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The Law of Value and Demand: Not Your Grandfather’s Economics

To reject one paradigm without simultaneously substituting another
is to reject science itself.
Thomas S. Kuhn

No rejection of science here. But we can dismiss an ineffective paradigm.

Paul Samuelson wrote that the law of supply and demand, the root paradigm of economics, meant that “the equilibrium price, i.e., the only price that can last…must be at this intersection point of supply and demand curves.” That model works for commodities such as gold, silver, or iron.

But what about jets and jet engines? They use iron. You’ll only gain deep insight into these markets by substituting economics with Hypernomics.

Its fundamental principle, The Law of Value and Demand, states that:

  1. Features define Value,
  2. Value determines Price,
  3. Price limits Quantity Sold, and
  4. Quantity Sold is a Feature.

You can study this new field in my upcoming book with Wiley, entitled Hypernomics: Using Hidden Dimensions to Solve Unseen Problems, in January 2024. In the meantime, have a look at my paper called “8D Cost Trades with Entanglement,” published in the April 2023 edition of the Journal of Cost Analysis and Parametrics,” to see how markets work.

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My Book Is Coming: What’s In It For You

It’s not what you look at that matters; it’s what you see
Henry David Thoreau

Many of you asked about it; now I can tell you: I’ve signed a deal with Wiley to publish my book, Using Hidden Dimensions to Solve Unseen Problems: Hypernomics and Markets.

It studies market phenomena we haven’t been able to examine previously, mainly because no one invented the techniques to do so.

Until now.

The book’s theme of finding the location and direction of market competitors mirrors the development of radar and has a like effect.
In the years between WWI and WWII, many countries sought to discover opposing planes’ positions and headings. Several had acoustic detectors like that in (A) but found they could only provide broad direction of incoming aircraft. It took the development of the Chain Home Radar (B) to reveal the value of having a much finer granularity of approaching enemy warplanes.

Modern economics gives us simple 2D charts such as (C), showing the intersection of iron supply and demand curves. But planes use iron, and to characterize them thoroughly, we need the 4D arrangements the book offers, as (D). The book’s readers will gain ways to see more clearly for themselves, improving bottom lines.

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Markets Across Seven Dimensions

One should concentrate on getting interesting mathematics.
Paul Dirac

Let’s examine how markets work together across 7 dimensions.

Far from being some exotic mathematical anomaly, such arrangements occur daily across many markets. Please feel free to offer some feedback.

To make a pencil, given wood, you’ll need graphite.  Making a bike takes a frame and tires.  These markets are bonded—you can’t make a final product without some key pieces.  How do bonded markets such as jets and their engines interact across 7 dimensions?

Let’s look.

In the 7D diagram below (with log scaling in all directions), turbofan engines use Dimensions (Dims) 1-4.  As Specific Fuel Consumption (SFC, Dim 1) goes down and Max Thrust goes up (Dim 2), turbofan prices, reflecting their Value, moves up as well (Dim 3), with Quantities sold (Dim 4) limited by the market’s demand frontier (yellow line on the red, right-hand Demand Plane).  Making a new engine with a specified level of SFC and Max Thrust yields a value of the large green sphere, marked by “T,” at left.

That engine supports a new business aircraft model and accounts for a portion of the plane’s cost, marked by the large green sphere labeled “B.”  Aircraft Value goes up (Dim 3, shared with the engines) with Max MPH (Dim 5) and Cabin Volume (Dim 6), as limited by their Demand Frontier (Dim 7).  Such entanglements exist in all bonded markets.  They must be studied thoroughly to be optimized.

#hypernomics #markets #innovation #economics

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Long Time Coming

It’s not that I’m so smart, it’s just that I stay with problems longer.
Albert Einstein

There’s something deeply affecting about staying with a problem for over 30 years. Once you get some resolution, part of you wonders why it took so long to get answers. A more forgiving part of you thanks Einstein for the inspiration to carry on. One can only be happy when that ah-ha moment finally arrives.

Such is the case with Hypernomics. After first entertaining the idea at 14, somewhere around 49, I saw the first hints of the practical applications of Hypernomics. 18 years later, we have evidence of its practicability in one of the most complicated markets, that of securities.

