Fantasy vs. Reality: Hypernomics & the End of Illusion

And yet it moves
Galileo

In 1633, the Roman Inquisition convicted Galileo of heresy. His offense? He pointed out that instead of the universe revolving around the Earth (A), Earth circled the Sun (B). For that, he spent the rest of his life under house arrest. In 1992, Pope John Paul II finally acknowledged that the Church had erred in condemning Galileo for saying the Earth revolved around the Sun.

The law of supply and demand tells us that markets have one equilibrium point where those lines intersect (C). Every introductory economics textbook has some version of it, an idea that has existed for over 130 years. And it works for commodities like iron ore.

But that’s where it ends.

It doesn’t work for business aircraft, where many models offer varying combinations of speed and cabin volumes command an equal number of prices, all upheld by variable quantities sold (D).

To understand economics, you need Hypernomics (E). It’s available for presale HERE.

Your competitors may be content waiting 359 years to see the world as it is.

But you shouldn’t be.

Announcing The Hypernomics YouTube Channel

It is the obvious which is so difficult to see most of the time.
Isaac Asimov, I, Robot

Here’s a question with a seemingly obvious answer:  How many stocks are part of the S&P 500?  If you guessed 500, you’d be close, as there are 504 companies listed there today.

You likely know that not all S&P companies have issued the same number of shares, nor do all share price match.  Too obvious?  Not really.

Consider what you were undoubtedly told if you ever took an economics class.  According to Paul Samuelson (Economics, 9th Ed., p. 63), “the equilibrium price, i.e., the only price that can last…must be at the intersection point of supply and demand curves.”  Samuelson would have you believe markets have but one equilibrium point.

But we know that is nonsense:  504 stocks in the S&P 500 form 504 quantity and price pairs.  While they are viable, all, in the language of Hypernomics, enjoy sustainable disequilibrium as their stock prices exceed their costs.

What’s really going on?  It turns out the value of products goes up as producers add features customers like.  At the same time, as prices go up, quantities sold fall.  To see this phenomenon, one must employ Hypernomics.

To find out how this works with as many as 8 dimensions, go to our new Hypernomics YouTube channel here:

https://www.youtube.com/channel/UCYsso5Yf0OFY3k78u5c30LQ

#hypernomics #marketanalysis #prices #demand

Market And Demand Formation

Tesla is here to stay and keep fighting for the electric car revolution.
Elon Musk

How do markets form?  What happens when they do?  Let’s look.

The modern mass-produced electric car market began in 2009.  As Figure A displays, there was a sole entrant then, the Mitsubishi i-MiEV.  By 2012, in Figure B, many more entrants came into play.  Three years later, with Figure C, prices for most models fell, and they attracted more customers.  Producers were able to drop prices because their production lines displayed learning curve effects.  They benefited from lower costs from more efficient workers, standardization, economies of scale, and other factors.

Figure D shows us that by 2018, many new models moved into the market.  Several models (all Teslas, marked with the yellow dots) combined to form the market’s Demand Frontier.  That line is highly correlated (adjusted R2 95.4%, P-value 5.04E-04) and relatively flat, with a slope of -0.36.

In 2019, electric car sales fell about 10% from 2018, despite Tesla’s Model 3 success.  Given the flattish Demand Curve, that suggests buyers would be eager for a high-range vehicle with a price lower than the Model 3.  All competitors priced less than the cheapest Model 3 have less range than it does.

#demand #marketanalysis #marketformation #demandformation #demandplanning #curve

Life’s Easier With Enhanced Vision

The good thing about science is that it’s true whether or not you believe in it – Neil deGrasse Tyson

What would it be like to do astronomy without a telescope, biology sans a microscope, or defend air raids without radar?  We don’t have to live without these visualization aids in the modern world.  We needn’t rely on Stone Age tech in the Age of Information.

But you are very likely working from a like disadvantage in market analysis.  While we proved 4D data science works in fields as varied as beef production, package delivery, and spaceships, up till 2020, we had not taken a run at the stock market.

Then we did.

As shown below, the principles of Hypernomics have been applied successfully for picking securities, as it has for us for the last 26 months, with actual monies and stellar returns.  This fund is yet another story about how we applied the tool profitably.  We believe the fund will be to Hypernomics as books were to Amazon.  Eleven years after we started, we’re looking for partners.

Who wants to join us?

#datascience #hypernomics #innovation #marketanalysis

Details Depict Markets

If you don’t understand the details of your business, you are going to fail – Jeff Bezos

You’ve heard about people getting lost in the details.  What if the opposite is true?

Hypernomics finds that diving into details is the only way to comprehend a market.

Paul Samuelson wrote, “the equilibrium price…the only price that can last, must be at the intersection point of supply and demand curves.” (Economics, 4th Edition, p. 63).  While he won the Nobel Memorial Prize in Economic Sciences, he never worked in aerospace.  If he had, he would have discovered that no solitary “equilibrium price” lives there.

But there is even more to it.  As A reveals, the new aircraft market splits into those for Civil and Military submarkets.  Within the former, there are five sub-submarkets, and all of those have their Demand Curves which combine to form a collective Aggregate Demand Curve, B.

Helicopters perform missions, and each of the eight has its Demand properties, C.  With 75 models, there are hundreds of sustainable prices, all held up by the Value of their models’ features (not shown), as limited by their available funds (Demand).

Dig deep into the data and pay attention to the details.

You’ll find they’ll pay off.

