Page 1 of 16

A Look at Zillow after Trulia’s IPO

Analysis of the Profits-Revenues Data

§ 1. Summary

After Trulia’s successful debut on the NYSE, its profits-revenues data were

analyzed to predict both the profits and revenues for the fiscal year ending

December 31, 2012. Trulia’s stock is being compared to Zillow, its main

competition. Unlike Trulia, which has yet to report a profit, Zillow has reported

quarterly profits for 4 out of 14 quarters and a profit for three consecutive quarters

starting Q42011. It has also reported a profit for the full year 2011.

The analysis of the profits and revenues data for Zillow (from 2006 to 2011, annual

basis and Q1 2009 to Q2 20102, quarterly basis) again reveals a simple linear law

y = hx + c = h(x – x0) relating the revenues x and profits y, regardless of whether

we consider the quarterly, cumulative quarterly, or the annual data. In all cases, as

revenues increase, losses decrease and eventually turn into profits at higher

revenues. Thus, the intercept x0 = - c/h made by the straight line on the x-axis

(revenue axis) equals the cut-off or “breakeven” revenue, the minimum revenue

needed before the company can report a profit. The slope h then gives the rate at

which additional revenues are converted into profits.

On a quarterly basis h = 0.518 and on an annual basis h = 0.574. In other words,

Zillow has the potential to convert about 52% of its quarterly revenues into profits,

or about 57% of its annual revenues into profits.

However, costs (as revealed by the increasing values of x0) have also been

increasing and consistent delivery of profits will require paying attention to three

fundamental constants (a, b, p) which appear in the classical breakeven analysis for

the profitability of any company. Here “a” is the fixed cost, “b” the unit variable

cost and “p” the unit price.

The two articles on Trulia and Zillow show that a simple approach based on the

analysis of the graphical trends in the profits-revenues diagram can serve as a

valuable tool for investors.

Page 2 of 16

Table of Contents

§

No.

Topic Page

No.

1. Summary 1

2. Introduction 3

3. Zillow’s Quarterly Profits-Revenue data 4

4. Zillow’s Annual Profits-Revenue data 7

Table 1: Annual Profits-Revenues data for Zillow 10

Table 2: Quarterly Profits-Revenues data for Zillow 11

5. List of References 13

Page 3 of 16

§ 2. Introduction

After the recent Facebook IPO, and some other disappointing IPOs, the news about

Trulia’s successful debut, on its first day of trading as a public company, caught

my attention, see Ref. [1], click here. The company sold six million shares at the

IPO price of $17 apiece, raising nearly $102 million in working capital. The stock

price went up from the IPO price of $17.00 to $24.00, a nice 40% boost, but was

down to $23.03 on Friday close, 9/21/2012, see Refs.[1-3].

Interestingly, though, Trulia has not made one single dime in profits since it has

existed [4]. The recent passing of the JOBS Act has made it easier for companies,

with under $1 billion in revenue, to more easily raise money by doing the IPO.

Morning star, Ref.[5], notes the new, reduced, regulations as being somewhat

positive for qualifying companies to go public, modestly negative to the

investment community and neutral to investment banks, see also Ref. [6].

If there ever was a shining example of how tax cuts for the rich is supposed to help

create jobs, this IPO is it, folks! The rich can use their money that would otherwise

end up as tax paid for wasteful government expenditures, and invest it in IPOs of

companies like Trulia, Facebook, Groupon, Zynga, you name it, who will then start

hiring and create jobs – good, well-paying, jobs – in the financial sector. This

JOBS Act is such a pro-business, pro-free-enterprise, pro-risk-taker, pro-market,

anti-business, anti-regulation, initiative that it truly warms my heart. Now all we

need to do is to unleash the creative genius and go straight to the rich folks all over

this country to raise cash, millions of dollars in working capital, without ever

having made one red cent in profits! I am not the least bit sarcastic folks! This is

how capitalism is supposed to work.

Now, if we can only get that top tax rate down once again to like 7%! Yes, that

was the top tax rate back in 1913 before President Woodrow Wilson raised it to

77%, as the US entered World War I, see Refs.[7-10].

Nonetheless, as hinted by Morning Star, especially in the title to Ref. [5], the

burden is now upon the investor to study such companies carefully and make wise

investment decisions.

