WEBVTT

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If your stock portfolio loses 50 percent on Tuesday

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and then gains 50 percent on Wednesday, how much

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money did you lose? Most people would say zero,

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right? Exactly. If your brain immediately answered,

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oh, I broke even, well, your brain is lying to

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you. And today we're going to show you exactly

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how. Yeah, it's a massive blind spot for human

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intuition. Because, you know, you are constantly

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bombarded with numbers and headlines, corporate

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reports, political polls, and they feel concrete.

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They feel objective. Right. Numbers feel like

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facts. But the way data is mathematically framed,

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like before it ever reaches your screen, can

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completely alter your perception of reality.

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So our mission today is to act as your shortcut.

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We want you to be truly well informed about the

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hidden mechanics of data presentation. Which

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is so crucial right now. It really is. We're

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doing a deep dive into some fascinating source

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material on the underlying math of relative change.

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We're exploring why absolute numbers deceive

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you. the specific vocabulary used to manipulate

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percentages, and the mathematical workarounds

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professionals use to find the actual truth. It's

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a profound shift in perspective, really. Once

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you learn to read the mechanical structure of

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the math rather than just, you know, the surface

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level numbers, you start seeing these subtle

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framing choices everywhere. Everywhere. And the

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illusion usually starts simply because our human

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brains naturally default to absolute numbers.

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We just prefer raw counts. OK, let's unpack this.

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Because To really understand how we get tricked,

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we need a functional way to think about it. I

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agree. Visuals help a lot here. Right. So think

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of an absolute number like saying a car costs

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$50 ,000 as a photograph of a mountain. It shows

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you the object, sure. But relative change is

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the scale on a map of that same mountain. Oh,

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that's a great way to frame it. Without the scale,

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you have absolutely no idea if you're looking

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at a tiny hill or Mount Everest. I mean, the

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photograph gives you the what, but the scale

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gives you the context. Exactly. And the problem

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with relying solely on the photograph, you know,

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the absolute change, is that it leaves you highly

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susceptible to the unit illusion. The unit illusion.

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Yeah. Absolute change is just taking a new value

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and subtracting the reference value. But the

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unit you choose to measure that change in completely

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dictates how your brain reacts. Right, because

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units feel arbitrary sometimes. They do. If you

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measure the difference between a two meter piece

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of wood and a one meter piece of wood, the absolute

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difference is just one. A difference of one meter.

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It sounds completely manageable. But if we measure

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that exact same physical distance in centimeters,

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you are now subtracting 100 centimeters from

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200 centimeters. Oh, wow. Right. The absolute

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difference is 100. Mechanically, the physical

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reality in space is identical. But the number

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100 triggers a significantly larger cognitive

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reaction than the number 1. Exactly. It feels

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like a bigger gap simply because of the unit

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chosen. And relative change neutralizes that

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illusion by mathematically stripping away the

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units entirely. You take that actual change and

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divide it by your reference value. Precisely.

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It levels the playing field. So a change of one

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meter divided by the starting one meter is one.

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And a change of 100 centimeters divided by the

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starting 100 centimeters is also one. Right.

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It yields a 100 % increase either way. You get

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a pure unit -less number that represents the

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actual proportion of the shift. If we connect

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this to the bigger picture, relative change is

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the great equalizer. It judges the underlying

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importance of a change rather than just the raw

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amount. Give me a real -world example of that.

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Well, if an item costs $50 and the price goes

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up by an absolute value of $100 to a total of

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$150, that item just tripled in cost. Yeah, the

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relative change is massive. That hurts your wallet.

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But if you are buying a $10 ,000 piece of industrial

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equipment, and the price goes up by that same

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absolute $100... The relative change is miniscule.

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Exactly. The absolute $100 bill is physically

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identical, but the mathematical importance of

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that bill changes depending on the reference

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value. I follow the logic, but I'm going to push

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back slightly here. Is absolute change strictly

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a trap, or is there a functional utility to it?

