[blackcat] L2 Ehlers Autocorrelation IndicatorLevel: 2
Background
John F. Ehlers introduced Autocorrelation Indicator in his "Cycle Analytics for Traders" chapter 8 on 2013.
Function
If we correlate a waveform composed of perfectly random numbers by itself, the correlation will be perfect. However, if we lag one of the data streams by just one bar, the correlation will be dramatically reduced. In a long memory process with normally distributed random numbers the autocorrelation follows the power law.
One of the underlying principles of technical analysis is that market data do not follow this power law of an efficient market, and we therefore can extract information from the partial correlation of the autocorrelation function. For example, assume the data being examined is a perfect sine wave whose period is 20 bars. The autocorrelation with zero lag, averaged over one full period of the sine wave, is unity. That is, the correlation is perfect. Introducing a lag of one bar in the autocorrelation process causes the average correlation to be decreased slightly. Introducing another bar of lag further decreases the average correlation, and so on. That is, until a lag of 10 bars is reached. In this case, the positive alternation of the sine wave is correlated with the negative alternation of the lagged waveform and the negative alternation of the sine wave is correlated with the positive alternation of the lagged waveform, with the result that perfect anticorrelation has been reached. Continued lag increases causes the average correlation to increase until a lag of 20 bars is reached. When the lag is equal to the period of the sine wave waveform, the correlation is again perfect. In this theoretical example, the correlation values as a function of lag vary exactly as a sine wave.
Market data are considerably messier than purely random numbers or perfect sine waves but contain features of both. However, the characteristics that are uncovered by autocorrelation offer unique trading perspectives. Aside from appearing psychedelic, there are two distinct characteristics of the autocorrelation indicator using minimum averaging. First, there is a sharp reversal from red to yellow and from yellow to red at the timing of price reversals for all periods of lag. Second, there is a variation of the thickness of the bars and the number of bars over the vertical range of the indicator as a function of time.
Key Signal
Corr --> Pearson correlation data array
Pros and Cons
I am sorry this script is NOT 100% as original Ehlers works but I modified it accordingly which demostrated with better visual effect.
Remarks
The 47th script for Blackcat1402 John F. Ehlers Week publication.
Courtesy of @RicardoSantos for RGB functions.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
חפש סקריפטים עבור "one一季度财报"
Using The AM/GM Inequality To Estimate VolatilityA volatility indicator derived from the AM/GM inequality. I don't think it will be necessary to describe the usage and interpretation of such indicator, and I don't think it is super useful, however, this is not the case of the script, which contains three ways to compute the geometric mean, with a classic, a simple, and an efficient way. The AM/GM inequality is also a really interesting concept, and I'll try to"prove" it in this post by using DSP. I also added more comments in the script in order to highlight some stuff.
The AM/GM Inequality
When we talk about the mean, we are referring to the "arithmetic" one by default, but there exist more types of means. Two other ones include the "geometric" and "harmonic" means, both are part of the Pythagorean means with the arithmetic mean.
Each one of them as several properties, but the most interesting aspect is their inequality, that is:
HM <= GM <= AM
The arithmetic mean is the one with the highest value, while the harmonic mean is the one with the lowest value. In the case each data point is equal to each other, all the means have the same value.
In our case, the inequality of interest is the inequality between the geometric and arithmetic mean, where the geometric mean is lower or equal than the arithmetic one. Many proofs/explanations exist, I'll try my version using DSP, where instead of thinking about means, we think about rolling means, which allows us to interpret them as low-pass filters. So we end up having the geometric moving average (GMA) and arithmetic moving average (SMA).
We know that GMA <= SMA , the SMA has a unity passband, this implies that the GMA has a passband lower than 1 (for non-equal input values), this explains why the GMA is smaller than the SMA. In order for a FIR filter to have a passband lower than 1, the sum of the filter coefficients must be lower than 1. In order to further proves this consider the following equation:
sqrt(a×b) = k×a + k×b
Here sqrt(a×b) is the geometric mean of a and b , the right-hand side of the equation is a weighted sum between a and b and coefficient k , we want to solve the equation with respect to k , if k×2 < 1 then we have the proof that GMA < SMA . The solution with respect to k is:
k = sqrt(a×b)/(a+b)
which always gives a number lower than 0.5, as such k×2 < 1 and thus the passband is lower than 1. If our input values are equal to each other, we end up with the following solution for k :
k = sqrt(a×a)/(a+a) = a/(2×a) = 0.5
as such the GMA has the coefficients of an SMA as long as the input values are equal to each other.
Because of this inequality, we can subtract the SMA to a GMA and take the square root of the result in order to have a volatility indicator, however, both moving averages are still pretty close to each other, which gives a very small result for the indicator.
Uwu I am a bit tired, better indicators coming up
CryptoSignalScanner - Advanced Moving Averages - Cross & RainbowDESCRIPTION:
With this script you can plot 6 moving averages.
You can decide which Moving Average you want to show or hide.
For every plot you can decide to display the Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ).
It provides CrossOver and CrossUnder labels when loading the script. Those labels you can show or hide.
You have the possibility to show or hide the rainbow colors. This rainbow function gives you a clear view of the current trend.
HOW TO USE:
• When one Moving Average crosses above another Moving Average it signals an uptrend.
• When one Moving Average crosses below another Moving Average it signals a downtrend.
• The higher to length of the Moving Average the stronger the trend.
FEATURES:
• You can show/hide the preferred Moving Averages.
• You can set the length, type and source for every Moving Average.
• You can show/hide the rainbow colors.
• You can show/hide the CrossUp labels.
• You can show/hide the CrossDown labels.
• You can set alerts for every Moving Average.
• Etc...
DEFAULT SETTINGS:
• MA1 => EMA5
• MA2 => EMA10
• MA3 => EMA20
• MA4 => SMA50
• MA5 => SMA100
• MA6 => SMA200
Simple Moving Average vs. Exponential Moving Average:
SMA and EMA are calculated differently. The exponential moving average ( EMA ) focuses more on recent prices than on a long series of data points, as the simple moving average required.
The calculation makes the EMA quicker to react to price changes and the SMA react slower. That is the main difference between the two.
One is not necessarily better than another. It comes down to personal preference. Plot an EMA and SMA of the same length on a chart and see which one helps you make better trading decisions.
Moving Average Trading Strategies:
The first strategy is a price crossover, when the price crosses above or below a moving average, it signals a potential change in trend.
The second strategy applies when one moving averages crosses another moving average.
• When the short-term MA crosses above the long-term MA, it signals a buy signal.
• When the short-term MA crosses below the long-term MA, it signals a sell signal.
REMARKS:
• This advice is NOT financial advice.
• We do not provide personal investment advice and we are not a qualified licensed investment advisor.
• All information found here, including any ideas, opinions, views, predictions, forecasts, commentaries, suggestions, or stock picks, expressed or implied herein, are for informational, entertainment or educational purposes only and should not be construed as personal investment advice.
• We will not and cannot be held liable for any actions you take as a result of anything you read here.
• We only provide this information to help you make a better decision.
• While the information provided is believed to be accurate, it may include errors or inaccuracies.
If you like this script please donate some coins to share your appreciation.
Good Luck,
SEOCO
hayatguzelHayatguzel indicator is a simple indicator which shows the price/ema ratio. Indicator uses the highest or lowest values for price while closure ones for ema. Ema value can be adjusted according to your choise such as 21, 34, 55 etc. or any value you prefer.
