Real-Fast Fourier Transform of Price Oscillator [Loxx]Real-Fast Fourier Transform Oscillator is a simple Real-Fast Fourier Transform Oscillator. You have the option to turn on inverse filter as well as min/max filters to fine tune the oscillator. This oscillator is normalized by default. This indicator is to demonstrate how one can easily turn the RFFT algorithm into an oscillator..
What is the Discrete Fourier Transform?
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
What is the Complex Fast Fourier Transform?
The complex Fast Fourier Transform algorithm transforms N real or complex numbers into another N complex numbers. The complex FFT transforms a real or complex signal x in the time domain into a complex two-sided spectrum X in the frequency domain. You must remember that zero frequency corresponds to n = 0, positive frequencies 0 < f < f_c correspond to values 1 ≤ n ≤ N/2 −1, while negative frequencies −fc < f < 0 correspond to N/2 +1 ≤ n ≤ N −1. The value n = N/2 corresponds to both f = f_c and f = −f_c. f_c is the critical or Nyquist frequency with f_c = 1/(2*T) or half the sampling frequency. The first harmonic X corresponds to the frequency 1/(N*T).
The complex FFT requires the list of values (resolution, or N) to be a power 2. If the input size if not a power of 2, then the input data will be padded with zeros to fit the size of the closest power of 2 upward.
What is Real-Fast Fourier Transform?
Has conditions similar to the complex Fast Fourier Transform value, except that the input data must be purely real. If the time series data has the basic type complex64, only the real parts of the complex numbers are used for the calculation. The imaginary parts are silently discarded.
Included
Moving window from Last Bar setting. You can lock the oscillator in place on the current bar by adding 1 every time a new bar appears in the Last Bar Setting
Search in scripts for "harmonic"
Real-Fast Fourier Transform of Price w/ Linear Regression [Loxx]Real-Fast Fourier Transform of Price w/ Linear Regression is a indicator that implements a Real-Fast Fourier Transform on Price and modifies the output by a measure of Linear Regression. The solid line is the Linear Regression Trend of the windowed data, The green/red line is the Real FFT of price.
What is the Discrete Fourier Transform?
In mathematics, the discrete Fourier transform (DFT) converts a finite sequence of equally-spaced samples of a function into a same-length sequence of equally-spaced samples of the discrete-time Fourier transform (DTFT), which is a complex-valued function of frequency. The interval at which the DTFT is sampled is the reciprocal of the duration of the input sequence. An inverse DFT is a Fourier series, using the DTFT samples as coefficients of complex sinusoids at the corresponding DTFT frequencies. It has the same sample-values as the original input sequence. The DFT is therefore said to be a frequency domain representation of the original input sequence. If the original sequence spans all the non-zero values of a function, its DTFT is continuous (and periodic), and the DFT provides discrete samples of one cycle. If the original sequence is one cycle of a periodic function, the DFT provides all the non-zero values of one DTFT cycle.
What is the Complex Fast Fourier Transform?
The complex Fast Fourier Transform algorithm transforms N real or complex numbers into another N complex numbers. The complex FFT transforms a real or complex signal x in the time domain into a complex two-sided spectrum X in the frequency domain. You must remember that zero frequency corresponds to n = 0, positive frequencies 0 < f < f_c correspond to values 1 ≤ n ≤ N/2 −1, while negative frequencies −fc < f < 0 correspond to N/2 +1 ≤ n ≤ N −1. The value n = N/2 corresponds to both f = f_c and f = −f_c. f_c is the critical or Nyquist frequency with f_c = 1/(2*T) or half the sampling frequency. The first harmonic X corresponds to the frequency 1/(N*T).
The complex FFT requires the list of values (resolution, or N) to be a power 2. If the input size if not a power of 2, then the input data will be padded with zeros to fit the size of the closest power of 2 upward.
What is Real-Fast Fourier Transform?
Has conditions similar to the complex Fast Fourier Transform value, except that the input data must be purely real. If the time series data has the basic type complex64, only the real parts of the complex numbers are used for the calculation. The imaginary parts are silently discarded.
