Wickless Candle Indicator with Extended Lines (final)This Pine Script indicator identifies “wickless” candles—those with no upper wick (when the close equals the high) or no lower wick (when the open equals the low)—and marks these events on the chart. When such a candle is detected, it:
Records the Level and Bar Index:
Saves the price level (high for wickless tops, low for wickless bottoms) and the bar index where the condition occurred.
Draws an Extended Horizontal Line:
Creates a green horizontal line for a wickless top or a red line for a wickless bottom, starting at the detection bar and extending across subsequent bars as long as the price remains below (for tops) or above (for bottoms) the recorded level.
Resets When the Price Breaks the Level:
If a future bar’s price moves beyond the saved level (i.e., a high above a wickless top or a low below a wickless bottom), the indicator resets that level, ending the extension of the line.
Visual Markers:
Additionally, it plots a small triangle above a wickless top and below a wickless bottom for easy identification on the chart.
Overall, this script helps traders visualize potential support or resistance levels created by candles that close at their highs or open at their lows, with lines that dynamically adjust as price evolves.
Komut dosyalarını "top" için ara
Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
.
(If you are comfortable with statistics feel free to skip ahead to the next section)
.
-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
.
---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
[MAD] Self-Optimizing RSIOverview
This script evaluates multiple RSI lengths within a specified range, calculates performance metrics for each, and identifies the top 3 configurations based on a custom scoring system. It then plots the three best RSI curves and optionally displays a summary table and label.
How It Works
The script calculates a custom RSI for each length in the range.
It simulates entering a long position when RSI crosses below the Buy Value and exits when RSI crosses above the Sell Value.
Each trade's return is stored in the relevant StatsContainer.
Metrics Computation
After all bars have been processed,
* Net Profit,
* Sharpe Ratio, and
* Win Rate
are computed for each RSI length.
A weighted score is then derived using the input weights.
Top 3 Identification
The script finds the three RSI lengths with the highest scores.
The RSI lines for these top 3 lengths are plotted in different colors.
If enabled, a table listing the top 3 results (Rank, RSI length, Sharpe, NetPnL, Win Rate) is shown.
If enabled, a label with the highest-scoring RSI length and its score is placed on the final bar.
Usage Tips
Adjust Min RSI Length and Max RSI Length to explore a narrower or wider range of periods.
Be aware, to high settings will slow down the calculation.
Experiment with different RSI Buy Value and RSI Sell Value settings if you prefer more or fewer trade signals.
Confirm that Min Trades Required aligns with the desired confidence level for the computed metrics.
Modify Weight: Sharpe, Weight: NetProfit, and Weight: WinRate to reflect which metrics are most important.
Troubleshooting
If metrics remain - or NaN, confirm enough trades (Min Trades Required) have occurred.
If no top 3 lines appear, it could mean no valid trades were taken in the specified range, or the script lacks sufficient bars to calculate RSI for some lengths. In this case set better buyvalue and sellvalues in the inputs
Disclaimer
Past performance is not indicative of future results specialy as this indicator can repaint based on max candles in memory which are limited by your subscription
Absolute Strength Index [ASI] (Zeiierman)█ Overview
The Absolute Strength Index (ASI) is a next-generation oscillator designed to measure the strength and direction of price movements by leveraging percentile-based normalization of historical returns. Developed by Zeiierman, this indicator offers a highly visual and intuitive approach to identifying market conditions, trend strength, and divergence opportunities.
By dynamically scaling price returns into a bounded oscillator (-10 to +10), the ASI helps traders spot overbought/oversold conditions, trend reversals, and momentum changes with enhanced precision. It also incorporates advanced features like divergence detection and adaptive signal smoothing for versatile trading applications.
█ How It Works
The ASI's core calculation methodology revolves around analyzing historical price returns, classifying them into top and bottom percentiles, and normalizing the current price movement within this framework. Here's a breakdown of its key components:
⚪ Returns Lookback
The ASI evaluates historical price returns over a user-defined period (Returns Lookback) to measure recent price behavior. This lookback window determines the sensitivity of the oscillator:
Shorter Lookback: Higher responsiveness to recent price movements, suitable for scalping or high-volatility assets.
Longer Lookback: Smoother oscillator behavior is ideal for identifying larger trends and avoiding false signals.
⚪ Percentile-Based Thresholds
The ASI categorizes returns into two groups:
Top Percentile (Winners): The upper X% of returns, representing the strongest upward price moves.
Bottom Percentile (Losers): The lower X% of returns, capturing the sharpest downward movements.
This percentile-based normalization ensures the ASI adapts to market conditions, filtering noise and emphasizing significant price changes.
⚪ Oscillator Normalization
The ASI normalizes current returns relative to the top and bottom thresholds:
Values range from -10 to +10, where:
+10 represents extreme bullish strength (above the top percentile threshold).
-10 indicates extreme bearish weakness (below the bottom percentile threshold).
⚪ Signal Line Smoothing
A signal line is optionally applied to the ASI using a variety of moving averages:
Options: SMA, EMA, WMA, RMA, or HMA.
Effect: Smooths the ASI to filter out noise, with shorter lengths offering higher responsiveness and longer lengths providing stability.
⚪ Divergence Detection
One of ASI's standout features is its ability to detect and highlight bullish and bearish divergences:
Bullish Divergence: The ASI forms higher lows while the price forms lower lows, signaling potential upward reversals.
Bearish Divergence: The ASI forms lower highs while the price forms higher highs, indicating potential downward reversals.
█ Key Differences from RSI
Dynamic Adaptability: ASI adjusts to market conditions through percentile-based scaling, while RSI uses static thresholds.
█ How to Use ASI
⚪ Trend Identification
Bullish Strength: ASI above zero suggests upward momentum, suitable for trend-following trades.
Bearish Weakness: ASI below zero signals downward momentum, ideal for short trades or exits from long positions.
⚪ Overbought/Oversold Levels
Overbought Zone: ASI in the +8 to +10 range indicates potential exhaustion of bullish momentum.
Oversold Zone: ASI in the -8 to -10 range points to potential reversal opportunities.
⚪ Divergence Signals
Look for bullish or bearish divergence labels to anticipate trend reversals before they occur.
⚪ Signal Line Crossovers
A crossover between the ASI and its signal line (e.g., EMA or SMA) can indicate a shift in momentum:
Bullish Crossover: ASI crosses above the signal line, signaling potential upside.
Bearish Crossover: ASI crosses below the signal line, suggesting downside momentum.
█ Settings Explained
⚪ Absolute Strength Index
Returns Lookback: Sets the sensitivity of the oscillator. Shorter periods detect short-term changes, while longer periods focus on broader trends.
Top/Bottom Percentiles: Adjust thresholds for defining winners and losers. Narrower percentiles increase sensitivity to outliers.
Signal Line Type: Choose from SMA, EMA, WMA, RMA, or HMA for smoothing.
Signal Line Length: Fine-tune the responsiveness of the signal line.
⚪ Divergence
Divergence Lookback: Adjusts the period for detecting divergence. Use longer lookbacks to reduce noise.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
PseudoPlotLibrary "PseudoPlot"
PseudoPlot: behave like plot and fill using polyline
This library enables line plotting by polyline like plot() and fill().
The core of polyline() is array of chart.point array, polyline() is called in its method.
Moreover, plotarea() makes a box in main chart, plotting data within the box is enabled.
