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Finding Winners and Avoiding Losers Among Glamour Stocks

by John Bajkowski

Finding Winners And Avoiding Losers Among Glamour Stocks Splash image

Most academic research suggests that investing in glamour stocks is a losing proposition.

On average, firms with high valuations determined by factors such as the price-earnings ratio or price-to-book-value ratio underperform the market over the long term. While the market does a good job of valuing securities in the long run, in the short term it can overreact and push prices away from their true value.

Stocks with high prices compared to their book values tend to be glamour or growth companies that have attracted significant investor attention. As investors pile into a growth stock because of hype, strong relative price strength or high past or expected growth, its price deviates further from its underlying fundamental value. As with value investing, some growth stocks deserve their high valuations, while many do not. Partha Mohanram, CGA Ontario professor of financial accounting at the University of Toronto’s Rotman School of Management, developed a scoring system to help separate the winners from the losers among stocks trading with high price-to-book-value ratios.

The price-to-book-value ratio is determined by dividing market price per share by book value per share. Book value is generally determined by subtracting total liabilities from total assets and then dividing by the number of shares outstanding. It represents the value of the owners’ equity based upon historical accounting decisions. If accounting truly captured the current value of the firm, then one would expect the current stock price to be near the firm’s accounting book value. Over the history of a firm, many events occur that can distort the book value figure. For example, inflation may leave the replacement cost of capital goods within the firm far above their stated book value. Different accounting policies among industries may also come into play when screening for high price-to-book stocks.

We have extensively covered the work of Joseph Piotroski, associate professor of accounting at Stanford University’s Graduate School of Business. Piotroski established basic financial criteria that help separate the winners from the losers of stocks trading with low price-to-book-value ratios.

Mohanram focuses on stocks at the other end of the valuation spectrum, looking for fundamental factors useful when studying growth companies. Investors tend to naïvely extrapolate the current fundamentals of growth stocks or even ignore the implications of using conservative accounting to project future earnings. Mohanram developed a grading system that looks at profitability and cash flow performance, adjusts for likely mistakes due to naïve growth projections, and considers the impact of conservative accounting policies. He refers to these signals as “growth” fundamental signals since they measure the fundamental strength of these companies in a context appropriate for growth firms. Mohanram feels that stocks with stronger growth fundamentals stand a better chance of expanding earnings and avoiding exchange delisting and are more likely to beat earnings forecasts. Most importantly, Mohanram uses simple measures based solely on financial statement data to separate winners from losers.

High Price to Book Value

Mohanram’s work starts with a universe of high price-to-book-value stocks. Mohanram warns investors that these stocks do not perform well as a group, but it is possible to use fundamental analysis to help avoid the biggest losers and select the strongest candidates.

Stock Investor Pro, AAII’s fundamental screening and stock database program, was used to perform most of the analysis suggested by Mohanram. One of Mohanram’s factors examines advertising spending, a data element not covered in our database. Stock Investor Pro covers a universe of 7,279 NYSE, NASDAQ, Amex and over-the-counter stocks. Mohanram first limited his universe to the top 20% of stocks according to their price-to-book-value ratio. Only 5,662 stocks have current price-to-book-value ratios in Stock Investor Pro. In our program, a company must have a positive book value in order to have a meaningful price-to-book-value ratio. While Mohanram considers firms with negative equity, our screen does not. A top 20% cut-off translates into approximately 1,160 stocks, with a maximum price-to-book-value ratio of 733.33 and minimum ratio of 4.26.

Valuation levels of stocks vary over time, often dramatically from bear market bottoms to bull market tops. During the depths of a bear market, many firms can be found selling for a price-to-book ratio less than 1.00. In the latter stages of a bull market, few companies other than troubled firms sell for less than book value per share. Today the median (mid-point) price-to-book-value ratio is 1.80 for all the stocks in Stock Investor Pro. If you go back to the bear market in early 2009, the median price-to-book-value ratio was 0.82.

