“Mathematics is the art of giving the same name to different things.” Henri Poincare
Compound Interest and The Laplace Transform
SP 500 2016 – 2021 Daily Laplace Solution.
The transform in the above charts uses a type of inverse Laplace transform coupled with a limit step function that follows the market to market in the change of the natural log of price so as to integrate out time. It is essentially a step filter that removes the high frequency fluctuations from the data letting the low frequency’s pass.
It then filters the output through a Poisson distribution counter to remove out the short term noise and swings to reveal the long term trend signal, without all the phase delay involved with moving averages that in many ways make them worse than useless.
Markets are telecommunications networks, the only difference between a telephone exchange and a financial exchange is the spelling. They both perform identical functions they match callers with receivers or buyers with sellers in real time at the speed of light.
We just use different names for same functions, to put it another way money and light are the same thing, money is information traveling at the speed of light and therefore obeys the same laws of physics as the wave propagation of electromagnetic energy.
Specifically markets when viewed on the Cartesian plane are price interference patterns that can be analyzed on the complex plane for the vector co ordinates of the component waves that form the primary trends as they change in real time.
The trading inputs of a market may seem to random from day to day but over time they accumulate and distribute in one direction or another and create stable trends that can last for decades which can be analyzed, as a time independent linear systems that have constant behaviors independent of time.
Contrary to what the conventional wisdom would have you believe that it is impossible to apply physics to finance the above proof would suggest otherwise, it is indeed possible to apply the principles of calculus to markets, after all market fluctuate and calculus is all about fluxions. It is just a matter of figuring out how to apply it which will inevitably mean finding the true names of the variables.
The difference is the kernel of the compound interest rate function and the Laplace transform use a different letter for the exponent, that is s instead of r. They are therefore the same formula and thus the same thing that is to say the Laplace transform is an integration of the compound interest rate function.
This also indicates that compound interest is by definition a complex number and thus can be translated to the complex plane and analyzed there for its wave components. So any impulse (transaction) will create point source interference that will propagate a wave front through the medium.
If many impulses that is to say trades are applied to the medium (market) they will form interference patterns as each wave front decays over time.
Where the interference is generated by the constant impulse responses from transactions that is taking an open position and closing it out at some future time. This will look very much like a chaotic system but don’t be fooled the reason markets form linear trend lines is because they are linear systems with a chaotic component as there inputs however the way the market reacts is what matters and that is a function of the elasticity of the market in question which remains constant over time.
More to the point markets are sum total of the supposition of the waves that form them. These patterns are not apparent to due to calibration problems inherent in the base ten number system when looking at a logarithmic system.
Which can be easily solved on the complex plane for the component parts of the interfering waves. Base ten pricing is the problem here, we know the markets are inherently exponential in there behavior it just does not show itself in standard base ten charts. The Laplace transform makes it possible to measure the change in the major trend in real time with out the phase delay in the signal caused by moving averages.