It works so slowy to manage array of chart.point, so limit the target to visible area of the chart.
Due to polyline specifications, na and expression can not be used for colors.
1. pseudoplot
pseudoplot() behaves like plot().
//use plot()
plot(close)
//use pseudoplot()
pseudoplot(close)
Pseudoplot has label. Label is enabled when title argument is set.
In the example bellow, "close value" label is shown with line.
The label is shown at right of the line when recent bar is visible.
It is shown at 15% from the left of visible area when recent bar is not visible.
Just set "" if you don't need label.
//use plot()
plot(close,"close value")
//use pseudoplot
pseudoplot(close, "close value")
Arguments are designed in an order as similar as possible to plot.
plot(series, title, color, linewidth, style, trackprice, histbase, offset, join, editable, show_last, display, format, precision, force_overlay) → plot
pseudoplot(series, title, ,linecolor ,linewidth, linestyle, labelbg, labeltext, labelsize, shorttitle, format, xpos_from_left, overlay) → pseudo_plot
2. pseudofill
pseudofill() behaves like fill().
The label is shown(text only) at right of the line when recent bar is visible.
It is shown at 10% from the left of visible area when recent bar is not visible.
Just set "" if you don't need label.
//use plot() and fill()
p1=plot(open)
p2=plot(close)
fill(p1,p2)
//use pseudofill()
pseudofill(open,close)
Arguments are designed in an order as similar as possible to fill.
fill(hline1, hline2, color, title, editable, fillgaps, display) → void
pseudofill(series1, series2, fillcolor, title, linecolor, linewidth, linestyle, labeltext, labelsize, shorttitle, format, xpos_from_left, overlay) → pseudo_plot
3. plotarea and its methods
plotarea() makes a box in main chart. You can set the box position to top or bottom, and
the box height in percentage of the range of visible high and low prices.
x-coordinate of the box is from chart.left_visible_bar_time to chart.right_visible_bar_time,
y-coordinate is highest and lowest price of visible bars.
pseudoplot() and pseudofill() work as method of plotarea(box).
Usage is almost same as the function version, just set min and max value, y-coodinate is remapped automatically.
hline() is also available. The y-coordinate of hline is specified as a percentage from the bottom.
plotarea() and its associated methods are overlay=true as default.
Depending on the drawing order of the objects, plot may become invisible, so the bgcolor of plotarea should be na or tranceparent.
//1. make a plotarea
// bgcolor should be na or transparent color.
area=plotarea("bottom",30,"plotarea",bgcolor=na)
//2. plot in a plotarea
//(min=0, max=100 is omitted as it is the default.)
area.pseudoplot(ta.rsi(close,14))
//3. draw hlines
area.hline(30,linestyle="dotted",linewidth=2)
area.hline(70,linestyle="dotted",linewidth=2)
4. Data structure and sub methods
Array management is most imporant part of using polyline.
I don't know the proper way to handle array, so it is managed by array and array as intermediate data.
(type xy_arrays to manage bar_time and price as independent arrays.)
method cparray() pack arrays to array, when array includes both chart.left_visible_bar_time and chart.right_visible_bar.time.
Calling polyline is implemented as methods of array of chart.point.
Method creates polyline object if array is not empty.
method polyline(linecolor, linewidth, linestyle, overlay) → series polyline
method polyline_fill(fillcolor, linecolor, linewidth, linestyle, overlay) → series polyline
Also calling label is implemented as methods of array of chart.point.
Method creates label ofject if array is not empty.
Label is located at right edge of the chart when recent bar is visible, located at left side when recent bar is invisible.
label(title, labelbg, labeltext, labelsize, format, shorttitle, xpos_from_left, overlay) → series label
label_for_fill(title, labeltext, labelsize, format, shorttitle, xpos_from_left, overlay) → series label
visible_xyInit(series)
make arrays of visible x(bar_time) and y(price/value).
Parameters:
series (float) : (float) series variable
Returns: (xy_arrays)
method remap(this, bottom, top, min, max)
Namespace types: xy_arrays
Parameters:
this (xy_arrays)
bottom (float) : (float) bottom price to ajust.
top (float) : (float) top price to ajust.
min (float) : (float) min of src value.
max (float) : (float) max of src value.
Returns: (xy_arrays)
method polyline(this, linecolor, linewidth, linestyle, overlay)
Namespace types: array
Parameters:
this (array)
linecolor (color) : (color) color of polyline.
linewidth (int) : (int) width of polyline.
linestyle (string) : (string) linestyle of polyline. default is line.style_solid("solid"), others line.style_dashed("dashed"), line.style_dotted("dotted").
overlay (bool) : (bool) force_overlay of polyline. default is false.
Returns: (polyline)
method polyline_fill(this, fillcolor, linecolor, linewidth, linestyle, overlay)
Namespace types: array
Parameters:
this (array)
fillcolor (color)
linecolor (color) : (color) color of polyline.
linewidth (int) : (int) width of polyline.
linestyle (string) : (string) linestyle of polyline. default is line.style_solid("solid"), others line.style_dashed("dashed"), line.style_dotted("dotted").
overlay (bool) : (bool) force_overlay of polyline. default is false.
Returns: (polyline)
method label(this, title, labelbg, labeltext, labelsize, format, shorttitle, xpos_from_left, overlay)
Namespace types: array
Parameters:
this (array)
title (string) : (string) label text.
labelbg (color) : (color) color of label bg.
labeltext (color) : (color) color of label text.
labelsize (int) : (int) size of label.
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
shorttitle (string) : (string) another label text for recent bar is not visible.
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 15%.
overlay (bool) : (bool) force_overlay of label. default is false.
Returns: (label)
method label_for_fill(this, title, labeltext, labelsize, format, shorttitle, xpos_from_left, overlay)
Namespace types: array
Parameters:
this (array)
title (string) : (string) label text.
labeltext (color) : (color) color of label text.
labelsize (int) : (int) size of label.
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
shorttitle (string) : (string) another label text for recent bar is not visible.
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 10%.
overlay (bool) : (bool) force_overlay of label. default is false.
Returns: (label)
pseudoplot(series, title, linecolor, linewidth, linestyle, labelbg, labeltext, labelsize, shorttitle, format, xpos_from_left, overlay)
polyline like plot with label
Parameters:
series (float) : (float) series variable to plot.
title (string) : (string) title if need label. default value is ""(disable label).
linecolor (color) : (color) color of line.
linewidth (int) : (int) width of line.
linestyle (string) : (string) style of plotting line. default is "solid", others "dashed", "dotted".
labelbg (color) : (color) color of label bg.
labeltext (color) : (color) color of label text.
labelsize (int) : (int) size of label text.
shorttitle (string) : (string) another label text for recent bar is not visible.
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 15%.
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (pseudo_plot)
method pseudoplot(this, series, title, linecolor, linewidth, linestyle, labelbg, labeltext, labelsize, shorttitle, format, xpos_from_left, min, max, overlay)
Namespace types: series box
Parameters:
this (box)
series (float) : (float) series variable to plot.
title (string) : (string) title if need label. default value is ""(disable label).
linecolor (color) : (color) color of line.
linewidth (int) : (int) width of line.
linestyle (string) : (string) style of plotting line. default is "solid", others "dashed", "dotted".
labelbg (color) : (color) color of label bg.
labeltext (color) : (color) color of label text.
labelsize (int) : (int) size of label text.
shorttitle (string) : (string) another label text for recent bar is not visible.