We then excluded companies that are not exchange-listed. This filter ensures better liquidity (ability to buy and sell shares in a timely and orderly fashion) and higher reporting standards for financial statements. This left us with a universe of 900 high price-to-book-value stocks.

Rating Stocks With the G-Score

Mohanram developed an eight-point scale that helps to identify attractive growth stocks and avoid bad growth companies. Profitability, naïve extrapolation and accounting conservatism are examined using popular ratios and basic financial statement data to create a “G-Score.” Mohanram found that high price-to-book-value stocks with higher G-Scores outperformed growth stocks will lower G-Scores.

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Profitability

Mohanram awarded up to three points for profitability: one point for return on assets above the industry median, one point for a ratio of cash flow from operations to assets above the industry median and one point if the cash flow from operations exceeds net income. These are simple tests and similar to Piotroski’s profitability scores. One key difference is that Mohanram compares company profitability to industry profitability. He highlights academic research indicating that ratio analysis benefits from industry comparisons. Since the Mohanram G-Score relies on some custom ratios that are not calculated in Stock Investor Pro, we imported the necessary data fields into Microsoft Excel and used the spreadsheet program to create custom ratios, sector medians and the G-Scores.

Mohanram defined return on assets (ROA) as net income before extraordinary items for the fiscal year preceding the analysis divided by total assets at the beginning of the fiscal year. Stock Investor Pro deviates by using net income after extraordinary items in its calculation. Since we are performing the analysis midway through the year, we are using trailing four-quarter figures for all of our calculations.

ROA examines the return generated by the assets of the firm. A high return implies the assets are productive and well-managed. If a company has an ROA greater than the sector median, it was given one point, otherwise it was given a zero.

Mohanram reminds us that earnings may be less meaningful than cash flow for the early-stage growth companies that are likely to be found among the high price-to-book-value stocks. Operating cash flow is reported on the statement of cash flows and is designed to measure a company’s ability to generate cash from day-to-day operations as it provides goods and services to its customers. Operating cash flows consider factors such as cash from the collection of accounts receivable, the cash incurred to produce any goods or services, payments made to suppliers, labor costs, taxes and interest payments. Positive cash flow from operations implies that a firm was able to generate enough cash from continuing operations without the need for additional funds. Negative cash flow from operations indicates that additional cash inflows were required for day-to-day operations of the firm.

Mohanram also measures profitability by dividing the cash flow from operations by total assets. This is like the ROA calculation but it is based upon cash flow instead of net income. A stock is awarded one growth point if the cash flow return on assets exceeds the firm’s sector median, otherwise a zero is recorded.

The final profitability variable examines the relationship between the earnings and cash flow. A growth point is awarded if cash from operations exceeds net income. The measure tries to avoid firms making accounting adjustments to boost earnings in the short run that may weaken long-term profitability.

Naïve Extrapolation

Too often the market simply examines the past growth pattern of a company and expects it to continue into the future. Two companies with the same historical growth might have the same high valuation, but a company with more stable and predictable earnings and sales is more desirable and more likely to continue its growth. Mohanram feels that stability of earnings may help to distinguish between “firms with solid prospects and firms that are overvalued because of hype or glamour.” Mohanram measures earnings variability as the variance of a firm’s return on assets in the past five years. A company is awarded one growth point if its variance in ROA is below the sector median. A company must have at least three years of data to calculate the variance, or it is given a value of zero for this signal.

The second growth signal in this category relates to the stability of year-to-year growth. A firm that has stable growth is less likely to disappoint in terms of future growth. Mohanram examined the stability of sales growth to help overcome the issues of negative earnings, which many high price-to-book-value stocks may have. Sales growth may also be more persistent and predicable than earnings growth because it is less subject to accounting judgments. Here, again, Mohanram compares the company variance of year-over-year sales growth to that of its sector median. Companies with lower variance than their sector median are awarded a growth point. A company must have at least three years of growth data to calculate the variance, or it is given a value of zero for this signal. Note that the annual growth in sales over the last five years is also presented in Table 1 to show the recent growth trends of this group of companies passing the screen.

