You likely have seen readouts from GPS applications, where a device reveals its latitude and longitude. That is a 2D plot. Some GPS outputs also include an altitude reading. That’s a 3D plot.

In the green Value Space at left, below, the Range (analogous to longitude), MV (momentum, akin to latitude), and 2016 Price (similar to altitude) reveal 3D positions of 1 bomb (the BLU-111) and 2 missiles (the AGMs -158-1 and -84). The BLU-111 has a Range, MV, and 2016 Price of (28, 364,389, $32,000), while the ordered triples for AGMs -158-1 and -84 are (1000, 1,225,2000, $1.912M) and (270, 577,125, $528K), in that order.

The red Demand Plane, at right, describes positions as ordered pairs, with Quantities as the horizontal component, and 2016 Prices on the vertical axis, as (33,330, $32,000), (275, $1.912M), and (4,152, $528K) for BLU-11, AGM-158-1, AGM-84, respectively. The Demand Plane is a 2D plot.

As the 3D Value Space and 2D Demand Plane share the Price axis, the collectively form a 4D system, as displayed in the diagram and described in the table.

How do we display 5D systems? Read the next post for an explanation.

#marketanalysis #3Dsystems #4Dsystems

## Five-Dimensional Markets

Markets move.

We may show the 2012 car market Value (the upper surface of the red space at left, the points deriving that surface omitted), and the Costs for those cars (an estimate shown by the lower red surface of that space). The region between those surfaces is the Financial Opportunity Space (FOS), where suppliers make Profits. That market’s matching Demand Frontier (in red) is at right. Electric car Value comes from Horsepower & Range (Dimensions 1 & 2), which determines Price (Dim 3), which drives Demand (Dim 4).

As this market moved into 2013, more entrants joined. Existing models sales climbed. Over Time (Dim 5), the 2013 Demand Frontier shifted to the blue line. Simultaneously, the viable profitability region moved too, from the red 2012 to the blue 2013 FOS. Values changed (Value Space points left out for clarity), and learning on existing models drove their costs lower (the lower blue space surface). We know costs fall over time for models due to the learning curves that apply to repetitive activities and producers drop prices at the same time to gain market size – see the post from a month ago on the Model T for a real-world example.

The origin of 5D systems is (0,0,0,0,Tn). Tn is a timestamp.

#markets #prices #profits #profitability

## Plotting in 4 Dimensions

You likely have seen readouts from GPS applications, where a device reveals its latitude and longitude. That is a 2D plot. Some GPS outputs also include an altitude reading. That’s a 3D plot.

In the green Value Space at left, below, the Range (analogous to longitude), MV (momentum, akin to latitude), and 2016 Price (similar to altitude) reveal 3D positions of 1 bomb (the BLU-111) and 2 missiles (the AGMs -158-1 and -84). The BLU-111 has a Range, MV, and 2016 Price of (28, 364,389, $32,000), while the ordered triples for AGMs -158-1 and -84 are (1000, 1,225,2000, $1.912M) and (270, 577,125, $528K), in that order.

The red Demand Plane, at right, describes positions as ordered pairs, with Quantities as the horizontal component, and 2016 Prices on the vertical axis, as (33,330, $32,000), (275, $1.912M), and (4,152, $528K) for BLU-11, AGM-158-1, AGM-84, respectively. The Demand Plane is a 2D plot.

As the 3D Value Space and 2D Demand Plane share the Price axis, the collectively form a 4D system, as displayed in the diagram and described in the table.

How do we display 5D systems? Read the next post for an explanation.

#marketanalysis #3Dsystems #4Dsystems

## Measuring Demand

Two useful measures of Demand are the Demand Frontier and Aggregate Market Demand.

The Demand Frontier describes a market’s outer boundary. For the S&P 500, the dark green dots show the outermost quantities (stock volumes) and prices (split-adjusted stock prices). The Demand Frontier is the green line of best fit through them. It shows the market’s price limits and its reaction to price changes.

Another way to portray buyers’ price sensitivity is with Aggregate Market Demand. Here, an algorithm splits the stocks into price bins, distributed 1) equally concerning price, or unequally distributed to price following 2) a Fibonacci or 3) Geometric series for the number of observations per bin. In this case, a 6 bin split (divided by red lines) provides 5 red points (bin 5 is empty). Each red point is the total stock quantity in each bin and the average weighted price of those stocks. The red line through them is Aggregate Market Demand.

Demand Frontier and Aggregate Market Demand slopes converge with many observations. Here, the slope of the Demand Frontier is -0.244; the Aggregate Market Demand is -0.236. Good agreement between the slopes provides good evidence about market workings.

How does Value relate to Demand? Read the next post.

#demandforecasting

## Many Features Can Determine Value

Last time we looked at how 3 features revealed value in stocks. But, stockholders do not limit themselves to some fixed number of features in their collection buying decisions.

Here, the market considers at least 4 features simultaneously. It entertains 1) book value per share on one horizontal axis, 2) market capitalization on the other, and then, if it sets 3) EPS to 20 and 4) stock volume to 10 million, it produces the surface at left. If it resets the stock volume to 1 million, it shifts that surface upward. [This analysis excludes Amazon.]