Inputs:
src = source price
uselreg = whether you wish to modify output with linear regression calculation
Windowin = windowing period, restricted to powers of 2: "4", "8", "16", "32", "64", "128", "256", "512", "1024", "2048"
Treshold = to modified power output to fine tune signal
dtrendper = adjust regression calculation
barsback = move window backward from bar 0
mutebars = mute bar coloring for the range
Further reading:
Real-valued Fast Fourier Transform Algorithms IEEE Transactions on Acoustics, Speech, and Signal Processing, June 1987
Related indicators utilizing Fourier Transform
Fourier Extrapolator of Variety RSI w/ Bollinger Bands
Fourier Extrapolation of Variety Moving Averages
Fourier Extrapolator of Price w/ Projection Forecast
Dynamic Zone Range on OMA [Loxx]Dynamic Zone Range on OMA is an One More Moving Average oscillator with Dynamic Zones.
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA , harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
Variety Moving Averages w/ Dynamic Zones contains 33 source types and 35+ moving averages with double dynamic zones levels.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included
4 signal types
Bar coloring
Alerts
Channels fill
Pips-Stepped, OMA-Filtered, Ocean NMA [Loxx]Pips-Stepped, OMA-Filtered, Ocean NMA is an Ocean Natural Moving Average Filter that is pre-filtered using One More Moving Average (OMA) and then post-filtered using stepping by pips. This indicator is quadruple adaptive depending on the settings used:
OMA adaptive
Hiekin-Ashi Better Source Input Adaptive (w/ AMA of Kaufman smoothing)
Ocean NMA adaptive
Pips adaptive
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA , harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
What is the Ocean Natural Moving Average?
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programed to do so. For more info, read his guide "Ocean Theory, an Introduction"
What's the difference between this indicator and Sloan's original NMA?
Sloman's original calculation uses the natural log of price as input into the NMA , here we use moving averages of price as the input for NMA . As such, this indicator applies a certain level of Ocean theory adaptivity to moving average filter used.
Included:
Bar coloring
Alerts
Expanded source types
Signals
Flat-level coloring for scalping
Adaptive, One More Moving Average (OMA) [Loxx]Adaptive, One More Moving Average (OMA) is an adaptive moving average created by Mladen Rakic that changes shape with volatility and momentum
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
The extras:
it has to be smooth
it has to be able to "change speed" without length change
it has to be able to adapt or not (since it has to "imitate" the non-adaptive as well as the adaptive ones)
The steps:
Smoothing - compared are the simple moving average (that is the basis and the first step of this indicator - a smoothed simple moving average with as little lag added as it is possible and as close to the original as it is possible) Speed 1 and non-adaptive are the reference for this basic setup.
Speed changing - same chart only added one more average with "speeds" 2 and 3 (for comparison purposes only here)
Finally - adapting : same chart with SMA compared to one more average with speed 1 but adaptive (so this parameters would make it a "smoothed adaptive simple average") Adapting part is a modified Kaufman adapting way and this part (the adapting part) may be a subject for changes in the future (it is giving satisfactory results, but if or when I find a better way, it will be implemented here)
Some comparisons for different speed settings (all the comparisons are without adaptive turned on, and are approximate. Approximation comes from a fact that it is impossible to get exactly the same values from only one way of calculation, and frankly, I even did not try to get those same values).
speed 0.5 - T3 (0.618 Tilson)
speed 2.5 - T3 (0.618 Fulks/Matulich)
speed 1 - SMA, harmonic mean
speed 2 - LWMA
speed 7 - very similar to Hull and TEMA
speed 8 - very similar to LSMA and Linear regression value
Parameters:
Length - length (period) for averaging
Source - price to use for averaging
Speed - desired speed (i limited to -1.5 on the lower side but it even does not need that limit - some interesting results with speeds that are less than 0 can be achieved)
Adaptive - does it adapt or not
Midas Mk. II - Ultimate Crypto Swing>> This scrip is only meant to be used in 4hour crypto chart <<
How It Works - To swing trade in a 4 hr candles, which has a much larger range than shorter timeframe candles, the script utilizes a longer timeframe ema, sma and MACDs to account for such. When the ema and sma crosses and the rate of change of the MACD histogram is in favor of the direction, then the system provides a long/short signal.
How To Use - The script works the best when the signal is in par with other analyses (trend, harmonic patterns, etc.) This script does not provide any exit signals , so I recommend exiting when the candle breaks out of the structure, or other strategies.
