Popularization of science is only necessary in this high global inequality not only in wealth but in educational opportunities for our people of seven billion. The fateful decision of the Kennan Doctrine of 1948 ensured that the postwar order would be to fuck the wretched of the earth, and thus the Anglo-American rulers of the new world order declared a permanent war on the world’s poor by making it a primary objective to deny them wealth — this is not even a particularly outrageous exaggeration of the text of the Kennan Doctrine, and of course the people who did 9/11–that would be Netanyahu, his spies and proteges working directly at high ranks of the American government the so-called Neoconservatives–had even more vicious ideas about how to take the world’s resources with vile policies of cohorts busy with racist propaganda and a bloody Middle East not only for resources but for hegemonic power and extermination based on propaganda history of lies about the Second World War. This is all the backdrop of the current non-science of finance. Predatory wealth is out of control and has usurped the ‘science’ of finance. What science can be produced in the pay of the wealthy predators I know well enough. The quants in Wall Street are not doing science. There is no science of finace, as I’ve said before many times, because the actual phenomenon of scientific interest regards this aspect of our lives having to do with wealth is not the rags-to-riches delusions; those are what Marquis de Laplace said of the poor fool at the casino which is a business set up to take money. The House always wins. So what do I propose we do? Very simple. This is an easy exercise in the grand scheme of things.

Model the entire world financial system as a graph. This is easy enough that for a small number of assets, 188 stocks, I did this in a few days: study the properties of the class of graphs matching the Laplace spectrum; ensure that a much larger dataset corroborates the class of graph. Then use the graph as space variable for dynamical systems and verify that world volatility does follow a dynamical law deterministic or stochastic. I have already shown universality in Mandelbrot’s program of long memory in stochastic volatility in the past two years and even have another failed attempt at setting up a business with coding star Peter Ogilvie. It was fated for this is much more important for my conscience and life. This is an expression for me of the indestructable in me that keeps me alive now: consider the market as a space-time dynamical system modeled directly on Navier-Stokes equation where space is a graph and the Navier-Stokes is translated directly as a delay differential equation. We, as in the human race, know a great deal since the pioneers of chaos in physics had a successful campaign. To me it’s not a particularly strange thing for dynamical systems were already absorbed in the collective psyche and I read the popular books on chaos while still in high school. Recall the navier Stokes equations:

where $u$ is a vector field. This is a simplified version of the incompressible equations:

In a more detailed presentation, there are external force and internal work terms we set them to zero. Let’s break up the terms into variation, convection and diffusion terms. Note that when there is no convection term we have a basic heat equation.

On a graph, the Diffusion term already exists with the Laplacian matrix, so the convection term needs definition; at the moment gradient on a graph has multiple definitions. Whether chaos holds for an ordinary differential delay equation is not an impossible question to answer: instability of ordinary differential equations is a classical topic. Let’s assume that some parameter controls a phase transition to chaotic dynamics.

So going back to the original issue of a lack of science of finance for the purpose of being the physicians for the volatility storms rather than being rats who work to fuel the fires, we have to discover the dynamical laws of volatility as a Navier-Stokes-like equation on a graph of the particular class and then study the phase transition to chaos by parameters and then we can address management of volatility storms. We cannot have a science based on hocus pocus marketing tricks to excite investor funding or be corrupted by the power of money. Real science in finance means to understand the dynamical system well enough to know why and when chaos appears; here Onsager’s vortex model for turbulence is a literal guide. We need to find the Navier-Stokes equivalent for volatility. The last is not possible to ask without a space for volatility. Time series models built in merchant shops trying to make a buck is not science.

Where’s some data and code for all this? You can find both data and R code here.

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