Combo 2/20 EMA & CCI
This is another part of my research work, where I test a combination of two strategies, receiving a combined signal. In order to understand which indicator combinations work better, which work worse, as filters for trades. This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Commodity Channel Index (CCI) is best used with markets that display cyclical or seasonal characteristics, and is formulated to detect the beginning and ending of the cycles by incorporating a moving average together with a divisor that reflects both possible and actual trading ranges. The final index measures the deviation from normal, which indicates major changes in market trend.
Strategy tester settings:
Initial capital: 1000
Order size: 0.5
Commission: 0.1%
Other as default.
Indicator settings:
EMA Length: 50
CCI Length: 10
Fast MA Length: 15
Slow MA Length: 20
Other as default.
WARNING:
- For purpose educate only
- This script to change bars colors.
在腳本中搜尋"CCI"
CFB-Adaptive CCI w/ T3 Smoothing [Loxx]CFB-Adaptive CCI w/ T3 Smoothing is a CCI indicator with adaptive period inputs and T3 smoothing. Jurik's Composite Fractal Behavior is used to created dynamic period input.
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 Jurik Volty used in the Juirk Filter?
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.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included:
Bar coloring
Signals
Alerts
Double CCIWith this variant of the CCI indicator you have 2 CCIs. I call it convenience the fast and the slow.
The slow one has the default period of 20. The fast one has a lower value and will therefore also change his direction much faster.
I don't use this as a decisive indicator, but the fast one does indicate where the standard CCI might go and so you are already prepared for the decisive moment.
I've added a zero line so you can visually track whether the buyers or the sellers are predominant.
Between 0 and +100, as well as between 0 and -100 there is still a battle between buyers and sellers and it is better to wait a little longer before entering a trade.
From +100 to +250 I have colored the zone green; here the buyers are winning and it is a confirmation that you can safer enter the BUY.
From -100 to -250 it's colored red; here the sellers are firmly winning and it is a confirmation to go into a SELL.
Most values are adjustable via the settings and can be switched on or off.
This indicator is not intended to be used as the sole decision element, but rather to fine-tune your entry and exit points . Maybe wait a little longer than you normally would, but then be able to step in at the right time that there is enough volume in your desired direction.
Good luck with it and I would love feedback.
Thank you Tradingview-community.
SSL HYBRID AdvancedSSL HYBRID Advanced
SSL Hybrid is an Advanced version of the default SSL Hybrid by Mihkel00.
Multiple Indicators
MACD Crossover Signals
EMA 200
Bollinger Band
Bollinger Band Squeeze
ADX Crossover and ADX level
CCI Over Brought /Sold
Stochastic Over Brought /Sold
RSI Over Brought /Sold
CREDITS
QQE MOD byMihkel00
SSL Hybrid by Mihkel00
Waddah Attar Explosion by shayankm
Support Resistance LonesomeTheBlue
Indicators On Chart
QQE MOD is plotted as Dot below and above the candle and also as Background
QQE line is plotted and can be used as crossover to find trend. Flat movement of QQE is Sideways
Weak ADX is plotted as a Background color. Same can be verified using Bollinger band Squeeze.
EMA crossover can be plotted by selecting MTF MA(multi time frame moving average indicator) Area plot is provided.
CCI , Stochastic, RSI signals provided in the table option
WAE (volume indicator ) is shown in Table
EMA 200 is plotted and color Represents ADX level and direction. Plots on EMA 200 are ADX crossovers
MACD crossovers are represented by Triangles above and below Candles
Support Resistance levels are plotted (change settings)
Pivot Points are plotted (change settings)
Bollinger Bands Plotted
EMA 20 and EMA 50 plotted with AREA for additional confirmation
Buy: When the table option shows completely Blue signals in all indicators
Sell: When the table option shows completely Pink signals in all indicators
WARNING not recommended for lower time frames. Use at your own Risk.
Updates will be released shortly if any. please provide your suggestions to make it more functional indicator.
RSI & CCi SIGNAlUsing the RSA cross-indicator at points 70 and 30
Using the CCI cross indicator at points 100 and -100
Simultaneous use of RSA or CCI signal or both
Exit at 0.5% profit
3GBH - CCI + HMAsCommodity Channel Index w/ Hull Moving Average's.
Included in this indicator:
- CCI
- 3x HMA's that use the CCI as the source.
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User-friendly.
You can change all the inputs, they are labelled for ease-of-use.
You can toggle On/Off any or all of the options.
TSI HMA CCIHi!
This strategy has TSI and CCI indicators with the CCI being based on a HMA instead of the Price.
There is a number of conditions that must combine to create buy or sell signals, but it is basically a couple of MA crossovers.
The strategy opens new orders on each candle if the conditions are met, Either direction, so it is hedging.
It wont open new orders if there is a floating loss, and so is constantly attempting to hold a floating profit (drawup instead of drawdown)
But It has a StopLoss (set by user) for closing of losing orders, and it closes all orders in basket style when account is in profit to users set amount target profit.
Low commission set to simulate swap but Forex pairs generally dont have commission like the crypto exchanges do. So if you use this on cryptos, remember to increase the commission to your brokers amount.
