Simple CycleIntroduction
A simple and really clean cycle oscillator, in fact its quite precise even if the script use recursion which can sometime produce totally uncorrelated results.
On The Code
The calculations start with a who is a smoothing/averaging constant. Then comes src who is the input and is defined as the sum of the closing price with the output, then the output is high-pass filtered in b , after that the output is just the weighted average of the input change with b .
All those recursions and detrending steps make the indicator able to highlights cycles.
Kitaran
Morphed Sine WaveIntroduction
If you rescale a sine wave to the price you will need to correlate it with it in order to show good results, today i present a different method that does not involve correlation to "morph" a sine wave to the price in order to provide forecast's and highlight market periodic patterns.
Parameters
length control the period of the sine wave, power control the "morphing" amount, if you see for example that the results are going nuts try to increase power , if the results are just the price and the delayed price try to decrease power .
power = 1
power = 100
Those settings might be different depending on which market you are in.
Various Uses
You can do a lot of things with this indicator, use filters as source :
Use the indicator as source for oscillators in order to create cycles indicators :
And certainly many more things
Conclusion
I presented a way to morph a sine wave to the price i order to highlight cycles. You can use any function that return a value between -1 and 1 instead of sin , this can be a scaled rsi/stochastic or correlation coefficient, its up to you :)
If you need help don't hesitate to commend or pm me. I hope you will like the indicator and that it will inspire you to make great things.
Thanks for reading !
Dominant Cycle Tuned RsiIntroduction
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters" , from the use of variable smoothing constant for exponential smoothing to artificial intelligence.
The dominant cycle tuned rsi depend on the dominant cycle period of the market, such method allow the rsi to return accurate peaks and valleys levels. This indicator is an estimation of the cycle finder tuned rsi proposed by Lars von Thienen published in Decoding the Hidden Market Rhythm/Fine-tuning technical indicators using the dominant market vibration/2010 using the cycle measurement method described by John F.Ehlers in Cybernetic Analysis for Stocks and Futures .
The following section is for information purpose only, it can be technical so you can skip directly to the The Indicator section.
Frequency Estimation and Maximum Entropy Spectral Analysis
“Looks like rain,” said Tom precipitously.
Tom would have been a great weather forecaster, but market patterns are more complex than weather ones. The ability to measure dominant cycles in a complex signal is hard, also a method able to estimate it really fast add even more challenge to the task. First lets talk about the term dominant cycle , signals can be decomposed in a sum of various sine waves of different frequencies and amplitudes, the dominant cycle is considered to be the frequency of the sine wave with the highest amplitude. In general the highest frequencies are those who form the trend (often called fundamentals) , so detrending is used to eliminate those frequencies in order to keep only mid/mid - highs ones.
A lot of methods have been introduced but not that many target market price, Lars von Thienen proposed a method relying on the following processing chain :
Lars von Thienen Method = Input -> Filtering and Detrending -> Discrete Fourier Transform of the result -> Selection using Bartels statistical test -> Output
Thienen said that his method is better than the one proposed by Elhers. The method from Elhers called MESA was originally developed to interpret seismographic information. This method in short involve the estimation of the phase using low amount of information which divided by 360 return the frequency. At first sight there are no relations with the Maximum entropy spectral estimation proposed by Burg J.P. (1967). Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City.
You may also notice that these methods are plotted in the time domain where more classic method such as : power spectrum, spectrogram or FFT are not. The method from Elhers is the one used to tune our rsi.
The Indicator
Our indicator use the dominant cycle frequency to calculate the period of the rsi thus producing an adaptive rsi . When our adaptive rsi cross under 70, price might start a downtrend, else when our adaptive rsi crossover 30, price might start an uptrend. The alpha parameter is a parameter set to be always lower than 1 and greater than 0. Lower values of alpha minimize the number of detected peaks/valleys while higher ones increase the number of those. 0.07 for alpha seems like a great parameter but it can sometimes need to be changed.
The adaptive indicator can also detect small top/bottoms of small periods
Of course the indicator is subject to failures
At the end it is totally dependent of the dominant cycle estimation, which is still a rough method subject to uncertainty.
Conclusion
Tuning your indicator is a great way to make it adapt to the market, but its also a complex way to do so and i'm not that convinced about the complexity/result ratio. The version using chart background will be published separately.
Feel free to tune your indicators with the estimator from elhers and see if it provide a great enhancement :)
Thanks for reading !