Updates or revisions will be recorded in the comments. Good luck with this script!
ABCD StrategyOne from many harmonic pattern that consists of two equivalent price legs. The ABCD pattern that helps traders predict when the price is about to change direction.
Tracing And Calculation
This code using pivot high and pivot low built-in method and calculate with Fibonacci Retracement.
Limitation
To find ABCD pattern is very difficult, just coming up a few from thousand candle. That why this code using little bit tolerance ratio to get more pattern.
Cyclic RSI High Low With Noise Filter█ OVERVIEW
This indicator displays Cyclic Relative Strength Index based on Decoding the Hidden Market Rhythm, Part 1 written by Lars von Thienen.
To determine true or false for Overbought / Oversold are unnecessary, therefore these should be either strong or weak.
Noise for weak Overbought / Oversold can be filtered, especially for smaller timeframe.
█ FEATURES
Display calculated Cyclic Relative Strength Index.
Zigzag high low based on Cyclic Relative Strength Index.
Able to filter noise for high low.
█ LEGENDS
◍ Weak Overbought / Oversold
OB ▼ = Strong Overbought
OS ▲ = Strong Oversold
█ USAGE / TIPS
Recommend to be used for Harmonic Patterns such as XABCD and ABCD.
Condition 1 (XABCD) : When ▼ and ▲ exist side by side, usually this outline XA, while the next two ◍ can be BC.
Condition 2 (ABCD) : When ▼ and ▲ exist side by side, usually this outline AB, while the next one ◍ can be BC, strong ABCD.
Condition 3 (ABCD) : When ▼ or ▲ exist at Point A, the next two ◍ can be Point B and Point C, medium ABCD.
Condition 4 (ABCD) : When ◍ exist at Point a, the next two ◍ can be Point b and Point c, weak ABCD usually used as lower case as abcd.
█ CREDITS
LoneSomeTheBlue
WhenToTrade
Pythagorean Means of Moving AveragesDESCRIPTION
Pythagorean Means of Moving Averages
1. Calculates a set of moving averages for high, low, close, open and typical prices, each at multiple periods.
Period values follow the Fibonacci sequence.
The "short" set includes moving average having the following periods: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377.
The "mid" set includes moving average having the following periods: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597.
The "long" set includes moving average having the following periods: 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181.
2. User selects the type of moving average: SMA, EMA, HMA, RMA, WMA, VWMA.
3. Calculates the mean of each set of moving averages.
4. User selects the type of mean to be calculated: 1) arithmetic, 2) geometric, 3) harmonic, 4) quadratic, 5) cubic. Multiple mean calculations may be displayed simultaneously, allowing for comparison.
5. Plots the mean for high, low, close, open, and typical prices.
6. User selects which plots to display: 1) high and low prices, 2) close prices, 3) open prices, and/or 4) typical prices.
7. Calculates and plots a vertical deviation from an origin mean--the mean from which the deviation is measured.
8. Deviation = origin mean x a x b^(x/y)/c.
9. User selects the deviation origin mean: 1) high and low prices plot, 2) close prices plot, or 3) typical prices plot.
10. User defines deviation variables a, b, c, x and y.
Examples of deviation:
a) Percent of the mean = 1.414213562 = 2^(1/2) = Pythagoras's constant (default).
b) Percent of the mean = 0.7071067812 = = = sin 45˚ = cos 45˚.
11. Displaces the plots horizontally +/- by a user defined number of periods.
PURPOSE
1. Identify price trends and potential levels of support and resistance.
CREDITS
1. "Fibonacci Moving Average" by Sofien Kaabar: two plots, each an arithmetic mean of EMAs of 1) high prices and 2) low prices, with periods 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181.
2. "Solarized" color scheme by Ethan Schoonover.
Divergence-Support/ResistenceAnother script based on zigzag, divergence, and to yield support and resistence levels.
This idea started with below two concepts:
▶ Support and resistence are simply levels where price has rejected to go further down or up. Usually, we can derive this based on pivots. But, if we start looking at every pivot, there will be many of them and may be confusing to understand which one to consider.
