Standard deviation channel of linear regression distance [AbAh]The indicator calculates the distance between linear regression line and the data point (price) as a percentage , then calculates the standard deviation for the linear regression distance , then draw the channel of two lines depending on the values of standard deviation .
///////// How to use ////////////////
1 - for Best result , indicator should be used on 2H frame Time of less : like 1H or 30 min
2 - The upper line and the lower line, both play a role as a support and resistance area, when the price bounces from the upper zone or lower zone, there is a high probability that it will move to the other line.
3 - The price breakout of one of the lower or upper lines may indicate a major price movement coming in the direction of the breakout
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Циклический анализ
Relative Volume Force IndexThis indicator can anticipate the market movements. Its posible because it calculates how much force (volume) it's necessary to move the price up or down. If it's necessary a lot of volume to move the price a little it's a reversion signal, but if a little volume could change the price whit elevate volatility, it's signal of reversion too. The indicator plots red if the market is down, and green if it's up, the size and the color of the bars cand demonstrate the movement relative force. Does it by the configurable averages. Not works well whit poor liquidity.
Pi Cycle Indicators Comparison IndicatorThere are now 3 Pi Cycle Indicators that I am aware of; the original, improved**, and bottom.
This indicator attempts to provide all three indicators in a dingle, easy to view script.
I coded this script to displace the moving averages above and below the price bars for easy viewing. This was accomplished by placing a scaling factor (/# or *#) at the end of the ta.sma or ta.ema functions.
A vertical arrow, purposely posing as a short vertical line, marks the crossing of the long and short MAs for each indicator. These are color coded to match their respective indicators and the long and short MAs are similarly color coded for easy differentiation.
The red colored MAs and arrows above the price line are the Improved Pi-Cycle Top Indicator.
The green colored MAs and arrows below the price line are the Original Pi-Cycle Top Indicator.
The blue colored MAs and arrows below the green lines and price line are the Pi-Cycle Bottom Indicator.
One last feature of the chart is the use of the location function to enable easy comparison of the crossings of each indicator to the indicator itself and to the price. This can be accomplished simply by moving the chart up and down.
**{I should note that while researching this I found that BitcoinMamo turns out to have beat me to the punch on the Improved Indicator Long.Short and Multiplier numbers. He should therefor get the credit for that}
90min cyclesI did this little script to help me with the cycle I hope it will help some of you too !
For default, I have made 90 min cycle, but you can change it easily on the settings if you prefer an other time interval because it is really subjectif.
By default the cycle will begin at midnight from YOUR local time, but this can be a little annoying when you want for example to make it begin at midnght from NY or London without changing the UTC of your chart (if you still want to have your hour displayed normally).
I couldn't find an indicator to help me do that so I added a little setting which allow you to move the start hour of your cycle (so you will have to do some math to move it accordingly to what you want but that's okay ;) ).
That way you can choose the interval you like AND when it begin !
Edm + LET + SessionThis script is adressed to the LIT trader or for those of you who trade with session ( between different hour)
It will add to the chart the differnet session :
- asian session (here color aqua (blue))
- frankfurt
- London
- MMM1
- NYTRAP (New York Trap)
- an New York
You can choose in the settings which one you want to see and how you want to see it ( boxes or background color) which helps a lot when you open your chart to know where you are what you should expect if your plan is based on session.
I put some default hours but if you want less session and change the hours you can easily do that in the settings too.
It will also show you as a label the EDM (which is simply a divergence with the RSI) that occured 5 candle after it happend, it can be very useful for those of you who trade with this confluence, you will directly have it on your chart.
If you don't use it, you can also disable it in the settings.
The LET (which are a rebund on the EMA) are shown like the EDM and can be disable too if you don't use it, they will here depend of the EDM (i.e the script will look for a LET only after an EDM occured, if there is no EDM, they will not be visible).
I have tried to make the most stuff as an input ( can be modified in the settings) to allow each and everyone to be able to adapt it to what you want to see or not see on your charts.
Hope this help some of you and don't hesitate to send some feedback if it does !
