Valuation Measures

As discussed above, this essay uses the valuation decile assignments de- veloped in the first essay as the measures of relative overvaluation used in the analyses of the determinants of mispricing. Valuation decile assign- ments are therefore used as the dependent variable in the general model presented in Equation 11. The main valuation measure employed in this essay is the set of full period decile assignments derived from the VERR

measure calculated with intrinsic values estimated using the static CAPM discount rate for each firm. The static CAPM approach is used in order to incorporate a firm specific risk adjustment without invoking the size and book-to-market connections inherent in the Fama-French discount model. Although the decile assignments using the Fama-French approach are very similar to the decile assignments using the CAPM approach, it is possible that mispricing may account for some degree of the observed premiums associated with the size and book-to-market factors. The size and book- to-market factors in the Fama-French approach are therefore more prone to being affected by mispricing itself, whereas using the CAPM methodology to estimate the cost of equity avoids that issue.

In order to produce the full period valuation decile assignments all the static CAPM VERR figures across the 1964–2009 period are grouped to- gether and then separated into valuation deciles. The first valuation decile contains the most relatively undervalued firm observations and the tenth valuation decile contains the most relatively overvalued firm observations. Using the full set of observations over the 1964–2009 period when assigning firms to valuation deciles makes the resulting decile assignments relative measures of valuation for the full time period since each firm observation is compared to the decile boundaries derived from the full sample when the decile assignments are made. Thus, firms at each point in time are assigned

to valuation deciles using decile thresholds derived from all observations over the full 1964–2009 period.

Assigning firms to full period valuation deciles using the CAPM based

VERR measure and the full 1964–2009 time period could cause the decile assignments to be driven by broad market mispricing in some time peri- ods. This could affect the determinants which appear to be statistically significantly related to mispricing. Specifically, analyses of determinants using full period decile assignments may indicate that determinants which capture broad market conditions are driving mispricing, possibly obscur- ing the effect of other determinants driving mispricing over shorter time periods. To examine the robustness of the main results using the full pe- riod decile assignments,VERR decile assignments made annually are also used in a series of analyses. With this approach the static CAPM discount rate is again employed in the calculation of the intrinsic value used in the

VERR formula, but firms are assigned to valuation deciles annually. As

VERR estimations are performed at the end of the month in which each fiscal year ends, all VERR calculations from within a calendar year are grouped together and separated into valuation deciles. Decile one contains the most relatively undervalued equities, and decile ten contains the most relatively overvalued equities. Using annual decile assignments shifts the focus from mispricing which may be driven by broad market factors to- wards mispricing which may be caused by other factors. For example, if investor sentiment affects mispricing, using full period decile assignments as the dependent variable in the analyses would be expected to more fully capture that impact because sentiment is more variable over broad time horizons and market conditions. Using annual decile assignments in the determinants analyses allows for less heterogeneity in investor sentiment values since allVERR measures within a given year will have one of twelve different dates because each company’s annualVERRmeasure is estimated at the end of the month in which the company’s fiscal year ends. Conse- quently, although the main valuation measure employed in this study is the set of full period VERR decile assignments using the static CAPM discount rate approach, annual VERR decile assignments are also used for robustness, and the corresponding results are presented in the Appendix. The sample of static CAPMVERR observations converted into full period and annual decile assignments consists of 134,205 observations.

In the Appendix, two additional valuation decile assignment variables are used in the determinants analyses as the dependent variable. The

eVERR measures developed in the first essay are based upon alternate

specifications for earnings and book values compared to the earnings and book values specifications used in the estimation of the VERR measures. Therefore, two of the sets of valuation decile assignments generated from

the eVERR measures are used to study the determinants of mispricing

in order to more fully examine the robustness of the results obtained to the use of alternate specifications of earnings and book values in the es- timation of intrinsic value. Both eVERR decile assignment variables em- ploy the static CAPM discount rate for each firm when performing the calculations to generate the eVERR figures. The first eVERR measure corresponds to the full period decile assignments using the VERR mea- sure to assign firms to deciles. For this set of eVERR decile assignments all observations over the full 1964–2009 period are grouped together and then assigned to valuation deciles, with the first decile containing the most relatively undervalued equities and the tenth decile containing the most relatively overvalued equities. The second eVERR measure corresponds to the annual decile assignments made using theVERRmeasure to assign firms to deciles. For this dependent variable alleVERR measures within a calendar year are assigned to valuation deciles. The discussion in the pre- ceding paragraph regarding the implications of assigning firm observations toVERR based valuation deciles over the full period or annually apply to the two eVERRbased valuation decile assignments as well. The sample of static CAPM eVERR observations converted into full period and annual decile assignments consists of 122,044 observations.