Accounting Conservatism

The final three growth signals deal with company actions that might depress current earnings and book value, but should result in greater growth and profitability down the line. Mohanram identified spending on research and development (R&D), capital expenditures (capex) and advertising as factors that may point to future sales and earnings expansion. Conservatism in accounting standards forces companies to expense outlays for many research and development and advertising efforts even if they create valuable intangible assets that do not show up in a firm’s book value calculation.

A firm is awarded growth point for R&D intensity if its ratio of R&D to assets is higher than its sector median.

The same is true for capital expenditures. One point is given for capex intensity if the firm’s ratio of capex to assets is higher than its sector median.

The Stock Investor Pro data set does not break out advertising expenditures, so we were unable to calculate a growth point for advertising intensity.

Summing It Up

Mohanram sums up the growth points into a G-Score with a maximum value of eight. Since we did not calculate the advertising intensity growth score, our maximum G-Score is seven.

Overall, Mohanram found that the higher the financial score, the higher the average portfolio return. High price-to-book-value companies with stronger G-Scores outperformed stocks with lower G-Scores.

Table 1 presents the nine high price-to-book-value companies with a G-Score of seven as well as the 49 high price-to-book stocks with G-Score of 6. The stocks are sorted alphabetically within each score range. The bottom of the table lists the sector medians that were calculated and used for sector comparisons. Valuation, profitability, growth and investment varies widely by sector, so it makes sense to make sector or industry comparisons when possible.

  P/B
Ratio
(X)
G-
Score
Return
on
Assets
(%)
Cash
Flow to
Assets
(%)
Ret on
Assets
Variance
(%)
5-Yr
Sales
Grth
(%)
Sales
Grth
Variance
(%)
R&D
to
Assets
(%)
Capex
to
Assets
(%)
 
   
   