I want to explain hayatguzel on XAUUSD chart. I marked 3 points on the chart. 1st one is the peak value of gold with a price/ema55 ratio around 1.30, the 2nd one is the other peak value of gold with a price/ema55 ratio around 1.27 and the 3rd one is also 1.30.
As can be seen, gold price has a maximum capability of going upto 1.30 times the ema55 value in an uptrend. And now this ratio is about 1.23, so we are expecting a maximum level of 1.30 for our predicted peak price value. You can also use this indicator for predicting lows of course but for this graph we are looking for the peak value. My strategy is to aim 1.30 value (30 value on the indicator chart) and therefore hold it until there and after that look for a sell opportunity. This simple approach is usefull especially for the ones who believe that "history repeats itself".
Green: Price > Ema
Red: Price < Ema
Special Thanks to @baymucuk for his great help ! Code was created by him.
ENG
Hayatguzel indikatörü basit ve sade bir indikatör. Fiyat/ema oranını hesaplayıp grafiğe döker. Bunu yaparken de en yüksek ve en düşük fiyat değerlerini alırken ema'larda kapanış değerlerini kullanır. Ema değerleri ayarlanabilir olup 21, 34, 55 vb ya da sizin tercihiniz olan herhangi bir değer olabilir.
Bu indikatörü XAUUSD grafiğinde anlatmak istiyorum. Grafikte 3 tane işaret var. İlkinde fiyat/ema55 oranının maksimum yaptığı yer işaretli ki bu oran 1.30 civarında. 2.sinde yine fiyat/ema55 oranının maksimum yaptığı yer olan 1.27 seviyesi işaretli. 3.'de de bu değer 1.30 seviyesinde.
Görüldüğü üzere ons altın grafiğinde maksimum fiyat ema 55'in en fazla 1.30 katı olabilmiş. Şimdi ise bu değer 1.23 civarında. O nedenle bu oranın 1.30 olmasını ve orada fiyatın tepe yapmasını bekleyebiliriz. Bu indikatörü aynı zamanda dipleri tahmin etmek için de kullanabilirsiniz ama burada grafiğimiz tepeleri bulmak üzerine. Buradaki stratejim fiyat/ema55 oranında 1.30 seviyesini (indikatördeki 30 seviyesi) hedefleyerek ons altını o noktaya kadar tutmak daha sonra o bölgede satış fırsatı aramak olacaktır. Bu basit yaklaşım özellikle "tarih tekerrüden ibarettir" sözüne inananlara ışık tutacaktır.
Yeşil: Fiyat > Ema
Kırmızı : Fiyat < Ema
Yardımları için @baymucuk a teşekkürlerimi sunuyorum ! Kod onun tarafından yazılmıştır.
TR
Minimum Variance SMAReturn the value of a simple moving average with a period within the range min to max such that the variance of the same period is the smallest available.
Since the smallest variance is often the one with the smallest period, a penalty setting is introduced, and allows the indicator to return moving averages values with higher periods more often, with higher penalty values returning moving averages values with higher periods.
Because variances with smaller periods are more reactive than ones with higher periods, it is common for the indicator to return the value of an SMA of a higher period during more volatile market, this can be seen on the image below:
here variances from period 10 to 15 are plotted, a blueish color represents a higher period, note how they are the smallest ones when fluctuations are more volatile.
Indicator with min = 50, max = 200 and penalty = 0.5
In blue the indicator with penalty = 0, in red with penalty = 1, with both min = 50 and max = 200.
On The Script
The script minimize Var(i)/p with i ∈ (min,max) and p = i^penalty , this is done by computing the variance for each period i and keeping the smallest one currently in the loop, if we get a variance value smaller than the previously one found we calculate the value of an SMA with period i , as such the script deal with brute force optimization.
For our use case it is not possible to use the built-in sma and variance functions within a loop, as such we use cumulative forms for both functions.
RenkoNow you can plot a "Renko" chart on any timeframe for free! As with my previous algorithm, you can plot the "Linear Break" chart on any timeframe for free!
I again decided to help TradingView programmers and wrote code that converts a standard candles / bars to a "Renko" chart. The built-in renko() and security() functions for constructing a "Renko" chart are working wrong. Do not try to write strategies based on the built-in renko() function! The developers write in the manual: "Please note that you cannot plot Renko bricks from Pine script exactly as they look. You can only get a series of numbers similar to OHLC values for Renko bars and use them in your algorithms". However, it is possible to build a "Renko" chart exactly like the "Renko" chart built into TradingView. Personally, I had enough Pine Script functionality.
For a complete understanding of how such a chart is built, you can read to Steve Nison's book "BEYOND JAPANESE CANDLES" and see the instructions for creating a "Renko" chart:
Rule 1: one white brick (or series) is built when the price rises above the base price by a fixed threshold value or more.
Rule 2: one black brick (or series) is built when the price falls below the base price by a fixed threshold or more.
Rule 3: if the rise or fall of the price is less than the minimum fixed value, then new bricks are not drawn.
Rule 4: if today's closing price is higher than the maximum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more white bricks of equal height. A new brick begins with the maximum of the previous brick.
Rule 5: if today's closing price is below the minimum of the last brick (white or black) by a threshold or more, move to the column to the right and build one or more black bricks of equal height. A new brick begins with the minimum of the previous brick.
Rule 6: if the price is below the maximum or above the minimum, then new bricks are not drawn on the chart.
So my algorithm can to plot Traditional Renko with a fixed box size. I want to note that such a "Renko" chart is slightly different from the "Renko" chart built into TradingView, because as a base price I use (by default) close of first candle. How the developers of TradingView calculate the base price I don’t know. Personally, I do as written in the book of Steve Neeson.
The algorithm is very complicated and I do not want to explain it in detail. I will explain very briefly. The first part of the get_renko () function — // creating lists — creates two lists that record how many green bricks should be and how many red bricks. The second part of the get_renko () function — // creating open and close series — creates open and close series to plot bricks. So, this is a white box - study it!
As you understand, one green candle can create a condition under which it will be necessary to plot, for example, 10 green bricks. So the smaller the box size you make, the smaller the portion of the chart you will see.
I stuffed all the logic into a wrapper in the form of the get_renko() function, which returns a tuple of OHLC values. And these series with the help of the plotcandle() annotation can be converted to the "Renko" chart. I also want to note that with a large number of candles on the chart, outrages about the buffer size uncertainty are heard from the TradingView blackbox. Because of it, in the annotation study() set the value of the max_bars_back parameter.
In general, use this script (for example, to write strategies)!
Time Range StatisticsA good amount of users requested a text box showing various price statistics, the following script returns various of these stats in a user-selected range, and include classical ones such as a central tendency measurement (mean), dispersion (normalized range) and percent change, but also include less common statistics such as average traded volume and number of gaps. The script also calculates the correlation between the closing price and another user-selected instrument.
The script is currently the longest one I ever made and took some efforts, as I wasn't satisfied with the statistics to be originally included. Big thx to Gael for the enormous feedback and the idea of the normalized range, to user @Cookiecrush for the feedback ( without ya I would have posted something bad you know umu ? ), and Lulidolce for the support, friendship is magic!
Selected Range
The setting Start determine the bar at which the range starts, while End determine at which bar the range end. To help you select these values, the current bar number (bar index) is displayed at the right of the indicator title in blue.