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 15%.
min (float)
max (float)
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (pseudo_plot)
pseudofill(series1, series2, fillcolor, title, linecolor, linewidth, linestyle, labeltext, labelsize, shorttitle, format, xpos_from_left, overlay)
fill by polyline
Parameters:
series1 (float) : (float) series variable to plot.
series2 (float) : (float) series variable to plot.
fillcolor (color) : (color) color of fill.
title (string)
linecolor (color) : (color) color of line.
linewidth (int) : (int) width of line.
linestyle (string) : (string) style of plotting line. default is "solid", others "dashed", "dotted".
labeltext (color)
labelsize (int)
shorttitle (string)
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 15%.
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (pseudoplot)
method pseudofill(this, series1, series2, fillcolor, title, linecolor, linewidth, linestyle, labeltext, labelsize, shorttitle, format, xpos_from_left, min, max, overlay)
Namespace types: series box
Parameters:
this (box)
series1 (float) : (float) series variable to plot.
series2 (float) : (float) series variable to plot.
fillcolor (color) : (color) color of fill.
title (string)
linecolor (color) : (color) color of line.
linewidth (int) : (int) width of line.
linestyle (string) : (string) style of plotting line. default is "solid", others "dashed", "dotted".
labeltext (color)
labelsize (int)
shorttitle (string)
format (string) : (string) textformat of label. default is text.format_none("none"). others text.format_bold("bold"), text.format_italic("italic"), text.format_bold+text.format_italic("bold+italic").
xpos_from_left (int) : (int) another label x-position(percentage from left of chart width), when recent bar is not visible. default is 15%.
min (float)
max (float)
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (pseudo_plot)
plotarea(pos, height, title, bordercolor, borderwidth, bgcolor, textsize, textcolor, format, overlay)
subplot area in main chart
Parameters:
pos (string) : (string) position of subplot area, bottom or top.
height (int) : (float) percentage of visible chart heght.
title (string) : (string) text of area box.
bordercolor (color) : (color) color of border.
borderwidth (int) : (int) width of border.
bgcolor (color) : (string) color of area bg.
textsize (int)
textcolor (color)
format (string)
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (box)
method hline(this, ypos_from_bottom, linecolor, linestyle, linewidth, overlay)
Namespace types: series box
Parameters:
this (box)
ypos_from_bottom (float) : (float) percentage of box height from the bottom of box.(bottom is 0%, top is 100%).
linecolor (color) : (color) color of line.
linestyle (string) : (string) style of line.
linewidth (int) : (int) width of line.
overlay (bool) : (bool) force_overlay of polyline and label.
Returns: (line)
pseudo_plot
polyline and label.
Fields:
p (series polyline)
l (series label)
xy_arrays
x(bartime) and y(price or value) arrays.
Fields:
t (array)
p (array)
Fund Master Plus (TV Rev1, Dec2024)License: Mozilla Public License 2.0 (Open Source)
Version: Pine Script™ v6
Indicator Name: Fund Master Plus (TV Rev1, Dec2024)
Short Title: Fund Master Plus
About Fund Master Plus
Fund Master Plus indicator is an oscillating technical analysis tool designed to simulate the fund inflow and outflow trend.
Key features:
1. Fund Master Value and Candle
The candle highlights the direction of the Fund Master value.
Green candles represent an upward trend, while red candles indicate a downward trend.
When the candle crossover 0, it is a sign of the start of mid term bull, vice versa.
When the candle is above 0, it is a sign of mid-term bull, vice versa.
2. Fund Master Bar
This bar provides added visual representation of the Fund Master value.
Green bars represent and upward trend, while red bars indicate a downward trend.
3. FM EMA (Exponential Moving Average)
The Fund Master EMA (Exponential Moving Average) helps smooth out FM value fluctuations
and identify the overall trend.
When the candle crossover FM EMA, it is a sign of the start of short term bull, vice vera.
When the candle is above FM EMA, it is a sign of short term bull, vice versa.
4. EMA of FM EMA
This is an EMA of the Fund Master EMA, which can provide additional insights into the
trend's strength.
5. Candle Turn Green or Red
This feature generates alerts to signal potential trend changes.
6. Bottom Deviation & Top Deviation
Line plot and label of these deviation will show on indicator and the price chart to help user
identify potential buying and selling opportunities.
7. Alertcondition for Turn Green or Turn Red
User can set the alert using the Create Alert (the Clock Icon).
8. Table Summary
A table summary is provided to show indicator name, FM value, FM candle status,
Crossover, Crossunder, Turn Green, Turn Red status, Bar Number etc.
A tooltip for Filter Setting and a filter status check.
SOP to use the indicator:
Table (GR1):
Show Table: This option enables or disables the display of the table.
Text Size: This option allows you to set the text size for the table entries.
Width: This option sets the width of the table.
Fund Master Candle Color Setting (GR2):
FM candle will up by default.
This option enables the color setting of Fund Master candle.
Up: This option sets the color of the Fund Master candle for uptrend.
Down: This option sets the color of the Fund Master candle for downtrend.
Fund Master Bar and Color Setting (GR3):
Show Fund Master Bar: This option enables or disables the display of the Fund Master bar.
Up: This option sets the color of the Fund Master bar for uptrend.
Down: This option sets the color of the Fund Master bar for downtrend.
Fund Master EMA plots (GR4):
Show FM EMA: This option enables or disables the display of the Fund Master EMA line.
Look Back Period: This option sets the lookback period for the Fund Master EMA calculation.
EMA Color: This option sets the color of the Fund Master EMA line.
Show EMA of FM EMA: This option enables or disables the display of the EMA of the Fund Master EMA line.
Look Back Period 2: This option sets the lookback period for the EMA of the Fund Master EMA calculation.
Alerts: Fund Master Crossover & Crossunder EMA Line or 0 (GR5):
Show FM Crossover 0: This option enables or disables the display of the alert for FM crossover above the 0 line.
Show FM Crossunder 0: This option enables or disables the display of the alert for FM crossover below the 0 line.
Show FM Crossover EMA: This option enables or disables the display of the alert for FM crossover above the EMA line.
Show FM Crossunder EMA: This option enables or disables the display of the alert for FM crossover below the EMA line.
Bottom and Top Deviation (GR6):
Show Bottom Deviation: This option enables or disables the display of the bottom deviation line.
Show Top Deviation: This option enables or disables the display of the top deviation line.
Turn Green, Turn Red Alert (GR7):
Show Turn Green/Red Alerts: This option enables or disables the display of alerts for when the Fund Master value changes direction.
Current & Turn Green/Red Alerts: This option sets the number of bars to look back for the turn green/red alerts.
Band and User Input Setting (GR8):
100: This option enables or disables the display of the 100 band.
0: This option enables or disables the display of the 0 band.
-100: This option enables or disables the display of the -100 band.
User Input: This option enables or disables the display of a custom band based on user input.
Value: This option sets the value for the custom band.
Disclaimer
Attached chart is for the purpose of illustrating the use of indicator, no recommendation of buy/sell.
In this chart, all features in the setting are turned on (default and non default).
This chart is used to demonstrate the FM trend movement from mid-term bear to mid-term bull,
short-term bear and bull, bottom deviation and top deviation.
Hope this help. Merry Christmas and Happy New Year.
