# OT - Year end thoughts

As we approach the end of the year and soon begin a new annual scorecard I wanted to post a few thoughts about our investing activities. I’ve been an adherent to this board nearly since its inception. Knowledge and thought processes freely given by Saul and many others shared on this blog have been the primary source of investment information for me over the last several years. I am indebted to the many experienced and intelligent folks who post here. I am deeply grateful, even to the occasional detractor who feels they must post in order to protect us from us. The rebuttals often carry valuable information for those of us who adhere to an investment strategy centered on companies with high revenue growth. But that leads me to my primary subject.

That subject being investment analysis based on the financial reports and the ability compare likely future performance across different companies based on mathematical functions.

There is great comfort to be gained from financial analysis. Math is remarkably consistent and reliable. We can argue about assumptions, will growth taper in eight quarters or twelve? Will SBC remain at the same level or be reined in sooner rather than later? Etc, etc. but you can’t argue about the math (not at this level anyway). At best you might point out a mistake. That’s not an argument, either a mistake was made or not.

Here’s the thing. Financial analysis has never been wanting for mathematical treatment of financial reports. Quite some time ago, before Saul started this board I was attracted to the notion of mathematical treatment as a guide to investment decisions. As noted, I found a level of comfort in mathematical analysis. Due to the fact that math never fails I gained a false sense of certainty in mathematical analysis of financial results. But the more I read about and studied financial analysis with respect to investing the sense of certainty began to fade as things became ever more bewildering. It’s not hard to find methodologies that employ 2nd and 3rd order derivatives of certain aspects of financial reports. It was not that rigorous mathematical analysis was difficult to come by, it was rather that it was difficult to understand how certain techniques provided useful information and what to make of it if one ratio appeared to contradict a different derivative. I could follow the math easily enough, but I struggled with the relative importance and value of the different indicators.

Then I came across Saul’s relatively new board. I think there were fewer than 1,000 posts when I first started following this board. Mind you, this was long before SaaS was a thing. At the time, Saul relied heavily on the simple old P/E ratio in his analysis.

Two things initially attracted me to Saul’s approach and made me an early adherent to his approach. The first things was his documented history of spectacular success. I suppose I might have worried that it was a fabrication, but I never seriously entertained doubts regarding his trustworthiness and candor. I mean why go to the trouble of creating such an elaborate hoax in order to establish a fee free information resource. Had he been selling a service and just had a board as a means of attracting potential clients an elaborate hoax might make some sense. But he was just giving it away and encouraging other to do the same. So I took it at face value. Establishing trust was a vitally important first step. The next thing that attracted me to his methodology was it’s apparent simplicity. Saul had (still has) an uncanny ability to ignore the unimportant. That sounds obvious and trivial. It’s neither.

I think Saul would agree that with the SaaS companies we entertain as investment opportunities, there are more meaningful variables than companies of the “old” economy. We never looked at ARR before because it didn’t exist. But given the somewhat more complex financial picture, Saul most often looks at the simple reports and 1st order derivatives (i.e., rate of change of a given variable). I may be wrong, but I don’t recall Saul presenting a complex multi-variate formula as a key financial analysis tool. He just doesn’t go there. To the best of my recollection, the most complex indicator Saul ever proposed was the 1YPEG (remember that long time members?). And he’s repeatedly demonstrated that it’s unnecessary to go there in order to have success as an investor. Most certainly, Saul is capable of performing analysis of greater depth and he’s done so on a few occasions in order to reveal “hidden growth” or just the opposite, but it’s not a routine part of his analytical methodology.

So as we round the corner into a new year I just want to put forth a reminder for us long time followers and maybe a notification for the more recent followers that Saul’s method does not rely on a lot of sophisticated mathematical techniques. It’s all based on simple arithmetic utilizing the company numbers as reported. If there’s any secret sauce, IMO it would be that Saul always seeks to understand why unexpected results occur. The primary reason Saul always uses adjusted reports is to eliminate the influence of financial outliers that are the result of one-off events that mask business operations. But given that, if there’s a sudden departure from an established pattern, Saul always seeks to understand what happened and why. He’s never satisfied with just recognizing the disruption, he needs to know the reason.

Complex numerical analysis might be an interesting intellectual exercise, but for the most part it’s just not necessary.