Page 4 of 16

And so, I have analyzed the profits-revenues data for Trulia and published it on

Sep 21, 2012 (click here and here). The analysis permits an estimate of both the

profits and the revenues for the fiscal year ending Dec 31, 2012. The reader is

referred to the article cited here for more details. The necessary background and all

the introductory material needed to understand the analysis (which is based on a

new, but very simple, methodology) may be found in there, see also Refs.[11,12]

for the links. In what follows here, we will consider the profits-revenues data for

Zillow Inc., Trulia’s main competition. Zillow went public in July 2011 and its

stock price has doubled since then. Trulia’s stock is considered to be a bargain

compared to Zillow’s [1].

§ 3. Zillow’s Quarterly Profits-Revenues Data

The annual (2006 to 2011) and quarterly (Q12009 to Q2 2012) profits and

revenues data for Zillow, can be readily obtained from the 2011 Annual Report and

the S-1 Registration filing and have been included here in Tables 1 and 2 for

convenience. A brief analysis of this data follows.

Consider first the quarterly data, for 14 consecutive quarters, which has been

plotted in Figure 1. We see nice a nice upward trend. As revenues increase, the

losses (the negative profits) decrease, which is mathematically equivalent to

increasing profits. Unlike Trulia, Zillow has reported a small profit for four out of

five recent quarters, starting Q22011 (a small loss for Q32011). However, as we

see from Figure 1, these five data points, at the highest revenues observed, deviate

from the nice linear upward trend for the earlier quarters and are scattered along

the x-axis, the horizontal y = 0 for ZERO profits (or losses).

The equation of the “best-fit” line, labeled A, through the remaining eight (x, y)

pairs, which seem to lie very nearly on a perfect straight line, can be determined

using the well-known linear regression analysis. The data for Q1 2011 was

excluded from this analysis since it seems to deviate slightly from the nice upward

trend. Thus, the regression equation y = hx + c = h(x – x0) = 0.5179x – 5.559 =

0.52(x – 10.73). The cut-off, or breakeven, revenue x = x0 = - c/h, above which a

profit will be reported is obtained by setting y = 0 in this equation and equals x0 =

$10.73 million. This means that if the quarterly revenues exceed this cut-off level,

Page 5 of 16

a profit will be reported. This prediction is confirmed if we examine the data for all

the quarters for which a profit was reported, all of which are in excess of the cut-

off, or breakeven x0 = $10.73 million. Even so, we find that the data do not follow

the regression line A but are scattered along the horizontal. The deviation from line

A implies lower profits, which also implies higher costs.

Figure 1: Quarterly profits-revenue diagram for Zillow Inc. The data for 14

consecutive quarters, from Q12009 to Q22012, has been plotted here. The

revenues have been increasing consistently and correspondingly losses have also

been decreasing (mathematically equivalent to increasing profits).

Indeed, as discussed in the Trulia article, the linear law y = hx + c deduced here

from the empirical observations of profits and revenues can be shown to be a

consequence of the classical breakeven analysis for the profitability of a company.

According to this breakeven model, the relation between revenues x and profits y

is linear with the slope h = 1 – (b/p) and the intercept c = - a, and the breakeven

-8.00

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

Quarterly Revenues, x [$, millions]

Qu

art

erl

y P

rofi

ts,

y [

$,

millio

ns]

y = hx + c = h(x – x0) y = 0.518x – 5.56 = 0.52 (x – 10.73)

with r2 = 0.9669

A

x0

Page 6 of 16

revenue x0 = ap/(p – b). Here “a” is the fixed cost, “b” the unit variable cost and

“p” the unit price. For a company making and selling N units of a product, the

total costs C = a + bN is the sum of the fixed cost “a” and the variable cost “bN”.

The revenues R generated by selling the N units R = pN. Hence, the profits P = R =

C = pN – a – bN = (p – b)N – a = [(p – b)/p] R – a which means the P-R relation is

linear with a slope and intercept as just noted.

The deviation of the most recent quarterly data from the regression line A for

earlier quarters thus implies an increase in the total costs C associated with the

operation, or a changing cut-off revenue x0 = ap/(p –b) which reflects the complex

interaction of all the three constants (a, b, p) in the breakeven model.