Crypto users will likely find that because this opens so many orders the commission could erase its profits.
So i recommend this for Forex only, and perhaps, only NZDUSD 4H chart. other pairs, change settings for.
The strategy has settings for testing on target time spans, so you could test it on just Jan-Feb 2020 for example, if you want, or from Jan 2020 to present day.
Have Fun! Open Script for copy/paste/edit/publish your own version :)
Daytrade strategy RSI CCI EMA 4/8This strategy is designed for daytrade charts.
Its made from
EMA 4 / EMA 8 to check for crosses
RSI levels for overbough/oversold
CCI levels
For entry, we check first if the ema 4 crossed ema 8
Secondly we confirm by checking the level of RSI level
Finally we confirm with CCI level
If all of them are on the same page we enter.
For exit we have a fixed pip points system for TP/SL
TSI CCI Hull with profit$$$This is a modified version of @SeaSide420 TSI CCI Hull with profits exit on long and short order
ORIGINAL SCRIPT:
/// /// feel free to edit/improve and comment
Trend Lines for RSI, CCI, Momentum, OBVHello Traders!
After publishing Trend Lines for RSI yesterday, I realized that Trend Lines for more indicators needed by the traders. so I decided to make it for four different indicators: RSI, CCI, OBV, Momentum
In the indicator options you can choose the indicator from pull-down menu.
How it works?
- On each bar it finds last 10 higher and lower Pivot Points (PP) for the indicator.
- from first bar to 10. Pivot Point it searchs if a trend line is possible
- for each PP it starts searching from the last PP .
- it checks if drawing a trend line possible or not and also it's broken or not
- if it's broken then optionally it shows broken trend lines as dotted (or you can option not to see broken lines)
- if it finds a continues trend line then it stops searhing more and draw trend line, this is done by checking angles (I did this to make the script faster, otherwise you may get error because of it needs time more than .2sec)
- the script makes this process for each PP
- then shows the trend lines
P.S. it may need 3-10 seconds when you added the script to the chart at first (because of calculations)
Trend lines for CCI:
Trend Lines for OBV
Trend Lines for Momentum:
You may want to watch how Trend Lines script works (that was made for RSI)
s3.tradingview.com
If you still didn't see Trend Lines v2 then visit:
All Comments are welcome..
Enjoy!
TSI CCI HullThis is TSI and CCI combined. The CCI is customized and is using HullMA, but the TSI is default TSI
For use with the HMAv420 indicator, to form trading strategy based on the 3 indicators.
Best as all 3 indicators used on 3 timeframes at once, ie 1m 5m 1H
Donochian CCISo this indicator have the following:
1. MTF CCI
2. donochian channel MTF both non repaint mode
buliish and bearish zone determine by ratio of the the donochian cahnnel
enter or exit can be either the bullish or bearish change of color or by cross over or under of the CCI
or combination of both
The high max and low max of the donochian channel show in hilated bar
MACD+CCI Strategya simple strategy based on Joseph Nemeth MACD+CCI strategy
Reference reading: sites.google.com
VW EMA CCI + TTM Volume Weighted EMA CCI + TTM squeeze in one indicator
Credit goes to SpreadEagle 71 for the CCI and Greeny for the TTM
RIZ OBV with coloured CCIThis ones useful for spotting divergence on OBV, and also includes CCI to show overbought and oversold areas in the volume. I've coloured the OBV bar with the CCI levels. Look for divergence (best results on 5min chart I believe) with this and you can spot where to sell if a second peak is not supported by volume, also shows where the big guns are dumping lots of volume!
A volume study is always a good addition to any analysis I feel, and this is one of my day to day always on indicators.
Trend and Entry CCI ST15This is a T3 CCI with a fast and slow line as well as extreme lines, a -15,15 filter to make zero line rejections and crosses more mechanical and help weed out whipsaw. I will probably update description in the future and get into more detail about how the indicator is used but for now if you want more info look up woodie CCI patterns :) Good Luck!!
HTF Oscillators RSI/ROC/MFI/CCI/AO - Dynamic SmoothingThe Interplay of Time Frames: A Balanced View
Navigating the markets often involves interpreting trends from multiple angles. The HTF Oscillators with Dynamic Smoothing indicator enables you to do just that. This tool provides the option to integrate smoothed oscillator readings from Higher Time Frames (HTF) into lower time frame charts, such as a 1-minute chart. By doing so, the indicator offers a balanced viewpoint that bridges the gap between micro and macro perspectives, helping you make informed decisions without losing sight of the broader market context.
Features
Multi-Oscillator Support
Choose from a range of popular oscillators like the Relative Strength Index (RSI), Rate of Change (ROC), Money Flow Index (MFI), Commodity Channel Index (CCI), and Awesome Oscillator (AO). These oscillators are commonly used as foundational building blocks in trading strategy scripts by traders worldwide. Switch effortlessly between them, depending on your trading strategy and requirements. To maintain consistency and a familiar user experience, our script adopts the same visual aesthetics that you'll find in Pine Script indicators on TradingView: a sleek purple line for the oscillator and a transparent band filling. These visual elements are not only pleasing to the eye but also widely appreciated by the trading community.