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Oh, there's definitely utility. Because if I

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think about my own paycheck... You know, if my

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boss tells me I'm getting $100 bonus this week,

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I care deeply about that absolute $100. Of course

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you do. That is real utility. I can buy groceries

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with that. Even if I calculate the relative change

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to my total annual salary and realize it's a

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fraction of a percent, the relative math doesn't

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diminish the absolute utility of the cash in

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my pocket. And that's a vital distinction, really.

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Absolute numbers are completely necessary when

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the real world utility of the unit matters to

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you directly. A dollar has a fixed purchasing

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power regardless of your total salary. Right.

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The mathematical trap only springs when you are

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attempting to compare two different scenarios

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or, and this is key, when a narrator is attempting

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to frame a change as inherently massive or insignificant.

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Ah, so when someone is trying to sell you a narrative.

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Yes, that is when relying on the absolute number

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leaves your perception highly vulnerable to manipulation.

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And if relative change is how we judge the importance

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of a comparison, percentages are the vocabulary

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we use to communicate it. But that vocabulary

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is incredibly fragile, isn't it? Fragile is the

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perfect word for it. It breaks so easily. Take

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the example of two vehicles from our source material.

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Let's say car M cost $50 ,000 and car L cost

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$40 ,000. Depending entirely on which car you

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anchor as your reference value, the grammatical

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phrasing of the comparison dictates a completely

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different mathematical reality. Walk me through

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that. Well, if car L is the reference, the absolute

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difference is $10 ,000. You divide 10 ,000 by

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car L's price of 40 ,000 and you get 0 .25. So

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you would say car M is 25 % more than car L.

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Right. Or if you express it as a direct ratio

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rather than a difference, car M is 125 % of the

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cost of car L. Oh, I see. The specific words

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more than versus of signal whether you are citing

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the relative difference or the total ratio. Exactly.

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The grammar literally dictates the math. But

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if you flip the anchor, the math changes completely.

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Like, if we start with CAR -M at $50 ,000 as

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the reference, the difference is now negative

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$10 ,000. Which changes everything. Right. Divide

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that by $50 ,000, and you get negative 0 .20.

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So suddenly, CAR -L is 20 % less than CAR -M,

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or 80 % of what CAR -M costs. Yes. The physical

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prices of the car is never moved. Yet you can

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truthfully report the gap as either 25 % or 20%,

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purely based on which bumper you decided to point

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at first. It really requires hypervigilance from

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the listener. I mean, if you aren't paying attention

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to the specific noun acting as the baseline,

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your brain will misinterpret the scale of the

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math. Here's where it gets really interesting,

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though. The ultimate manipulation of this vocabulary

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is the percentages of percentages trap. Oh, this

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one drives mathematicians crazy. We see this

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constantly with interest rates. Let's say a bank

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raises the interest rate on a mortgage from 3

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% to 4%. The bank sends out a notice saying,

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we have implemented a 1 % increase in your rate.

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And that phrasing is fundamentally incorrect.

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Completely wrong. Yeah. It is a conflation of

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absolute and relative terms. The absolute change

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between 3 % and 4 % is one percentage point.

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Right. A point, not a percent. Exactly. But to

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find the relative change, you must take that

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one point absolute difference and divide it by

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the original reference value of 3%. Which means

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the actual relative change to your interest rate

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is 33 and one -third percent. Yes. Your interest

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burden didn't go up by one percent, it went up

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by a third. It's difficult not to assume that

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marketers and financial institutions intentionally

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exploit the public's misunderstanding of a percentage

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point versus a percent increase. It's a very

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convenient confusion for them. Calling a massive

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33 % spike in borrowing costs a 1 % increase.

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Just brilliantly downplays the bad news. When

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the underlying variable you are measuring is

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already formatted as a percentage, the linguistic

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waters become very muddy. Muddy and expensive.

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Very true. It requires strict discipline to separate

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absolute percentage points from relative percentage

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change. Otherwise, the magnitude of the shift

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is completely obscured. So the language of relative

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change is easily weaponized? But the actual formula

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for relative change has its own mechanical failures,

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doesn't it? There are situations where taking

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the new value, subtracting the old value, and

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dividing by the old value just mathematically

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breaks down. It does. The most obvious failure

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is when your reference value is zero. You cannot

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divide by zero. The function is undefined. Just

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a classic math error. Right. But the far more

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counterintuitive failure occurs when your reference

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value is negative. The denominator sign completely

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corrupts the logic of the result. Let's use temperature

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to visualize this. Imagine the weather outside

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goes from negative 10 degrees to negative 6 degrees.

