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Trulia after its IPO

Analysis of the Profits-Revenues Data Profits-Revenues Prediction for 2012

Trulia (an online property listing service)

stock began trading on Thursday Sep 19,

2012 at $17.00 per share, the IPO price,

and was up $7.00, closing at $24.00 on

its debut, after the first day of trading,

see Refs. [1-3].

The company offered six million shares

of common stock to the public at the IPO

price of $17.00.

http://sec.gov/Archives/edgar/data/1349454/000119312512359749/g352334g08i94.jpg

Image from the S-1 Registration Statement with the United State Securities Exchange

Commission

However, based on the financial data for the years 2007 to 2011 and the first two

quarters of 2012, reported in the S-1 Filings (Registration Statement with the

United States Securities Exchange Commission, filed August 17, 2012), the

company has not yet reported a profit. Thus, assessment is not very kind, as noted

by Cyram, Ref. [1], especially after some of the recent IPO fiascos, “It also has

never turned a profit in seven years of existence, a foundation on which only a web

IPO could be built. If Trulia can’t swing into the black soon, investors could move

the shares into the shabby tech neighborhood.”

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Table of Contents

§

No.

Topic Page

No.

1. Summary 3

2. Introduction 3

3. Linear Profits-Revenue Relation 4

4. Linear law and Breakeven Analysis for Profitability 6

5. Revenues and Profits Projections for 2012 7

6. List of References 9

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§ 1. Summary

A revenues estimate and a profits estimate for Trulia, for the fiscal year ending

December 31, 2012 is provided here. Using a high revenue growth rate (observed

between 2009 and 2011), the revenue estimate is $52 .608 million.The linear

profits-revenue relation, observed between 2008 and 2010, then permits an

estimate of the profits (or losses). The profits-to-revenues conversion rate (slope

of the profits-revenues graph) of about 50% will be required to boost the profits

from the 2011 level (which were lower than for earlier years). The profits-revenues

conversion rate currently is 34.4%.

******************************************************************

§ 2. Introduction

The main purpose here is to analyze the annual profits-revenues data for Trulia,

which can be obtained from its S-1 filings prior to the recent IPO. The data is

summarized in Table 1 and can be represented graphically as seen in Figure 1.

Table 1: Annual Profits-Revenues data for 2007-2011

Year Revenues, x

$, 000s

Profits, y

$, 000s

Change, ∆x

$, 000s

Change, ∆y

$, 000s

Slope

h = ∆y/∆x

2007 1,675 -7,646

2008 8,066 -7,866

2009 10,338 -6,983

2010 19,785 -3,838 11,719 4,028 0.344

2011 38,518 -6,155

2012 28,987 -7,640

For 2012 through June 30. The changes are between 2008 and 2010.

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§ 3. Linear Profits-Revenue Relation

Any two points (x1, y1) and (x2, y2) on this Profits-Revenues (P-R) diagram can

always be joined by a straight line. However, we notice that the data for the years

2008, 2009, and 2010, seem to fall on a nice upward sloping straight line. The data

for 2007 and 2011 do not fall on this line. Although revenues increased between

2007 and 2008, there was very little change in the losses (or negative profits).

Likewise, even with the greatly increased revenues for the six-months ending June

30, 2012, the loss is again roughly the same as for 2007 and 2008. (All the three

points lie close to the horizontal for a loss of $8 million loss in Figure 1.)

Figure 1: Profits-Revenues diagram for Trulia, based on the financial data from

the S-1 filing on August 17, 2012. The stock started trading on Thursday, Sep 20,

2012 at the IPO price of $17.00 and was up to $24.00 after first day of trading.

The 2012 data is through June 30, 2012. With greatly increased revenues, the loss

for six-month ending June 30, 2012 is roughly the same as for 2007.

-10.0

-8.0

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

0.0 10.0 20.0 30.0 40.0 50.0

Revenues, x [$, millions]

Pro

fits

, y [

$,

mil

lio

ns

]

x0

y = hx + c = h(x – x0) = 0.344x – 10.64 = 0.344(x -10.64)

2011

2007

1

A

2012

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Between 2008 and 2010, on the other hand, the revenues increased by the amount

∆x = (x2 – x1) = $11.719 million and losses decreased (mathematically equivalent

to profits increasing) by ∆y = (y2 – y1) = $4.028 million. Hence, the slope of the

straight line joining these two points equals, h = ∆y/∆x = 0.344. The intercept

made by the straight line with the y-axis is c = y1 – hx1 = y2 – hx2 = -$10.64 million

and the intercept x0 = -c/h, made with the x-axis, has the value x0 = $30.95 million.