2.5.2 CEO Compensation Characteristics

The characteristics of managerial compensation are identified in the Lit- erature Review of Factors and in the Hypothesis Development sections as likely being related to overvaluation. In particular, the sensitivity of the executive’s wealth to the volatility of the stock (vega), and the sensitivity of the executive’s wealth to the stock price (delta), are hypothesized to be related to mispricing. Vega and delta data are obtained from Professor Naveen’s website, with the data covering the period 1992–2010 and includ- ing delta and vega for various executives. The vega and delta measures provided by Professor Naveen were calculated using Execucomp data fol- lowing methodologies developed by Core and Guay (2002) and Coles et al. (2006).

The delta and vega obtained from Professor Naveen’s website are matched with data from Execucomp to separate out the data for CEOs specifically. In some cases delta and vega are included for multiple CEOs for a given year. When that occurs, the average of the deltas and vegas is used. Be- cause delta and vega are hypothesized to affect overvaluation by influencing the decisions of managers in areas such as R&D, using the average of the deltas and vegas for multiple CEOs during a year better reflects the in- centives which may have affected managerial decisions during that period. The final set of delta and vega data consists of 29,427 observations, and both delta and vega are rescaled to be in terms of millions of dollars of

change in the executive’s wealth relative to the change in the stock price or the volatility of the stock. The rescaling is performed to facilitate the interpretation of the resulting coefficients in the analyses without affecting the inferences.

2.5.3 Firm Characteristics

As detailed in the Hypothesis Development section, various firm character- istics have been hypothesized to be related to overvaluation. To test these hypotheses, various variables are constructed. Research and development expenditures (COMPUSTAT variable XRD) are scaled by the average to- tal assets during the fiscal year to obtain the measure of R&D used in most of the analyses. The average total assets is computed as the aver- age of the total assets at the end of the fiscal year and the total assets at the end of the prior fiscal year. The average total assets during the year is used to better match the periodic nature of R&D expenditures given that total assets figures taken from balance sheets are point estimates. An average total assets figure therefore better matches the level of assets as- sociated with the R&D expenditures during the fiscal year. Missing values of R&D expenditures are treated as zeros. The same procedure is followed when using the advertising expenditures (COMPUSTAT variable XAD) to compute the advertising measure used in the analyses. For robustness, R&D expenditures are also scaled by sales in some analyses to provide an alternative measure of R&D intensity.

Scaled values of net property, plant, and equipment and intangible as- sets are also calculated. The corresponding COMPUSTAT variables for net property, plant, and equipment and intangible assets arePPENT and

INTAN, respectively. Because the net property, plant, and equipment and

intangible assets figures are obtained for the end of the fiscal year, the total assets figure for the end of the fiscal year is used when scaling the variables. This approach to scaling matches the point estimates of intangi- ble assets and net property, plant, and equipment with the corresponding point estimate of total assets.

Two different measures of cash flow and accruals are utilized. The first set of measures is calculated using the approach documented by Sloan (1996). Following that method, cash flow and accruals are calculated as follows:

ACCSloan = (4ACT−4CHE)−(4LCT−4DLC−4T XP)−DP (12)

CFSloan =OIADP −ACCSloan (13) The abbreviations in the equations above refer to the COMPUSTAT vari- able names, where ACT is total current assets, CHE is cash and cash

equivalents, LCT is total current liabilities, DLC is total debt in current liabilities, TXP is income taxes payable, DP is depreciation and amorti- zation expense, and OIADP is operating income after depreciation. The data required to calculate the cash flow and accruals measures following Sloan (1996) is available sporadically for firms prior to mid-1970, and very consistently thereafter. The second set of measures is calculated using the approach documented by Collins, Gong, and Hribar (2003). Following that method, cash flow and accruals are calculated as follows:

CFCollins =OAN CF −XIDOC (14)

ACCCollins =IBC −CFCollins (15) In the above equations the COMPUSTAT variables are provided. OANCF

is the net cash flow from operating activities and XIDOC is the cash flow from extraordinary items and discontinued operations. IBC is the income before extraordinary items. The data required to calculate the cash flow and accruals measures following Collins et al. (2003) is available sporad- ically for firms beginning in 1987 and continuing through mid-1988, and consistently thereafter. The accruals and cash flow measures calculated following both Sloan (1996) and Collins et al. (2003) are scaled by average total assets before being used in the analyses. The average total assets during the year is used to better match the periodic nature of cash flow and accruals given that total assets figures taken from balance sheets are point estimates. An average total assets figure therefore better matches the level of assets associated with the cash flow and accruals during the fiscal year.