This can also be appreciated if we take a careful look Figure 1. Notice that the two

(x, y) pairs for Q1 2011 (11.255, -0.830) and Q2 2011(15.85, 1.58), representing a

loss and a small profit, seem to fall on a line that is roughly parallel to the

regression line A. Likewise, the (x, y) pairs for Q3 2011 and Q1 2012, at even

higher revenues (another profit-loss pair), are also joined by a line segment that is

roughly parallel to line A. The equations of the line segments are given below. In

each case, as revenues increase, losses turn into profits with a higher and higher

cut-off, or breakeven, revenue x0; i.e., higher costs as revenues have increased.

Line B, y = 0.524x – 6.733 = 0.524 (x – 12.84) joins Q1 2011 and Q2 2011

Line C, y = 0.607x – 12.15 = 0.607 (x – 19.998) joins Q3 2011 and Q12012

The point marked by the red square on Line A in Figure 2, at the value of x =

27.77, the revenue for Q2 2012 is the projected profit if Zillow had continued to

operate along line A as its revenues increased. The vertical separation between the

red square and the actual profit for Q2 2012 represents the “lost” profits due to the

higher costs, or the higher value of x0 as revealed by the intercepts made by Lines

B, C, etc. at higher and higher values of the “cut-off”, or breakeven revenues.

The rather simple analysis presented here thus given us some invaluable insights

about the reasons for the “scatter” in the profits-revenues data. More importantly, it

also tells us what Zillow must do to increase its profits and return to line A, or

establish a new parallel to line A with increasing profits and increasing revenues,

following either lines B, or C, or a new parallel to line A in the near future.

Page 7 of 16

Figure 2: A set of parallels (or nearly parallel lines) are revealed as shown here

by a careful consideration of the profits-revenue data that do not lie along Line A.

Each of these lines, with a more negative value of the intercept c, or equivalently

higher cut-off, or breakeven, revenue x0, implies higher costs and therefore

decreased profits for the company.

§ 4. Zillow’s Annual Profits-Revenues Data

As we know, the. quarterly observations plotted in Figures 1 and 2 are combined

into six-month, nine-month and yearly revenues and profits and revenues and

reported in the 10-Q filings for each quarters. The cumulative revenues and profits

reveal the same linear behavior, see Figure 3, where we consider the four

consecutive quarters starting with Q32011 (with a small loss) to Q2 2012. As

revenues increased, the losses decreased and turned into a profit and the company

moves into the positive territory. (As an aside, this is similar to the situation

observed during the Clinton years with the US budget Surplus-Receipts data. As

-15.00

-10.00

-5.00

0.00

5.00

10.00

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00

Quarterly Revenues, x [$, millions]

Qu

art

erl

y P

rofi

ts,

y [

$,

millio

ns]

A B

C

Q2 2012 x0

x0

A

Page 8 of 16

the government’s receipts increased, the deficits decreased and turned into a nice

surplus, for four consecutive years, see discussion in Refs. [13-16], click here to

see the graph for the Clinton years. )

Thus, based on its current “cost structure”, we expect Zillow to report a profit, on a

quarterly basis, as long as the revenues exceed the cut-off, or breakeven, value of

x0 = $29.18 million. This is higher the cut-off estimated from Line C of Figure 2.

Figure 3: The cumulative profits, obtained by combining the quarterly values,

increase as the cumulative revenues increase. Starting with the data for Q3 2011,

when a small loss was reported, we see the company moving into the positive

territory as it started reported a profit for each quarter. Again, the same linear law

y = hx + c is observed. The cut-off revenue x0 = $29.18 million.

Finally, the annual data (where the four quarterly points for each year are collapsed

into one single point), for the years 2006 to 2011, is plotted in Figure 4. Once

again, we see the same linear trends and also what appears to be a movement of the

data along parallel lines, as discussed earlier with the quarterly data (in Figure 2).

-2.00

-1.00

0.00

1.00

2.00

3.00

4.00

5.00

6.00

0 20 40 60 80 100 120 140

Cumulative Revenues, x [$, millions]

Cu

mu

lati

ve

Pro

fits

, y [

$, m

illi

on

s]

y = 0.056x – 1.643 = 0.056 (x – 29.18)

x0

Cumulative Values Q32011 to Q2 2012

Page 9 of 16

For 2006, Zillow reported a loss. As revenue increased, between 2006 and 2007,

the loss actually increased. However, as revenues increased further, Zillow started

reported lower and lower losses each year. A small profit, on an annualized basis,

was finally reported in 2011. However, as with the quarterly data, the (x, y) pair for

2011 does not fall on the line, labeled A in Figure 5. Instead, we can imagine a

parallel B to line A through the 2011 data point, which would intersect the x-axis

at a much higher value of x0, the cut-off revenue (on an annualized basis).