Company (Ticker) Sector
G-Score 7
Blackbaud, Inc. (BLKB) 11.19 7 2.3 20.7 11.6 11.7 49.0 10.1 3.3 Technology
Citrix Systems (CTXS) 4.35 7 6.6 25.8 0.9 13.2 34.4 11.5 3.7 Technology
CommVault Systems (CVLT) 10.52 7 10.0 29.5 2.2 20.1 25.0 11.2 5.8 Technology
Genomic Health (GHDX) 7.12 7 1.1 19.2 100.5 29.7 484.8 22.9 6.8 Health Care
Illumina, Inc. (ILMN) 7.25 7 4.3 16.3 2.2 25.6 295.3 10.2 3.5 Technology
PROS Holdings, Inc. (PRO) 9.54 7 3.4 25.3 29.8 13.7 250.4 22.9 7.3 Technology
Red Hat Inc. (RHT) 7.30 7 5.7 26.5 0.6 20.5 16.2 11.1 5.3 Technology
Ultimate Software (ULTI) 27.68 7 3.2 11.7 3.7 17.2 18.2 15.9 6.2 Technology
VMware, Inc. (VMW) 6.09 7 7.4 28.6 3.4 28.3 165.2 10.6 3.3 Technology
G-Score 6
3M Co. (MMM) 4.62 6 13.1 24.3 0.6 4.1 68.5 5.0 4.7 Capital Goods
ABIOMED, Inc. (ABMD) 5.86 6 6.1 19.0 141.5 21.8 12.5 16.5 2.0 Health Care
Actavis Inc. (ACT) 5.07 6 -4.6 8.1 3.6 18.8 129.8 7.7 2.5 Health Care
AEP Industries (AEPI) 4.80 6 5.0 18.4 7.9 11.6 72.8 na 13.3 Basic Mat’ls
Air Methods Corp. (AIRM) 5.17 6 5.6 16.6 2.4 16.4 97.3 na 10.1 Transport’n
Alliance Hld’gs Gp (AHGP) 7.93 6 10.9 48.5 2.6 14.5 70.9 na 18.8 Energy
American Tower Corp. (AMT) 8.31 6 4.6 14.8 0.4 14.6 30.0 na 4.9 Services
Arbitron Inc. (ARB) 7.07 6 19.3 46.8 1.5 5.9 4.6 18.2 9.9 Services
Autodesk, Inc. (ADSK) 4.46 6 5.4 21.6 5.9 1.3 216.5 17.8 2.1 Technology
Birner Dental Mgmt (BDMS) 4.99 6 3.4 26.9 4.3 1.0 13.3 na 17.0 Health Care
Buffalo Wild Wings (BWLD) 4.89 6 10.4 38.9 0.1 25.8 40.7 na 29.7 Services
C.R. Bard, Inc. (BCR) 6.05 6 4.4 22.2 8.2 6.1 10.5 5.7 2.1 Health Care
Cabot Oil & Gas Corp. (COG) 6.94 6 4.5 25.1 2.9 10.5 191.8 0.6 23.6 Energy
CEC Entertainment (CEC) 4.71 6 6.0 27.4 0.8 0.5 3.6 na 10.4 Services
Cedar Fair, L.P. (FUN) 62.35 6 3.4 20.7 5.3 1.6 27.5 na 5.2 Services
Clorox Co., The (CLX) 74.41 6 12.7 25.6 0.4 1.3 5.4 3.0 4.5 Cons Non-Cyc
Compass Minerals Int’l (CMP) 5.00 6 7.5 24.1 17.8 1.9 380.6 na 10.2 Basic Mat’ls
CorVel Corporation (CRVL) 6.71 6 15.8 44.6 2.6 7.3 12.9 na 9.8 Health Care
Ellie Mae Inc. (ELLI) 4.51 6 9.6 29.9 20.9 21.5 1,024.10 19.2 6.7 Technology
Emeritus Corporation (ESC) 5.09 6 -2.8 3.6 1.3 23.8 156.4 na 2.2 Health Care
Financial Engines (FNGN) 10.45 6 7.6 23.9 328.3 24.0 52.2 10.2 4.5 Financial
FMC Corp. (FMC) 6.29 6 10.2 11.7 4.3 7.3 83.8 3.1 5.7 Basic Mat’ls
Fortinet Inc. (FTNT) 6.07 6 6.0 23.3 29.6 28.0 41.0 10.1 2.5 Technology
Grupo Televisa (ADR) (TV) 358.38 6 5.4 18.3 1.3 10.8 6.2 na 8.7 Services
Guidance Software (GUID) 8.04 6 -10.2 15.6 43.1 10.4 236.1 29.4 10.4 Technology
Guidewire Software (GWRE) 12.26 6 5.2 15.3 17.8 33.6 358.9 23.3 3.2 Technology
HealthStream, Inc. (HSTM) 6.94 6 4.6 19.7 47.8 18.8 33.6 6.1 4.9 Services
Interactive Intelligence (ININ) 7.73 6 2.2 12.5 10.3 16.7 61.0 20.4 9.0 Technology
Intuit Inc. (INTU) 5.64 6 17.4 37.1 8.2 6.9 13.1 14.6 4.5 Technology
Kroger Co., The (KR) 4.33 6 6.4 20.2 4.7 6.6 10.3 na 9.3 Services
LinkedIn Corp. (LNKD) 24.41 6 2.8 35.9 10.1 97.3 896.6 24.9 19.2 Technology
NeoGenomics, Inc. (NEO) 6.50 6 -2.5 0.4 93.9 39.1 388.3 9.6 8.2 Health Care
NetSuite Inc. (N) 39.47 6 -11.3 14.2 4.1 23.3 121.0 20.3 5.5 Technology
Onvia, Inc. (ONVI) 4.28 6 5.0 20.4 62.2 1.0 139.2 19.1 10.7 Technology