This means that if Trulia had maintained the nice linear trend observed between

2008 and 2010, it would “turn the corner” and report a profit when revenues x > x0

= $30.95 million. This is indicated by the solid blue dot, placed on the x-axis (red

horizontal, ZERO profits) in Figure 1. Indeed, revenues in excess of this cut-off, or

“breakeven”, level were reported in 2011. The revenues had nearly doubled

between 2010 and 2011, from $19.785 million to $38.518 million. If the linear

trend had continued, a profit of $2.601 million (the second blue dot on Line A)

would have been reported, instead of loss of $6.155 million.

The missing profits gap is indicated by the “red bracket” placed between the actual

2011 data point and the projected profits for 2011. The vertical separation means

that the data for 2011 can be imagined to fall on a parallel to Line A with the

equation y = 0.344x – 19.394. The intercept c for this parallel is more negative and

the difference in the two intercepts ∆c = $19.394 – $10.638 = $8.756 million is the

profits “gap”. (Note: The profit gap $8.756 = $6.155+$2.601 = $8.755 which is

sum of projected profit and the actual loss.)

In spite of the increase in the losses in 2011, it is still too soon to rush to a

judgment about Trulia, Inc. The fact that the loss for 2008 and the loss for 2012

(through June 30) are roughly constant, even with the increased revenues, is a

cause for some concern, some losses must decrease (or equivalently profits must

increase) as the revenues increase.

However, exactly similar trends have been observed with successful companies,

for example, Google and Southwest Airlines. The financial performance of these

two companies have been discussed in Refs.[5,6]. Google reported a loss in 1999

and 2000, with increasing revenues, just as we see with Trulia. Southwest Airlines

also reported a loss in 1971 (partial year of operation) and 1972 (full year of

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operation) before “turning the corner” and reporting a profit in 1973. It has since

reported a profit for every year for the past 37 years.

Let us wish Trulia well and hope that it emulates these two successful companies.

Of course, there are also examples of struggling companies and others doing well,

after recent IPOS, see Ref.[7-9].

Nonetheless, it is nice to see that Trulia has been able to establish the nice upward

sloping linear pattern revealed in Figure 1. Since the slope h = ∆y/∆x = 0.344 for

Line A, when Trulia is operating on this line, it is able to convert 34.4% of the

additional revenues ∆x into profits ∆y. It can either return to line A by the end of

FY2012, or continue along a parallel to line A, in the coming years, following the

example of other successful companies.

The significance of this movement of the profits-revenues data along parallel, or

roughly parallel, lines can be appreciated by recalling the classical breakeven

analysis for the profitability of a company which is discussed in the next section.

§ 4. Linear Law and Breakeven

Analysis for Profitability

The linear law y = hx + c = h(x – x0) relating revenues x and profits y can be

shown to be a consequence of the classical “breakeven” analysis for the

profitability of a company.

Consider the simple case of a company making and selling N units of product. The

total costs C associated with the operation equals the sum of the fixed cost “a” and

the variable cost “bN” where “b” is the unit variable cost. Hence, C = a + bN. The

revenues R generated from the sale of the U units is given by R = pN where “p” is

the unit price. The profits P = (R – C) = pN - a - bN = (p – b)N – a. Now, we can

eliminate N using N = R/p to get profits P = [(p –b)/p] R – a. This can be written as

P = hR + c, or as y = hx + c where x is revenues and y is profits.

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Slope h = 1 – (b/p) depends on unit variable cost b and unit price ……(1)

Intercept c = - a Depends on the fixed cost, y-axis intercept ……(2)

Breakeven x0 = - c/h = ap/(p – b), x-axis intercept ……(3)

Not all the revenues R generated by a company appear as profits. Profits can only

be reported if fixed costs are exceeded. Even after the fixed costs are exceeded,

only a portion of the revenues (pN – bN) will appear as profit because of the

variable costs associated with the operation. The slope h of the profits-revenues

graph therefore tells us the rate of conversion of profits to revenues. The breakeven

x0 = -c/h = ap/(p –h) reflects the complex interaction of the three constants (a, b, p).

Although we have used a simple model here, empirical evidence suggests that the

same linear y = hx + c = h(x – x0) is also followed by many real world companies,

such as Microsoft, Google, Apple, Southwest Airlines, General Motors (after its

bankruptcy. The analysis of their financial performance has been presented in other

articles cited in the reference list.