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The temperature got warmer. it increased by a

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positive 4 degrees. But if we plug those numbers

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into the standard relative change formula, we

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take the actual change, which is positive 4,

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and we divide it by the reference value, which

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is negative 10. OK, so positive 4 divided by

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negative 10. Which yields negative 0 .4. So the

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formula outputs a relative change of negative

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40%. It's telling me the temperature decreased

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by 40%, even though I know definitively that

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the absolute temperature increased. Yes. The

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math is outputting a direct contradiction to

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physical reality. That is wild. The classic formula

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simply doesn't know how to handle the crossing

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of the negative threshold. It yields a negative

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relative change for a positive absolute increase.

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So how do people fix that? Well... To bypass

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this mechanical flaw, professionals use a special

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variation called percent error. It's heavily

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utilized in scientific fields when comparing

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an experimental value, like a measurement taken

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in a lab, to a theoretical or widely accepted

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value. I like to visualize this using a dartboard.

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Treat the theoretical accepted value like the

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bullseye. The standard formula for percent error

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puts absolute value brackets around the top part

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of the fraction. Right. It forces the numerator

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to be positive. So if you throw a dart, that

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standard formula just measures the pure magnitude

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of your miss. It tells you that you missed the

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bullseye by two inches, but it strips away the

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context of where the dart landed. What's fascinating

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here is that scientists will frequently and intentionally

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remove those absolute value brackets. Why? Because

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the negative or positive sign of the error holds

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vital physical context. The directionality matters

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just as much as the magnitude. Right, because

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if you take the brackets away, the math tells

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you whether you overthrew or underthrew the dart.

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And there's a brilliant example in the sources

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regarding the speed of light. Oh yes, that's

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a perfect illustration. If a physicist measures

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the speed of light in a vacuum, and they calculate

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a negative percent error without the brackets,

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it simply means their experimental velocity was

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slower than the accepted speed of light. The

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dart landed short. They just need to recalibrate

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their lasers. But if they calculate a positive

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percent error without those brackets... Then

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the dart went straight through the backboard.

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A positive percent error means they recorded

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a speed faster than light. They just mathematically

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violated the theory of relativity. Which is huge.

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That isn't a measurement error you just file

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away in a drawer. That is data that rewrites

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the laws of physics. The presence or absence

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of that single negative sign completely alters

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the interpretation of the data. And this raises

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an important question about the rigidity of these

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formulas. In percent error, you must adhere to

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a strict operational order. It has to be experimental

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value minus theoretical value. The order matters.

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Yes, the values do not commute. If you flip them,

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the sign flips, and a scientist might mistakenly

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believe they broke relativity when in reality

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they simply subtracted in the wrong direction.

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Which introduces a massive mechanical headache

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for systems that rely on automated math. Oh,

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a nightmare for programmers. Right. If the basic

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formula explodes when it hits zero and outputs

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contradictions on negative numbers, how do software

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programmers or economists stabilize their models?

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They can't have a global financial model crash

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just because a localized metric dropped below

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zero. They stabilize it by fundamentally reinventing

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the denominator. You see, the core mechanical

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flaw with the classic relative change formula

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is that it lacks symmetry. Standard division

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inherently anchors to the past. The starting

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reference value. Let's walk through why that

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asymmetry happens. If a stock goes from $100

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up to 125, the absolute change is $25. Yeah.

