Disclaimer; This analysis for educational purposes, its not a financial advise. Please do your own research
What is Fisher Transform?
How is it work?
How probability of distribution calculated? And why it works?
FTransform ; The accuracy of calling tops and bottoms almost to perfect ratio when Fisher & trigger line crosses. Best buys /sells are clearly at OS/OB region when they are very close to Bollinger Bands.
I just marked some of the buy (blue) - sell (red) signals (vertical lines) along with TD sequential.
Lets dive in. Following paragraph from the genius J.Ehler who created this solid indicator
"The input values are constrained to be within the range -1 < X < 1. When the input data is near the mean, the gain is approximately unity. By contrast, when the input approaches either limit within the range the output is greatly amplified. This amplification accentuates the largest deviations from the mean, providing the “tail” of the Gaussian PDF. The transformed output Probability Density Function is nearly Gaussian, a radical change in the PDF.
So what does this mean to trading? If the prices are normalized to fall within the range from –1 to +1 and subjected to the Fisher Transform, the extreme price movements are relatively rare events. This means the turning points can be clearly and unambiguously identified. Value1 is a function to normalize price within its last 10 day range. The period for the range is adjustable as an input. Value1 is centered on its midpoint and then doubled so that Value1 will swing between the –1 and +1 limits. Value1 is also smoothed with an EMA whose alpha is 0.33. The smoothing may allow Value1 to exceed the ten day price range, so limits are introduced to preclude the Fisher Transform from blowing up by having an input value larger than unity. The Fisher Transform is computed which is delayed by one bar are plotted to provide a crossover system that identifies the cyclic turning points.
How probabilities are measured by (-/+) deviations on Fisher Transform?
A) -If Fisher transformed indicator has a value of −1, it has a value of negative one standard deviation and therefore there is a 32 percent chance prices will go lower.
B) -If the transformed indicator has a value of −2, it has a value of negative two standard deviations, and therefore there is only an 8 percent chance prices will go lower.
This is a high-probability buying opportunity.
C) At a level of −3, the negative 3 standard deviations means there is only a 2 percent chance of the prices going lower.
FT values are symmetrical, so positive deviations are high-probability indications to exit a long position or to sell short. If the prices are normalized to fall within the range from –1 to +1 and subjected to the TF, the extreme price movements are relatively rare events. This means the turning points can be clearly and unambiguously identified"
For detailed trading concept of join us. t.me/cryptokingfish
What is Fisher Transform?
How is it work?
How probability of distribution calculated? And why it works?
FTransform ; The accuracy of calling tops and bottoms almost to perfect ratio when Fisher & trigger line crosses. Best buys /sells are clearly at OS/OB region when they are very close to Bollinger Bands.
I just marked some of the buy (blue) - sell (red) signals (vertical lines) along with TD sequential.
Lets dive in. Following paragraph from the genius J.Ehler who created this solid indicator
"The input values are constrained to be within the range -1 < X < 1. When the input data is near the mean, the gain is approximately unity. By contrast, when the input approaches either limit within the range the output is greatly amplified. This amplification accentuates the largest deviations from the mean, providing the “tail” of the Gaussian PDF. The transformed output Probability Density Function is nearly Gaussian, a radical change in the PDF.
So what does this mean to trading? If the prices are normalized to fall within the range from –1 to +1 and subjected to the Fisher Transform, the extreme price movements are relatively rare events. This means the turning points can be clearly and unambiguously identified. Value1 is a function to normalize price within its last 10 day range. The period for the range is adjustable as an input. Value1 is centered on its midpoint and then doubled so that Value1 will swing between the –1 and +1 limits. Value1 is also smoothed with an EMA whose alpha is 0.33. The smoothing may allow Value1 to exceed the ten day price range, so limits are introduced to preclude the Fisher Transform from blowing up by having an input value larger than unity. The Fisher Transform is computed which is delayed by one bar are plotted to provide a crossover system that identifies the cyclic turning points.
How probabilities are measured by (-/+) deviations on Fisher Transform?
A) -If Fisher transformed indicator has a value of −1, it has a value of negative one standard deviation and therefore there is a 32 percent chance prices will go lower.
B) -If the transformed indicator has a value of −2, it has a value of negative two standard deviations, and therefore there is only an 8 percent chance prices will go lower.
This is a high-probability buying opportunity.
C) At a level of −3, the negative 3 standard deviations means there is only a 2 percent chance of the prices going lower.
FT values are symmetrical, so positive deviations are high-probability indications to exit a long position or to sell short. If the prices are normalized to fall within the range from –1 to +1 and subjected to the TF, the extreme price movements are relatively rare events. This means the turning points can be clearly and unambiguously identified"
For detailed trading concept of join us. t.me/cryptokingfish
Free TA channel t.me/cryptokingfish
Tom DeMark & Fibonacci & Harmonics & Fisher Transform, Renko. Kagi, PA ,Chart Patterns trader
Tom DeMark & Fibonacci & Harmonics & Fisher Transform, Renko. Kagi, PA ,Chart Patterns trader