▶ Lot of people asked about one of my previous script on divergence detector on how to use it. I believe divergence should be considered as area of support and resistence because, they only amount to temporary weakness in momentum and nothing more. As per my understanding
Trend > Hidden Divergence > Divergence > Oscillator Levels of Overbought and Oversold
⬜ Process
▶ Now combining the above two concepts - what we are trying to do here is draw support resistence lines only on pivots which has observed either divergence or hidden divergence. Continuation and indecision pivots are ignored.
▶ Input requires only few parameters.
Zigzag lengths and oscillator to be used. Oscillator periods are automatically calculated based on zigzag length. Hence no other information required. You can also chose custom oscillator via external source.
▶ Display include horizontal lines of support/resistence which are drawn from the candle from where divergence or hidden divergence is detected.
▶ Support resistence lines are colored based on divergence. Green shades for bullish divergence and bullish hidden divergence whereas red shades for bearish divervence and bearish hidden divergence. Please note, red and green lines does not mean they only provide resistence or support. Any lines which are below the price should be treated as support and any line which are above the price should be treated as resistence.
▶ Divergence symbols are also printed on the bar from where divergence/hidden divergence is detected.
↗ - Bullish Hidden Divergence
↘ - Bearish Hidden Divergence
⤴ - Bullish Divergence
⤵ - Bearish Divergence
▶ Script also demonstrates usage of libraries effectively. I have used following libraries in this code.
import HeWhoMustNotBeNamed/ zigzag /2 as zg
import HeWhoMustNotBeNamed/enhanced_ta/8 as eta
import HeWhoMustNotBeNamed/ supertrend /4 as st
Can be good combination to use it with harmonic patterns.
Zigzag SARThis is another ZigZag script. But the difference between this and other ZigZag indicators on TV is that here we find highs and lows based on Parabolic SAR.
It repaints?
YES.
On last line of ZigZag you get repainting, because the highs and lows get confirmation only if direction (SAR dots) changes.
This shouldn't be used to forecast highs and lows directly anyway, it's just a visual guide for past highs and lows.
I'm using it to spot harmonic patterns and Wolfe waves more easily. The plan is to draw these automatically in the future, but my skills at Pinescript are limited at the moment.
PS. Ideas for my scripts are coming from @Jegejig1 on Stocktwits, if you want to know who to blame lol
Multi Level ZigzagAt first I thought of doing double zig zag. Once developed I thought it is not much effort to make it multi level zigzag. This script is not same as multi-zigzag indicator (link in the end). In multi zigzag indicator we use zigzag based on different length and each zigzag has no relation to each other. In this script however, each zigzags are related to each other. We cannot just derive Zigzag 4 without deriving Zigzag 3. (Though we can hide each of them individually)
The logic is simple.
Zigzag1: This is the basic zigzag plotted based on given length.
Zigzag2, Zigzag2, Zigzag3 : These are built based on lower level zigzags.
For example, Zigzag2 is built based on Zigzag1 pivots. For calculation, we just use N*2 number of Zigzag1 pivots to derive the next level. Similarly Zigzag2 will become input for Zigzag 3 and Zigzag3 will become input for Zigzag4
Input parameters allow you to chose upto 4 levels of zigzag along with zigzag line color and length. Max array lines also defines how many lines back you want to calculate the zigzag pivots and display then in the stats. Lowering this number will not reduce the number of lines - but, it will limit possibility of calculating higher level zigzags. Stats table just highlight which pivots are applicable for which outer level.
Application: Can be used in pattern recognization scripts to improve accuracy.
Disclaimer: This is not working in intraday charts. Nothing I could do at this point of time. Use it only for daily + timeframes.
Related scripts:
Simple Moving Average Trend Strategiemy own word
so I think my pine is Indicator to find some market entrys or market exits and you can also define fast which trend is possible active.
description of the indicator:
BUY/SELL Signal with Filter based on a simple Moving Average strategie.
The simple Moving Average strategie based on theory that a Trend is made after price cross the Moving Average.
To show a possible Trend simple the Candle bodys change Colors if the close Price is below or above the fast Moving Average.
above the Average =green
below the Average =red
The Indicator shows you a BUY Signal when the Candle is crossover the fast Moving Average but only when the fast Moving Average is above the slow Moving Average.
The Indicator also show you a Buy Signal when the Candle is crossover two Moving Averages.
The Indicator shows you a Sell Signal when the Candle is crossbelow the fast Moving Average but only when the fast Moving Average is below the slow Moving Average.