RVL Unreal Edge (concept build)Designed with a purpose, this script was intended for use by bots automating trading of XLM using a 6hr timeframe.
It's now being shaped into fantastic indicator on its own with very actionable signals and essentially zero lag. Much of the power behind it is derived from standard deviation/mean reversion strategies, and John Ehlers' incredible CG oscillator.
John Ehlers was an electrical engineer and Raytheon employee who began trading in the 1970's. He is best known for his work creating super-smoothing algorithms and methods of analysing cycle length and behaviour, and his work in the field of zero-lag indicators - indicators that don't follow the price action but are in fact capable of leading it actionably and responding with essentially zero lag.
By approaching the price action as a sine wave with a demonstrably fractal nature and thus subject to the phenomena of spectral dilation, Ehler's makes a number of important advancements. His CG indicator is derived from calculations typically used to derive the centre of gravity in a physical object. It effectively works as a band-pass filter, and is possibly one of the very best leading indicators available.
This script catches breakouts, tops and bottoms, leads reversals and the start/end of cycles. It functions as an excellent way to secure entries/exits around support and resistance. There are some methods of charting support and resistance built into the script currently, and lots more to add. One of the next major adjustments will be to hide or reduce the strength of buy/sell signals when price might be overextended (seen by the larger triangles, and + x symbols - these signal that a reversion back to the mean may be imminent).
The early version of this script had a 65% winrate and fantastic profit factor.
Stay tuned!
Support/Resistance:
The Ichimoku cloud, in this case has been custom tuned to the XLM 6 hour chart.
The 42 period EMA is a moving average that gets notable reactions from the price.
The 200 period EMA is the same.
The automatic Pitchfork almost always provides relevant Fibonacci based levels, but can sometimes require manually flicking through a few different presets to find a combination that fits the current price action. This will be automated in future.
RVL Unreal Edge (concept build)Designed with a purpose, this script was intended for use by bots automating trading of XLM using a 6hr timeframe.
However the script has turned out to be a fantastic indicator on its own, and much of the power behind it is derived from John Ehler's incredible CG oscillator.
John Ehler was an electrical engineer, a Raytheon employee who began trading in the 1970's. He is best known for his work creating super-smoothing algorithms and methods of analysing cycle length and behaviour in price action, and his work in the field of zero-lag indicators - indicators that don't follow the price action, but are in fact capable of leading it actionably, and responding with essentially zero lag.
By approaching the price action as a sine wave with demonstrably a fractal nature, Ehler's makes a number of important advancements. His CG indicator is derived from calculations typically used to derive the centre of gravity in a physical object. It effectively works as a band-pass filter and is possibly one of the very best leading indicators avaliable.
candles by samThis indicator shows bearish and bullish candle in series.
Describes the sequence of bullish candles higher highs and bearish lower low ones
Purple represents bullish sequence and yellow represents bearish .
"A" in the code refers to bearish seq .
"B" in the code refers to bullish seq .
Pi Cycle Bottom IndicatorBack in June 2021, I was able to find two moving averages that crossed when Bitcoin reached it's cycle bottom, similar to Philip Swift's Pi-Cycle Top indicator.
The moving average pair used here was the x0.475 multiple of the 471 MA and the 150 EMA ( EMA to take into account of short term volatility ).
I have a more in-depth analysis and explanation of my findings on my medium page .
Trader Dončić.
Socrate's Bottom FinderENGLISH :
Hi everybody,
This indicator will give you the market bottoms with remarkable accuracy.
/!\ Be aware that the indicator cannot know the current economic situation and that in the event of a major crisis, it can signal a market bottom despite the decline not being over. /!\
How to read it ?
It is composed of two visual sections:
- The first section materialized by the white line is a "treshhold" which gives the current trend of the week. It is used to filter most of the "fake signals"
- The second section, materialized by a green and red band, gives the strength of the price trend. If for example the trend is rather bullish, this bar will turn green, the opposit will produce red. An "opportunity" signal will appear when the optimal conditions are met to define a market bottom. Before an opportunity signal there will always be an "Surrender" signal, wich means the trend has weakened and the bottom is near in time.