Fractal levels Gold [AstroHub]This indicator detects key fractal points on a price chart and visually marks them with shapes and levels. It helps traders identify potential reversal zones and dynamic support/resistance levels, enhancing market analysis.
Key Features:
Fractal Detection:
The indicator identifies top and bottom fractals using a 5-bar pattern.
A top fractal forms when the middle bar has a higher high compared to the two bars on either side.
A bottom fractal forms when the middle bar has a lower low compared to the two bars on either side.
Fractal Filtering:
The indicator can filter out "pristine" fractals (uninterrupted fractal patterns) based on custom conditions, making it more selective and reducing false signals.
Fractal Plotting:
are plotted as downward triangles.
are plotted as upward triangles.
Users can choose to display or hide fractal points and their corresponding labels.
Fractal Levels:
The indicator automatically plots fractals' levels on the chart, marking potential resistance and support zones.
Fractal levels change dynamically as new fractals are identified.
Customizable Display Options:
Show or hide fractals and levels with adjustable settings.
Choose whether to apply filtering for pristine fractals.
Display the pivot labels to easily track fractal positions.
How It Works:
The indicator uses a simple approach to recognize top and bottom fractals . When a valid fractal is detected, it highlights it on the chart and plots the corresponding price level.
By default, top fractals are shown above the bars (red color), and bottom fractals are shown below the bars (green color).
Fractal levels represent potential reversal points and can act as dynamic support and resistance zones.
Best Use:
The indicator is particularly useful in identifying reversal points and trend changes, helping traders to spot key price levels.
It can be used across various timeframes and markets, particularly for trend-following or reversal strategies.
Customizable Settings:
Show Pivots: Toggle the display of pivot points.
Show Pivot Labels: Display labels for pivot levels.
Show Fractals: Toggle fractal points on the chart.
Show Fractal Levels: Show or hide the levels corresponding to the detected fractals.
Filter for Pristine Fractals: Enable this option to filter out non-pristine fractals for higher accuracy.
Conclusion:
This indicator provides clear, actionable fractal signals, helping traders easily identify critical levels for entry and exit. With customizable settings and visual cues, it's suitable for both novice and expe
Ensemble Alerts█ OVERVIEW
This indicator creates highly customizable alert conditions and messages by combining several technical conditions into groups , which users can specify directly from the "Settings/Inputs" tab. It offers a flexible framework for building and testing complex alert conditions without requiring code modifications for each adjustment.
█ CONCEPTS
Ensemble analysis
Ensemble analysis is a form of data analysis that combines several "weaker" models to produce a potentially more robust model. In a trading context, one of the most prevalent forms of ensemble analysis is the aggregation (grouping) of several indicators to derive market insights and reinforce trading decisions. With this analysis, traders typically inspect multiple indicators, signaling trade actions when specific conditions or groups of conditions align.
Simplifying ensemble creation
Combining indicators into one or more ensembles can be challenging, especially for users without programming knowledge. It usually involves writing custom scripts to aggregate the indicators and trigger trading alerts based on the confluence of specific conditions. Making such scripts customizable via inputs poses an additional challenge, as it often involves complicated input menus and conditional logic.
This indicator addresses these challenges by providing a simple, flexible input menu where users can easily define alert criteria by listing groups of conditions from various technical indicators in simple text boxes . With this script, you can create complex alert conditions intuitively from the "Settings/Inputs" tab without ever writing or modifying a single line of code. This framework makes advanced alert setups more accessible to non-coders. Additionally, it can help Pine programmers save time and effort when testing various condition combinations.
█ FEATURES
Configurable alert direction
The "Direction" dropdown at the top of the "Settings/Inputs" tab specifies the allowed direction for the alert conditions. There are four possible options:
• Up only : The indicator only evaluates upward conditions.
• Down only : The indicator only evaluates downward conditions.
• Up and down (default): The indicator evaluates upward and downward conditions, creating alert triggers for both.
• Alternating : The indicator prevents alert triggers for consecutive conditions in the same direction. An upward condition must be the first occurrence after a downward condition to trigger an alert, and vice versa for downward conditions.
Flexible condition groups
This script features six text inputs where users can define distinct condition groups (ensembles) for their alerts. An alert trigger occurs if all the conditions in at least one group occur.
Each input accepts a comma-separated list of numbers with optional spaces (e.g., "1, 4, 8"). Each listed number, from 1 to 35, corresponds to a specific individual condition. Below are the conditions that the numbers represent:
1 — RSI above/below threshold
2 — RSI below/above threshold
3 — Stoch above/below threshold
4 — Stoch below/above threshold
5 — Stoch K over/under D
6 — Stoch K under/over D
7 — AO above/below threshold
8 — AO below/above threshold
9 — AO rising/falling
10 — AO falling/rising
11 — Supertrend up/down
12 — Supertrend down/up
13 — Close above/below MA
14 — Close below/above MA
15 — Close above/below open
16 — Close below/above open
17 — Close increase/decrease
18 — Close decrease/increase
19 — Close near Donchian top/bottom (Close > (Mid + HH) / 2)
20 — Close near Donchian bottom/top (Close < (Mid + LL) / 2)
21 — New Donchian high/low
22 — New Donchian low/high
23 — Rising volume
24 — Falling volume
25 — Volume above average (Volume > SMA(Volume, 20))
26 — Volume below average (Volume < SMA(Volume, 20))
27 — High body to range ratio (Abs(Close - Open) / (High - Low) > 0.5)
28 — Low body to range ratio (Abs(Close - Open) / (High - Low) < 0.5)
29 — High relative volatility (ATR(7) > ATR(40))
30 — Low relative volatility (ATR(7) < ATR(40))
31 — External condition 1
32 — External condition 2
33 — External condition 3
34 — External condition 4
35 — External condition 5
These constituent conditions fall into three distinct categories:
• Directional pairs : The numbers 1-22 correspond to pairs of opposing upward and downward conditions. For example, if one of the inputs includes "1" in the comma-separated list, that group uses the "RSI above/below threshold" condition pair. In this case, the RSI must be above a high threshold for the group to trigger an upward alert, and the RSI must be below a defined low threshold to trigger a downward alert.
• Non-directional filters : The numbers 23-30 correspond to conditions that do not represent directional information. These conditions act as filters for both upward and downward alerts. Traders often use non-directional conditions to refine trending or mean reversion signals. For instance, if one of the input lists includes "30", that group uses the "Low relative volatility" condition. The group can trigger an upward or downward alert only if the 7-period Average True Range (ATR) is below the 40-period ATR.
• External conditions : The numbers 31-35 correspond to external conditions based on the plots from other indicators on the chart. To set these conditions, use the source inputs in the "External conditions" section near the bottom of the "Settings/Inputs" tab. The external value can represent an upward, downward, or non-directional condition based on the following logic:
▫ Any value above 0 represents an upward condition.
▫ Any value below 0 represents a downward condition.
▫ If the checkbox next to the source input is selected, the condition becomes non-directional . Any group that uses the condition can trigger upward or downward alerts only if the source value is not 0.
To learn more about using plotted values from other indicators, see this article in our Help Center and the Source input section of our Pine Script™ User Manual.
Group markers
Each comma-separated list represents a distinct group , where all the listed conditions must occur to trigger an alert. This script assigns preset markers (names) to each condition group to make the active ensembles easily identifiable in the generated alert messages and labels. The markers assigned to each group use the format "M", where "M" is short for "Marker" and "x" is the group number. The titles of the inputs at the top of the "Settings/Inputs" tab show these markers for convenience.
