The Inc.100 ranking of the fastest growing
public companies in America, where growth is measured by the
average sales growth figure over the previous 5-year period, was
first published by *Inc.* magazine in May 1979 and has been
a regular feature ever since, with the exception of 1991. All
rankings from 1979 until 1990, or 12 complete rankings of the 100
best performing firms, are used here. The post-1990 rankings are
ignored because of insufficient post-event time to test for the
existence of abnormal returns in various arbitrage strategies
consisting in buying (selling) shares in the Inc.100 rankings and
because of the problem introduced by the non-existence of the
1991 ranking.

Collecting the data on the firms included in the older rankings proved a difficult task, with a number of firms having disappeared without any traces. A number of firms also suffered from early delisting, a fact which can happen for a multitude of reasons, including merger, acquisition, going-private, bankruptcy, or liquidation. The first three categories possibly provide shareholders with reasonable returns upon delisting; the last two are more questionable. No information is available at this stage on delisting reasons, nor the performance of the stocks from ranking until delisting.

For each firm in the sample, the following information was collected: rank in Inc.100 survey, name, industry code, sales growth in the five years prior to the ranking, revenues and net income in last financial report and five years prior to the that, number of employees in ranking year and five years prior to it, year the company went public and on which market, salary of CEO, whether the CEO founded the company, and the equity ownership of the CEO. Monthly return and systematic risk data was obtained from Compustat sources and the monthly CRSP tapes from the University of Chicago. Economic series, such as monthly risk-free rates and returns on market indices (Standard & Poors 500 and Dow Jones Industrial) were downloaded from Citibase.

The traditional event study performance analysis is based on the measurement of some "abnormal" return for the shares investigated over a period of interest. In the case at hand, the objective is to determine to what extent a ranking in the Inc.100 list of the fastest growing public companies in America actually conveys information about future returns, i.e. is it possible to implement, on the basis of the rankings, investment strategies that will earn returns higher than expected by the standard risk/return models ?

This objective implies that the period of interest for the analysis is the post-ranking months, since trading (or arbitrage) strategies must be based on information released in the Inc.100 rankings. These rankings have historically been published in May each year (with the exception of the 1991 lapse mentioned above). The month of publication of the ranking is then referred as Month 0 in the event study. All subsequent months are denoted by higher integers, i.e. the third month post-ranking is month 3.

The definition of what constitutes "abnormal" returns presupposes 1) the knowledge of what a "normal" return should look like, and, 2) market efficiency, in the sense that risk information is indeed reflected in the prices. Accordingly, event studies are always joint tests of both market efficiency and the particular model being used to represent the return process. Two models are used here for the latter. First is a simple market model, assuming the expected return for all stock is the actual return realized on the market for the period. This implicitly assumes an average beta of 1.0, an assumption which will be tested later. Abnormal returns are then measured by:

(1)

where *ARi,t* is the market-adjusted
abnormal return on share *i* in post-event month* t, Ri,t*
is the raw return on share *i* in month* t*, and *Rm,t*
is the corresponding return on the market index. The choice of an
adequate market benchmark potentially influences the reported
results, so two indices are used here: the Standard & Poors
500 and the Dow Jones 30 Industrial. The second model explicitly
incorporates the systematic risk of individual securities in the
adjustment procedure, using a CAPM-type risk/return relationship.
Abnormal returns are measured as follows:

(2)

where *Ri,t* is the raw return on share *i*
in month* t*, and *Rf,t* is the corresponding return on
the risk-free security (proxied here by the return on the U.S.
Treasury 90-day bill), b _{i }is share *i’s *systematic risk
coefficient measured over the previous 60 months, and *MRP *is
the Market Risk Premium, or the price the market has historically
been willing to pay per unit of beta risk carried by investors. A
70-year average is used here, from Roger G. Ibbotson and Rex A.
Sinquefield’s 1994 *Stocks, Bonds, Bills and Inflation:
1994 Yearbook*. This average market risk premium amounts to
8.5% per year per unit of beta risk.

For each method, an average abnormal return is then calculated for each event month following the Inc.100 ranking, using:

(3)

where *nt* is the number of shares in the
cross-section in post-ranking month *t*. The long-run
perfor-mance measure involves the cumulating of these abnormal
returns over time for each individual firm, followed by
cross-sectional averages [Dimson and Marsh (1986)]:

(4)

Although this has been the method of choice for the last 20 years, Conrad and Kaul (1993) high-lighted the potential bias in this procedure, which aggregates not only returns but also individual estimation errors. In general, estimation errors seem to cancel out, but the potential remains and the magnitude of the problem is unknown.