Special Recommandation :
- The best results are on 1W, 3D, 1D. The indicator work on lower TF but it's not his purpose and you may drop significantly your W/L rate.
- Avoid stocks/crypto with poor stability in the very long time, a good hint is to look after thoses who mostly are above SMA200 on weekly TF.
- Avoid cyclical stock, as they tend to bounce up and down way to often.
Please do your own diligence. Trading may conduct you to loose capital.
Apply your own trading strategy :)
-----------------------------------------------------------------------------------------------------------------------------
FRANCAIS :
Salut tout le monde,
Cet indicateur vous donnera les creux du marché avec une précision remarquable.
/!\ Sachez que l'indicateur ne peut pas connaître la situation économique actuelle et qu'en cas de crise majeure, il peut signaler un creux de marché même si la baisse n'est pas terminée. /!\
Comment le lire ?
Il est composé de deux sections visuelles :
- La première section matérialisée par la ligne blanche est un « seuil » qui donne la tendance actuelle de la semaine. Il est utilisé pour filtrer la plupart des "faux signaux"
- La deuxième section, matérialisée par une bande verte et rouge, donne la force de la tendance des prix. Si par exemple la tendance est plutôt haussière, cette barre deviendra verte, l'inverse produira du rouge. Un signal "d'opportunité" apparaîtra lorsque les conditions optimales seront réunies pour définir un creux de marché. Avant un signal d'opportunité, il y aura toujours un signal "Abandon", ce qui signifie que la tendance s'est affaiblie et que le creux est proche dans le temps.
Recommandations spéciales :
- Les meilleurs résultats sont sur 1W, 3D, 1D. L'indicateur fonctionne sur des TF plus faibles mais ce n'est pas son but et vous risquez de faire chuter considérablement votre ratio de W/L.
- Évitez les stocks/crypto avec une faible stabilité sur le long terme, un bon indice est de cibler ceux qui sont majoritairement (dans leur historique) au-dessus de leur SMA200 en TF hebdomadaire.
- Prioriser les actifs de type "HyperGrowth", l'indicateur fonctionne moins bien avec les cycliques
Veuillez faire vos propres recherches en parallèle. Le trading pouvant vous conduire à perdre du capital.
Appliquez à cet indicateur votre propre stratégie :)
Adaptivity: Measures of Dominant Cycles and Price Trend [Loxx]Adaptivity: Measures of Dominant Cycles and Price Trend is an indicator that outputs adaptive lengths using various methods for dominant cycle and price trend timeframe adaptivity. While the information output from this indicator might be useful for the average trader in one off circumstances, this indicator is really meant for those need a quick comparison of dynamic length outputs who wish to fine turn algorithms and/or create adaptive indicators.
This indicator compares adaptive output lengths of all publicly known adaptive measures. Additional adaptive measures will be added as they are discovered and made public.
The first released of this indicator includes 6 measures. An additional three measures will be added with updates. Please check back regularly for new measures.
Ehers:
Autocorrelation Periodogram
Band-pass
Instantaneous Cycle
Hilbert Transformer
Dual Differentiator
Phase Accumulation (future release)
Homodyne (future release)
Jurik:
Composite Fractal Behavior (CFB)
Adam White:
Veritical Horizontal Filter (VHF) (future release)
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman's adaptive moving average (KAMA) and Tushar Chande's variable index dynamic average (VIDYA) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is this Hilbert Transformer?
An analytic signal allows for time-variable parameters and is a generalization of the phasor concept, which is restricted to time-invariant amplitude, phase, and frequency. The analytic representation of a real-valued function or signal facilitates many mathematical manipulations of the signal. For example, computing the phase of a signal or the power in the wave is much simpler using analytic signals.
The Hilbert transformer is the technique to create an analytic signal from a real one. The conventional Hilbert transformer is theoretically an infinite-length FIR filter. Even when the filter length is truncated to a useful but finite length, the induced lag is far too large to make the transformer useful for trading.