For upward conditions, the labels and alert messages show group markers with upward triangles (e.g., "M1▲"). For downward conditions, they show markers with downward triangles (e.g., "M1▼").
NOTE: By default, this script populates the "M1" field with a pre-configured list for a mean reversion group ("2,18,24,28"). The other fields are empty. If any "M*" input does not contain a value, the indicator ignores it in the alert calculations.
Custom alert messages
By default, the indicator's alert message text contains the activated markers and their direction as a comma-separated list. Users can override this message for upward or downward alerts with the two text fields at the bottom of the "Settings/Inputs" tab. When the fields are not empty , the alerts use that text instead of the default marker list.
NOTE: This script generates alert triggers, not the alerts themselves. To set up an alert based on this script's conditions, open the "Create Alert" dialog box, then select the "Ensemble Alerts" and "Any alert() function call" options in the "Condition" tabs. See the Alerts FAQ in our Pine Script™ User Manual for more information.
Condition visualization
This script offers organized visualizations of its conditions, allowing users to inspect the behaviors of each condition alongside the specified groups. The key visual features include:
1) Conditional plots
• The indicator plots the history of each individual condition, excluding the external conditions, as circles at different levels. Opposite conditions appear at positive and negative levels with the same absolute value. The plots for each condition show values only on the bars where they occur.
• Each condition's plot is color-coded based on its type. Aqua and orange plots represent opposing directional conditions, and purple plots represent non-directional conditions. The titles of the plots also contain the condition numbers to which they apply.
• The plots in the separate pane can be turned on or off with the "Show plots in pane" checkbox near the top of the "Settings/Inputs" tab. This input only toggles the color-coded circles, which reduces the graphical load. If you deactivate these visuals, you can still inspect each condition from the script's status line and the Data Window.
• As a bonus, the indicator includes "Up alert" and "Down alert" plots in the Data Window, representing the combined upward and downward ensemble alert conditions. These plots are also usable in additional indicator-on-indicator calculations.
2) Dynamic labels
• The indicator draws a label on the main chart pane displaying the activated group markers (e.g., "M1▲") each time an alert condition occurs.
• The labels for upward alerts appear below chart bars. The labels for downward alerts appear above the bars.
NOTE: This indicator can display up to 500 labels because that is the maximum allowed for a single Pine script.
3) Background highlighting
• The indicator can highlight the main chart's background on bars where upward or downward condition groups activate. Use the "Highlight background" inputs in the "Settings/Inputs" tab to enable these highlights and customize their colors.
• Unlike the dynamic labels, these background highlights are available for all chart bars, irrespective of the number of condition occurrences.
█ NOTES
• This script uses Pine Script™ v6, the latest version of TradingView's programming language. See the Release notes and Migration guide to learn what's new in v6 and how to convert your scripts to this version.
• This script imports our new Alerts library, which features functions that provide high-level simplicity for working with complex compound conditions and alerts. We used the library's `compoundAlertMessage()` function in this indicator. It evaluates items from "bool" arrays in groups specified by an array of strings containing comma-separated index lists , returning a tuple of "string" values containing the marker of each activated group.
• The script imports the latest version of the ta library to calculate several technical indicators not included in the built-in `ta.*` namespace, including Double Exponential Moving Average (DEMA), Triple Exponential Moving Average (TEMA), Fractal Adaptive Moving Average (FRAMA), Tilson T3, Awesome Oscillator (AO), Full Stochastic (%K and %D), SuperTrend, and Donchian Channels.
• The script uses the `force_overlay` parameter in the label.new() and bgcolor() calls to display the drawings and background colors in the main chart pane.
• The plots and hlines use the available `display.*` constants to determine whether the visuals appear in the separate pane.
Look first. Then leap.
No Wick Setup Indicator
**No Wick Setup Indicator**
This is a custom trading indicator designed to identify and signal potential buy and sell opportunities based on candlestick patterns with no wicks. Specifically, it looks for candles with no wicks at the bottom (bullish setup) or no wicks at the top (bearish setup). Here's how it works:
**Key Features:**
- **Bullish Setup**: A green candlestick with no bottom wick (i.e., the open price is equal to the low price of the candle) is considered a potential bullish signal. A trendline is drawn at the bottom of this candle. When the market price returns to this trendline, a buy signal is generated.
- **Bearish Setup**: A red candlestick with no top wick (i.e., the open price is equal to the high price of the candle) is considered a potential bearish signal. A trendline is drawn at the top of this candle. When the market price returns to this trendline, a sell signal is generated.
- **Timeframe**: This indicator works exclusively on the **30-minute timeframe**.
**How It Works:**
1. When a candlestick pattern with no bottom wick (bullish setup) is identified, a trendline is drawn at the low of the candlestick.
2. When a candlestick pattern with no top wick (bearish setup) is identified, a trendline is drawn at the high of the candlestick.
3. The indicator then tracks the market price and waits for it to return to the respective trendline level.
4. **Buy Signal**: When the market price touches or goes below the bullish trendline, a **Buy** signal is displayed on the chart with an upward arrow.
5. **Sell Signal**: When the market price touches or goes above the bearish trendline, a **Sell** signal is displayed on the chart with a downward arrow.
**Visual Elements:**
- **Trendlines**: Horizontal lines drawn at the bottom (bullish) or top (bearish) of the candlesticks with no wick.
- **Buy/Sell Labels**: Labels indicating "Buy" or "Sell" appear when the market price returns to the trendline.
**Why Use This Indicator?**
- This indicator helps identify specific price levels where the market might reverse or consolidate based on candlestick structure, offering potential entry points for trades.
- It allows traders to focus on price action and market behavior without relying on more complex indicators.
Bitcoin Cycle High/Low with functional Alert [heswaikcrypt]Introduction
Just as machines are fine-tuned for maximum efficiency, trading indicators must evolve to meet the demands of ever-changing markets.
Credit goes to the initial author, @NoCreditsLeft I only improved the existing Pi-cycle indicator with a functional alert and included a bull mode indicator in the script. The alert can help you get a live alert at candle close when the cycle tops, bottoms, and the potential bull phase switch occurs.
Philip Swift’s Pi Cycle Top Indicator is a brilliant example of leveraging mathematical relationships to signal critical turning points in Bitcoin’s price cycles. Historically, it has identified market and local tops with some relative accuracy, often within three days, as demonstrated in all the previous bull run cycles.
At its core, the Pi Cycle Indicator derives its name from the mathematical constant π (pi), achieved by using simple moving averages (MAs) in a specific ratio: 𝜋 = Long MA/short MA
The Bull mode switch is calculated using a crossover of the short exponentia moving average and the long moving average.
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.
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Knowing when Bitcoin reaches its top—and receiving timely alerts about it—is crucial for successful trading. The indicator is designed to signal;
Potential Bitcoin tops: Purple label
Potential Bitcoin bottoms : green Label, and
Parabolic swing : Yellow diamond shape (relating to the market switching to a potential bull mode)
"Please note: This indicator is tailored for Bitcoin using historical data analysis and should not be considered definitive. However accurate it might be."
Setting alerts
To set the alert conditions, select any alert function call to get alert whenever the conditions are met. The script is configured on dialy TF; you can set it on 1D or weekly TF.