§ 5. Revenues-Profits Projections

Finally, consider the growth of the revenues, as a function of time, using the

graphical representation in Figure 2, permits two estimates for the revenues for the

fiscal year ending Dec 31, 2012. Through June 30, 2012, Trulia (SEC filing) has

reported revenues of $28.99 million with a loss of $7.64 million. This six-month

ended data falls right on the line A, which connects the 2007 and 2010 data. The

data for 2011 and 2009 fall above and below this line and are joined by Line B,

with the steeper slope.

A high revenues estimate of $52.608 million is obtained if the data follows line B.

The equation of this line is x = 14.09 t – 28,296.5 where x is in millions and t the

calendar year.

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A lower revenues estimate of $31.858 million is obtained by extrapolation along

line A. This is lower than the actual revenue for 2011. Although the six-month data

falls on line A, this follows the data for earlier years, whereas line B follows the

data for 2009 and 2011. Hence, the higher revenue estimate seems more feasible.

Figure 2: Growth of revenues as a function of time t, in calendar years. Each data

is for the 12-month ending Dec 31 of each year. The data for six-months ending

June 30, 2012 is therefore plotted at 2011.5 years.

Now, using the profits-revenues diagram, let us estimate the profits for revenues of

$52.608 million. The data point for 2011 falls below the line A on the P-R

diagram. Let us assume that the 2012 point will lie on a parallel to line A, passing

through the 2011 point. This permits an estimate of the increase in profits (or

reduced losses) over the 2011 value. The estimate y = -$1.312 million, i.e., a lower

loss than for 2011. However, if the slope h = 0.344 is exceeded, and h = 0.50, then

a profit of $0.890 million is possible.

0.000

10.000

20.000

30.000

40.000

50.000

60.000

70.000

80.000

2006 2007 2008 2009 2010 2011 2012 2013 2014

Re

ven

ues, x [

$,

millio

ns]

Time, t [Calendar year]

June 2012

Dec 2011

Dec 2009

A

B

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In other words, between 2007 and 2010, Trulia was able to convert 34.4% of its

revenues into reduced losses (effectively into profits). To turn the corner in 2012

and report a profit, the profits to revenues conversion rate must exceed the 34.4%

rate since losses had increased in 2011 compared to 2010. If not, Trulia will

continue to report a (smaller) loss in 2012 and most likely report a profit in 2013.

§ 6. List of References

1. Real Estate Wave Helps an IPO Avoid a Tech Wipeout, by Robert Cyram,

slate.com, Sep 20, 2012,

http://www.slate.com/blogs/breakingviews/2012/09/20/real_estate_wave_helps

_an_ipo_avoid_a_tech_wipeout_.html

2. Trulia Soars in Trading After IPO Prices Above Range, by Dan Levy and

Lee Spears, Sep 20, 2012, http://www.businessweek.com/news/2012-09-

20/trulia-surges-in-trading-debut-after-pricing-ipo-above-range

3. Trulia stocks to begin trading Thursday at $17 per share, by AGBeat,

http://agbeat.com/news-business/trulia-stocks-to-begin-trading-thursday-at-17-

per-share/

4. Trulia, Inc. Form S-1 United States SEC Registration Statement, Filed on

August 17, 2012,

http://sec.gov/Archives/edgar/data/1349454/000119312512359749/d352334ds1

.htm

5. Google Inc. A Lovable One-Trick Pony Another Single-product Company

Analyzed using the New Methodology.

http://www.scribd.com/doc/98825141/Google-A-Lovable-One-Trick-Pony-

Another-Single-Product-Company-Analyzed-Using-the-New-Methodology,

Published July 1, 2012.

6. The Future of Southwest Airlines, Completed June 14, 2012 (to be

published). http://www.scribd.com/doc/102835946/The-Future-for-Southwest-

Airlines-The-Unknown-Story-of-Rising-Costs-and-the-Maximum-Point-on-

Profits-Revenues-Curve Published August 14, 2012.

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7. A Fresh Look at Microsoft after its Historic Quarterly Loss, http://www.scribd.com/doc/101062823/A-Fresh-Look-at-Microsoft-After-its-

Historic-Quarterly-Loss , Published July 25, 2012.

8. A Second Look at Microsoft, http://www.scribd.com/doc/101518117/A-

Second-Look-at-Microsoft-After-the-Historic-Quarterly-Loss , Published July

30, 2012.

9. Analysis of the Groupon Profits-Revenues data,

http://www.scribd.com/doc/103265909/A-Brief-Analysis-of-Groupon-s-Profits-

Revenues-Data Published August 19, 2012.