In Feb 2020, we made our first investments based entirely on Hypernomics. Far from being perfect, tests suggested that given a market downturn, we would suffer losses. Figure A shows we’ve endured setbacks in 2022. But backtesting supported the idea we would lose less than the competition.

In the longer run, in Figure B, the theory has had a chance to shine. Note the Hypernomics fund is doing more than 2X as well as Berkshire Hathaway and over 3X what the other major indices are doing.

#innovation #markets #investments #hypernomics

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Call Off the Panic

“Present fears are less than horrible imaginings.”—William Shakespeare

The FAA recently made clear it will impose more stringent requirements on Urban Air Mobility (UAM) vehicles.  In response, pundits started screaming about the end of that market even before it began.  They think the added costs are insurmountable.

Who told them that?

Yes, there will be significant costs in the added requirements.  But many companies have managed to work themselves through FAA regulations and come out with safe and profitable models.

Profitability, of course, is the key.  To clear development and certification costs, UAM manufacturers need to know if they can make money with their products.  All should note the United Airlines (UA) order from Archer.  UA will spend $5M for five-seat Archers, which are only slightly faster than five-seater Robinson R66s, which sell for $1.1M.  Oh, and the Archer has about a seventh the range of the R66.  The difference is the decibels.  Lower noise widens the market for UAMs, which should have comparable or lower costs than traditional helicopters (due to fewer parts) and higher prices.

Next time someone tells you the sky (or UAM market) is falling, see what they’ve shorted.

#urbanairmobility #UAM #markets #innovation #FAA

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

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The Little Fund That Could – And Did And Does

Yeah. Beethoven was deaf.  Helen Keller was blind.  I think Rocky’s got a good chance.
Adrian, ‘Rocky’

Funny thing about entering a game late.  People think you can’t play just because you haven’t been on the field.

Make no mistake.  We’re a late entrant.  Many might think of us as a world-weary veteran reliever, coming in the bottom of the ninth to get out the last batter.

We see ourselves more as an untested first-round draft pick sitting on the bench.  And we’ve been studying the game – and we think we’ve figured a few things out.  Our fund reflects that.

We founded Hypernomics, Inc. (yes, it’s official, we were formerly MEE Inc.) to offer training, software, and consulting for the field we discovered, which, of course, is Hypernomics.  We still do that, and that’s what’s kept the lights on.

More and more, though, our advisors and we are seeing the potential of this fund.  We’re not open to the public, but we think one or more firms could benefit from licensing our analytics.  Just as we didn’t know about Hypernomics until we discovered it, we don’t know what to do or where to go exactly.

If you have some thoughts, please share them.

#hypernomics, #stockmarkets, #innovation, #stockanalysis

The Value And Demand For Taxpayer Dollars

Don’t Worry, Be Happy – Bobby McFerrin

In May 2020, CA Gov. Gavin Newsom said he wasn’t worried about Tesla leaving the state.  Last month, when Elon Musk announced he was moving Tesla to TX, the Gov. changed his tune.  It seems he felt he helped create the company, citing the tax breaks he gave them.

Hypernomics has seen this argument before.  Breaks in CA usually amount to slight and temporary reductions in the business-crushing tax rates CA has compared to other states.  That’s why companies by the thousands have been leaving CA.  A legislative “solution” to lost tax revenue is to have CA tax requirements follow businesses and individuals once they leave the state.  But that 1) denies some tax monies to other jurisdictions and 2) makes it less likely for new companies to enter CA.

CA has the best weather in the US, but the Tax Foundation ranks it next to last in its business climate.  As hypothesized below, the Value to taxpayers increases with the physical and business environments. Increasing the latter’s Value makes it more appealing to taxpayers – if they are attracted enough to come into the state, they offer more Ways for CA to get needed tax dollars.  At the same time, all mature markets have Demand Frontiers, which deliver the Means by which they must abide.  It’d take lots of work to learn these forces in detail. But avoiding that effort leads to unpleasant surprises.

And worry.

#hypernomics #innovation #taxpayer #taxanalysis #markets #economics

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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

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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