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We divide that by the starting anchor of 100,

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which gives us a 25 % increase. But if that same

00:12:59.899 --> 00:13:04.080
stock drops from 125 back down to 100, the absolute

00:13:04.080 --> 00:13:07.360
change is negative $25. OK, sure. However, your

00:13:07.360 --> 00:13:10.049
anchor has now shifted. You are now dividing

00:13:10.049 --> 00:13:14.669
that negative 25 by 125, which yields a 20 %

00:13:14.669 --> 00:13:17.070
decrease. The journey is physically identical

00:13:17.070 --> 00:13:19.730
in distance. But because the denominator changed,

00:13:19.909 --> 00:13:22.610
the relative math is totally skewed. Going up

00:13:22.610 --> 00:13:26.210
is 25%, coming down is 20%. It feels mathematically

00:13:26.210 --> 00:13:29.269
unbalanced. It is. And in data science, that

00:13:29.269 --> 00:13:31.769
lack of balance creates compounding errors over

00:13:31.769 --> 00:13:34.580
time. A relative change from state A to state

00:13:34.580 --> 00:13:38.100
B inherently must have the exact same magnitude

00:13:38.100 --> 00:13:41.000
as moving from state B back to state A. So how

00:13:41.000 --> 00:13:44.179
do they force this symmetry? Experts use indicators

00:13:44.179 --> 00:13:46.840
of relative change. Instead of dividing by the

00:13:46.840 --> 00:13:49.179
starting reference value, they replace the denominator

00:13:49.179 --> 00:13:52.019
with a mean, an average of the two numbers. Wait,

00:13:52.019 --> 00:13:53.620
so if I use the average of the two numbers as

00:13:53.620 --> 00:13:56.440
the denominator, the math stabilizes. Let's test

00:13:56.440 --> 00:13:59.039
it on the stock. Okay, the mean of 100 to 125

00:13:59.039 --> 00:14:03.870
is 112 .5. So if the stock goes up, we divide

00:14:03.870 --> 00:14:08.409
the positive $25 change by 1 .12 .5, which is

00:14:08.409 --> 00:14:11.750
about 22 .2%. And if the stock goes down, you

00:14:11.750 --> 00:14:14.590
divide the negative $25 change by that exact

00:14:14.590 --> 00:14:19.190
same mean of 1 .12 .5, yielding negative 22 .2%.

00:14:19.190 --> 00:14:21.610
The symmetry is perfectly restored. Whether you're

00:14:21.610 --> 00:14:24.149
moving forward or backward, the denominator acts

00:14:24.149 --> 00:14:26.769
as a fixed anchor midway between the two states.

00:14:27.100 --> 00:14:30.080
Exactly. But mathematicians don't just use a

00:14:30.080 --> 00:14:33.080
simple average. They tailor the type of mean

00:14:33.080 --> 00:14:35.580
to the specific vulnerabilities of their field.

00:14:36.059 --> 00:14:38.500
Like what? For instance, programmers checking

00:14:38.500 --> 00:14:40.940
floating point values in computer code are heavily

00:14:40.940 --> 00:14:44.299
advised to use maximum mean change. Floating

00:14:44.299 --> 00:14:47.139
point values are essentially decimal calculations

00:14:47.139 --> 00:14:49.740
in software, right? Why do they specifically

00:14:49.740 --> 00:14:52.889
need the maximum mean? Because computers struggle

00:14:52.889 --> 00:14:56.210
with dividing by incredibly tiny numbers. If

00:14:56.210 --> 00:14:58.629
a programmer uses a standard average and the

00:14:58.629 --> 00:15:01.330
numbers are close to zero, the resulting fraction

00:15:01.330 --> 00:15:03.929
could become massively inflated. Which causes

00:15:03.929 --> 00:15:07.110
a crash. Right, a floating point overflow. By

00:15:07.110 --> 00:15:09.529
forcing the denominator to be the maximum, the

00:15:09.529 --> 00:15:11.490
larger of the two numbers being compared, they

00:15:11.490 --> 00:15:14.250
guarantee the denominator is as robust as possible,

00:15:14.769 --> 00:15:16.669
mathematically minimizing the resulting fraction

00:15:16.669 --> 00:15:18.950
and keeping the software stable. That is incredibly

00:15:18.950 --> 00:15:21.370
clever. They are choosing a mathematical flavor

00:15:21.370 --> 00:15:23.509
that actively defends against the hardware's

00:15:23.509 --> 00:15:25.950
weakness. And economists do the exact opposite

00:15:25.950 --> 00:15:29.850
right. They use minimum mean change. Yes. Economists

00:15:29.850 --> 00:15:32.049
modeling massive financial systems will often

00:15:32.049 --> 00:15:34.690
use the smaller of the two numbers as their denominator.

