BTC - Order and Disorder Phases & Bayesian Phase Determination
Idea for Bitcoin:
- Here is my reasoning and approach for my BTC short trade using Wyckoff, Order and Disorder, Bayes Theorem, and Reflexivity.
- I made a conjecture on Mar. 14 in my Fed Funds rate idea, stating:
1. Bitcoin is an inflation derivative, its movement is correlated with CPI.
2. On average, correlation coefficient yielded:
- p value < 0.02.
- r value between 0.6 and 0.9, except for shakeouts.
In March, r had already risen past the typical range.
What does it mean?
Markets are not a Random Walk:
"This is a corollary to Efficient Market Hypothesis and assumes that since markets efficiently price in all information, no investor can beat the market consistently because any information which an investor might rely on to make an investment decision is already reflected in the current market price. This means than future market prices are independent of past market prices and will be based solely on future events that are essentially unknowable and therefore random." - Jim Rickards (1)
Markets alternate between order and disorder phases, according to Jim Rickards.
This also aligns with the Theory of Reflexivity:
Reflexivity is a theory that positive feedback loops between expectations and economic fundamentals can cause price trends that substantially and persistently deviate from equilibrium prices, according to George Soros.
The last 3 times r deviated to such an extent, a "disorder" phase began in Bitcoin and price saw massive downswings.
Soros' Reflexivity states that when a market is speculated to such an extent in divergence with objective economic fundamentals, it must eventually fill the spread and converge again.
This is still speculative - still a coin toss at best, can we do better than that?
Bayes Theorem:
I speculated on Mar. 15 that RIOT had finished its Wyckoff Distribution Cycle... I had suspicions that Bitcoin would follow then, but it was better to attack the weaker link at that point.
RIOT Wyckoff Cycle:
Let's go back in time, and assume the market was a random walk.
Swing 1, 2 and 3 following this Wyckoff forecast = 3 coin flips = 1/2 x 1/2 x 1/2 chance.
On Apr. 8, I speculated the top for Bitcoin and its Wyckoff Distribution Cycle end...
Wyckoff Cycle:
5 Swings following this forecast = 5 coin flips = 1/2 x 1/2 x 1/2 x 1/2 x 1/2 chance.
Twice I speculated the DOGE Distribution Cycles:
1 coin flip = 1/2 chance.
1 coin flip = 1/2 chance.
Had the market been truly random, the chances of these speculated chain of events occurring due to coin flips would have been 0.098%.
Lets only use Bitcoin? 3.1% chance.
0.098-3.1% chance of occurring in a random walk leads me to believe that the chain of events was not so random after all, and that the Wyckoff distribution cycle existed in this market according to my speculations.
Today I speculated the end of the BTC Distribution Cycle...
Using Bayes, or 'reverse probability', I am able to determine if my speculation of an event occurring was true. It could be right, it could be wrong - I may never know... But the end result is that the price moves as if my speculation was correct.
BTC Ponzi Cycle:
This would be my personal final target should my speculation be correct. While there is no guarantee of achieving this price target, even if my speculation of the event was correct, I assert that a 'disorder' phase has begun for crypto, meaning that it should replicate its previous behavior during 'disorder' phases, beginning a bear market.
GLHF
- DPT
References:
(1) www.researchgate.net...ownload/rickards.pdf
- Here is my reasoning and approach for my BTC short trade using Wyckoff, Order and Disorder, Bayes Theorem, and Reflexivity.
- I made a conjecture on Mar. 14 in my Fed Funds rate idea, stating:
1. Bitcoin is an inflation derivative, its movement is correlated with CPI.
2. On average, correlation coefficient yielded:
- p value < 0.02.
- r value between 0.6 and 0.9, except for shakeouts.
In March, r had already risen past the typical range.
What does it mean?
Markets are not a Random Walk:
"This is a corollary to Efficient Market Hypothesis and assumes that since markets efficiently price in all information, no investor can beat the market consistently because any information which an investor might rely on to make an investment decision is already reflected in the current market price. This means than future market prices are independent of past market prices and will be based solely on future events that are essentially unknowable and therefore random." - Jim Rickards (1)
Markets alternate between order and disorder phases, according to Jim Rickards.
This also aligns with the Theory of Reflexivity:
Reflexivity is a theory that positive feedback loops between expectations and economic fundamentals can cause price trends that substantially and persistently deviate from equilibrium prices, according to George Soros.
The last 3 times r deviated to such an extent, a "disorder" phase began in Bitcoin and price saw massive downswings.
Soros' Reflexivity states that when a market is speculated to such an extent in divergence with objective economic fundamentals, it must eventually fill the spread and converge again.
This is still speculative - still a coin toss at best, can we do better than that?
Bayes Theorem:
I speculated on Mar. 15 that RIOT had finished its Wyckoff Distribution Cycle... I had suspicions that Bitcoin would follow then, but it was better to attack the weaker link at that point.
RIOT Wyckoff Cycle:
Let's go back in time, and assume the market was a random walk.
Swing 1, 2 and 3 following this Wyckoff forecast = 3 coin flips = 1/2 x 1/2 x 1/2 chance.
On Apr. 8, I speculated the top for Bitcoin and its Wyckoff Distribution Cycle end...
Wyckoff Cycle:
5 Swings following this forecast = 5 coin flips = 1/2 x 1/2 x 1/2 x 1/2 x 1/2 chance.
Twice I speculated the DOGE Distribution Cycles:
1 coin flip = 1/2 chance.
1 coin flip = 1/2 chance.
Had the market been truly random, the chances of these speculated chain of events occurring due to coin flips would have been 0.098%.
Lets only use Bitcoin? 3.1% chance.
0.098-3.1% chance of occurring in a random walk leads me to believe that the chain of events was not so random after all, and that the Wyckoff distribution cycle existed in this market according to my speculations.
Today I speculated the end of the BTC Distribution Cycle...
Using Bayes, or 'reverse probability', I am able to determine if my speculation of an event occurring was true. It could be right, it could be wrong - I may never know... But the end result is that the price moves as if my speculation was correct.
BTC Ponzi Cycle:
This would be my personal final target should my speculation be correct. While there is no guarantee of achieving this price target, even if my speculation of the event was correct, I assert that a 'disorder' phase has begun for crypto, meaning that it should replicate its previous behavior during 'disorder' phases, beginning a bear market.
GLHF
- DPT
References:
(1) www.researchgate.net...ownload/rickards.pdf
עסקה פעילה:
"In the case of the 2008 crash, the fictitious capital was house prices. These were bid up way beyond their real value by over-geared borrowers wielding their non-conforming loans.
After the crash, the U.S. Federal Reserve, instead of allowing the credit markets to find their own equilibrium, began offering credit at 0 percent. As Japan discovered in the 1990s, prescribing whiskey to cure a hangover simply leads to lost decades."
- Matthew Bransgrove, Principles of Good Government
What is Bitcoin? What is DOGE? It is fictitious capital.
After the crash, the U.S. Federal Reserve, instead of allowing the credit markets to find their own equilibrium, began offering credit at 0 percent. As Japan discovered in the 1990s, prescribing whiskey to cure a hangover simply leads to lost decades."
- Matthew Bransgrove, Principles of Good Government
What is Bitcoin? What is DOGE? It is fictitious capital.