The setting evaluate to last bar will use a range starting at Start and ending at the last bar, as such you can use a full range by using Start = 0 and select evaluate to last bar
The range is highlighted by an area on the chart. By default Start = 9000 and End = 10000, you might not have this amount of data in your chart, as such use the displayed bar index to select Start and End, then set the settings as default.
Displayed Statistics
The statistics panel is displayed on the right side of the last bar, the panel has 3 sections, a title section who shows the symbol ticker, timeframe, and overall trends represented by a chart emoji, the overall trends are determined by comparing the number of higher highs with the number of lower low.
Below are displayed the date ranges with time format: year/month/day/hour:minute.
The second section shows the general statistics. The first one is the mean, also represented by the orange line in the chart, the blue line displayed represent the highest price value in the range, while the red one represents the lowest price value.
The second stat is the normalized range, and determine how spread is the price in the user-selected range, why not the standard deviation? Because the standard deviation might return results varying widely depending on the scale of the closing price, you could get measures such as 0.0156 or 16 or even 56 depending on the instrument, as such using a normalized range can be more appropriate as it lays in a range of (0,1). Lower values indicate a low degree of price variation. Note that I still want to find another measure in the future.
The percentage change (or relative change) indicates at which percentage the price has increased or decreased, and is calculated by subtracting the closing at bar Start with the price at bar End , divided by the price at bar End , the result is then multiplied by 100.
The average traded volume calculate the mean of the volume in the selected range, I used the same format used by the original volume indicator for clarity.
Finally, the last stats of the section is the number of gaps, this stat is by default hidden. An up gap is detected when the open price is superior to the previous high, while a down gap is detected when the open price is inferior to the previous low, this allow to only retain significant gaps.
The last section of the indicator panel shows the correlation between the closing price and another instrument, by default GOOG, this correlation is also calculated within the user-selected range. Positive values indicate a positive relationship, that is the two instruments tend to move in the same direction. Negative values indicate a negative relationship, both instruments tend to move in a direction opposite to each other. Values closer to 1 or -1 indicate a stronger relationship, while values closer to 0 indicate no relationship.
In Summary
The script shows various stats, each calculated within a user-selected range, in general one would be more interested in how these stats might evolve with time, but checking them in a custom range can be quite interesting.
Thx for reading. umu
Histogram - Price Action - Dy CalculatorThis script aims to help users of Price Action robot, for Smarttbot (brazilian site that automates Brazilian market (B3)).
You can use on any symbol.
The script will follow price action principles. It will calculate the absolute value of last candle and compare with actual candle. Colors are:
- Red - If the actual candle absolute value is higher than previous one, and the price is lower than last candle. It would be a short entry.
- Blue - If the actual candle absolute value is higher than previous one, and the price is higher than last candle. It would be a long entry.
- Black - The actual candle absolute value is lower than previous one, so there is no entry.
If there is a candle that is higher than previous one, and both high and low values are outside boundaries of previous one, it will calculate which boundary is bigger and will apply the collor accordingly.
eha Moving Averages StrategyMoving Average based strategies are very popular ones among both long-term investors and short-term traders as they can be tailored to any time frame. One of the main moving average strategies are crossovers. The very simple type is a price crossover , which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer (or slow) and one shorter (or fast). When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up (also known as “ Golden Cross ”). Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down (which is also known as “ Dead/Death Cross ”).
This is a study to find a suitable trading strategy for 4-6 hour time frames. As you can see the performance is currently very poor. It has just generated almost 90 trades in a very long period from January 2017 to the time of publishing the study for the first time.
Moving averages work quite well in strong trending conditions but poorly in choppy or ranging conditions. Adjusting the time frame can correct this problem temporarily, although, at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
I am working on this basic strategy to make its performance better and I will update the post in the future. So keep in touch by following the post.
Why have I republished my study?
It sounds like TradingView stores and indexes scripts based on the title of the post rather than the actual title of the scripts and if one chose general terms as the title of the post, the TradingView script search engine may be unable to find it. So I decided to repost the strategy with a more searchable and unique prefix of " eha ".
Please provide me with your precious feedback.
Dual Purpose Pine Based CorrelationThis is my "Pine-based" correlation() function written in raw Pine Script. Other names applied to it are "Pearson Correlation", "Pearson's r", and one I can never remember being "Pearson Product-Moment Correlation Coefficient(PPMCC)". There is two basic ways to utilize this script. One is checking correlation with another asset such as the S&P 500 (provided as a default). The second is using it as a handy independent indicator correlated to time using Pine's bar_index variable. Also, this is in fact two separate correlation indicators with independent period adjustments, so I guess you could say this indicator has a dual purpose split personality. My intention was to take standard old correlation and apply a novel approach to it, and see what happens. Either way you use it, I hope you may find it most helpful enough to add to your daily TV tool belt.
You will notice I used the Pine built-in correlation() in combination with my custom function, so it shows they are precisely equal, even when the first two correlation() parameters are reversed on purpose or by accident. Additionally, there's an interesting technique to provide a visually appealing line with two overlapping plot()s combined together. I'm sure many members may find that plotting tactic useful when a bird's nest of plotting is occurring on the overlay pane in some scenarios. One more thing about correlation is it's always confined to +/-1.0 irregardless of time intervals or the asset(s) it is applied to, making it a unique oscillator.
As always, I have included advanced Pine programming techniques that conform to proper "Pine Etiquette". For those of you who are newcomers to Pine Script, this code release may also help you comprehend the "Power of Pine" by employing advanced programming techniques in Pine exhibiting code utilization in a most effective manner. One of the many tricks I applied here was providing floating point number safeties for _correlation(). While it cannot effectively use a floating point number, it won't error out in the event this should occur especially when applying "dominant cycle periods" to it, IF you might attempt this.
NOTICE: You may have observed there is a sqrt() custom function and you may be thinking... "Did he just sick and twistedly overwrite the Pine built-in sqrt() function?" The answer is... YES, I am and yes I did! One thing I noticed, is that it does provide slightly higher accuracy precision decimal places compared to the Pine built-in sqrt(). Be forewarned, "MY" sqrt() is technically speaking slower than snail snot compared to the native Pine sqrt(), so I wouldn't advise actually using it religiously in other scripts as a daily habit. It is seemingly doing quite well in combination with these simple calculations without being "sluggish". Lastly, of course you may always just delete the custom sqrt() function, via Pine Editor, and then the script will still operate flawlessly, yet more efficiently.
Features List Includes:
Dark Background - Easily disabled in indicator Settings->Style for "Light" charts or with Pine commenting
AND much, much more... You have the source!
The comments section below is solely just for commenting and other remarks, ideas, compliments, etc... regarding only this indicator, not others. When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. As always, "Like" it if you simply just like it with a proper thumbs up, and also return to my scripts list occasionally for additional postings. Have a profitable future everyone!
Pivots MTF [LucF]Pivots detected at higher timeframes are more significant because more market activity—or work—is required to produce them. This indicator displays pivots calculated on the higher timeframe of your choice.
Features
► Timeframe selection
— The higher timeframe (HTF) can be selected in 3 different ways:
• By steps (15 min., 60 min., 4H, 1D, 3D, 1W, 1M, 1Y). This setting is the default.
• As a multiple of the current chart's resolution, which can be fractional, so 3.5 will work.
• Fixed.
— The HTF used can be displayed near the last bar (default).
— Note that using the HTF is not mandatory. If it is disabled, the indicator will calculate on the chart's resolution.
