Partha Mohanram - Applying Fundamental Analysis for Growth Stocks - BOS - 10.9.07

8/12/2019 Partha Mohanram - Applying Fundamental Analysis for Growth Stocks - BOS - 10.9.07

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Applying Fundamental Analysis for Growth Stocks

October 9, 2007

Boston

Partha MohanramPhillip H. Geier Jr. Associate Professor of Business

Columbia Business School


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Council Member Biography

Partha Mohanram is the Phillip H. Geier Jr. Associate Professor atColumbia Business School. His research focuses on the valuationof stocks, corporate disclosure and earnings management. Hispapers have studied the valuation of Internet stocks, thecalculation of cost of capital, the use of fundamental analysis forvaluing growth stocks, the analysis of earnings management

related to executive compensation, and the impact of Reg FD onsell side analysts. He has published in top accounting journalsand is on the editorial board of The Accounting Review. Hisresearch has been featured in the New York Times and he hasappeared on CNBC. Prof Mohanram teaches Financial StatementAnalysis and Valuation with an emphasis on exposing students topotential manipulations of financial statements. Prof Mohanramwas a faculty member at the Stern School (NYU) from 1998-2003.He holds a B.Tech in Computer Science from IIT-Madras, an MBAfrom IIM-Ahmedabad and a PhD in Business Economic fromHarvard.


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Topics

How fundamental analysis applies to growth stocks

Applying the GSCORE to growth stock portfolios

Historical portfolio results of the growth stock model

Unsuccessful approaches of fundamental analysis to growth

stock portfolios


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Fundamental Analysis for Growth

Stocks

By

Partha Mohanram

Phillip H. Geier Jr. Associate Professor of Business

Columbia Business School


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About Me

Professor at Columbia since 2003 On NYU Stern Faculty since 1998

Ph.D. in Business Economics From Harvard

Extensive Research Work on Valuation, with emphasis on early stage growth forms

Implied Cost of Capital

Earnings Management and Compensation

Published in Leading Accounting Journals

Editorial Board of The Accounting Review

Teach Financial Statement Analysis to 2ndyear MBAs,Executive MBAs and Executives


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GSCORE Paper

Todays presentation based on the paper

Separating Winners from Losers Among Low Book-to-

Market Stocks using Financial Statement Analysis

Presented at NYU, Harvard, Berkeley and the Review of

Accounting Studies Conference

Published in the Review of Accounting Studies (2005)


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Growth Stocks

Growth Firms identified by their Market-to-Book (or Book-to-Market) ratio is. Firms in the top 20% of MB, or equivalently bottom 20% of BM

considered growth stock.

Empirical Fact Growth Stocks perform poorly, underperforming by almost 10%

historically

Unclear if this is because of risk or mispricing

However, we do know that some growth stocks end up as the Googles

and Microsofts of the world and others as the Dr. Koops.

Growth stocks by definition have lofty valuations Can one apply fundamental analysis to systemically predict which ones

deserve this and which dont?


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Fundamental Analysis in Growth

Firms

Why it may not work?

Markets may use non-financial metrics

These firms are not ignored

Early stage firmstraditional ratios may not work

Why it may work?

In the long run, fundamentals will matter

Firms may be hyped systematically

While traditional ratios may not work, some otherfinancial statement info may be useful


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Modified Fundamental Analysis

Focus on cross-sectional vs. time series Comparison of firm with other low BM firms in same industry (2 digit SIC

code)

Eight Yes/No Questions in three categories. Can be viewed as a serialstock screening method

Three kinds of signals Traditional profitability signals (ROA, CF ROA)

No breakdowns into margins, turnovers etc

Signals related to nave extrapolationROA variability, growth variability Firms less likely to have chance high realization

Separating out the low B firms from the high M firms Firms investing in the future (R&D, Capex, Advertising)


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Basic Profitability Signals (3)

1. Is Firm more profitable than peers?

Profitability defined as Net Income/Total Assets

2. Is Firm generating more cash flows than peers? Measured as Cash from Operations/Total Assets

3. Does the firm have lower accruals than peers?

Measured as difference between above two metrics An attempt to control for Accrual Anomaly of Sloan

(1996)


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Earnings and Growth Stability Signals

(2)

Investors naively extrapolate current earnings and growthperformance into stock price

Some firms may have lucky current realizations, not likely to persist

Focus on firms with track record of stable earnings and growth

Measure earnings and growth variability as variance of past earnings(NI/Assets) and sales growth respectively

1. Does firm have less variable earnings than peers?

2. Does firm have less variable (sales) growth than peers?


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Investing in Future Signals (3)

High valuations are all about the future

Which firms are investing in the future?