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, pages 186-187:
"I want to emphasize that the only reason for including this section is for completeness. Unless you are interested in research, I suggest you skip this section entirely. To further emphasize my point, do not use the code for trading. A vastly superior approach to compute the dominant cycle in the price data is the autocorrelation periodogram. The code is included because the reader may be able to capitalize on the algorithms in a way that I do not see. All the algorithms encapsulated in the code operate reasonably well on theoretical waveforms that have no noise component. My conjecture at this time is that the sample-to-sample noise simply swamps the computation of the rate change of phase, and therefore the resulting calculations to find the dominant cycle are basically worthless.The imaginary component of the Hilbert transformer cannot be smoothed as was done in the Hilbert transformer indicator because the smoothing destroys the orthogonality of the imaginary component."
What is the Dual Differentiator, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 187:
"The first algorithm to compute the dominant cycle is called the dual differentiator. In this case, the phase angle is computed from the analytic signal as the arctangent of the ratio of the imaginary component to the real component. Further, the angular frequency is defined as the rate change of phase. We can use these facts to derive the cycle period."
What is the Phase Accumulation, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 189:
"The next algorithm to compute the dominant cycle is the phase accumulation method. The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle's worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio."
What is the Homodyne, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 192:
"The third algorithm for computing the dominant cycle is the homodyne approach. Homodyne means the signal is multiplied by itself. More precisely, we want to multiply the signal of the current bar with the complex value of the signal one bar ago. The complex conjugate is, by definition, a complex number whose sign of the imaginary component has been reversed."
What is the Instantaneous Cycle?
The Instantaneous Cycle Period Measurement was authored by John Ehlers; it is built upon his Hilbert Transform Indicator.
From his Ehlers' book Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading by John F. Ehlers, 2004, page 107:
"It is obvious that cycles exist in the market. They can be found on any chart by the most casual observer. What is not so clear is how to identify those cycles in real time and how to take advantage of their existence. When Welles Wilder first introduced the relative strength index (rsi), I was curious as to why he selected 14 bars as the basis of his calculations. I reasoned that if i knew the correct market conditions, then i could make indicators such as the rsi adaptive to those conditions. Cycles were the answer. I knew cycles could be measured. Once i had the cyclic measurement, a host of automatically adaptive indicators could follow.
Measurement of market cycles is not easy. The signal-to-noise ratio is often very low, making measurement difficult even using a good measurement technique. Additionally, the measurements theoretically involve simultaneously solving a triple infinity of parameter values. The parameters required for the general solutions were frequency, amplitude, and phase. Some standard engineering tools, like fast fourier transforms (ffs), are simply not appropriate for measuring market cycles because ffts cannot simultaneously meet the stationarity constraints and produce results with reasonable resolution. Therefore i introduced maximum entropy spectral analysis (mesa) for the measurement of market cycles. This approach, originally developed to interpret seismographic information for oil exploration, produces high-resolution outputs with an exceptionally short amount of information. A short data length improves the probability of having nearly stationary data. Stationary data means that frequency and amplitude are constant over the length of the data. I noticed over the years that the cycles were ephemeral. Their periods would be continuously increasing and decreasing. Their amplitudes also were changing, giving variable signal-to-noise ratio conditions. Although all this is going on with the cyclic components, the enduring characteristic is that generally only one tradable cycle at a time is present for the data set being used. I prefer the term dominant cycle to denote that one component. The assumption that there is only one cycle in the data collapses the difficulty of the measurement process dramatically."
What is the Band-pass Cycle?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 47:
"Perhaps the least appreciated and most underutilized filter in technical analysis is the band-pass filter. The band-pass filter simultaneously diminishes the amplitude at low frequencies, qualifying it as a detrender, and diminishes the amplitude at high frequencies, qualifying it as a data smoother. It passes only those frequency components from input to output in which the trader is interested. The filtering produced by a band-pass filter is superior because the rejection in the stop bands is related to its bandwidth. The degree of rejection of undesired frequency components is called selectivity. The band-stop filter is the dual of the band-pass filter. It rejects a band of frequency components as a notch at the output and passes all other frequency components virtually unattenuated. Since the bandwidth of the deep rejection in the notch is relatively narrow and since the spectrum of market cycles is relatively broad due to systemic noise, the band-stop filter has little application in trading."