— Non-repainting or repainting mode can be selected. This has no impact on the display of historical bars, but when no repainting is selected, pivot detection in the realtime bar will be delayed by one chart bar (not one bar at the HTF).
► Pivots
— Three color schemes are provided: green/red, aqua/pink and coral/violet (the default).
— Both the thickness and brightness of lines can be controlled separately for the hi and lo pivots.
— The visibility of the last hi/lo pivots can be enhanced.
— Prices can be displayed on pivot lines and the text's size and color can be adjusted.
— The number of bars required for the left/right pivot legs can be controlled (the default is 4).
— The source can be selected individually for hi and lo pivots (the default is hlc3 and low .
— The mean of the hi/lo pivot values of the last few thousand chart bars can be displayed. Pivots having lasted longer during the mean's period will weigh more in the calculation. The mean can be displayed in running mode and/or only showing its last level as a long horizontal line. I don't find it very useful; maybe others will.
► Markers and Alerts
— Markers can be configured on breaches of either the last hi/lo pivot levels, or the hi/lo mean. Crossovers and crossunders are controlled separately.
— Alerts can be configured using any of the marker combinations. As is usual for my indicators, only one alert is used. It will trigger on the markers that are active when you create your alert. Once your markers are set up the way you want, create your alert from the chart/timeframe you want the alert to run on, and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of the combination of markers used when creating the alert. If you use multiple markers to trigger one alert, then having the indicator show those markers will be important to help you figure out which marker triggered the alert when it fired.
A quick look at the pattern of these markers will hopefully convince you that using them as entry/exit signals would be perilous, as they are prone to whipsaw. I have included them because some traders may use the markers as reminders.
Using Pivots
These pivots can be used in a few different ways:
— When using the high / low sources they will show extreme levels, breaches of which should be more significant.
— Another way to use them is with hlc3 (the average of the high , low and close ) for hi pivots and low for the lo pivots. This accounts for my personal mythology to the effect that drops typically reach previous lows more easily than rallies make newer highs.
— Using low for hi pivots and high for lo pivots (so backward) can be a useful way to set stops or to detect weakness in movements.
You will usually be better served by pivots if you consider them as denoting regions rather than precise levels. The flexibility in the display options of this indicator will help you adapt it to the way you use your pivots. To indicate areas rather than levels, for example, try using a brightness of 1 with a line thickness of 30. The cloud effect generated this way will show areas better than fine lines.
Realize that these pivot lines are positioned in the past, and so they are drawn after the fact because a given number of bars need to elapse before calculations determine a pivot has occurred. You will thus never see a pivot top, for example, identified on the realtime bar. To detect a pivot, it takes a number of bars corresponding to the dilation of the higher timeframe in the current one, multiplied by the number of bars you use for your pivots' right leg. Also note that the Pine native function used to detect pivots in this indicator considers a summit to be a top when the number of bars in each leg are lower or equal to that top. Bars in legs do not need to be progressively lower on each side of the pivot for a pivot to be detected.
If you program in Pine
— See the Pinecoders MTF Selection Framework for an explanation of the functions used in this script to provide the selection mechanism for the higher timeframe.
— This code uses the Pine Script Coding Conventions .
Thanks
— To the Pine coders asking questions in the Pine Script chat on TV ; your questions got me to write this indicator.
Center Of Linearity - A More Efficient Alternative To Elhers CGIntroduction
The center of gravity oscillator (CG) is one of the oscillators presented in Elhers book "cybernetic analysis for stocks and futures". This oscillator can be described as a bandpass filter centered around 0, its simplicity is ridiculous yet this indicator managed to get a pretty great popularity, this might be due to Elhers saying that he has substantial advantages over conventional oscillators used in technical analysis.
Today i propose a more efficient estimation of the center of gravity oscillator, this estimation will only use one convolution, while the original and other estimations use 2. I will also explain everything about the center of gravity oscillator, because even if its name can be imposing its actually super easy to understand.
The Center Of Gravity Oscillator
The CG oscillator is a bandpass filter, in short it filter high frequencies components as well as low frequency ones, this is why the oscillator is both smooth (no high frequencies) as well as detrended (no low frequencies), and therefore the oscillator focus exclusively on the cycles.
Its calculation is simple, its just a linearly weighted moving average minus a simple moving average wma - sma , this is not what is showcased in its book, but the result is just the same, the only thing that change is the scale, this is why some estimates have a weird scale that is not centered around 0, the output is technically the same but the scale isn't, however the scale of an oscillator isn't a big deal as long as the oscillator is centered around 0 and we don't plan to use it as input for overlay indicators.
If you are familiar with moving averages you'll know that the wma is more reactive than the sma, this is because more recent values have higher weights, and since subtracting a low-pass filter with another one conserve the smoothness while removing low-frequency components, we end up with a bandpass filter, yay!
Why "Center" Of Gravity ?
Elhers explain the idea behind this title with a pretty blurry analogy, so i'll try to give a visual explanation, we said earlier that the center of gravity was simply : wma - sma, ok lets look at their respective impulse responses,
Those are basically the weights of each filters, also called filter coefficients, lets denote the coefficients of the wma as a and the coefficients of the moving average as b . So whats the meaning behind center of gravity ? We basically want to "center" the weights of the wma, this can be done with a - b
The coefficients of the wma are therefore centered around 0, but actually there is more to that than a simple title explanation, basically a - b = c , where c are the coefficients of the center of gravity bandpass filter, therefore if we where to apply convolution to the price with c , we would get the center of gravity oscillator. Thats the thing with FIR filters, we can use convolution for describing a lot of FIR systems, and the difference between two impulse responses of two low-pass filters (here wma, sma) give us the coefficients of a bandpass filter.
The Center Of Linearity
At this point we could simply get the oscillator by using length/2 - i as coefficient, however in order to propose a more interesting variation i decided to go with a less efficient but more original approach, the center of linearity. Imagine two convolutions :
a = i*src and b = i*src
a only has a reversed index length-i , and is therefore describe a simple wma. Both convolutions give the following impulse responses :
Both are symmetrical to each others, and cross at a point, denoted center of linearity. The difference of each responses is :
Using it as coefficients would give us a bandpass filter who would look exactly like the Cg oscillator, this would be calculated as follows in our convolution :
i*src -i*src ) = i*(src -src )
Lets compare our estimate with the CG oscillator,
Conclusion
I this post i explained the calculation of the CG oscillator and proposed an efficient estimation of it by using an original approach. The CG oscillator isn't something complicated to use nor calculate, and is in fact closely related to the rolling covariance between the price and a linear function, so if you want to use the crosses between the center of gravity and 0 you can just use : correlation(close,bar_index,length) instead, thats basically the same.
The proposed indicator can also use other weightings instead of a linear one, each impulses responses would remain symmetrical.
Smart Envelope - Running Away From The TrendIntroduction
Envelopes indicators consist in displaying one upper and one lower extremity on the price chart. They are most of the time built by adding/subtracting a volatility estimator (rolling stdev, atr, range...etc) to a central tendency estimator (SMA, EMA, LSMA...etc) . Their interpretation is often subject to debate amongst technical analyst, some will use a support and resistance methodology, where price will start a downtrend once it cross the upper extremity, and a down trend once it cross the lower one. Others will prefer a breakout methodology, where price will reach higher highs once it cross the upper extremity, and lower lows when it cross the lower one. Because of price non stationarity its hard to select the best methodology, the support and resistance one will mostly work on ranging markets, while the breakout methodology mostly work on trending ones.
