanken (1992) correction (reported in parentheses) are based on the coefficients obtained by estimating the crosssectional regression monthly. The panel partitions refer to three types of portfolios: (1) “25 B/M and Size Portfolios” are based on quintiles of the booktomarket ratio and size; (2) “100 DD Measure Portfolios” are based on percentiles of the DD Measure; and (3) “64 B/M, Size and DD Measure Portfolios” are based on quartiles of the booktomarket ratio, size, and the DD Measure. The stocks in the portfolios are equally weighted. For each firm and each year t, DD Measure is calculated as the standard deviation of residuals over the [t4, t] period, where residuals are obtained from the following regression estimated crosssectionally for each year and each of the 48 Fama and French (1997) industries: TCAit = t + 0t 1/ATAit + 1t CFOit1 + 2t CFOit + 3t CFOi t+1 + 4t REVit + 5t PPEit + it, where TCAit is total current accruals for year t (estimated using the balance sheet approach: TCAit = CAit  CLit  Cashit + STDEBTit , where CAit is oneyear change in current assets (#4); CLit is oneyear change in current liabilities (#5); Cashit is oneyear change in cash (#1); STDEBTit is oneyear change in debt in current liabilities (#34)); CFOit is cash flow from operations for year t estimated as NIBEit  TAit, where NIBEit is net income before extraordinary items (#18); TAit is total accruals (TAit = TCAit  DEPNit, where DEPNit is depreciation and amortization expense in year t (#14)); REVit is oneyear change in revenues (#12); PPEit is property, plant, and equipment for year t (#7); ATAit is average value of total assets (#6) over years t1, t, and t+1. All variables are scaled by the average value of total assets. At least 20 observations are required for each regression. All numbered items in the description of variables refer to Compustat annual data items. The mean coefficient estimates are based on 420 monthly estimates from the crosssectional regressions. The pvalues are based on the FamaMacBeth tstatistics that 