As mentioned above, 1,200 firms entered the 1979-1990 Inc.100 rankings. Some of these firms could not be located using a combination of Bridge on-line, Compustat, Standard and Poors Stock Listings, Datastream, and Dial-Data Stock Lookup, possibly resulting from typos in the original Inc.100 listings.

The distribution of the sample’s sales growth in the five years leading to the ranking are depicted below in exhibit 1. Most firms experience average compounded annual growth rates over that 5 year span in excess of 100% (mean=122.85%), with the top ranked firms exceeding 500% (maximum=678%). These figures qualify the sample firms as supergrowth firms, justifying the title of the paper. The cumulative distribution of reported net incomes in the ranking years further qualifies these sample firms as "growth" companies with relatively small current incomes. Indeed, over 80% of the sample firms report net incomes below $5 million in the ranking years.

Growth firms have also gained wide recognition
as the true engines of employment. The distribution of employment
among sample firms is instructive in this regard. The sample mean
is at 671 employees, but a standard deviation of 1173 (minimum=5;
maximum=12000) indicates wide dispersion about that mean. The
same sample of firms had, on average, only 84 employees (with a
standard deviation = 289) 5 years before the rankings, indicating
a __compound annual growth rate__ in employment in these
hypergrowth firms of __nearly 52% per year__.

The corporate control and governance literature also highlights the strong convergence of ownership and control in younger, entrepreneurial institutions as a possible explanation for the superior performance observed. A first glimpse at the distribution of CEO salaries for the firms sampled after 1988 discloses that the mean salary is equal to $229,164, with a standard deviation of $391,501 (Minimum = $12,500; Maximum = $5,000,000). The distribution of salaries is in fact very concentrated in the $150,000 to $500,000 range. Even more relevant to the control issue is the distribution of CEO ownership of their own companies. For the same sample the mean ownership position is at 15.75%, with a standard deviation of 15% (Minimum = 0%; Maximum = 75%).

The results presented so far are static by design, assuming that the variables described did not significantly change over the period of investigation. In order to analyze possible evolution through time, similar descriptive statistics have been estimated by year of ranking.

The average sales growth for each cohort year (ranking year) is a statistic that can also be interpreted as the average sales growth a firm must have achieved in order to deserve the right to appear in the Inc.100 ranking. Since all rankings are relative by design, economy-wide factors may determine which firms actually show up in any one particular table. An examination of the data indicates that firms in the 1979 ranking averaged 64% average sales growth per year in the 5 years prior to the ranking year. The firms in the 1990 cohort, for their part, average 143% per year over the same prior 5 years. As the data indicate, making the ranking has become a much more competitive sport as well.

It is also interesting to note the relative lack of evolution of the average number of employees in the Inc.100-listed firms. From an average of 510 employees in 1979, the figure does not change statistically throughout the 12-year analysis period, ending with 670 employees on average in the 1990 rankings.

The empirical finance literature also highlights the explanatory power of both the market to book ratio (also known as the Q-ratio) and the Price-Earning Multiple. Both measures are forward-looking in perspective, interpreted as reflections of the "growth opportunities" of the company. These two measure thus offer a valuable piece of information to add to the historical-based growth rates and may help understand the future performance of the hypergrowth firms.

Exhibit 2 indicates that indeed market-to-book ratios significantly evolve through the post-ranking periods, falling from around 135 in the month of the Inc.100 ranking to an average of 74 some 36 months following the ranking. These figures can be interpreted in different ways. For one, this evolution could be the natural consequence of these growth opportunities being converted over time into assets in place, and hence greater book values. On the other hand, the fall in the ratio could also mean that the exceptionally high growth rates experienced by these firms often cannot be repeated in the future. Although it would be pure speculation at this point to support one explanation over the other, it is interesting to note that the average market to book ratio remains exceptionally high over the whole period for sample firms compared to the ratios prevailing in the stockmarket-listed firms at large. The price-earnings multiples tell a very similar story, although very little trend can be detected in the results there. Indeed, the observed average price-earnings multiples in the 30-40 range are quite unusual and again indicate the exceptional growth potential of these sample supergrowth firms.

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Last Updated 4/12/97 by Cheryl Ann Lopez & Dennis Valencia

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