Therefore new methods where proposed, instead of using moving averages with a high lag, faster filters where used, such as the least squares moving average or zero lag exponential moving average, other band indicators where also created using adaptive filters, but improvements remain relatively low. The most difficult task would be to make extremities with the ability to return accurate support and resistances levels, and today i want to provide a new way to construct such extremities by using the recursive bands framework that allow extremely creative and efficient indicators.
The Main Idea
With classical bands indicators, the upper and lower extremity will still be correlated with the main trend, the problem behind such method is that we can't use a support and resistance methodology with trending markets, the fact that reversals exist tells us that our extremities will always be crossed by the main trend, here is an example :
Here the support is correlated with the main trend, in order for it to be accurate we must assume the trend will go on for ever, and will only detect higher lows, this is what we expect with the orange line, but we can see that a severe down trend totally destroy our plan.
In short we need to give some headroom to our extremities, and thus one extremity can't be correlated with the main trend.
The proposed Indicator
We want to minimize the correlation between the extremities, so if the upper extremity rise, the lower one must fall. This allow to give some headroom and allow the user to anticipate larger movements, this is how bands seeking to give support and resistances points should work.
The indicator has a length setting that control the wideness of the extremities, unlike other indicators low values such as 14 can still create really wide bands, take that into account.
length = 5. Lower length values allow for more motion from the extremities, but does not necessarily involve detecting shorter terms support and resistances levels. The factor setting is not that important, but it allow to return extremities with more motion when high, and really wide bands when below 1 and greater than 0.
Central Tendency Estimator
Something fun with the recursive band framework is that the bands are no longer based on the central tendency estimator but its the central tendency estimator who is based on the bands. The central tendency estimator can also provide support and resistances points with the price, like classical moving averages, altho its lack of motion is this time a downside.
Conclusion
Altho the extremities are more accurate than other band indicators, the problem remain the same, larger trend will always break the extremities and continue creating higher/lower highs/lows, at this point our stop loss would certainly be triggered. This is a huge downsides of contrarian strategy, we sure might anticipate reversals earlier, but we are exposed to larger price movements, therefore the risk is extreme.
But the proposed methodology might still prove useful to develop more robust support and resistances levels based on envelopes indicators.
Thanks for reading !
Visual RSI [LucF]Visual RSI offers a different way of looking at RSI by providing a composite representation of 9 different RSI-generated components. Instead of focusing on one line only, this approach blends multiple sources to provide the viewer with a larger context RSI-based picture.
For those who don’t want to read
• Green in bullish (>50) zone is the most bullish.
• Red in bullish zone doesn’t necessarily mean bearish—it just means bullish strength is weakening. It may be just a pause before a reprise or exhaustion signalling a reversal—impossible to tell.
• The same in inverse applies to the bearish zone (<50).
For those who want to understand
The nine components making up Visual RSI are:
• a current timeframe RSI
• a higher timeframe RSI
• the delta between these two RSI lines
• for each of these three basic components, two independent Bollinger band: one calculated for the bullish section of the scale (>50) and a separate one calculated for the lower bearish region.
Dual BBs
In my view, RSI’s position with regards to the centerline is much more important than its position in extreme areas. Why? Because the building block of RSI is the ratio of the averages of up/down moves during the RSI period. When the average of ups is greater, RSI is > 50. So while a rising signal starting from 20 let’s say, indicates that the rate of change is increasing, only when it crosses 50 can we say that sentiment balance has truly become bullish, and this information is more reliable than the signal being at a level corresponding to whatever estimate we make of what constitutes an extreme value. In my landscape, the general balance of a ratio provides more valuable information than the ratio’s exact value.
The idea behind the dual BBs is to provide independent tracking information for both halves of the indicator’s space, which I find more useful than the normal method of simply adding a multiple of the standard deviation on both sides of the mean. With dual BBs, the upper BB will never go lower than the indicator’s centerline, and the lower BB will never go higher. The upper BB focuses on upper-bound volatility when the signal is bearish, and the lower BB focuses on downside volatility when the signal is bearish.
The functions used to calculate the independent BBs are reusable on other signals if a centerline can be defined for them. A clamping percentage is implemented, so that when a BB line is hugging the centerline it clamps to it. This helps in providing earlier signals when they use the BB line states.
Providing context to RSI
What RSI measures indirectly is the balance in the rate of change—or the speed of price movement, but not its instant value, otherwise RSI would be even noisier. More precisely, RSI represents the relative strength of the up/down movement in the last n bars of RSI’s length, with 14 often used because that’s what Wilder proposed (Visual RSI’s defaults are 20 for the current timeframe and 40 for the higher timeframe). At every bar, a new value is added to the equation and an old value carrying equal weight is dropped, so a large dropped off value will have more impact on RSI’s value if the new bar’s move is small. This accounts for some of RSI’s speed in identifying exhaustion after important moves, but almost for some of its noise.
Visual RSI is the result of trying to drown RSI’s noise in the context of other informational streams, while simultaneously providing even faster information than RSI alone, by giving more visual weight to the delta between the current and higher timeframe RSI’s.
How to read Visual RSI
The default settings show all 9 basic components as green/red areas of intensities varying with their importance. The most intense colors are reserved for the delta RSI and the BBs have the lightest intensities. The individual lines of components are intentionally difficult to distinguish so that focus is first on the general picture, including the all-important six-state background, and then on the delta RSI.
One entry setup could be reversals in a larger trend context, so low pivots of the delta in a fully bullish context (a green background in the upper section of the indicator), and inversely, high pivots in a fully bearish context (a red background in the lower section of the indicator).
Please resist the common misconception, when interpreting RSI, that a reversal in the signal will necessarily lead to a reversal in price. Each trend has its rhythm. Only machine-generated price action can progress regularly. It’s normal for trends to take a breather for some time before they continue or reverse, as traders driving the trend experience emotional fatigue and gradual fear. RSI reversals merely signify that such a breather has occurred—nothing more. Only the larger context can provide information that can situate that pause and put more meaningful odds on it having more probability of continuing in one direction or the other. This is the reasoning behind the setup just described.
Features
• All components can be hidden, displayed as a simple line, a uniformly colored fill, or a green/red fill (the default).
• The background can be colored using 9 different methods, including 3 six-state methods using the rising/falling BB lines of the 3 basic components. These six states allow for bullish/bearish/neutral sentiment in both the upper and lower regions of the indicator. A bearish (dark red) background in the bullish (>50) section of the indicator represents decreasing bullishness. A bearish (slightly brighter red) in the bearish (<50) section of the indicator means incresingly bearish sentiment. The six-state backgrounds allow for neutral (no color) sentiment when no compelling signs can be found to conclude anything with meaningful odds. The default background uses the six-state method on the higher timeframe RSI’s BBs because I find it the most useful, as it represents the largest—and slowest—context sentiment among all the indicator’s components.
• A thin status bar in the top part of the indicator also allows selection of the same 9 methods to color it. The default is a triple-state system using the rising/falling characteristics of the current timeframe RSI’s BBs to provide a short-term counterbalance to the long-term background.
• Three different markers can be configured using approximately 70 permutations each, each filtered by 20 different filter permutations. When modification of the relevant parameters in the script’s Settings/Settings/Parameters section is added, possibilities are almost endless. If the generated signals are then fed into the PineCoders Engine and combined with the Engine’s own options, the permutations go up another order of magnitude, and changes to any setting can be instantly evaluated using the Engine’s backtesting results.