References
for the calculation of the dominant cycle estimator originally from www.davenewberg.com
Decoding the Hidden Market Rhythm (2010) Lars von Thienen
Ehlers , J. F. 2004 . Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading . Wiley
Ehlers Triple Delay-Line DetrenderThis indicator was originally developed by John F. Ehlers (Stocks & Commodities , V.18:7 (July, 2000): "Optimal Detrending").
Mr. Ehlers applied the ideas of the radar systems for the financial time series detrending.
Mr. Ehlers constructed the Triple Delay-Line Canceller first, then smoothed it with the Modified Optimum Elliptic Filter with minimal lag. The smoothed detrended signal is smoothed again with the Modified Optimum Elliptic Filter to obtain signal line.
As result, the crossings of the two indicator lines catch every major cyclic move and the detrender itself can be used as the first step in more sophisticated analyses.
Recursive StochasticThe Self Referencing Stochastic Oscillator
The stochastic oscillator bring values in range of (0,100). This process is called Feature scaling or Unity-Based Normalization
When a function use recursion you can highlights cycles or create smoother results depending on various factors, this is the goal of a recursive stochastic.
For example : k = s(alpha*st+(1-alpha)*nz(k )) where st is the target source.
Using inputs with different scale level can modify the result of the indicator depending on which instrument it is applied, therefore the input must be normalized, here the price is first passed through a stochastic, then this result is used for the recursion.
In order to control the level of the recursion, weights are distributed using the alpha parameter. This parameter is in a range of (0,1), if alpha = 1, then the indicator act as a normal stochastic oscillator, if alpha = 0, then the indicator return na since the initial value for k = 0. The smaller the alpha parameter, the lower the correlation between the price and the indicator, but the indicator will look more periodic.
Comparison
Recursive Stochastic oscillator with alpha = 0.1 and bellow a classic oscillator (alpha = 1)
The use of recursion can both smooth the result and make it more reactive as well.
Filter As Source
It is possible to stabilize the indicator and make it less affected by outliers using a filter as input.
Lower alpha can be used in order to recover some reactivity, this will also lead to more periodic results (which are not inevitably correlated with price)
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Bollinger Breaks and Cycles Indicator - JDThe BBC indicator shows price in relation to the upper (in red) and lower (in green) Bollinger Bands
It highlights breaks in the Bands, where the 0-line represents a price equal to the band.
These breaks can either be used as take-profit points or as entry points, depending on trend direction.
Entries can be at the beginning of a break (eg. for impulse or continuation moves)
or at the end (mostly for expected trend reversals)
To find the best setups, the BBC should be accompanied by other indicators (preferably ones that focus on different aspects)
The oscilating line in the middle indicates market cycles
JD.
#NotTradingAdvice #DYOR
RSI Bollinger WaveTrend Cycle Multi Free TSPMulti indicator
Bollinger Band x RSI
Wave Trend
Cycles
Free users will like it :)
Fell free to like share comments... and check my other stuff :]
Schaff Trend CycleThis indicator was originally developed by Doug Schaff in the 1990s (published in 2008).
Stochastic CG Oscillator (Center of Gravity)Stochastic CG Oscillator (Center of Gravity) script.
This indicator was originally developed by John F. Ehlers (see his book `Cybernetic Analysis for Stocks and Futures`, Chapter 8: `Stochasticization and Fisherization of Indicators`).
DFT - Dominant Cycle Period 8-50 bars - John EhlerThis is the translation of discret cosine tranform (DCT) usage by John Ehler for finding dominant cycle period (DC).
The price is first filtered to remove aliasing noise(bellow 8 bars) and trend informations(above 50 bars), then the power is computed.
The trick here is to use a normalisation against the maximum power in order to get a good frequency resolution.
Current limitation in tradingview does not allow to display all of the periods, still the DC period is plot after beeing computed based on the center of gravity algo.
The DC period can be used to tune all of the indicators based on the cycles of the markets. For instance one can use this (DC period)/2 as an input for RSI.
Hope you find this of some interrest.
HurstCycles PeaksOnly way I found to plot hurst cycles. I gave up on anything other than daily chart.
Published on request.
HurstCycles ThroughsOnly way I found to plot hurst cycles. I gave up on anything other than daily chart.
Published on request.