Enjoy and Trade smartly
Advanced Pattern Detector**Script Overview**
**Indicator Name:** Advanced Pattern Detector
**Pine Script Version:** v5
**Indicator Type:** Overlaid on the chart (overlay=true)
**Main Features:**
- Detection and visualization of various technical patterns.
- Generation of BUY and SELL signals based on detected patterns.
- Display of Fibonacci levels to identify potential support and resistance levels.
- Ability to enable or disable each pattern through the indicator settings.
---
**Indicator Settings**
**Switches to Enable/Disable Patterns**
At the top of the indicator, there are parameters that allow the user to select which patterns will be displayed on the chart:
- Three Drives
- Rounding Top
- Rounding Bottom
- ZigZag Pattern
- Inverse Head and Shoulders
- Fibonacci Retracement
**Parameters for ZigZag**
Settings are also available for the ZigZag pattern, such as the depth of peak and trough detection, allowing the user to adjust the indicator's sensitivity to price changes.
---
**Pattern Detection**
Each pattern is implemented with its own logic, which checks specific conditions on the current bar (candle). Below are the main patterns:
1. **Three Drives**
- **Description:** This pattern consists of three consecutive price movements in one direction (up or down). It can signal the continuation of the current trend or its reversal.
- **How It Works:**
- **Upward Drive:** The indicator checks that the closing price of each subsequent candle is higher than the previous one for three bars.
- **Downward Drive:** The indicator checks that the closing price of each subsequent candle is lower than the previous one for three bars.
2. **Rounding Top**
- **Description:** A pattern representing a smooth decrease in maximum prices over several bars, which may indicate a potential downward trend reversal.
- **How It Works:**
- The indicator checks that the maximum prices of the last five bars are gradually decreasing, and the current bar shows a decrease in the maximum price.
3. **Rounding Bottom**
- **Description:** A pattern characterized by a smooth increase in minimum prices over several bars, signaling a possible upward trend reversal.
- **How It Works:**
- The indicator checks that the minimum prices of the last five bars are gradually increasing, and the current bar shows an increase in the minimum price.
4. **ZigZag Pattern**
- **Description:** Used to identify corrective movements on the chart. The pattern shows peak and trough points connected by lines, helping to visualize the main price movement.
- **How It Works:**
- The indicator uses a function to determine local maxima and minima based on the specified depth.
- Detected peaks and troughs are connected by lines to create a visual zigzag structure.
5. **Inverse Head and Shoulders**
- **Description:** An inverted head and shoulders formation signals a possible reversal of a downward trend to an upward one.
- **How It Works:**
- The indicator looks for three local minima: the left shoulder, the head (the lowest minimum), and the right shoulder.
- It checks that the left and right shoulders are approximately at the same level and below the head.
6. **Fibonacci Retracement Levels**
- **Description:** Automatically builds key Fibonacci levels based on the maximum and minimum prices over the last 50 bars. These levels are often used as potential support and resistance levels.
- **How It Works:**
- Daily, the minimum and maximum prices over the last 50 bars are calculated.
- Based on these values, Fibonacci levels are drawn: 100%, 23.6%, 38.2%, 50%, 61.8%, and 0%.
- Old levels are removed when a new day begins to keep the chart clean and up-to-date.
---
**Generation of Buy and Sell Signals**
The indicator combines the results of detected patterns to generate trading signals:
- **Buy Signals (BUY):**
- Rounding Bottom
- Three Drives Up
- Inverse Head and Shoulders
- ZigZag Low
- **Sell Signals (SELL):**
- Rounding Top
- Three Drives Down
- Inverse Head and Shoulders
- ZigZag High
**How It Works:**
- If one or more buy conditions are met, a "BUY" label is displayed below the corresponding bar on the chart.
- If one or more sell conditions are met, a "SELL" label is displayed above the corresponding bar on the chart.
---
**Visualization of Patterns on the Chart**
Each detected pattern is visualized using various graphical elements, allowing traders to easily identify them on the chart:
- **Three Drives Up:** Green upward triangle below the bar.
- **Three Drives Down:** Red downward triangle above the bar.
- **Rounding Top:** Orange "RT" label above the bar.
- **Rounding Bottom:** Blue "RB" label below the bar.
- **Inverse Head and Shoulders:** Turquoise "iH&S" label below the bar.
- **ZigZag High/Low:** Purple circles at the peaks and troughs of the zigzag.
---
**Displaying Fibonacci Levels**
Fibonacci levels are displayed as horizontal lines on the chart with corresponding labels. These levels help traders determine potential entry and exit points, as well as support and resistance levels.
---
**Drawing ZigZag Lines**
ZigZag lines connect the detected peaks and troughs, visualizing corrective movements. To avoid cluttering the chart, the number of lines is limited, and old lines are automatically removed as new ones are added.
Bitcoin Cycle [BigBeluga]Bitcoin Cycle Indicator is designed exclusively for analyzing Bitcoin’s long-term market cycles, working only on the 1D BTC chart . This indicator provides an in-depth view of potential cycle tops and bottoms, assisting traders in identifying key phases in Bitcoin’s market evolution.
🔵 Key Features:
Heatmap Cycle Phases: The indicator colors each cycle from blue to red , reflecting Bitcoin’s market cycle progression. Cooler colors (blue/green) signal potential accumulation or early growth phases, while warmer colors (yellow/red) indicate maturation and potential top regions.
All-Time High (ATH) and Future ATH Projection: Tracks the current ATH in real-time, while applying a linear regression model to project a possible new ATH in the future. This projection aims to provide insights into the next major cycle peak for long-term strategy.
Dashboard Overview: Displays the current ATH, potential new ATH, and the percentage distance between them. This helps users assess how far the current price is from the projected target.
Top & Bottom Cycle Signals: Red down arrows mark significant price peaks, potentially indicating cycle tops. Up arrows, numbered sequentially (inside each cycle), denote possible bottom signals for strategic DCA (Dollar Cost Averaging) entries.
1D BTC Chart Only: Built solely for the 1D BTC timeframe. Switching to any other timeframe or asset will trigger a warning message: " BTC 1D Only ." This ensures accuracy in analyzing Bitcoin’s unique cyclical behavior.
🔵 When to Use:
Ideal for long-term Bitcoin investors and cycle analysts, the Bitcoin Cycle Indicator empowers users to:
Identify key accumulation and distribution phases.
Track Bitcoin’s cyclical highs and lows with visual heatmap cues.
Estimate future potential highs based on historical patterns.
Strategize long-term positions by monitoring cycle tops and possible accumulation zones.
By visualizing Bitcoin’s cycles with color-coded clarity and top/bottom markers, this indicator is an essential tool for any BTC analyst aiming to navigate market cycles effectively.
Open-Close Absolute Difference with Threshold CountsThe Open-Close Absolute Difference with Threshold Counts indicator is a versatile tool designed to help traders analyze the volatility and price movements within any given timeframe on their charts. This indicator calculates the absolute difference between the open and close prices for each bar, providing a clear visualization through a color-coded histogram.
Key features include:
• Timeframe Flexibility: Utilizes the current chart’s timeframe, whether it’s a 5-minute, hourly, or daily chart.
• Custom Thresholds: Allows you to set up to four custom threshold levels (Thresholds A, B, C, and D) with default values of 10, 15, 25, and 35, respectively.