Stocks support higher prices with higher earnings and book values per share. But prices climb as market capitalization goes up and volume falls. Accounting for opposing forces is crucial to market analysis.

This S&P 500 study only examines stock parameters. As the world reacts to COVID-19, we see the impact of global market factors. Stocks fall with uncertainty.

In markets such as the S&P 500, with a sufficient number of entrants, several measures of demand come into view. The slopes of 2 important demand curves start to converge with enough market participants. See the next post for a discussion of their differences and similarities.

#stockmarket #equities #markets #trading #stocks

## Features Determine Value

In every market, buyers determine Value, the sustainable prices for products based on their features. This phenomenon is never more evident than in stock markets.

Consider the S&P 500 from one day in July 2019, as shown below. After filtering out those stocks with negative figures for book values, earnings per share, and returns on assets, we have 411 stocks left.

At left, the plane running through the data reveals how the market rewards market capitalization (showing larger companies draw larger prices) and book value per share (how the market rewards a measure of safety if the company were to dissolve), given earnings per share (EPS) of $2. We could imagine stockholders consider EPS as part of their Value calculation as well, and if we increase it from $2 to $20, as shown at right, we see how the market rewards that feature.

Book value per share, market cap, and earnings per share (with P-values of 0.58%, 1.88E-67, and, 1.17E-11, respectively, where P-values measure the chance a variable contribution is due to chance) are parts of an equation with more contributors to Value as a part of it.

What else might add Value? Check in to the next post for some answers.

#prices#stocks#value#sustainable#market

## Value, Demand, and 4D States

Last time we tackled Value as sustainable Prices based on product Features, shown in Value Space. There, 2 Valued Features, horizontal dimensions 1 & 2, drive Value, which determines Price, vertical dimension 3.

We earlier depicted Demand with a horizontal Quantity dimension 4 and the same Price dimension 3.

Last week we showed how the Antarctic claims of Argentina and Australia meet at the South Pole, their air spaces abutting the Earth’s axis. If we call the South Pole “0,” every point away from it is positive.

As Value Spaces and Demand Planes share a common Price Axis, they abut one another as do the Argentinian and Australian claims.

It follows Value and Demand form 4D systems, such as that for electric cars below. Every point in Value Space has a matching one on the Demand Plane. Look at the green lines running to the isolated point in Value Space, connecting to its opposing Demand Plane point.

The diagram shows the Law of Value and Demand:

Value and Demand form linked, dual states.

How do we handle more valued features? Please see the next post for the answer.

#prices#demand#4Dsystems#marketanalysis

## What Holds Up Prices?

Price formation often seems steeped in mystery. “Seeing what the market will bear” is a mantra for many, but why would we want to leave prices to chance if we could avoid it?

What supported the prices for 2013 electric cars? As shown below, we could make a statistically significant (9.3E-09) estimate of prices using a surface running through the 18 electric car models (as green spheres) that made up the market that year. That surface reflects that after buyers paid about $6,500 to enter the market, the Price went up $102 for every horsepower and $172 for every added mile of range (P-Values, 0.00038, 4.19E-07, respectively). Models priced above the surface may be overpriced, those below may be under-priced, or some other significant Features may be at work.

The diagram & the market math behind it demonstrates the first 2 adages of the Law of Value and Demand, which are:

The green region is Value Space. How does it relate to Demand? Read the next post for an answer.

#prices#value

## The Demand For Money

Well, that’s an odd title, I’ll grant you that.

Really, what we’re addressing here is the demand for fiat currency.

Recall in previous posts we found Demand Frontiers for multiple markets. Sometimes these curves have breaks. Such is the case for fiat currencies. As shown in the diagram, this market has an Upper Demand Frontier and an Outer Demand Frontier.

Upper Demand Frontiers emphasize the price-limiting boundary for a market, while Outer Demand Frontiers focus on the quantity-limiting ability of a market to absorb the product. These boundaries help countries’ central banks to figure out how many currency units to issue.

What maintains the price of any currency? Please look at the next post for the first of two answers.

#demand #prices #currency #demandforecasting

## Something In Common

I posed these questions last time:

Which two countries are these? Argentina and Australia.

Where do they touch? Yes, this is a trick question. Nothing touches Australia. However, both Australia and Argentina have claims on Antarctica. They touch at the South Pole. The Earth’s axis marks the common line that divides their respective air spaces (

https://lnkd.in/gAnDGaw).Why does it matter?

We call the South Pole 90° south latitude. But what if we called it “0”? If we called it “0,” then every point moving away from it would be positive. That’s because geography is never negative. If we started at the South Pole and walked one step into the Argentinian claim, we could say we moved into positive Argentinian space, but we wouldn’t say we were in negative Australian space. If we turned around, retraced our step onto the South Pole, and then took another step into the Australian claim, we would be in positive Australian space and not in any other.

This seemingly odd construct proves useful. Look at upcoming posts to see why.

## A Change Of Perspective

Modern economics gets inspiration from thermodynamics, constantly looking for the equilibriums such systems demonstrate.

Multidimensional Economics has a different point of origin.

Consider the maps below and the three questions that follow.

Which two countries are these?

Where do they touch?

Why does it matter?

Look to the next post for the answers.

#demandforecasting #prices