The Indicator also show you a Sell Signal when the Candle is crossbelow two Moving Averages.
The Filter is in use to count Bars bevor the Candle Crossover the Moving Average and to count how many Bars bevor the breakout hit Moving Average.
if you want you can use your own Filter
you can also use the Notifications to get a Signal on your Phone whenn a Buy or Sell Signal is activ.
User Manual
to use the indicator there 3 Rules to minimize fail decissions
the Signal is only true when
-Rule#1 Signal has same color like the Candle Bar Body and the slow Moving Average
-Rule#2 Signal is at the crossover the Moving Average maybe when Candle close its to late
-Rule#3 Price must be Analyzed don´t Buy at a Market Top and don´t Sell at the Market bottom
its also a good indicator to have a close view in the trend of a product
you can also find Harmonic Patterns better .
for all of my German friends:
Beschreibung
BUY/SELL Indikator mit Filter basierend auf einer einfachen Gleitenden Durschnitt Strategie.
Die einfache Gleitende Durschnitt Strategie besagt das ein Kurs in ein Trend übergeht nach dem durchbruch eines Gleitenden Durschnittes.
Um einen Trend möglichst einfach zu zeigen färben sich die Kerzen wenn sie unterhalb des schnellem gleitenden Durschnittes laufen.
Rot für einen Abwärtstrend und Grün für einen Aufwärtstrend.
Der Indikator zeigt dir ein Kaufsignal wenn der Preis den schnellen Gleitenden Durchschnitt nach oben durchbricht aber nur wenn der schnelle Durschnitt über dem langsamen verläuft um Fehler zu vermeiden.
Der Indikator zeigt dir ein Verkaufsignal wenn der Preis den schnellen Gleitenden Durchschnitt nach unten durchbricht aber nur wenn der schnelle Durschnitt unter dem langsamen verläuft um Fehler zu vermeiden.
Der Filter Zählt maximalen Betrag der Balken bevor der Preis den Durschnitt durchbricht und ausserdem zählt er wieviele maximal möglichen Balken direkt vor dem Ausbruch den Durschnitt berührt haben.
Anhand dieser Zahlen Filtert er nochmals Signale. (mal die Werte hoch stellen so Werden Gewinnraten bis 80% erzielt)
natürlich kann jeder eigene Filter verwenden.
Abschlusswort
guter Indikator um Signale auf das Handy zu bekommen oder um schnell einen Trend im Markt zu erkennen.
Benutzeranweisung
Um den Indikator im Swing bereich zu nutzen und Fehler zu vermeiden gibt es 3 Hauptregeln.
Regel#1 Signal hat die gleiche Farbe wie der Kerzen Körper und die gleiche Farbe wie der langsame Gleitende Durschnitt.
Regel#2 Signal entsteht bei dem kreuzen des Gleitenden Durschnittes, hier ist auf den Kerzenschlusskurs zu achten weil es dann in dieser Zeit Ansicht im zeitschluss zu fehlern kommt.
Regel#3 Markt Preis sollte vorher immer Analysiert werden um keine Shorts in Allzeittiefs zu kaufen oder Longs in Allzeithochs.
//viel Spaß und lasst einen Daumen da
//mit besten grüßen
//euer Petie
[blackcat] L3 Ehlers Spectrogram IndicatorLevel: 3
Background
John F. Ehlers introuced Dominant Cycle and Spectrogram Indicator in Mar, 2008.
Function
In "Measuring Cycle Periods" in Mar, 2008, John Ehlers presented a very interesting technique of measuring dominant market cycle periods by means of multiple bandpass filtering. By utilizing an approach similar to audio equalizers, the signal (here, the price series) is fed into a set of simple second-order infinite impulse response bandpass filters. Filters are tuned to 8,9,10,...,50 periods. The filter with the highest output represents the dominant cycle. This script implements a high-pass filter and a six-tap low-pass Fir filter on input, then 42 parallel Iir band-pass filters. Finally, it plots the Ehlers spectrogram as a heat map.
Ehlers Spectrogram indicates market power status:
With high market power, the spectrogram become fuzzy;
With low market power, the spectrogram become distinct.
