Tag Archive for: hypernomics

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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

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Assumptions vs. Observations: The A380

Assumptions are what we don’t know we are making.
Douglas Adams

Launched in 2000, the Airbus ceased its A380 (A) production in December 2021, as the 251st unit rolled off the line.  That’s lots of big jets. But, their 20-year goal was 1250.  How did it go so wrong?

Assumptions are what we don’t know we are making – Douglas Adams

Launched in 2000, the Airbus ceased its A380 (A) production in December 2021, as the 251st unit rolled off the line.  That’s lots of big jets. But, their 20-year goal was 1250. How did it go so wrong?

Many pundits claim they knew it wouldn’t make its target.  Most appeared when the program floundered late in its lifespan.  What would it take to predict its future in advance?

Projects often use 1) business case analyses and 2) customer polls to “verify it pencils out.”  That works if 1) analysts conceive those cases fairly and 2) buyers convert at or above a target sales figure.

What if we don’t have to rely on those techniques?

To forecast the next 20 years, study the last 20.  As B reveals (summing all model types to base versions), the airliner market had a poorly correlated (Adj R^2 0.458) yet statistically significant (P-Value 0.035) Demand Frontier over that period.  Airbus’s target was nearly ten standard deviations past it.

The A380 took €25B to develop. It didn’t recoup its investment. Take time to model markets in advance. See what a market did to bound what it will do. You may not like the answers, but it beats losing billions.

#A380 #demandfrontier #hypernomics

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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

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

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Abiding By Minimums

One bourbon, one scotch, one beer – George Thorogood

In addition to all the great music he made, George Thorogood knew when he wasn’t drinking alone, he could move it on over to his local tavern and abide by their two-drink minimum.

Bar owners found enforcing that requirement necessary to keep them in business when they had entertainment. Who wants free riders when you can find those who will pay?

Hypernomics knows that minimum requirements are just as crucial as those dealing with maximums. Businesses go under if they don’t make enough sales – we’ll have more on that in the future.

Military forces have similar considerations. The United States Air Force found that spreading their aircraft around gave them more flexibility to fly to distal locations. They typically group aircraft into squadrons of 12 or 24 planes. But, when it came to the B-2, they found themselves at a loss.

As its price soared past the $330M/unit limit backing the 132 bombers they wanted, they got 21 B-2s at $1.2B each instead. With so few, they put them all at a single site, Missouri’s Whiteman Air Force Base, losing flexibility and response time in the process.

Too often, as we try to get everything we want, we lose sight of what we need.

#hypernomics #minimum #markets

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

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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