OpenTable Inc. (OPEN) 9.12 6 12.1 36.1 32.7 31.5 117.7 na 8.9 Technology
Pall Corporation (PLL) 4.78 6 16.6 16.0 12.2 0.6 78.1 2.8 3.3 Capital Goods
Pegasystems Inc. (PEGA) 6.11 6 8.0 31.9 21.1 23.3 46.2 20.7 2.8 Technology
Qihoo 360 Tech (QIHU) 18.73 6 9.8 35.4 2.2 nmf 2,006.6 42.6 13.9 Technology
Qualys Inc. (QLYS) 7.36 6 1.3 23.6 0.0 18.3 24.8 27.7 15.5 Technology
Quidel Corporation (QDEL) 4.31 6 7.4 24.4 90.1 5.7 610.3 11.8 15.7 Health Care
Rackspace Hosting (RAX) 7.92 6 8.1 48.0 3.8 29.3 93.2 7.8 31.8 Technology
Raven Industries (RAVN) 5.09 6 15.8 31.2 3.2 11.7 262.9 5.6 10.2 Basic Mat’ls
RealPage, Inc. (RP) 6.27 6 2.8 20.9 95.5 31.0 25.7 11.2 6.5 Technology
Responsys Inc. (MKTG) 5.16 6 2.8 18.7 2.8 34.1 63.9 9.1 10.6 Technology
rue21, inc. (RUE) 5.28 6 8.6 27.1 1.4 24.9 43.7 na 16 Services
salesforce.com, inc. (CRM) 11.11 6 -3.8 17.5 12.4 32.4 61.7 11.0 5.8 Technology
Sonic Corporation (SONC) 16.99 6 6.0 19.2 3.6 -6.7 91.7 na 5.9 Services
Sourcefire, Inc. (FIRE) 8.52 6 1.6 16.0 21.0 31.9 20.5 14.6 3.1 Technology
Tenet Healthcare (THC) 4.84 6 -0.6 8.3 26.5 2.4 10.8 na 6.0 Health Care
Sector Medians
Basic Materials 1.59 3.1 10.9 22.4 4.3 395.0 1.9 5.3  
Capital Goods 1.95 4.9 10.2 12.6 2.7 251.4 2.7 2.5  
Conglomerates 3.43 4.1 18.0 3.5 -0.3 183.6 na 3.9  
Consumer Cyclical 2.17 5.2 12.5 30.3 1.6 238.6 4.8 3.5  
Consumer Non-Cyclical 2.87 6.1 12.0 8.9 6.3 67.2 1.8 3.7  
Energy 1.66 3.3 15.8 24.7 9.3 983.3 1.1 12.2  
Financial 1.08 1.0 2.4 0.7 -2.1 90.5 2.9 0.1  
Health Care 3.46 -9.2 -5.7 184.7 8.2 690.5 20.2 1.7  
Services 2.22 3.2 10.8 10.3 4.4 92.5 5.1 4.3  
Technology 2.26 2.2 11.5 46.9 5.9 316.1 9.7 2.8  
Transportation 1.54 2.9 11.5 8.1 5.1 221.4 1.9 5.9  
Utilities 1.66 2.8 10.5 0.6 2.7 150.7 0.4 7.4  
Source: AAII’s Stock Investor Pro/Thomson Reuters. Data as of 9/20/2013.

Beyond finding winning growth stocks, Mohanram’s work reveals that growth stocks with low G-Scores should be avoided.

Mohanram’s work consists of creating high price-to-book portfolios and further segmenting them in varying G-Score portfolios. Overall, the higher the G-Score the greater the average portfolio return. Results of individual stocks will vary dramatically. The individual components of the G-Score represent a useful checklist for investors examining growth stocks. However, even with these additional financial tests, it is important to perform a careful analysis of any passing stock.

John Bajkowski is president of AAII.


Discussion

Mark Stern from Arizona posted about 1 year ago:

It would be interesting to seem ten year historical test of this approach with each year including an updated group that fits the 6 and 5 scores, and running each group separately as well as comparing the groups retrospectively with 1 and 2 scoring groups.


Dave from MA posted about 1 year ago:

It would be extremely interesting to have access to the Excel spreadsheet used to calculate the G score.

Thanks,


Toby Brown from VA posted 12 months ago:

Seems like an interesting approach; i'll give it a try . Thanks, Toby.


Cathy Bazeley from OH posted 12 months ago:

Will this approach be included in the AAII stock screens?


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