#hypernomics #innovation #marketanalysis #markets

Hypernomics: 3rd in a Series

Perfect is the enemy of good – Voltaire

Suppose you have the task that fell to Cristina (C): Find the Demand Frontier slope for flat-screen TVs. Her sister, Sheila, charged with estimating their value, had it easier, as she found the features and prices for these devices on many sites (see the post three months ago).

In a perfect world, Cristina would have receipts for all models sold, forming a complete database. But no one has that. How can she discover a work-around? She gets an idea.

She finds a nearly perfect world for stocks. In studying the S&P 500, she sees all outstanding shares and prices (A, less Amazon and Google). When she charts their Demand Frontier in blue, she finds their slope is -0.413, a statistically significant result with a P-value of 7.9E-06. She hypothesizes that the Demand Frontier slope of the market’s daily volume will mimic all shares. She plots volume against price and finds its slope of -0.398 (P-Value 8.16E-04), which varies less than 4% from the total.

Excited, she maps the number of ratings for TVs against their prices and finds that they too form a viable Demand Frontier (B) at their limit (P-Value 1.99E-05).

It’s not perfect.

But it’s good.

#hypernomics #innovation #markets #marketanalysis

Simplify Results For Management

“Simple can be harder than complex.” – Steve Jobs

Suppose you analyze a market and find four features that help describe a product’s value or sustainable price. Your power form equation reads Price = constant * feature 1^a * feature 2^b…feature 4^d. How can you simplify each expression so that more people can grasp its meaning?

Helicopters (A-C) come in many designs and sizes. You suspect their useful loads, cruise speeds, and the number of engines support their prices. Analysis confirms that, but the resulting equation is complicated. You want to know how noise, or its lack, contributes to prices too. You find data on cabin and sideline decibel levels, but it’s spotty.

You want to be both simpler and more thorough. What to do?

Poring over the data, you find that pound for useful load pound, helicopters with more main blades fetch more money. That’s because rotor systems with more and smaller blades disturb the air less and create less noise. In D, you can take that expression, Blades^d, and depict the projected Value increase as you add blades. Combining D (and like tables for features a-c) with Demand analysis (see the last post) permits fine-tuning against the market’s needs.

#hypernomics #markets #marketanalysis #innovation #future #futurism

Don’t Leave Money On The Table

“The more you learn, the more you earn” – Warren Buffett

In this true story, we hide the names to protect the players and don’t tell you the venue, either.

In 2014 (A), we ran three market Y value equations (not shown).  All showed that Project X was under-priced.  We find validation of these projections in 2021, as used X versions sell for more than their original $1M price (also not shown).  X sold amply, with 300 units in the market by 2021, and if C’s assumptions were correct, it made a profit, too (D).  Joy in Mudville!  But wait a minute.

Had X’s producers studied Y’s Demand Frontier (B), they might have noticed its negative slope of -1.24.  That means that at the limiting slope, had X’s price been raised to $1.34M, it would have made more revenue, despite the sales drop.  Also, with fewer units, recurring costs fall (C).

The overall effect in D is that selling Project X too cheaply costs Y both revenue and profit.

Hypernomics notes it’s easy to think that if a project makes a profit, it is doing well. But if we learn about all the market forces at work, often we’ll find well isn’t well enough.  Don’t leave money on the table because you didn’t study your market thoroughly.

#hypernomics #innovation #markets #marketanalysis #pricing #analytics

Structure Turns Up

Things don’t turn up in this world until somebody turns them up.
James A. Garfield

In the mid-1900s, there was a race to find the mechanism that passed on genetic instructions.  The double helix structure of DNA that James Watson and Francis Crick discovered was a simpler solution than many biologists thought possible and caught many of them by surprise (A).

Imagine the surprise of many, then, when no one else thought to look, the law of supply and demand is supplanted by the Law of Value and Demand from Hypernomics, which, like DNA, is a long-standing structure which only turns up with lots of hard work and a little imagination.  As shown in B, two market dimensions, Dividends and Earnings Per Share, describe a surface (P-Value 1.55E-06) that drove the Value of the Dow 30 stocks yesterday (stocks above it may be overpriced, those below it, undervalued).  That Value determines Price, a third market dimension, which, in turn, limits the Quantity sold, a fourth market dimension.

The secret, such as it is, is that such structures occur in mathematical, not physical space.  But they turn up in all markets since they began, just as our DNA has always been with us.

#marketDNA #technology #markets #innovation #hypernomics #4D

The Utility Case Vs. Value Analysis

Every time you spend money, you’re casting a vote for the kind of world you want – Anne Lappé

Recently, long-dead Jeremy Bentham took a cross-campus trip. Shunning a wooden cupboard he long occupied in the Wilkins Building at University College London, he moved, greatly aided, to a shiny new booth in UCL’s Student Centre (A). Famously, his penultimate journey was to a UCL council meeting, where they recorded him as “present, but not voting.”

Bentham’s ideas about utility theory still hold sway. Many firms used it to figure cell phone prices (B). Such studies queried participants’ willingness to pay for features, to which researchers assigned utils, a utility measure. Then analysts converted utils to dollars.

Hypernomics notes respondents gave hypothetical answers; they weren’t buying phones, that util value varies widely, and that this method ignored available relevant communication data at their peril.

We display our willingness to pay to connect when we put up cash to make towers (C), walkie-talkies (D), or car phones (E). Value Analysis considers past and present market states to predict the future.

Jeremy may not vote, but we do.

The best utility case holds its inventor.

#value #utility #hypernomics #innovation #marketanalysis