Dynamic Smoothing
The unique dynamic smoothing feature calculates a smoothing factor based on the ratio of minutes between the Higher Time Frame (HTF) and your current time frame. This provides a sleek and responsive oscillator line that still holds the weight of the longer trend. One of the significant advantages of this feature is user experience; when you change your time frame, the HTF-values in your settings will remain consistent. This ensures that you can easily switch between different time frames without losing the insights provided by your selected HTF.
Visual Aids
Visual cues are an essential part of any trading strategy. The indicator not only plots signals to mark overbought and oversold conditions based on the dynamically smoothed oscillator but also provides you with the flexibility to customize your visual experience. You have the option to toggle on/off the display of these signals depending on your specific needs. Additionally, bands can be displayed at overbought and oversold levels, along with a reference middle line. If you switch between different oscillators (available in the parameter settings), remember to manually adjust the bands in the input settings to ensure signals matches with the type of oscillator to your liking.
User-Friendly Settings
We've grouped related settings together, making it easier for you to find what you're looking for. Adjust the oscillator type, length of bars, smoothing settings, and more with just a few clicks.
Information Table
A standout feature of this indicator is the real-time information table, which displays the values of all selected oscillators based on your specified Higher Time Frame (HTF) settings. This can be particularly useful for traders who depend on multiple indicators for their decision-making process. The data presented in the table is synchronized with the HTF options you've configured in the input settings, allowing for a more efficient and quick scan of values from higher time frames.
Educational Corner: The Power of the Information Table and Customization
The table incorporated into this indicator isn't just eye-candy; it's a practical tool designed to elevate your trading strategy. It dynamically displays real-time values of various oscillators for the HTF you've chosen. This is an exemplary use of TradingView's scripting capabilities to blend multiple indicators into a single visual panel, streamlining your analysis and decision-making process.
But here's the best part: You're not limited to what we've created. With some basic understanding of TradingView's scripting language, Pine Script, you can easily adapt this table to include different indicators that suit your unique trading style. The logic in the script is modular and can serve as a foundation for your own customized trading dashboard. So, go ahead, get creative and explore new combinations of indicators that will help you excel in your trading endeavors!
You no longer have to toggle between different charts or indicators to get the information you need; it's all there in one neatly organized table. We encourage you to tap into this feature and make it your own, empowering your trading like never before.
By doing so, you not only gain a more comprehensive toolset, but you also engage more deeply with your trading strategy, understanding its nuances and, ultimately, making more informed decisions.
Conclusion
The HTF Oscillators with Dynamic Smoothing is a versatile and powerful tool that brings together the best of both worlds: the perspective of higher time frames and the granularity of shorter ones. Its feature-rich setting options and real-time information table make it a potential useful addition to your trading toolkit.
Remember, while this indicator offers a comprehensive and smarter way to look at the markets, it is not a foolproof method for predicting market movements. Always use it in conjunction with other analysis methods and risk management strategies.
Supertrend ANY INDICATOR (RSI, MFI, CCI, etc.) + Range FilterThis indicator will generate a supertrend of your chosen configuration on any of the following indicators:
RSI
MFI
Accum/Dist
Momentum
On Balance Volume
CCI
There is also a RANGE FILTER built into the scripts so that you can smooth the indicators for the supertrend. This is an optional configuration in the settings. Also, you can change the oversold/overbought bounds in the settings (they are removed entirely for indicators without bounds).
If you find this indicator useful, please boost it and follow! I am open to suggestions for adding new indicators to this script, it's very simple to add new ones, just suggest them in the comments.
Fusion Oscillator (COMBINED RSI+MFI+MACD+CCI+TSI+RVI)The Fusion Oscillator aggregates several extremely-similar directional oscillators (RSI, MFI, MACD, CCI, TSI, RVI) into one average to visualize indicator agreement. To do this, I normalized several oscillators between to ensure equal weight.
The white line is the directional oscillator . The yellow line (turned off) is the nondirectional oscillator - namely, the ADX and ATR - this determines the buy/sell signals in conjunction with overbought/oversold levels for the directional oscillator.
The overall length is the sensitivity of the oscillator, not the lookback period. The maximum that works on the default settings is 3. Higher means less sensitive and more accurate.
I hope you all find this useful!
Quick and Simple - WPR+RSI+CCITake a look.
Couple of confluencial reversal signals from popular indicators (W%R, RSI & CCI). I can only say this shows how random the "stanard tools" are and how the market makers "play" these kind of tools to their advantage.
That said. It's better tha average, but not top-class, so expect to have to take signals with other confluence. DON'T take the plots or signals as buy / sell signals, they are just confluencial movements from these indicators based on how they should be "traditionally" used. Instead, use it as a guide as to what other traders may be thinking, or as a pull-back identifier.
Included 100 period ema as basic trend filter.
Not my normal type of script + been away for some time so be kind, lol :)
You might find it useful however so sharing.
More stuff to follow :)
Suchit RSI CCISuchit RSI CCI strategy uses the Relative Strength Index and Commodity Channel Index levels and their movement for buy and sell calls