00:15:35.450 --> 00:15:37.509
Dividing by the minimum value yields the largest

00:15:37.509 --> 00:15:40.190
possible relative change. So it exaggerates the

00:15:40.190 --> 00:15:43.230
shift. In econometrics, this acts as a built

00:15:43.230 --> 00:15:46.409
-in stress test. It forces the economic model

00:15:46.409 --> 00:15:49.090
to react to the most volatile possible interpretation

00:15:49.090 --> 00:15:51.590
of the data, ensuring the system can survive

00:15:51.590 --> 00:15:54.990
extreme variance. It's fascinating how the specific

00:15:54.990 --> 00:15:57.529
denominator is chosen not just for accuracy but

00:15:57.529 --> 00:16:00.330
for survival. But, you know, averaging the denominator

00:16:00.330 --> 00:16:02.529
is still essentially just patching a broken system.

00:16:03.029 --> 00:16:05.950
If we want a mathematical framework that is fundamentally

00:16:05.950 --> 00:16:08.809
unbroken from the ground up, we have to abandon

00:16:08.809 --> 00:16:11.149
standard percentages entirely. We have to change

00:16:11.149 --> 00:16:13.779
the scale. Which brings us to logarithmic change.

00:16:14.139 --> 00:16:16.700
It is arguably the most elegant solution in mathematics

00:16:16.700 --> 00:16:19.100
for tracking relative proportion over time. So

00:16:19.100 --> 00:16:20.580
what does this all mean? Let's break down the

00:16:20.580 --> 00:16:23.299
mechanics. Logarithmic change uses the natural

00:16:23.299 --> 00:16:26.279
logarithm of the ratio of the two numbers. Scientists

00:16:26.279 --> 00:16:29.139
scale this result by 100 to create units called

00:16:29.139 --> 00:16:32.210
log points, or centinovers. The brilliance of

00:16:32.210 --> 00:16:34.669
log points is that for very small fluctuations,

00:16:35.129 --> 00:16:37.830
they are virtually indistinguishable from standard

00:16:37.830 --> 00:16:41.669
percentages. A 1 % increase in a standard formula

00:16:41.669 --> 00:16:46.669
translates to roughly 0 .995 centintopers. So

00:16:46.669 --> 00:16:49.309
to the layperson, the day -to -day numbers look

00:16:49.309 --> 00:16:52.629
identical. Exactly. But log points possess a

00:16:52.629 --> 00:16:55.070
mathematical superpower that standard percentages

00:16:55.070 --> 00:16:58.639
lack, true additivity. And to understand why

00:16:58.639 --> 00:17:01.379
additivity matters, we have to resolve the trap

00:17:01.379 --> 00:17:03.320
I mentioned at the very beginning of this deep

00:17:03.320 --> 00:17:07.740
dive, the 50 % trap. Ah, yes. Standard percentages

00:17:07.740 --> 00:17:10.299
are inherently multiplicative, but they masquerade

00:17:10.299 --> 00:17:12.700
as additive. This is why the human brain gets

00:17:12.700 --> 00:17:15.140
wiped out by volatility. Let's run the math on

00:17:15.140 --> 00:17:18.140
the casual investor. You put $100 into a stock,

00:17:18.279 --> 00:17:21.839
it goes up 50%. You now have $150. Pretty straightforward.

00:17:22.140 --> 00:17:24.440
Then the next day, the market corrects and your

00:17:24.440 --> 00:17:27.279
stock drops 50%. Your brain naturally adds plus

00:17:27.279 --> 00:17:30.119
50 and minus 50 and assumes you're back at zero.

00:17:30.299 --> 00:17:32.180
You assume you still have your original $100.