• Five simple filters can be combined. They are additive. They include volume-related conditions and a chandelier, which I find useful because both volume and volatility (the chandelier using highs/lows and ATR) are sensible complementary sources to RSI’s momentum information. The filter’s state can be shown as a thin line at the bottom of the indicator.
• Alerts can be configured using any of the marker/filter combinations mentioned. As usual, once your markers/filters are set up the way you want, create your alert from the chart/timeframe you want the alert to run on and be sure to use the “Once Per Bar Close” triggering condition. Use an alert message that will remind you of which combination of markers were used when creating the alert.
• A plot providing entry signals for the PineCoders Backtesting & Trading Engine is supplied. It will use whichever marker/filter configuration is active to generate signals.
• All higher timeframe information is non-repainting. Higher timeframe lines can be smoothed (the default). The selection of the higher timeframe can be made using 3 different methods:
1. By steps (if current timeframe <= 1 minute: 60 min, <= 60 min: 1D, <= 6H: 3D, <= 1D: 1W, <=1W: 1M, >1W: 12M)
2. By a user-defined multiple of the current timeframe
3. Using a fixed timeframe
Thanks to:
• Alex Orekhov aka @everget for the chandelier code.
• @RicardoSantos who through a small remark early on, unknowingly put me on the track of eliminating noise through visual crowding.
• The brilliant guys in the PineCoders Pro room for your knowledge, limitless creativity and constant companionship.
Forecasting - Drift MethodIntroduction
Nothing fancy in terms of code, take this post as an educational post where i provide information rather than an useful tool.
Time-Series Forecasting And The Drift Method
In time-series analysis one can use many many forecasting methods, some share similarities but they can all by classified in groups and sub-groups, the drift method is a forecasting method that unlike averages/naive methods does not have a constant (flat) forecast, instead the drift method can increase or decrease over time, this is why its a great method when it comes to forecasting linear trends.
Basically a drift forecast is like a linear extrapolation, first you take the first and last point of your data and draw a line between those points, extend this line into the future and you have a forecast, thats pretty much it.
One of the advantage of this method is first its simplicity, everyone could do it by hand without any mathematical calculations, then its ability to be non-conservative, conservative methods involve methods that fit the data very well such as linear/non-linear regression that best fit a curve to the data using the method of least-squares, those methods take into consideration all the data points, however the drift method only care about the first and last point.
Understanding Bias And Variance
In order to follow with the ability of methods to be non-conservative i want to introduce the concept of bias and variance, which are essentials in time-series analysis and machine learning.
First lets talk about training a model, when forecasting a time-series we can divide our data set in two, the first part being the training set and the second one the testing set. In the training set we fit a model to the training data, for example :
We use 200 data points, we split this set in two sets, the first one is for training which is in blue, and the other one for testing which is in green.
Basically the Bias is related to how well a forecasting model fit the training set, while the variance is related to how well the model fit the testing set. In our case we can see that the drift line does not fit the training set very well, it is then said to have high bias. If we check the testing set :
We can see that it does not fit the testing set very well, so the model is said to have high variance. It can be better to talk of bias and variance when using regression, but i think you get it. This is an important concept in machine learning, you'll often see the term "overfitting" which relate to a model fitting the training set really well, those models have a low to no bias, however when it comes to testing they don't fit well at all, they have high variance.
Conclusion On The Drift Method
The drift method is good at forecasting linear trends, and thats all...you see, when forecasting financial data you need models that are able to capture the complexity of the price structure as well as being robust to noise and outliers, the drift method isn't able to capture such complexity, its not a super smart method, same goes for linear regression. This is why more peoples are switching to more advanced models such a neural networks that can sometimes capture such complexity and return decent results.
So this method might not be the best but if you like lines then here you go.
Dollar Cost Average (Data Window Edition)Hi everyone
Hope you had a nice weekend and you're all excited for the week to come. At least I am (thanks to a few coffee but that still counts !!!)
This indicator is inspired from Dollar-Cost-Average-Cost-Basis
EDUCATIONAL POST
The educational post is coming a bit later this afternoon explaining how to use the indicator so I would advise to follow me so that you'll get updated in real-time :) (shameless self-advertising)
1 - What is Dollar-Cost Averaging (DCA)?
Dollar-Cost Averaging is a strategy that allows an investor to buy the same dollar amount of an investment on regular intervals. The purchases occur regardless of the asset's price.
I hope you're hungry because that one is a biggie and gave me a few headaches. Happy that it's getting out of my way finally and I can offer it
This indicator will analyse for the defined date range, how a dollar cost average (DCA) method would have performed vs investing all the hard earnt money at the beginning
2- What's on the menu today ?
Please check this screenshot to understand what you're supposed to see : CLICK ME I'M A SCREENSHOT (I'll repeat this URL one more time below as I noticed some don't read the information on my description and then will come pinging me saying "sir me no understand your indicator, itz buggy sir"
(yes I finally thought about a way to share screenshots on TradingView, took me 4 weeks, I'm slow to understand things apparently)
My indicator works with all asset classes and with the daily/weekly/monthly timeframes
As always, let's review quickly the different fields so that you'll understand how to use it (and I won't get spammed with questions in DM ^^)
- Use current resolution : if checked will use the resolution of the chart
- Timeframe used for DCA : different timeframe to be used if Use current resolution is unchecked
- Amount invested in your local currency : The amount in Fiat money that will be invested at each period selected above
- Starting Date
- Ending Date
- Select a candle level for the desired timeframe : If you want to use the open or close of the selected period above. Might make a diffence when the timeframe is weekly or monthly
3 - Specifications used
I got the idea from this website dcabtc.com and the result shown by this website and my indicator are very interesting in general and for your own trading
The formula used for the DCA calculation is that one : Investopedia Dollar Cost Average
4 - How to interpret the results
"But sir which results ??"...... those ones : CLICK ME I'M A SCREENSHOT :) (strike #2 with the screenshot)
It will draw all the plots and will give you some nice data to analyze in the Data Window section of TradingView
I'm not completely satisfied with the tool yet but the results are very closed to the dcabtc website mentioned above
If you're trading a very bullish asset class (who said crypto ?), it's very interesting to see what a DCA strategy could bring in term of performance. But DCA is not magic, there is a time component which is the day/week/month you'll start to invest (those who invested in crypto beginning of 2018 in altcoins know what I'm talking about and ..............will hate me for this joke)
5 - What's next ?
As said, the educational post is coming next but not only.
