The Mars/Shmita Year Hypothesis
- Indbinding:
- Paperback
- Sideantal:
- 602
- Udgivet:
- 29. december 2023
- Størrelse:
- 140x36x216 mm.
- Vægt:
- 838 g.
- 2-4 uger.
- 18. december 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af The Mars/Shmita Year Hypothesis
Back in 2020, I came up with the idea that the Federal Reserve can set interest rates based on the movements of the planet Mars and then wrote a book explaining how it was feasible. In the earlier versions of that book entitled "The Mars Hypothesis," I formulated an algorithm based on solar and planetary positions. But over the course of applying it to the actual price movements of the Dow Jones Industrial Average, I would see correlations, but suddenly run into major problems with its application when the Shmita year came around. In the earlier of versions of The Mars Hypothesis, I made this observation, but then attempted to apply an algorithm that could account for Dow Jones price movements without having to observe the Shmita year. However, now I think its unfair to leave out the Shmita year aspect, especially when it seems to clearly throw off algorithms the year that it comes around. Keep in mind that this is not the only time I have run into the Shmita year problem. In the second volume of this book, entitled "A Torah-Based Stock Prediction Algorithm," I apply a different algorithm to the historical Dow Jones Data, using a solar thesis instead of a martian one. Even in that application of an algorithm to the Dow Jones price movements, I found a decline in the algorithm's performance and applicability to what actually happened in the market when the Shmita year came around. This begs the question. Are algorithms living things that obey the Torah? Lets find out. The algorithm laid out in this version of "The Mars Hypothesis" now entitled "The Mars/Shmita Year Hypothesis," sticks with the initial algorithm which involved 2 parameters in tandem with observing the Shmita year. The first parameter was that when the sun would enter within 30 degrees opposite the lunar node, the start of a bear market phase would be predicted. The ensuing phase of Mars within 30 degrees of the lunar node would predict the low of that bear market phase, while the end of the Mars within 30 degrees of the lunar node phase would signal the end of the predicted bear market phase. In reading this book you will notice how this algorithm is very much applicable until the Shmita years come around. All of a sudden the algorithm would seem to take a Sabbatical, thus causing us to alter our algorithmic approach. In this book, as a consequence, I take heed to the Shmita year and later formulate an interest rate setting system based on both Sun and Mars and the Shmita year.
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