• Period Customization: Enables you to define the number of bars (N) over which the indicator calculates the counts, with a default of 100 bars.
• Visual Threshold Lines: Plots horizontal dashed lines on the histogram representing each threshold for easy visual reference.
• Dynamic Counting: Counts and displays the number of times the absolute difference is less than or greater than each threshold within the specified period.
• Customizable Table Position: Offers the flexibility to position the results table anywhere on the chart (e.g., Top Right, Bottom Left).
How It Works:
1. Absolute Difference Calculation:
• For each bar on the chart, the indicator calculates the absolute difference between the open and close prices.
• This difference is plotted as a histogram:
• Green Bars: Close price is higher than the open price.
• Red Bars: Close price is lower than the open price.
2. Threshold Comparison and Counting:
• Compares the absolute difference to each of the four thresholds.
• Determines whether the difference is less than or greater than each threshold.
• Utilizes the ta.sum() function to count occurrences over the specified number of bars (N).
3. Results Table:
• Displays a table with three columns:
• Left Column: Counts where the absolute difference is less than the threshold.
• Middle Column: The threshold value.
• Right Column: Counts where the absolute difference is greater than the threshold.
• The table updates dynamically and can be positioned anywhere on the chart according to your preference.
4. Threshold Lines on Histogram:
• Plots horizontal dashed lines at each threshold level.
• Each line is color-coded for distinction:
• Threshold A: Yellow
• Threshold B: Orange
• Threshold C: Purple
• Threshold D: Blue
How to Use:
1. Add the Indicator to Your Chart:
• Open the Pine Editor on TradingView.
• Copy and paste the provided code into the editor.
• Click “Add to Chart.”
2. Configure Settings:
• Number of Bars (N):
• Set the period over which you want to calculate the counts (default is 100).
• Thresholds A, B, C, D:
• Input your desired threshold values (defaults are 10, 15, 25, 35).
• Table Position:
• Choose where you want the results table to appear on the chart:
• Options include “Top Left,” “Top Center,” “Top Right,” “Bottom Left,” “Bottom Center,” “Bottom Right.”
3. Interpret the Histogram:
• Observe the absolute differences plotted as a histogram.
• Use the color-coded bars to quickly assess whether the close price was higher or lower than the open price.
4. Analyze the Counts Table:
• Review the counts of occurrences where the absolute difference was less than or greater than each threshold.
• Use this data to gauge volatility and price movement intensity over the specified period.
5. Visual Reference with Threshold Lines:
• Refer to the horizontal dashed lines on the histogram to see how the absolute differences align with your thresholds.
Example Use Case:
Suppose you’re analyzing a 5-minute chart for a particular stock and want to understand its short-term volatility:
• Set the Number of Bars (N) to 50 to analyze the recent 50 bars.
• Adjust Thresholds based on the typical price movements of the stock, e.g., Threshold A: 0.5, Threshold B: 1.0, Threshold C: 1.5, Threshold D: 2.0.
• Position the Table at the “Top Right” for easy viewing.
By doing so, you can:
• Quickly see how often the stock experiences significant price movements within 5-minute intervals.
• Make informed decisions about entry and exit points based on the volatility patterns.
• Customize the thresholds and periods as market conditions change.
Benefits:
• Customizable Analysis: Tailor the indicator to fit various trading styles and timeframes.
• Quick Visualization: Instantly assess market volatility and price movement direction.
• Enhanced Decision-Making: Use the counts and visual cues to make more informed trading decisions.
• User-Friendly Interface: Simple configuration and clear display of information.
Note: Always test the indicator with different settings to find the configuration that best suits your trading strategy. This indicator should be used as part of a comprehensive analysis and not as the sole basis for trading decisions.
LiquidityFlow Dominance+Alerts (btc.d, T3, Stables)LiquidityFlow Dominance+Alerts: Overview & Usage Guide
Overview
The LiquidityFlow Dominance+Alerts indicator provides a dynamic view of liquidity flow across Bitcoin, Altcoins, and Stablecoins, helping track liquidity shifts and identify market sentiment. By integrating moving averages, custom alerts, and thresholds for extreme outliers, this indicator helps to anticipate bullish and bearish shifts in liquidity and alert market tops and bottoms.
Key features include:
1. Liquidity Flow Monitoring : Track liquidity flow across Bitcoin (BTC), Altcoins (TOTAL3), and Stablecoins (USDT, USDC, DAI).
2. Custom Alerts : Set alerts for key liquidity shifts and extreme conditions in Stablecoin dominance, both with static and moving average (MA)-based calculations.
3. Moving Averages : Use Simple, Exponential, or Weighted Moving Averages to smooth out market data for more reliable signals.
4. Outlier Detection : Identify potential tops and bottoms using thresholds for Stablecoin dominance, with alerts for extreme movements.
Functionality
Data Inputs and Key Metrics
- Symbols Monitored:
- Bitcoin Dominance (BTC.D)
- Altcoin Market Cap (TOTAL3)
- Stablecoins (USDT.D, USDC.D, DAI.D)
- Liquidity Flow Conditions:
- Track percentage changes in dominance across sectors to detect liquidity flow into Bitcoin, Altcoins, or Stablecoins.
- Custom Metrics:
- Liquidity Flow Index: BTC Dominance minus Stablecoin Dominance.
- Liquidity Flow Ratio: BTC Dominance divided by the combined dominance of Stablecoins and Altcoins.
Moving Average Integration
- Select from SMA, EMA, or WMA to apply moving averages to the dominance metrics. Moving averages help smooth out short-term volatility and provide more consistent signals.
- Moving averages are applied to each sector (BTC, Altcoins, and Stablecoins) and compared to their previous period values to determine shifts in liquidity.
Alerts and Thresholds
- % Change Lookback Period: Adjust the lookback period to align with the timeframe of your chart. Shorter timeframes may require a lower lookback period, while higher timeframes may benefit from longer periods.
- Stables Bull/Bear % for Alerts: Set a threshold for when Stablecoin dominance becomes a bullish or bearish signal relative to BTC and Altcoins. A higher threshold may be used in volatile markets to filter out noise.
- Extreme Outliers Detection: Use the **Stables Up/Down Extreme Threshold** to identify potential market tops or bottoms when Stablecoin dominance deviates significantly from historical trends. The **Extreme Lookback Period** controls the time window for detecting these anomalies.
How to Use the Indicator
Adjusting the % Change Lookback Period
- The `% Change Lookback Period` should be adjusted based on your chart’s timeframe. For example, a shorter period (e.g., 7) works well for intraday charts, while longer periods (e.g., 14) might be more suitable for daily or weekly charts.
Setting Thresholds for Alerts
- Stables Bull/Bear % for Alerts: Adjust this setting to define when Stablecoin dominance triggers bullish or bearish alerts. A value like 1% could be a good starting point for most market conditions but can be fine-tuned based on volatility.
- Extreme Lookback Period: Define the lookback period for detecting extreme moves in Stablecoin dominance. This will help identify major tops and bottoms in the market. For shorter-term trades, consider using a shorter extreme lookback (e.g., 7-10 periods).
Alerts for Liquidity Shifts
- The indicator supports alerts for key liquidity shifts, which are useful for staying ahead of market movements. Alerts can be set to notify you when liquidity moves into:
- Bitcoin: Indicating a potential bullish trend for Bitcoin.