Will probably post a strategy tomorrow using this indicator so that you can compare what's performing best between your trading and a dollar cost average method
I'll publish as a protected source this time a more advanced version of that one including DCA forecasts
6 - Suggested alternative (but I'll you doing it)
If you don't want to have this panel in the bottom with the plots and analyze the results in the data window, you can always create an infopanel like shown here Risk-Reward-InfoPanel/ and display all the data there
Hope you'll like it, like me, love it, love me, tip me :)
____________________________________________________________
Feel free to hit the thumbs up as it shows me that I'm not doing this for nothing and will motivate to deliver more quality content in the future. (Meaning... a few likes only = no indicators = Dave enjoying the beach)
- I'm an offically approved PineEditor/LUA/MT4 approved mentor on codementor. You can request a coaching with me if you want and I'll teach you how to build kick-ass indicators and strategies
Jump on a 1 to 1 coaching with me
- You can also hire for a custom dev of your indicator/strategy/bot/chrome extension/python
sma-pivotsThis model is based on this script
I change it to sma model . the model run on pivots high or low that are base on SMA
I make two SMA one for high pivots and one for low pivots ( I put for now at same distance but you need to change it according to needs)
because asset can be in bull period or bear period when we have two separate distance of SMA we can find the correct combination if to buy more or less by changing either the sma pivot of the low end or the sma pivots of the high end using the length . also global we can use the lookbar of bar numbers
one sma to both pivots is bad as it not consider the market situation but separation to two one for sell and one for buy can give you a better flexible model for enter or exit
so its your job to find what length is best suited for exit and what for enter .
example when we have two different length how it work on 4 hour
TTM SQUEEZE with ALERT by NM// ######################################################################################
// This script was created because the original TTM Squeeze script
// did trigger when only one of the Bollinger Bands was
// in the Keltner channel. It now gives the option to use it as was
// or to force it to only give a signal when both BB are in the Keltner channels
//
// Furthermore an alert was added to fire when we are squeezing
// no matter which option your choose (original or strict)
//
// To create an alert, click on the alerts in the right column on your screen
// then click on the +button to add an alert.
// Select from the conditions "CTTV Squeeze" and "Once per bar close"
// Keep in mind that you set this alert for one instrument and one particular time frame
//
// If you would have any questions, contact me :
// TradingView : @Nico.Muselle
// ######################################################################################
How to start using this script ?
1. Add this script to your favorites
2. Click on the Indicator-button on the top bar of your chart
3. Click on Favorites and find CTTV TTM
Do also check out my other indicators :
Percentage change -
Power Moving Average Pro - (use Moving Averages of higher time frames on lower time frame charts) -
Power Moving Average - (use 1 moving average of a higher time frame on the current time frame) -
BitFinex Longs vs. Shorts -
Relative Strength Index Direction -
Reversal Candles -
EMADiff -
Improved Linear Regression Bull and Bear Power v02 -
Improved Linear Regression Bull and Bear Power v01 -
PS : Sorry about the messy chart - Bottom indicators show the TTM Squeeze, top one being the original posted here, bottom one being the more strict option.
Guerrilla AdvancedThis indicator was designed with people without Pro License in mind (Including many of my close friends).
Basically, you will get a combo of few different tools in one box, with ability to turn them on and off with a single check mark, also, you have total control over the input numbers that was used in calculations if you so want to, for example, sometimes when i see a massive bullish up trend, i reduce the short rally from 12 to 8 even 6 to get faster signal for selling the trend.
So, what will you get in this pack?
1- Ichimoko. Yes, you heard it right, although we have it in the default tools but hey, it will use one indicator slot and if you don't have a pro license, you will use that slot
2- Rally. This is an old yet very powerful system for getting buy or sell signals, basically, you get two lines and for making the life easier i draw a cloud between them. when the trend passes above the cloud and it was bellow it in past, right after the very first candle that gets above the cloud you can put the buy order, and vice versa, the moment a candle body enters the cloud, if you want an aggressive signal, you can sell, if not, you may want to wait to see if the candles drop bellow the cloud or not then decide.
3- Resistance Support Cloud. Most of us always heard about resistance and support "lines" but many of us don't know that, in each trend, the trend line itself is a resistance or support line, and when you are going in a bullish or bearish tunnel, the floor and roof of tunnels are again resistance and supports, using this part of the tool, just like rally, you get a cloud that shows you the resistance / support "zone"
4- William Fractals. To be honest, I got this part of the code from another source available around. Why? looking at those fractal indicators, you can easily eyeball the trend line or existence of a tunnel.
5- Different EMA lines. If you are one of those people that use EMA lines for their trading, have fun with them, there are few different standard ones and even a custom one that you can put your desired number for it.
Trench Cross ScalperThe original script was posted on ProRealCode by user Nicolas.
This indicator is an attempt of scalping strategy by crossing the mean high or low weigthed price over a short "n" period. This 2 lines represent the black "trench" on screenshots attached.
When signal line (blue one) crossing the buy trigger one (dotted green one) a buy signal should occur and vice-versa for a sell signal (when crossing the dotted red one). I add an option to draw the white signal line as the close price value of the high/low ones if they are respectively above or below the trench' buy or sell lines trigger.
The yellow green and red brick lines serve as stoploss.
The indicator can be use alone with no price chart as its values are derivated from it, of course if you dont mind about candlesticks informations.
I think enter/exit trades should occur very quickly, as it were designed for scalping trading purpose. I didn't have much time to test it for a long period, so here it is as a concept indicator, despite that, it does have sense.
Fibonacci WavesFirst of all, ignore all other lines in the example chart except the four FAT lines. The four fat lines are the ones that define the fibonacci price leves. The lines have different extension offset to the right. The shortest one is the end of the second wave ( or leg B ), the next one is the end of C, the one following that is the end of D and the final one is the end of the final leg E.
The two input parameters is the start of A and the end of A.
If the start of A is larger than then end of A, the calculated series is a downward trend, else it is an upward trend.
Calculation based on old EWT simple wave expansion by fibonacci sequence.
0.618, 1.618, 0.382
Based on this source:
www.ino.com
Best Regards,
/Hull, 2015.05.20.15:50 ( placera.se )
Script_Algo - Double Smoothed CCI Strategy📉 The uniqueness of this non-trending oscillator strategy lies in the combination of two smoothed CCI lines: one signals entry into a position from overbought/oversold zones, and the other serves as a trend filter for entries. The smoothing of the fast and slow CCI lines significantly reduces market noise, allowing the filtering of false signals often generated by the standard CCI.
📚 For those unfamiliar with CCI:
The Commodity Channel Index (CCI) is a momentum-based oscillator used to identify overbought and oversold conditions.
It helps traders spot potential trend reversals or confirm trend strength by comparing the current price to its average over a period of time.
1️⃣ General Principle of Operation
⚡ Fast CCI: Generates main signals when exiting oversold and overbought zones.
📈 Slow CCI: Acts as a trend filter. For long positions, the slow CCI must be above zero (confirmation of an uptrend), and for short positions, it must be below zero (confirmation of a downtrend). This prevents the strategy from opening trades against the dominant trend.
🛡️ Dynamic ATR Stop-Loss: Unlike fixed-percentage stop-losses, a stop tied to the Average True Range (ATR) considers market volatility. During calm periods, the stop will be narrower, allowing for more profit capture. In highly volatile periods, the stop becomes wider, protecting against premature closures caused by noise.
📊 Comprehensive Risk Management: The strategy uses not only a take-profit based on signals (exit into the opposite zone) but also a protective ATR stop-loss and a mechanism to close trades upon receiving an opposite signal (e.g., closing a long when a short signal appears).
💡 Usefulness of the Strategy:
👨💻 For traders: Provides clear, mathematically justified entry and exit signals with built-in loss protection.
📉 For analysts: Visualizes the behavior of the double CCI on a separate panel, allowing study of the interaction of the fast and slow lines and their reaction to levels without mandatory trades.
📚 For learning: An excellent example of combining multiple indicators and capital management tools into a single trading system.
2️⃣ Detailed Algorithm Logic
📥 Long Entry Signals:
The fast smoothed CCI was below the oversold level (oversold_level, e.g., -100) and crossed this level upward (fast_exits_oversold).