It also discloses market dominant cycles and subcycles, which indicates the major rhythm. Regarding the rhythm of the market, Chinese and Western cultures have reached a consensus: Dr. Ehlers can find the main harmonic components of the market through DSP analysis via spectrum; Master Zen compares the market rhythm to Bach’s fugue from a philosophical perspective, where there is a rhythm of life.
Finally, please allow me to quote Master Zen’s statement on market rhythm:
"The market is cruel. For those who try to violate the market rhythm, the market is their death place; the market is beautiful, and the market is Bach’s fugue. There is a rhythm of life. Rhythm is always the rhythm of the market. A market participant without a sense of rhythm is always torturing. Put aside your greed and fear and listen to the rhythm of the market. In the weekend, let go of everything, but listen to the rhythm of nature, the rhythm of life, the rhythm of music, and then come back to listen to the rhythm of the market. Dancing with the market, your greed and fear are peeled off one by one, you will become very bright."
Key Signal
DomCyc--> Ehlers Dominant Cycle
Plot2~Plot60--> Ehlers Spectrum Heat Map
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 73th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
[Daveatt] BEST ABCD Pattern Strategy (Trailing SL + TP)Hello traders
This is the strategy version of my ABCD pattern. I added the Trailing Stop and Trailing Profit upon a follower request
I - Concept
I present to you, ladies and gentlemen, the first screener for harmonic patterns .
Starting with an ACBD pattern screener this time!!
I used the calculations from Ricardo Santo's script
In short, he's using fractals (regular or Bill Williams ) for the pattern calculations. A masterpiece !!!
II - Definitions
The ABCD pattern ( AB=CD ) is one of the classic chart patterns which is repeated over and over again.
The ABCD pattern shows perfect harmony between price and time.
The Williams Fractal is an indicator, developed by Bill Williams , that aims to detect reversal points (highs and lows) and marks them with arrows.
Up fractals and down fractals have specific shapes. The Williams Fractal indicator helps users determine in which direction price will develop
💎Strategy filters💎
I included some cool backtest filters:
- Trailing stop with trigger concept coming from this Trailing Stop Strategy
- Trailing profit with trigger coming from this Trailing Profit Strategy
Last words
It works for all asset classes (Forex, crypto, indices, etc...) and does not repaint
All the BEST
Dave
BEST ABCD Pattern StrategyHello traders
This is the strategy version of this script
I - Concept
I present to you, ladies and gentlemen, the first screener for harmonic patterns.
Starting with an ACBD pattern screener this time!!
I used the calculations from Ricardo Santo's script
In short, he's using fractals (regular or Bill Williams ) for the pattern calculations. A masterpiece !!!
II - Definitions
The ABCD pattern ( AB=CD ) is one of the classic chart patterns which is repeated over and over again.
The ABCD pattern shows perfect harmony between price and time.
The Williams Fractal is an indicator, developed by Bill Williams, that aims to detect reversal points (highs and lows) and marks them with arrows.
Up fractals and down fractals have specific shapes. The Williams Fractal indicator helps users determine in which direction price will develop
💎Strategy filters💎
I included some cool backtest filters:
- flexible take profit in USD value (plotted in blue)
- flexible stop loss in USD value (plotted in red)
The take profit and stop loss should work with Forex/FX pairs as well
All the BEST
Dave
ZigZag++Hey Awesome Traders
I noticed people were so happy with my ZigZag lucemanb script and so I made one that is more user-friendly and customizable
Please note the original one is dedicated to developers, The code is very minimal for fast understanding when anyone wants to use it in their development
In this script, I have included several features like multi-timeframe and alerts. Do take a look and enjoy
If you are using the indicator, please comment down the link to your script
If you would love to support my work through donations, Am so happy to receive them
ADDITIONAL FEATURES
Do u have an idea or a feature that you want to be added,
You can ping me or ask about it here, I can always update
Check out some of the best works i have done with this script
1. Angle trading
2. Harmonic Patterns
BEST ABCD Pattern ScreenerHello ladies and gentlemen traders
Continuing deeper and stronger with the screeners' educational series one more time.
This one is heavy crazy mega cool (pardon my french).
I - Concept
I present to you, ladies and gentlemen, the first screener for harmonic patterns.
Starting with an ACBD pattern screener this time!!
I used the calculations from Ricardo Santo's script
In short, he's using fractals (regular or Bill Williams ) for the pattern calculations. A masterpiece !!!