Better RSI with bullish / bearish market cycle indicator This script improves the default RSI. First. it identifies regions of the RSI which are oversold and overbought by changing the color of RSI from white to red. Second, it adds additional reference lines at 20,40,50,60, and 80 to better gauge the RSI value. Finally, the coolest feature, the middle 50 line is used to indicate which cycle the price is currently at. A green color at the 50 line indicates a bullish cycle, a red color indicators a bearish cycle, and a white color indicates a neutral cycle.
The cycles are determined using the RSI as follows:
if RSI is overbought, cycle switches to bullish until RSI falls below 40, at which point it becomes neutral
if RSI is oversold, cycle switches bearish until RSI rises above 60, at which point it becomes neutral
a neutral cycle is exited at either overbought or oversold conditions
Very useful, please give it a try and let me know what you think
Ehlers Stochastic Cyber CycleEhlers Stochastic Cyber Cycle indicator script.
This indicator was originally developed by John F. Ehlers (see his book `Cybernetic Analysis for Stocks and Futures`, Chapter 8: `Stochasticization and Fisherization of Indicators`).
Ehlers Cyber CycleEhlers Cyber Cycle indicator script.
This indicator was originally developed by John F. Ehlers (see his book `Cybernetic Analysis for Stocks and Futures`, Chapter 4: `Trading the Cycle`).
TSP Cycles DoubleDouble Cycles
You can setup higher timeframe cycle period's as argument, default is M30
Cyclical TrackThe cyclical track is a simple momentum indicator, created to measuring the speed of prices
Hurst Exponent Market Phases [DW]This study is an experiment designed to identify market phases using changes in an approximate Hurst Exponent.
The exponent in this script is approximated using a simplified Rescaled Range method.
First, deviations are calculated for the specified period, then the specified period divided by 2, 4, 8, and 16.
Next, sums are taken of the deviations of each period, and the difference between the maximum and minimum sum gives the widest spread.
The rescaled range is calculated by dividing the widest spread by the standard deviation of price over the specified period.
The Hurst Exponent is then approximated by dividing log(rescaled range) by log(n).
The theory is that a system is persistent when the Hurst Exponent value is above 0.5, and antipersistent when the value is below 0.5.
The color scheme indicates 4 different phases I found to be significant in this formula:
- Stabilization Phase
- Destabilization Phase
- Chaos Increase Phase
- Chaos Decrease Phase
This script includes two visualization types to choose from:
- Bar Counter Mode, which displays the number of bars the exponent is consecutively in each phase.
- Hurst Approximation Mode, which displays the approximated exponent value.
Custom bar colors are included.
Please note: This is a rough estimate of the Hurst Exponent. It is not the actual exponent. Numerous approximations exist, and their results all differ slightly.
Madrid SinewaveThis implements the Even Better Sinewave indicator as described in the book Cycle Analysis for Traders by John F. Ehlers .
In the example I used 36 as the cycle to be analyzed and a second cycle with a shorter period, 9, the larger period tells where the dominant cycle is heading, and the faster cycle signals entry/exit points and reversals.
Ehlers Simple Cycle Indicator [LazyBear]One of the early cycle indicators from John Ehlers.
Ehlers suggests using this with ITrend (see linked PDF below). Osc/signal crosses identify entry/exit points.
Options page has the usual set of configurable params.
More info:
- Simple Cycle Indicator: www.mesasoftware.com
List of my public indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
Hurst Cycle Channel Clone [LazyBear]Cycle Channel is loosely based on Hurst's nested channels. Basic idea is to identify and highlight the shorter cycles, in the context of higher degree cycles.
This indicator plots the shorter term (red) & medium term (green) cycles as channels. Some things to note:
As you can see the red channel keeps moving with in the bounds of green channel. When green breaches red channel, it usually signifies extreme market condition.
Both red & green channels provide support/resistance levels. Also, the green channel provides S/R levels to the inner red channel.
Movement of red channel with reference to green highlights reversal points, reducing momentum et al. For ex., point "(x)" in the chart shows how red channel failed to reach the upper green channel line and highlighted the local top.
Use this just like other bands/channels. I have more indicators derived from this idea, will post them later.
Some more examples:
---------------------------------
MSFT 1M:
DXY 1M:
IWM 1M:
More info:
------------
cyclicwave.blogspot.com
List of my free indicators: bit.ly
List of my app-store indicators: blog.tradingview.com
(Support doc: bit.ly)