The slow CCI at this moment is above zero (confirming an uptrend).
If both conditions are met, a long position is opened.
📤 Long Exit: Happens under one of these conditions:
The fast CCI crosses the overbought level (overbought_level) downward (exit_long).
The price reaches a stop-loss level calculated as entry price - (ATR * multiplier).
An opposite short signal appears (enter_short).
📥 Short Entry Signals:
The fast CCI was above the overbought level (overbought_level, e.g., 100) and crossed this level downward (fast_exits_overbought).
The slow CCI at this moment is below zero (confirming a downtrend).
If both conditions are met, a short position is opened.
📤 Short Exit: Happens under one of these conditions:
The fast CCI crosses the oversold level (oversold_level) upward (exit_short).
The price reaches a stop-loss level calculated as entry price + (ATR * multiplier).
An opposite long signal appears (enter_long).
3️⃣ Default Settings Description
⚙️ General Strategy Settings (strategy):
overlay=false: The indicator is displayed in a separate panel below the chart, not overlaid on it.
default_qty_type=strategy.cash, default_qty_value=1000, initial_capital=100000: The strategy manages a virtual capital of 100,000 USD, using 1,000 USD per trade.
commission_value=0.1, slippage=1: Commission (0.1%) and slippage (1 tick) are considered for more realistic testing.
⚡ Fast CCI (Signal Generator):
Length: 8 (short enough for quick price reactions).
Source: hlc3 (average of High, Low, Close).
Smoothing: WMA (Weighted Moving Average) for smoother results than SMA.
Smoothing Length: 5 (removes part of the noise).
📈 Slow CCI (Trend Filter):
Length: 20 (standard mid-term trend period).
Source: close.
Smoothing: WMA.
Smoothing Length: 21 (even stronger smoothing for a clean trend line).
📊 Levels:
Overbought Level: 100 (classic CCI level).
Oversold Level: -100 (classic CCI level).
🛡️ Stop-Loss (ATR):
ATR Length: 6 (short period for quick adaptation).
ATR Multiplier: 10.0 (very wide stop, designed for long-term trade holding and noise filtering).
💰 As seen in backtests, this strategy shows a steadily growing equity curve with minor drawdowns. On the highly liquid crypto pair XRPUSDT, the algorithm demonstrated a fairly high win rate and relatively high profit factor on a 4-hour timeframe over 4 years, though the overall profit is moderate.
⚠️ Important Notes
Always remember: Strategy results may not repeat in the future.
The market constantly changes, so:
✅ Monitor the situation
✅ Backtest regularly
✅ Adjust settings for each asset
Also remember about possible bugs in any algorithmic trading strategy.
Even if a script is well-tested, no one knows what unpredictable events the market may bring tomorrow.
⚠️ Risk Management:
Do not risk more than 1% of your deposit per trade, otherwise you may lose your account balance, since this strategy works without stop losses.
⚠️ Disclaimer
The author of the strategy does not encourage anyone to use this algorithm and bears no responsibility for any possible financial losses resulting from its application!
Any decision to use this strategy is made personally by the owners of TradingView accounts and cryptocurrency exchange accounts.
📝 Final Notes
This is not the final version. I already have ideas on how to improve it further, so follow me to not miss updates.
🐞 Bug Reports
If you notice any bugs or inconsistencies in my algorithm,
please let me know — I will try to fix them as quickly as possible.
💬 Feedback & Suggestions
If you have any ideas on how this or any of my other strategies can be improved, feel free to write to me. I will try to implement your suggestions in the script.
Wishing everyone good luck and stable profits! 🚀💰
Greer Gap# Greer Gap Indicator (No mitigation: i.e. removing false signals)
## Summary
The **Greer Gap Indicator** identifies **Fair Value Gaps (FVGs)** and introduces specialized **Greer Bull Gaps (Blue)** and **Greer Bear Gaps (Orange)** to highlight high-probability trading opportunities. Unlike traditional FVG indicators, it avoids hindsight bias by not removing historical gaps based on future price action, ensuring transparency in signal accuracy. Built upon LuxAlgo’s FVG logic, it adds unique filtering: only the first Greer Gap after an opposite gap is plotted if its level (min for Bull, max for Bear) is not higher/lower than the previous Greer Gap of the same type, while all valid gaps are recorded for comparison. Traders can use these gaps as support/resistance or entry signals, customizable via timeframe, look back, and display options.
## Description
This indicator detects and displays **Fair Value Gaps (FVGs)** on the chart, with a focus on specialized **Greer Gaps**:
- **Bullish Gaps (Green)**: Areas where the low of the current candle is above the high of a previous candle (look back period), indicating potential upward momentum.
- **Bearish Gaps (Red)**: Areas where the high of the current candle is below the low of a previous candle, indicating potential downward momentum.
- **Greer Bull Gaps (Blue)**: A bullish gap that is above the latest bearish gap's max. Only the first such gap after a bearish gap is plotted if it meets criteria (not higher than the previous Greer Bull Gap's min), but all valid ones are recorded for comparison.
- **Greer Bear Gaps (Orange)**: A bearish gap that is below the latest bullish gap's min. Only the first such gap after a bullish gap is plotted if it meets criteria (not lower than the previous Greer Bear Gap's max), but all valid ones are recorded.
## How It Works
The script uses a dynamic look back period to detect FVGs. It maintains a record of all detected gaps and applies additional logic for Greer Gaps:
- **Greer Bull Gaps**: Checks if the new bullish gap's min is above the latest bearish gap's max. Plots only if it's the first since the last bearish gap and its min is <= previous Greer Bull min (or first one).
- **Greer Bear Gaps**: Checks if the new bearish gap's max is below the latest bullish gap's min. Plots only if it's the first since the last bullish gap and its max is >= previous Greer Bear max (or first one).
- **Resets**: A new bearish gap resets the Greer Bull Gap flag, and a new bullish gap resets the Greer Bear Gap flag.
## How to Use
- **Timeframe**: Set a higher timeframe (e.g., 'D' for daily) to detect gaps from that timeframe on the current chart.
- **Look back Period**: Adjust to change gap detection sensitivity (default: 34). Use 2 if you want to compare to LuxAlgo
- **Extend**: Controls how far right the gap boxes extend.
- **Show Options**: Toggle visibility of all bullish/bearish gaps or Greer Gaps.
- **Colors**: Customize colors for each gap type.
- **Application**: Use Greer Gaps as potential support/resistance levels or entry signals, but combine with other analysis for confirmation.
## Originality and Credits
This script is inspired by and builds upon the **"Fair Value Gap "** indicator by LuxAlgo (available on TradingView: ()).
**Credits**: Thanks to LuxAlgo for the core FVG detection logic.
**Significant Changes**:
- Added **Greer Bull and Bear Gap** logic for filtered, directional gaps with reset mechanisms.
- Introduced recording of all valid Greer Gaps without plotting all, to compare levels without hindsight bias.
- **No mitigation/removal of gaps**: Unlike LuxAlgo's approach, which mitigates (removes or alters) gaps based on future price action (e.g., when filled), this can create a hindsight bias where incorrect signals disappear over time. If a signal is used for a trade and later removed due to new data, it doesn't reflect real-time performance accurately. The Greer Gap avoids this by using gap comparisons to validate signals without altering historical boxes, ensuring transparency in when signals were right or wrong.