00:17:32.759 --> 00:17:37.839
But a 50 % drop on $150 is $75. You are left

00:17:37.839 --> 00:17:41.460
with $75. You just lost a quarter of your entire

00:17:41.460 --> 00:17:43.720
portfolio, even though the headline percentages

00:17:43.720 --> 00:17:45.900
were equal and opposite. Standard percentages

00:17:45.900 --> 00:17:48.440
simply cannot be added together over time. A

00:17:48.440 --> 00:17:51.759
50 % loss actually requires a 100 % gain just

00:17:51.759 --> 00:17:55.319
to break even. But log points mechanically translate

00:17:55.480 --> 00:17:58.539
multiplicative relationships like scaling a portfolio

00:17:58.539 --> 00:18:01.759
up and down onto a genuinely additive scale,

00:18:02.680 --> 00:18:05.200
they calculate the continuous area of change.

00:18:05.319 --> 00:18:08.279
Which means if we map that exact same stock market

00:18:08.279 --> 00:18:10.920
journey using logarithmic change? If your stock

00:18:10.920 --> 00:18:13.779
gains 50 cent in tulpers and then loses 50 cent

00:18:13.779 --> 00:18:16.049
in tulpers, Well, you can literally just sum

00:18:16.049 --> 00:18:19.069
them up. Plus 50 minus 50 equals zero. You are

00:18:19.069 --> 00:18:21.869
left with exactly $100. Log points allow you

00:18:21.869 --> 00:18:24.250
to perfectly sum up a series of volatile changes

00:18:24.250 --> 00:18:26.809
over time without the math wildly skewing as

00:18:26.809 --> 00:18:28.730
you move up and down the scale. It completely

00:18:28.730 --> 00:18:31.450
neutralizes the 50 % trap. It's so clean. It

00:18:31.450 --> 00:18:35.279
really is. Log change is the unique two variable

00:18:35.279 --> 00:18:37.920
function that is both perfectly additive and

00:18:37.920 --> 00:18:40.960
matches relative change linearly. It removes

00:18:40.960 --> 00:18:43.880
the illusion of volatility and provides a stable

00:18:43.880 --> 00:18:46.980
baseline for complex systems. So you now possess

00:18:46.980 --> 00:18:49.440
the ultimate decoder ring for the data you encounter

00:18:49.440 --> 00:18:52.259
every day. You understand the mechanics of the

00:18:52.259 --> 00:18:55.259
unit illusion and why 100 centimeters feels scarier

00:18:55.259 --> 00:18:57.420
than one meter. And you know how to parse the

00:18:57.420 --> 00:19:00.180
vocabulary of deception, separating absolute

00:19:00.180 --> 00:19:02.700
percentage points from relative percent increases.

00:19:02.940 --> 00:19:05.440
You've seen how mean denominators force symmetry

00:19:05.440 --> 00:19:07.839
in computer models and how the additivity of

00:19:07.839 --> 00:19:10.259
log points saves you from the stock market's

00:19:10.259 --> 00:19:12.839
50 % trap. And this raises an important question

00:19:12.839 --> 00:19:15.279
for you to take forward. The next time you see

00:19:15.279 --> 00:19:17.500
a news headline declaring a massive percentage

00:19:17.500 --> 00:19:20.240
drop in a market or a huge swing in a political

00:19:20.240 --> 00:19:22.400
poll stop and check the math. Always check the

00:19:22.400 --> 00:19:25.079
math. What was the reference value? Is the narrator

00:19:25.079 --> 00:19:27.559
using a specific unit or a shifted denominator

00:19:27.559 --> 00:19:29.960
to artificially inflate the scale of the change?

00:19:30.640 --> 00:19:33.279
Look past the math they want you to see and calculate

00:19:33.279 --> 00:19:35.579
the math that actually matters. Remember the

00:19:35.579 --> 00:19:37.359
mountain. Don't just stare at the photograph

00:19:37.359 --> 00:19:40.240
and let the raw numbers induce panic. Find the

00:19:40.240 --> 00:19:42.160
scale on the map. Find your reference value.

00:19:42.670 --> 00:19:44.890
Thank you for joining us on this custom Taylor

00:19:44.890 --> 00:19:47.410
deep dive. Keep questioning the numbers around

00:19:47.410 --> 00:19:48.490
you and we'll catch you next time.