The screener will show in 1 consolidated chart the ABCD patterns for 5 selected assets. Could be stocks, forex, crypto, whatever you feel like making money with
II - Definitions
The ABCD pattern ( AB=CD ) is one of the classic chart patterns which is repeated over and over again.
The ABCD pattern shows perfect harmony between price and time.
More info here
The Williams Fractal is an indicator, developed by Bill Williams, that aims to detect reversal points (highs and lows) and marks them with arrows.
Up fractals and down fractals have specific shapes. The Williams Fractal indicator helps users determine in which direction price will develop
Source: www.tradingview.com
III - How did I set the screener
The visual signals are as follow:
- square: whenever there is an ABCD pattern detected
Then the colors are:
- green when a bullish pattern is detected
- red when a bearish pattern is detected
🔸 The script screenshot shows two red squares matching two ABCD bearish pattern from the above panel. As the chart is showing APPL, I highlighted where the screener mentioned the fruit stock ( APPLE, pun, bad joke, Dave out...)
🔸 I tried to make it as clear as I could with red arrows
Once again, we pushed together the limits of pine script beyond of what we thought was possible, beyond the realm of this world, reaching finally the dreamt pine script heaven (am I going too far? feel free to tell me)
Best regards,
Dave
Multistep AutocorrelationAutocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay. Informally, it is the similarity between observations as a function of the time lag between them. The analysis of autocorrelation is a mathematical tool for finding repeating patterns, such as the presence of a periodic signal obscured by noise, or identifying the missing fundamental frequency in a signal implied by its harmonic frequencies. It is often used in signal processing for analyzing functions or series of values, such as time domain signals.
This multistep autocorrelation function calculates the correlation of roc (rate of change) between an asset at t and t-1 as well as the correlation of the same asset at t and t-4. The output is an average of the two.
If both outputs show a positive correlation, the color will be green.
If only one shows a positive correlation, the color will be yellow.
If neither show a positive correlation, the color will be red.
This indicator can be useful as a filter for strategy entry logic (only enter on strong correlation and the strategy entry condition), or as standalone confirmation of strength in a specific direction. It can also be used to filter chop.
Another potential usecase would be as a variable in regression applications.
Enjoy!
MS MONEY CCI SQUEEZEAbout
I have used this indicator to find many lucrative opportunities. This indicator takes the moving average of CCI in custom, volatility-specific conditions. CCI measures "overbought" in the red-shaded region and "Oversold" in the green-shaded region. The shaded regions do not constitute a buy/sell signal alone, the MS CCI Squeeze is best used when market conditions agree and is best used when the user has fundamental reasoning for "reversal-like" situations to align. The MS CCI Squeeze will soon have a synergistic partner called "MS RSI Squeeze" indicator that will look similar to help better measure volatility and strength trend.
About the Commodity Channel Index (CCI)
The commodity channel index (CCI) is an oscillator originally introduced by Donald Lambert in 1980. Since its introduction, the indicator has grown in popularity and is now a very common tool for traders in identifying cyclical trends not only in commodities, but also equities (stocks) and currency trading.
How to set an Alert
If the user wants to set an alert , click on one of the support/ resistance lines (black-dashed) near the zero mark. Clicking on the horizontal line above or below the zero line will populate a yellow arrow which will allow you to set alerts when wanted.
Please Read For Better Efficiency
When using this indicator, keep an eye out for harmonic patterns, both bullish and bearish head and shoulders patterns for "HIDDEN" breakout opportunities.
Please like, follow and share and I will continue building better indicators.
New Choppiness IndexThis script tries to identify trending regions and ranging choppy regions.
Green areas are trends; Red areas are consolidation areas.
If you are a trend follower trader you should focus on green areas;
If you are a harmonic pattern trader you should focus on red areas.
I did not play with the parameters extensively, but as a rule of thumb higher parameters
helps on long term trades.
This tool seems to work better for major currencies pairs, presumably due to the
high exchanged volumes that reduces weird fluctuations.
Good set of parameters are:
(55, 9) the default ones, doing impressively well in EURUSD Daily;
(8, 5) doing well in GBPCHF Daily, short trades to be set at lower timeframes.
Happy trading,
vitelot/yanez/Vts
January 2019
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