KISS - - - and happy holidays. And deep thanks to the many contributors here who have literally helped to enrich my life.

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The problem is not mathematics, simple or complex. The problem is GIGO - Garbage in → Garbage out! Let me illustrate with a perfectly good calculation, discounted cash flow (DCF). You can use the Excel XIRR function.

Let’s go back to the beginning of Security Analysis, circa 1934. Back then bonds were investments and stocks were speculation. Bonds have accurate numbers, time to maturity, interest rate, date when interest is paid. Plug them in you get a darn good result. Of course there is uncertainty, the company could run into problems and not pay back the capital. But chances are that the DFC is accurate. Now try to use the same calculation on stocks. Most of the inputs are, at best, educated guesses, interest rate, future revenue, etc. It’s mostly garbage and the output is garbage. Even if only one input is wrong, specially the interest rate, the output is garbage.

Happy Holidays and a Prosperous 2020!

Denny Schlesinger

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The problem is GIGO - Garbage in → Garbage out! Let me illustrate with a perfectly good calculation, discounted cash flow (DCF). You can use the Excel XIRR function. Let’s go back to the beginning of Security Analysis, circa 1934. Back then bonds were investments and stocks were speculation. Bonds have accurate numbers, time to maturity, interest rate, date when interest is paid. Plug them in you get a darn good result. Of course there is uncertainty, the company could run into problems and not pay back the capital. But chances are that the DFC is accurate. Now try to use the same calculation on stocks. Most of the inputs are, at best, educated guesses, interest rate, future revenue, etc. It’s mostly garbage and the output is garbage. Even if only one input is wrong, specially the interest rate, the output is garbage.

Hi Denny,
You unfortunately forgot the punch line!!! Money in invested in the risky stocks with all that garbage in, since the beginning of 1934, is now worth six thousand three hundred and eighty times what you invested (figuring the S&P total return). That means each \$1 became \$6,380, probably tens if not hundreds of times as much as the bonds where you had all that good data.
Saul

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Hi Denny,
You unfortunately forgot the punch line!!!

Originally published in 1924, Common Stocks as Long-Term Investments was the first book to promote the idea that stocks surpass bonds in long-term investments. The work, which was highly reviewed and praised, was a key component in the stock market boom of the 1920s. Author and banker Edgar Lawrence Smith was startled to discover, when writing a pamphlet touting the advantages of bonds, that stocks were a better form of long-term investment, yielding a higher return. The New York Times claimed that the book “laid down a principle which so reverses the accepted estimate of the relative investment value of bonds and common stocks as to have aroused the keen interest of Wall Street and investment bankers in general.” This book will fascinate not only history buffs, but those interested in taking out stocks of their own. EDGAR LAWRENCE SMITH (1882-1971) was an American economist and financier, best known for his book Common Stocks as Long-Term Investments. After attending Harvard University, Smith worked in the finance industry until he became an adviser to the Low, Dixon & Co. brokerage firm. It was there he discovered, while trying to advertise the advantages of bonds in long-term investment, that stocks were actually a superior alternative, thus prompting his book. Its success enabled him to launch a mutual fund firm, Investment Managers Company, which he lost in the stock market crash of 1929.

https://www.amazon.com/Common-Stocks-Long-Term-Investments/d…

Benjamin Graham accused Smith of causing the 1929 stock market bubble!

https://discussion.fool.com/yep-you39re-right-captain-investors-…

Denny Schlesinger

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Small observation on mathematics.IMHO when you study quarterly tables showing changes in rates of growth you are working with 2nd order changes. These aren’t 2nd derivatives per se but that is inferred in the interpretation. Further by making extrapolations as to future behavior inferences are drawn concerning future changes in the 2nd order effects…in fact nonlinear inferences in some cases. Just go back and read the debates in the responsive posts. So the analysis is quite complex but the presentation is so good that it doesn’t matter.

GIGO will render any model worse than useless. The challenge is not always to find the best model but to select the most pertinent information to examine.Always. And what is pertinent to one investment style may not be so for some other approach. I think Saul’s methodology is perfect for the type of stocks he selects to consider.

Another observation. The S&P has done well since 1934 but many stocks have come and gone since then.

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Another observation. The S&P has done well since 1934 but many stocks have come and gone since then.