10. Groupon’s Business Model,

http://www.scribd.com/doc/103027366/Groupon-Analysis-of-Profits-

Revenues-Data-and-its-Business-Model Published August 16, 2012. More

detailed analysis including discussion of the idea of a work function.

11. Analysis of Zynga’s Profits-Revenues data and Maximum Point on the

profits-revenues curve, http://www.scribd.com/doc/103369016/Analysis-of-

Zynga-s-Profits-Revenues-Data-Maximum-point-on-the-profits-revenues-curve

Published August 20, 2012.

12. The Perfect Apple-II: Taking A Second Bite: A Simple Methodology for

Revenues Predictions (Completed July 8, 2012, To be Published)

http://www.scribd.com/doc/101503988/The-Perfect-Apple-II, Published

July 30, 2012.

13. Annie’s Inc. A Single-Product Company Analyzed using a New

Methodology, http://www.scribd.com/doc/98652561/Annie-s-Inc-A-Single-

Product-Company-Analyzed-Using-a-New-Methodology Published June 29,

2012

14. The Future of Facebook, http://www.scribd.com/doc/94325593/The-

Future-of-Facebook-I Facebook and Google data are compared here.

Published May 21, 2012.

15. The Facebook Future, http://www.scribd.com/doc/94103265/The-

FaceBook-Future Published May 19, 2012 (the day after IPO launch on

Friday May 18, 2012).

16. Discussion of the new GM data from 1Q2010 to 1Q2011,

http://www.scribd.com/doc/103600274/The-New-GM-A-Brief-Analysis-of-the-

Profits-Revenues-Data-through-1Q2011, Published May 9, 2011 and again on

August 22, 2012,

17. Why Can’t GM be more like Microsoft?

http://www.scribd.com/doc/103607023/Why-Can-t-General-Motors-be-more-

like-Microsoft-The-new-GM-may-just-be Published August 22, 2012.

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18. GM Before the Bankruptcy, http://www.scribd.com/doc/103938349/GM-

Before-the-Bankruptcy-Maximum-Point-on-Profits-Revenue-Graph Maximum

point on the profits-revenues graph, Published August 25, 2012.

19. Trulia IPO: With no profits, who will invest? By Erik Sherman,

cbsnews.com http://www.cbsnews.com/8301-505124_162-57496310/trulia-ipo-

with-no-profits-who-will-invest/

About the author

V. Laxmanan, Sc. D.

Email: vlaxmanan@hotmail.com

The author obtained his Bachelor’s degree (B. E.) in Mechanical Engineering from

the University of Poona and his Master’s degree (M. E.), also in Mechanical

Engineering, from the Indian Institute of Science, Bangalore, followed by a

Master’s (S. M.) and Doctoral (Sc. D.) degrees in Materials Engineering from the

Massachusetts Institute of Technology, Cambridge, MA, USA. He then spent his

entire professional career at leading US research institutions (MIT, Allied

Chemical Corporate R & D, now part of Honeywell, NASA, Case Western Reserve

University (CWRU), and General Motors Research and Development Center in

Warren, MI). He holds four patents in materials processing, has co-authored two

books and published several scientific papers in leading peer-reviewed

international journals. His expertise includes developing simple mathematical

models to explain the behavior of complex systems.

While at NASA and CWRU, he was responsible for developing material processing

experiments to be performed aboard the space shuttle and developed a simple

mathematical model to explain the growth Christmas-tree, or snowflake, like

structures (called dendrites) widely observed in many types of liquid-to-solid phase

transformations (e.g., freezing of all commercial metals and alloys, freezing of

water, and, yes, production of snowflakes!). This led to a simple model to explain

the growth of dendritic structures in both the ground-based experiments and in the

space shuttle experiments.

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More recently, he has been interested in the analysis of the large volumes of data

from financial and economic systems and has developed what may be called the

Quantum Business Model (QBM). This extends (to financial and economic

systems) the mathematical arguments used by Max Planck to develop quantum

physics using the analogy Energy = Money, i.e., energy in physics is like money in

economics. Einstein applied Planck’s ideas to describe the photoelectric effect (by

treating light as being composed of particles called photons, each with the fixed

quantum of energy conceived by Planck). The mathematical law deduced by

Planck, referred to here as the generalized power-exponential law, might actually

have many applications far beyond blackbody radiation studies where it was first

conceived.

Einstein’s photoelectric law is a simple linear law, as we see here, and was

deduced from Planck’s non-linear law for describing blackbody radiation. It

appears that financial and economic systems can be modeled using a similar

approach. Finance, business, economics and management sciences now essentially

seem to operate like astronomy and physics before the advent of Kepler and

Newton.

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