One Hundred Years of The All Ords as a Function of Pi.


Y = ( LOG ( Price , PI() ) – LOG( (2^0.5+1)*PI()^3 , PI() ) ) * 2 + 2


Data:ASX Research Reconstruction of the All Ords  ISBN O 9591857 8 X


Table 1: The All Ords 1937 high to 2020 high scaled to the square root of Pi.

  • 74.5   * Pi^1/2     = 132.04 The high of the wool boom
  • 132    * Pi^1/2     = 234.04 High of the Transistor boom.   
  • 234    * Pi^1/2     = 414.84 Highs of the 60’s mining boom.
  • 414    * Pi^1/2     = 735.28 Right shoulder of the Fraser resources boom.
  • 735    * Pi^1/2     = 1303.2 Intermediate  support level post 87 crash.
  • 1303  * Pi^1/2     = 2309.9 18/09/1987 All Time High 2312.5
  • 2309  * Pi^1/2     = 7253.9  – 20/2/20 – 7287 Covid Correction.

The All Ords 1917 to 2020 Scaled to The Square Root of Pi.



This All Ords 1917 to 2020 Scaled to The Square Root of Pi.


In the chart above the price axis is in log base ten and the levels are marked off as log scale of Pi where each level is 3.141 times the previous, if you consider that all market movements are part of a longer term cycle of circular activity it only makes sense that the constant Pi would be somehow involved, it is after all the basis of all cyclic behavior and therefore should show up strongly in the data.

As it turns out there is a very strong correlation between Pi and the All ordinaries index, all the major and minor highs of the market in the post depression era are related to each other by Pi and its roots, if you take the first high of the Australian market after the great depression @74.5 and multiply it by Pi you get the number 234.04, which is surprisingly close to the high in the market at 239 in 1960.  

If you repeat this the next number in the series is 735.28. This is also surprisingly close to the high of the Fraser resources boom at 746 in Jan 1981 and there was an intermediate high during the topping out of the market at 736

The next number in the series is 74.5 * Pi^3 = 2309.96, the exact high of the 1987 market was 2312 on the cash and 2343 on the SPI with the cash closing at 2305. The final number in the series is 7253 the recent high was on 20/2/20 @7289

So after decades of market action the same constant keeps reappearing this cannot be a coincidence. 

It is no great surprise that Pi would turn up somewhere after all it is the most basic function of money and markets to circulate hence they are polar functions.

Greater resolution can be obtained by smaller increments of Pi to form a diffraction grid to find the calculus limit of the function which you can see in the charts below.


This All Ords 1917 to 2020 Scaled to The Fourth Root of Pi.



This All Ords 1917 to 2020 Scaled to The Eight Root of Pi.



All Ords 1917 – 2021 Polar Form.



Markets Are Telecommunications Networks.


This is the last thing you would expect a random walk system to do, it is however the first thing you would expect a wave function to do, what we are looking at is wave propagation that takes the form of a set of concentric circles where the high of one boom is the diameter of a circle the radius of which is the high of a future boom cycle peak.  

What this is telling us is that we are looking at the data in the wrong co ordinate system rectangular and not polar form. The way the highs of the major crashes line up over time prove they are a function of a set of concentric circles. 

In that each major leg of the market like the high of 87 and the present is one are an order of magnitude of Pi above one another with the intermediate steps occurring on the square root steps of pi.

This is no small coincidence and demo straights that markets are not random walks at all, but are a complex harmonic motion and are therefore a wave functions that are communicated over telecommunications networks and therefore have carrier waves which is the ones we are interested in.

So the question begs what is the general form of the differential equation that unlocks the co ordinates of the wave function of an active market in real time or what you and I call trend and volatility.

When asked what he thought what stock prices would do he replied “they will fluctuate” which is another word for Newtonian Fluxion which is the key to understanding what is going on here.

The following links open new tabs and take you to my research site and the second will take you to a Google excerpt summary of the calculus of what is going on here and how it relates to trading based on known laws of physics and a pure math solution that explains market behavior.