The “S” curve shows that not only do technologies and businesses have limited lifespans but that there is a middle period in that lifespan that is most fruitful for investors. The S&P does not represent the whole lifespan of the businesses in the index, only the middle period while they are the most representative of business in general.

There is this notion that we should look for permanence, there is no such thing. That’s the whole point of creative destruction.

Denny Schlesinger

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In observations of the people that exist in or have passed through my life, the most dramatic accumulation of wealth by the “guy next door” occurred via the pursuit of a business venture in the private sector and not in stock/bond market ventures.

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Since the beginning of 1934, is now worth six thousand
three hundred and eighty times what you invested (figuring
the S&P total return). That means each \$1 became \$6,380…

You are quite right that stocks killed bonds over long
periods of time and it is the way to invest over a life,
especially from today with equity yields comparatively
attractive compared to bond yields.

But your calculation is profoundly misleading despite it
almost being the de facto standard to leave out tax and
inflation. We do operate in the real world though, would
have operated, and will operate, so it makes sense to
include it.

To confirm your ~6 thousand times your money over the
last years, we’ll use 11% as:

(1 + .11)^85 = 7 thousand times your money

But correcting for inflation and tax, we’ll assume
just a 30% total tax rate, and just 3% inflation, but
which underestimate the true effect:

(1 + .11*.7 - 0.03)^85 = 50 times your money

Just a simple completion makes changes 7 thousand
times your money right down to 50 times your money - quite
a difference. That is not to mention that 85 years is
in practice 3 about 3 generations worth of saving. With
a good career of starting early for building the bulk
of one’s savings at say 40 years old and taking it from
there for another 50 years, you get (1 + .11*.7 - 0.03)^50 =
just ten times your starting spending capacity. Not bad, but
different to the usual quotes of wealth multiplying by
thousands.

Earnings yields are however low right now, compared to
almost any point in the the past 135 years, and the
normalised earnings yields isn’t a bad proxy for what
you would expect to get over the long-term. Investing
in a situation where stock prices are perpetually low
would make you far richer than if they were perpetually
high (both starting and ending values) as the dividend
yield received along the way would be higher. As
multiples are high now (even if justified with continued
low interest rates, and further justified by remaining
high for longer than people expect) then the total
real returns will anyway be be quite lower than they
were in the past.

And this is coming from an optimist, as your message is
nevertheless quite right - staying in for the long haul is
a very, very worthwhile pursuit.

• Manlobbi
15 Likes

Since the beginning of 1934, an investment in stocks is now worth six thousand
three hundred and eighty times what you invested (figuring
the S&P total return). That means each \$1 became \$6,380…

You are quite right that stocks killed bonds over long
periods of time and it is the way to invest over a life,
especially from today with equity yields comparatively
attractive compared to bond yields.

But your calculation is profoundly misleading despite it
almost being the de facto standard to leave out tax and
inflation.

But correcting for inflation and tax, we’ll assume
just a 30% total tax rate, and just 3% inflation, but
which underestimate the true effect: (1 + .11*.7 - 0.03)^85 = 50 times your money

This really is OT but I have to respond because I feel that what you are saying is profoundly misleading.

First, on the 3% inflation, I was talking about how many dollars a dollar invested in 1934 would become today. It was contrasted to the much smaller amount that the same investment in bonds would be worth. By definition, it has nothing to do with inflation, as inflation reduces buying power but has nothing to do with the number of dollars. (However you reduced the number of dollars received in your calculation by per year, which is totally incorrect). Besides, inflation hits dollars equally whether they were made in stocks or bonds.

Second, you reduced your increase in S&P stock price by 30% COMPOUNDED each year, as if you had sold out of your entire position in the S&P stocks at the end of each year, and paid taxes on the gain. This is profoundly dead wrong! Why in the world would anyone do that? The idea was to hypothetically hold the S&P for 85 years, not to sell out and pay taxes each year! Over those years the average LONG TERM capital gains tax has averaged between 20% and 25% (it’s now a maximum of 20%), but that is just once, when you sell the investment, not every year compounded.

The taxed result would thus be much closer to my \$6,380 than to your \$50, but I wasn’t talking about the taxed result anyway.

Saul

PS - LET’S DROP THIS NOW AS WE’VE EACH HAD OUR SAY. If you feel you just have to respond, please do it off board.

Saul

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