R&D, Capex, Advertising

Accounting treatment for these also depress current earningsand book values

Low B vs. High M Stocks

1. Is firms R&D/Assets greater than peers?

2. Is firms Advertising/Assets greater than peers?

3. Is firms Capex/Assets greater than peers?


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The GSCORE Metric

Combine 8 binary signals into single metric,GSCORE

Made it simple; no weighted measure or continuousmeasure

Can take value from 0 to 8

If this works Low GSCORE firms should perform poorly

High GSCORE firms should perform well


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Individual Examples

High GSCORE SAMPLE

TICKER NAMEGSCORE

(end of 2005)Return

(in 2006) Works

CSCO CISCO SYSTEMS INC 8 30.5% YES

ACN ACCENTURE LTD 8 28.4% YES

MSFT MICROSOFT 7 24.9% YES

LLTC LINEAR TECHNOLOGY CORP 7 -13.8% NO

Low GSCORE SAMPLE

TICKER NAMEGSCORE

(end of 2005)Return

(in 2006) Works

OPWV OPENWAVE SYSTEMS INC 2 -50.4% YES

SIRI SIRIUS SATELLITE RADIO INC 2 -24.4% YESAMTD TD AMERITRADE HOLDING CORP 2 -12.8% YES

MICC MILLICOM INTL CELLULAR SA 2 25.3% NO


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Portfolio Results (from Paper)

TABLE 4. Returns to an Investment Strategy Based on GSCORE for Low BM Firms.

Panel B: Distribution of SRET1(One-Year Size Adjusted Returns)

GSCORE N Mean 10% 25% Median 75% 90% % Positive

0 614 -19.1% -87.8% -61.7% -34.7% 2.7% 62.0% 26.2%

1 2191 -17.0% -86.1% -62.4% -34.0% 5.0% 52.8% 27.4%

2 4038 -14.0% -84.8% -61.4% -30.9% 7.6% 60.1% 28.6%

3 4378 -12.7% -83.1% -57.4% -25.2% 10.8% 60.6% 31.3%

4 3974 -6.7% -71.8% -46.0% -15.7% 16.9% 61.4% 36.4%

5 3477 -3.2% -62.7% -38.5% -10.2% 18.3% 56.3% 39.7%

6 2139 1.3% -54.0% -31.2% -5.1% 20.4% 57.6% 44.0%

7 803 6.8% -49.7% -23.9% 0.0% 23.3% 62.7% 49.9%

8 110 11.4% -51.9% -22.5% -0.2% 21.1% 62.4% 50.0%

ALL 21724 -8.7% -76.4% -50.7% -19.1% 14.3% 58.6% 34.6%

HIGH (6,7,8) 3052 3.1% -52.6% -29.1% -3.7% 21.1% 58.9% 45.8%

LOW (0,1) 2805 -17.5% -86.3% -62.1% -34.0% 4.5% 54.7% 27.2%

HIGHLOW 20.6% 30.3% 18.6%

t-statistic/ z-statistic 10.41*** 21.23*** 15.12***

Bootstrap Result 0/1000 0/1000 0/1000

p-value (0.000) (0.000) (0.000)


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Portfolio Results (2 year Horizon)

Panel D: Distribution of SRET12(Two-Year Size Adjusted Returns)

GSCORE N Mean 10% 25% Median 75% 90% % Positive

0 614 -36.1% -120.8% -92.5% -58.1% -10.6% 50.0% 26.2%

1 2191 -32.8% -116.3% -91.1% -56.5% -5.9% 60.1% 27.4%

2 4038 -26.4% -114.4% -88.6% -54.2% -1.9% 69.4% 28.6%

3 4378 -22.4% -111.7% -86.7% -46.4% 7.5% 74.5% 31.3%

4 3974 -9.9% -102.0% -71.9% -30.5% 21.4% 90.6% 36.4%

5 3477 -6.2% -92.1% -61.1% -21.1% 22.3% 81.8% 39.7%6 2139 0.9% -81.0% -49.3% -11.8% 28.1% 82.9% 44.0%

7 803 13.4% -73.1% -41.2% -1.7% 40.4% 108.3% 49.9%

8 110 15.5% -64.1% -38.4% -4.3% 34.0% 121.7% 50.0%

ALL 21724 -15.9% -106.5% -77.2% -36.1% 14.7% 79.1% 34.6%

HIGH (6,7,8) 3052 4.7% -77.5% -46.9% -8.8% 31.5% 89.6% 45.8%

LOW (0,1) 2805 -33.5% -117.8% -91.4% -57.0% -7.2% 58.2% 27.2%

HIGHLOW 38.3% 48.2% 18.6%

t-statistic/ z-statistic 14.25

***

21.24

***

15.12

***

Bootstrap Result 0/1000 0/1000 0/1000

p-value (0.000) (0.000) (0.000)


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Results Across Time (1 year Horizon)

Post 2001 numbers based on additional analysis

GSCORE Strategy return:

Return to a strategy of going long in High GSCORE Firms and going short on low GSCORE

Firms

-20.0%

-10.0%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005


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Analysis of Results

Robust Across Time Unlikely to be driven by risk based explanations

Most of the Returns from the DownsideNeed to have the ability to short Difficult to pick undervalued gems in this highly valued

space

Robust across partitions Size, Analyst Following, Liquidity, Exchange Listing

Should allay implementability concerns


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Implications

This approach helps identify which stocks to avoid. Important for investors who can use this approach to separate the wheat from

the chaff.

This strategy can be profitable if one has the ability and willingness to short

Basic Fundamental Analysis has a role to play in the growth stock space aswell. Dont waste your time looking for the next new paradigm.

One has to tailor fundamental analysis to suit growth stocks where it is allabout expectations and long term performance.

Strategy works well in portfolioswith at least 50 stocks in both groups(high GSCORE and low GSCORE stocks). It may not work well with individual picks.

Documents

Partha Mohanram - Applying Fundamental Analysis for Growth Stocks - BOS - 10.9.07