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 59:
"The band-pass filter can be used as a relatively simple measurement of the dominant cycle. A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero crossing of the indicator marks a half cycle period. We can establish the dominant cycle period as twice the spacing between successive zero crossings."
What is Composite Fractal Behavior (CFB)?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Long and Short Signal_1hours [zavaUnni]This indicator is available in the 1 hour chart.
The Stochastic value of 1 hour of 3 types of length was requested, summed, and then the value was derived.
The blue line is the K and the orange line is D of the Stochastic.
The default is Stochastic, but when RSI is selected in the settings, it can be viewed as the relative strength index of the Stochastic.
If the K value crosses down at 100, a short signal is generated
Cross up below -100 and you'll get a long signal.
You can receive a ready signal by checking Position Ready in Settings.
Short ready signal when the k line goes up to 100.
Long ready signal when the k line goes below -100.
A small spread value of the candle relative to the volume is the principle that resistance has occurred.
Displayed the resistance value based on the average value of the last 100 candles.
The higher the value of the red Histogram, the stronger the selling.
The lower the value of the green Histogram value, the stronger the buying .
The gray histogram is when there's no buying or selling pressure.
BTC Pi MultipleThe Pi Multiple is a function of 350 and 111-day moving average. When both intersect and the 111-day MA crosses above, it has historically coincided with a cycle top with a 3-day margin.
With the Pi Multiple, this intersection is visible when the line crosses zero upwards.
The indicator is called the Pi Multiple because 350/111 is close to Pi. It is based on the Pi Cycle Top Indicator developed by Philip Swift and has been modified for better readability by David Bertho.
Intraday rejection levels3 supports, 3 resistances and an equilibrium price per day displayed at 9am (GMT+2), calculated on the dynamic study of the market at its opening over a certain period that we could qualify as "first opening interventions"
Method: We are interested in the first reaction of the market when it discovers one of the levels.
The red and green zones (from levels R2 to R3) are the zones of rejections/daily overextensions with large RRs of which we will appreciate a rejection for the US opening (where the zones are more opaque, the Killzone!), because the session US is known to either accompany the London session or completely break the trend.
Equilibrium, on the other hand, is a retest zone that can be traded in several directions, ideal for capturing the first retracement / retest of a recently broken structure:
Activate "EL" to display an ideally early morning rejection area so levels can be scalped! They correspond to opportunistic areas above the high and below the low of a custom Asian session ignoring part of the London open - which I consider to be liquidity :):
FIRST SETUP: Confluence R1/R2 with the EL!
SECOND SETUP: The price does not frequent the R2/R3 zone during London but only during the killzone:
Anticipate rejection zones, put them in confluence to find the best opportunity!
Tips:
I'm only interested in the first reaction on these levels
You can measure the difference between R1 and EQ: on average on the EURUSD it must be 20 to 30 pips! Apart from these values, I deduce that the market is unbalanced: I lower my risk on my scalps and I am more cautious.
It is possible to use the previous day's levels to look for correlations
Ideally, the Asia range Custom should not take the high/low of the day before (see "LIquidity maps" indicator on our profile for optimal use)
As an option you can display the standard pivot, and activate the "crypto" mode to be able to use it on your favorite crypto :)
More than three Candles in a roww Changes color of more than three candles in a row, when there are consecutive candles of same color green or red
OhManLan Golden CloudThis indicator is a modification of the popular Ichimoku indicator, build high/low channels using the Golden Ratio, Volume-weighted average price allows smoother components.
high/low channels moves based on Fibo Levels (Golden Ratio: 1.618).
- Settings -
The indicator can be adjusted to your needs.
- How to use -
OhManLan Golden can be used a Support/Resistance , Stop loss, Trailing stop and Price target.
Volume-weighted average price allows smoother components.
Can be used with other indicators such as Moving Average Convergence Divergence (MACD).