The cut-off, or “breakeven”, revenue given by x0 = ap/(p – b) = -c/h, has increased

between 2010 and 2011 and this explains the reduced profits compared to the

projected value (given by the red square on Line A).

Figure 4: The annualized profits, obtained by combining the quarterly values,

increase as the annualized revenues increase. Line A is the best-fit line through the

2007-2010 data. Again, the same linear law y = hx + c is observed. The cut-off

revenue x0 = $41.53 million on an annualized basis. The data for 2011 falls on the

parallel B with a higher intercept x0 which means the costs have increased between

2010 and 2011.

-50.00

-40.00

-30.00

-20.00

-10.00

0.00

10.00

20.00

0 10 20 30 40 50 60 70 80

Annual Revenues, x [$, millions]

An

nu

al P

rofi

ts,

y [

$, m

illio

ns]

y = 0.574x – 23.84 = 0.574 (x – 41.53)

r2 = 0.9348

y = 0.574x – 36.81 = 0.574 (x – 64.13)

A

B

Page 10 of 16

The equation for line A was determined using linear regression analysis. At first

five data points (2007, 2008, 2009, 2010) were considered with 2006 and 2011

being excluded for obvious reason. However, the final equation was determined by

eliminating the 2008 data as well from the regression analysis. This yields the

“best” fit to the data for 2007, 2009 and 2010. The straight line joining the 2007

and 2010 has the slope h = ∆y/∆x = 13.516/23.361 = 0.5786, which is very nearly

the same as the slope h = 0.574 from the regression analysis.

The vertical separation between the parallels is equal to the differences in the

values of the intercepts. The line A has the equation yA = hx + cA where yA means

the value of y on Line A for any x and cA is the intercept made by Line A. The

equation for line B is yB = hx + cB . The vertical separation between the parallels A

and B is therefore given by (yA – yB) = (cA – cB). In other words, the difference in

the profits on line A and B (for any fixed revenues x) is equal to the difference in

the values of the intercepts.

Table 1: Annual Profits-Revenues Data for Zillow

Year Revenues, x [$, millions] Profits, y [$, millions]

2011 66.053 1.102

2010 30.467 -6.774

2009 17.491 -12.855

2008 10.593 -21.217

2007 7.106 -20.29

2006 4.289 -12.589

Source: http://investors.zillow.com/secfiling.cfm?filingID=1193125-11-

100697&CIK=1334814

Page 11 of 16

Table 2: Quarterly Profits-Revenues Data for Zillow

Quarter Revenues, x [$, millions] Profits, y [$, millions]

Q22012 27.77 1.33

Q12012 22.83 1.72

Q42011 19.89 0.92

Q32011 19.06 -0.57

Q22011 15.85 1.58

Q12011 11.255 -0.830

Q42010 9.573 -0.486

Q32010 8.229 -1.510

Q22010 7.334 -1.972

Q12010 5.331 -2.806

Q42009 4.704 -2.932

Q32009 5.541 -2.425

Q22009 4.504 -3.069

Q12009 2.742 -4.429

Let us consider the data for 2009, which reveals an interesting trend. Since a loss

(negative profits) was reported for all four quarters in 2009, the cumulative losses

just keep on increasing as revenues increase (when we combine the data for each

consecutive quarter to arrive at the annual profits-revenues figures). Hence, the

slope of the graph h is negative.

This would be similar to the case of profits decreasing with increasing revenues,

which would also yield a negative slope. This too is observed when we analyze

financial data, some companies do report decreasing profits with increasing

revenues, for example, General Motors before its bankruptcy, see Refs.[17-19].

Struggling companies usually have this pattern (negative slope h) but with graph

being entirely in the first quadrant. With Zillow, however, the graph is

entirely in the fourth quadrant. Notice that the intercept made with the y-axis is

also negative, c = - 2.863. Hence, the extrapolation of this line will cut the x-axis at

a a negative value, which means x0 = - c/h = - 5.01. Such a trend is obviously not

desirable. The cumulative profits-revenue graph for the year must have a positive

slope, as we see for successful companies like Microsoft, Google, Apple, etc. This

has been discussed in other articles, see Refs. [20-23]. It is also of interest to note

Page 12 of 16

that the absolute magnitude of the (without the negative sign) is very close to the

numerical value of the slope h = 0.574 for the annual data (Figure 4).