Adaptive, Double Jurik Filter Moving Average (AJFMA) [Loxx]Adaptive, Double Jurik Filter Moving Average (AJFMA) is moving average like Jurik Moving Average but with the addition of double smoothing and adaptive length (Autocorrelation Periodogram Algorithm) and power/volatility {Juirk Volty) inputs to further reduce noise and identify trends.
What is Jurik Volty?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Double calculation of AJFMA for even smoother results
Adaptive Look-back/Volatility Phase Change Index on Jurik [Loxx]Adaptive Look-back, Adaptive Volatility Phase Change Index on Jurik is a Phase Change Index but with adaptive length and volatility inputs to reduce phase change noise and better identify trends. This is an invese indicator which means that small values on the oscillator indicate bullish sentiment and higher values on the oscillator indicate bearish sentiment
What is the Phase Change Index?
Based on the M.H. Pee's TASC article "Phase Change Index".
Prices at any time can be up, down, or unchanged. A period where market prices remain relatively unchanged is referred to as a consolidation. A period that witnesses relatively higher prices is referred to as an uptrend, while a period of relatively lower prices is called a downtrend.
The Phase Change Index (PCI) is an indicator designed specifically to detect changes in market phases.
This indicator is made as he describes it with one deviation: if we follow his formula to the letter then the "trend" is inverted to the actual market trend. Because of that an option to display inverted (and more logical) values is added.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
That's why investors, banks and institutions worldwide ask for the Jurik Research Moving Average ( JMA ). You may apply it just as you would any other popular moving average. However, JMA's improved timing and smoothness will astound you.
What is adaptive Jurik volatility
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers, 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average (KAMA) and Tushar Chande’s variable index dynamic average (VIDYA) adapt to changes in volatility. By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic, relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
-Your choice of length input calculation, either fixed or adaptive cycle
-Invert the signal to match the trend
-Bar coloring to paint the trend
Happy trading!
Ehlers Autocorrelation Periodogram [Loxx]Ehlers Autocorrelation Periodogram contains two versions of Ehlers Autocorrelation Periodogram Algorithm. This indicator is meant to supplement adaptive cycle indicators that myself and others have published on Trading View, will continue to publish on Trading View. These are fast-loading, low-overhead, streamlined, exact replicas of Ehlers' work without any other adjustments or inputs.
Versions:
- 2013, Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers
- 2016, TASC September, "Measuring Market Cycles"
Description
The Ehlers Autocorrelation study is a technical indicator used in the calculation of John F. Ehlers’s Autocorrelation Periodogram. Its main purpose is to eliminate noise from the price data, reduce effects of the “spectral dilation” phenomenon, and reveal dominant cycle periods. The spectral dilation has been discussed in several studies by John F. Ehlers; for more information on this, refer to sources in the "Further Reading" section.
As the first step, Autocorrelation uses Mr. Ehlers’s previous installment, Ehlers Roofing Filter, in order to enhance the signal-to-noise ratio and neutralize the spectral dilation. This filter is based on aerospace analog filters and when applied to market data, it attempts to only pass spectral components whose periods are between 10 and 48 bars.
Autocorrelation is then applied to the filtered data: as its name implies, this function correlates the data with itself a certain period back. As with other correlation techniques, the value of +1 would signify the perfect correlation and -1, the perfect anti-correlation.
Using values of Autocorrelation in Thermo Mode may help you reveal the cycle periods within which the data is best correlated (or anti-correlated) with itself. Those periods are displayed in the extreme colors (orange) while areas of intermediate colors mark periods of less useful cycles.
What is an adaptive cycle, and what is the Autocorrelation Periodogram Algorithm?
From his Ehlers' book mentioned above, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator.This look-back period is commonly a fixed value. However, since the measured cycle period is changing, as we have seen in previous chapters, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
How to use this indicator
The point of the Ehlers Autocorrelation Periodogram Algorithm is to dynamically set a period between a minimum and a maximum period length. While I leave the exact explanation of the mechanic to Dr. Ehlers’s book, for all practical intents and purposes, in my opinion, the punchline of this method is to attempt to remove a massive source of overfitting from trading system creation–namely specifying a look-back period. SMA of 50 days? 100 days? 200 days? Well, theoretically, this algorithm takes that possibility of overfitting out of your hands. Simply, specify an upper and lower bound for your look-back, and it does the rest. In addition, this indicator tells you when its best to use adaptive cycle inputs for your other indicators.