Figure 5: The Cumulative Profits-Revenues graph for the year 2009. Notice again

the nearly perfectly linear trend.

-16.00

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

0.00 5.00 10.00 15.00 20.00 25.00

Cumulative Revenues, x [$, millions]

Cu

mu

lati

ve

Pro

fits

, y [

$, m

illi

on

s]

y = -0.5714x – 2.863 = -0.571 (x – 5.01)

Page 13 of 16

§ 5. List of References

1. Trulia stock soars in debut, By Maureen Farrell, cnn.com, Sep 20, 2012,

http://buzz.money.cnn.com/2012/09/20/trulia-ipo-stock/

2. 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_help

s_an_ipo_avoid_a_tech_wipeout_.html

3. 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

4. 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/

5. JOBS Act Resulting in Easier IPO Roadmap but at Investor’s Cost, http://news.morningstar.com/articlenet/article.aspx?id=568389

6. The IPO Quandry, By Atmabus, Sep 23, 2012, seekingalpha.com,

http://seekingalpha.com/article/883021-the-ipo-

quandary?source=marketwatch

7. Sixteenth Amendment to the United States Constitution, Wikipedia article,

http://en.wikipedia.org/wiki/Sixteenth_Amendment_to_the_United_States_Co

nstitution http://www.shmoop.com/constitution/16th-amendment.html

8. Woodrow Wilson, Congress and the Income Tax, March 16, 2004,

wilsoncenter.org http://www.wilsoncenter.org/sites/default/files/ACF18.pdf

9. Top Tax rates, Historical facts, taxpolicycenter.org

http://www.taxpolicycenter.org/taxfacts/displayafact.cfm?Docid=213

10. Top Federal Income tax rates, 1916-2013, findthedata.org, http://top-

federal-tax-rates.findthedata.org/

11. Trulia After its IPO, Analysis of Profits-Revenues Data, Published Sep 21,

2012, http://www.scribd.com/doc/106573459/The-Trulia-IPO-Analysis-of-

Profits-Revenues-Data

12. The Trulia IPO: Analysis of Profits-Revenues Data, vlaxmanan’s

Instablog, Published Sep 21, 2012, http://seekingalpha.com/instablog/958073-

vlaxmanan/1096481-the-trulia-ipo-analysis-of-profits-revenues-data

13. The Amazing US Government Surplus (Deficits)-Receipts Relation

during the Clinton Presidency, http://www.scribd.com/doc/105821230/The-

Page 14 of 16

Amazing-US-Government-Receipts-Surplus-Relation-during-the-Clinton-

Presidency, Published Sep 13, 2012.

14. A Brief Review of the Historical US Government Receipts-Surplus

(Deficit) Relation, http://www.scribd.com/doc/106003088/A-Brief-Review-of-

the-Historical-US-Government-Surplus-Receipts-Relation , Published Sep 15, 2012.

15. The Clinton Budget Surpluses, http://www.scribd.com/doc/105819500/The-

Clinton-Budget-Surpluses-Treating-Government-like-a-Business, Published

Sep 13, 2012 , Google financial data for early years may be found in Table 2.

16. The Efficiency of Government Compared to the Thermal Efficiency of a

Heat Engine, Sep 18, 2012, http://www.scribd.com/doc/106220758/The-

Efficency-of-Government-Compared-to-Thermal-Efficiency-of-a-Heat-Engine

17. GM Before the Bankruptcy:Maximum point on the profits-revenues graph,

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

Maximum-Point-on-Profits-Revenue-Graph , Published August 25, 2012.

18. The New GM: A Brief Analysis of the Profits-Revenues Data,

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

19. Why Can’t GM be more like Microsoft? The New GM Just May be.

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.

20. 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.

21. A Second Look at Microsoft after its Quarterly loss,

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

the-Historic-Quarterly-Loss , Published July 30, 2012.

22. 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.

23. 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.

Page 15 of 16

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.

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

Page 16 of 16

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.

Cover page of AirTran 2000 Annual