Usage Example 1
Let's say you're using "Adaptive Qualitative Quantitative Estimation (QQE) ". This indicator has the option of adaptive cycle inputs. When the "Ehlers Autocorrelation Periodogram " shows a period of high correlation that adaptive cycle inputs work best during that period.
Usage Example 2
Check where the dominant cycle line lines, grab that output number and inject it into your other standard indicators for the length input.
Ehlers Adaptive Relative Strength Index (RSI) [Loxx]Ehlers Adaptive Relative Strength Index (RSI) is an implementation of RSI using Ehlers Autocorrelation Periodogram Algorithm to derive the length input for RSI. Other implementations of Ehers Adaptive RSI rely on the inferior Hilbert Transformer derive the dominant cycle.
In his book "Cycle Analytics for Traders Advanced Technical Trading Concepts", John F. Ehlers describes an implementation for Adaptive Relative Strength Index in order to solve for varying length inputs into the classic RSI equation.
What is an adaptive cycle, and what is the Autocorrelation Periodogram Algorithm?
From his Ehlers' book mentioned above, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average (KAMA) and Tushar Chande’s variable index dynamic average (VIDYA) adapt to changes in volatility. By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic, relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator.This look-back period is commonly a fixed value. However, since the measured cycle period is changing, as we have seen in previous chapters, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the autocorrelation periodogram algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is Adaptive RSI?
From his Ehlers' book mentioned above, page 137:
"The adaptive RSI starts with the computation of the dominant cycle using the autocorrelation periodogram approach. Since the objective is to use only those frequency components passed by the roofing filter, the variable "filt" is used as a data input rather than closing prices. Rather than independently taking the averages of the numerator and denominator, I chose to perform smoothing on the ratio using the SuperSmoother filter. The coefficients for the SuperSmoother filters have previously been computed in the dominant cycle measurement part of the code."
Happy trading!
Buying power against Bitcoin and EthereumI created a simple tool where you can input your capital (in USD) and it will track your buying power against Bitcoin and Ethereum.
A handy tool for Dollar Cost Averaging and trend following systems.
Default value: You have 1000$
Formula: Buying power = Capital / Underlying assets
Adaptive Qualitative Quantitative Estimation (QQE) [Loxx]Adaptive QQE is a fixed and cycle adaptive version of the popular Qualitative Quantitative Estimation (QQE) used by forex traders. This indicator includes varoius types of RSI caculations and adaptive cycle measurements to find tune your signal.
Qualitative Quantitative Estimation (QQE):
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index (RSI) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
Wilders' RSI:
The Relative Strength Index ( RSI ) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI , when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
RSX RSI:
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
Rapid RSI:
Rapid RSI Indicator, from Ian Copsey's article in the October 2006 issue of Stocks & Commodities magazine.
RapidRSI resembles Wilder's RSI , but uses a SMA instead of a WilderMA for internal smoothing of price change accumulators.
VHF Adaptive Cycle:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Band-pass Adaptive Cycle:
Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode.
There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility.
We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month.
When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth.
Included:
-Toggle on/off bar coloring
-Customize RSI signal using fixed, VHF Adaptive, and Band-pass Adaptive calculations
-Choose from three different RSI types
Visuals:
-Red/Green line is the moving average of RSI
-Thin white line is the fast trend
-Dotted yellow line is the slow trend
Happy trading!
Trend IdentifierTrend Identifier for 1D BTC.USD
It smoothens a closely following moving average into a polynomial like plot.
And assumes 4 stage cycles based on the first and second derivatives.
Green: Bull / Exponential Rise
Yellow: Distribution
Red: Bear / Exponential Drop
Blue: Accumulation
Red --> Blue --> Green: indicates the start of a bull market
Green --> Yellow --> Red: indicates the start of a bear market
Green --> Yellow: Start of a distribution phase, take profits
Red --> Blue: Start of a accumulation phase, DCA