- Altcoins: Signaling altcoins are bullish.
- Stablecoins: Suggesting a risk-off environment or market correction.
Extreme Alerts for Stables
- Extreme Up/Down Alerts: These are triggered when Stablecoin dominance crosses extreme thresholds. For example, if Stablecoin dominance rises more than 14% over a set period, it could signal a market top, while a significant drop could indicate a market bottom.
Moving Average Calculations
- In addition to static percentage changes, moving averages can be applied to smooth out dominance values. The type and length of the moving average can be customized:
- SMA (Simple Moving Average): Best for smoothing out volatility in a linear way.
- EMA (Exponential Moving Average): More responsive to recent data, making it useful in faster markets.
- WMA (Weighted Moving Average): Emphasizes more recent data, but less reactive than the EMA.
Additional Usage Tips:
- Background Colors: The indicator visually highlights the dominant liquidity flow:
- Orange: Liquidity is shifting toward Bitcoin.
- Aqua: Liquidity is flowing into Altcoins.
- Red: Liquidity is moving into Stablecoins.
BTC Arcturus IndicatorBTC Arcturus Indicator: This indicator is designed to create buy and sell signals based on the market value of Bitcoin. It also predicts potential market tops with the Pi Cycle Top indicator.
How Does It Work?
1. MVRVZ (Market Value to Realized Value-Z Score) Calculation:
MC: Bitcoin's market cap (Market Cap) is pulled daily from Glassnode data.
MCR: Realized Market Cap of Bitcoin is taken daily from Coinmetrics data.
MVRVZ: It is calculated by dividing the difference between Bitcoin's market value and realized market value by one standard deviation. This value indicates whether the market is overvalued or undervalued.
2. Reception and Warning Signals:
Buy Signal: When MVRVZ falls below the -0.255 threshold value, the indicator gives a "Buy" signal. This indicates that Bitcoin is undervalued and may be a buying opportunity.
Warning Signal: A warning signal turns on when MVRVZ exceeds the threshold value of 2.765. This indicates that the market is approaching saturation and caution is warranted.
3. Tracking the Highest MVRVZ Value:
The indicator records the highest MVRVZ value in the last 10 candlesticks. This value is used to determine whether the market has reached its highest risk levels.
4. Warning Display:
If the MVRVZ value matches the highest value in the last 10 bars and this warning has not been displayed before, a "Warning" signal is displayed.
Once the warning signal is shown, no further warnings are shown for 10 candles.
5. Pi Cycle Top Indicator:
Pi Cycle Top: This indicator predicts Bitcoin tops by comparing two moving averages (350-day and 111-day). If the short-term moving average falls below the long-term moving average, this is considered a sell signal.
The indicator displays this signal with the label "Sell", indicating a potential market top.
User Guide:
Green Buy Signal: It means Bitcoin is cheap and offers a buying opportunity.
Yellow Warning Signal: Indicates that Bitcoin has reached possible profit taking points and caution should be exercised.
Red Sell Signal: Indicates that Bitcoin has reached market saturation and it may be appropriate to sell.
Gann Swing Strategy [1 Bar - Multi Layer]Use this Strategy to Fine-tune inputs for your Gann swing strategy.
Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data.
MEANINGFUL DESCRIPTION:
The Gann Swing Chart using the One-Bar type, also known as the Minor Trend Chart, is designed to follow single-bar movements in the market. It helps identify trends by tracking price movements. When the market makes a higher high than the previous bar from a low price, the One-Bar trend line moves up, indicating a new high and establishing the previous low as a One-Bar bottom. Conversely, when the market makes a lower low than the previous bar from a high price, the One-Bar swing line moves down, marking a new low and setting the previous high as a One-Bar top. The crossing of these swing tops and bottoms indicates a change in trend direction.
HOW TO USE THE INDICATOR / Gann-swing Strategy:
The indicator shows 1, 2, and 3-bar swings. The strategy triggers a buy when the price crosses the previously determined high.
HOW TO USE THE STRATEGY:
Strategy to Fine-Tune Inputs for Your Gann Swing Strategy
This strategy allows for the fine-tuning of indicators for one timeframe at a time. Cross-timeframe input fine-tuning is done manually after exporting the chart data.
Meaningful Description:
The Gann Swing Chart using the One-Bar type, also known as the Minor Trend Chart, is designed to follow single-bar movements in the market. It helps identify trends by tracking price movements. When the market makes a higher high than the previous bar from a low price, the One-Bar trend line moves up, indicating a new high and establishing the previous low as a One-Bar bottom. Conversely, when the market makes a lower low than the previous bar from a high price, the One-Bar swing line moves down, marking a new low and setting the previous high as a One-Bar top. The crossing of these swing tops and bottoms indicates a change in trend direction.
How to Use the Indicator / Gann-Swing Strategy:
The indicator shows 1, 2, and 3-bar swings. The strategy triggers a buy when the price crosses the previously determined high.
How to Use the Strategy:
The strategy initiates a buy if the price breaks 1, 2, or 3-bar highs, or any combination thereof. Use the inputs to determine which highs or lows need to be crossed for the strategy to go long or short.
ORIGINALITY & USEFULNESS:
The One-Bar Swing Chart stands out for its simplicity and effectiveness in capturing minor market trends. Developed by meomeo105, this Gann high and low algorithm forms the basis of the strategy. I used my approach to creating strategy out of Gann swing indicator.
DETAILED DESCRIPTION:
What is a Swing Chart?
Swing charts help traders visualize price movements and identify trends by focusing on price highs and lows. They are instrumental in spotting trend reversals and continuations.
What is the One-Bar Swing Chart?
The One-Bar Swing Chart, also known as the Minor Trend Chart, follows single-bar price movements. It plots upward swings from a low price when a higher high is made, and downward swings from a high price when a lower low is made.
Key Features:
Trend Identification : Highlights minor trends by plotting swing highs and lows based on one-bar movements.
Simple Interpretation : Crossing a swing top indicates an uptrend, while crossing a swing bottom signals a downtrend.
Customizable Periods : Users can adjust the period to fine-tune the sensitivity of the swing chart to market movements.
Practical Application:
Bullish Trend : When the One-Bar Swing line moves above a previous swing top, it indicates a bullish trend.
Bearish Trend : When the One-Bar Swing line moves below a previous swing bottom, it signals a bearish trend.
Trend Reversal : Watch for crossings of swing tops and bottoms to detect potential trend reversals.
The One-Bar Swing Chart is a powerful tool for traders looking to capture and understand market trends. By following the simple rules of swing highs and lows, it provides clear and actionable insights into market direction.
Why the Strategy Uses 100% Allocation of a Portfolio:
This strategy allocates 100% of the portfolio to trading this specific pair, which does not mean 100% of all capital but 100% of the allocated trading capital for this pair. The strategy is swing-based and does not use take profit (TP) or stop losses.
Auto Volume Spread Analysis (VSA) [TANHEF]Auto Volume Spread Analysis (visible volume and spread bars auto-scaled): Understanding Market Intentions through the Interpretation of Volume and Price Movements.
All the sections below contain the same descriptions as my other indicator "Volume Spread Analysis" with the exception of 'Auto Scaling'.
█ Auto-Scaling
This indicator auto-scales spread bars to match the visible volume bars, unlike the previous "Volume Spread Analysis " version which limited the number of visible spread bars to a fixed count. The auto-scaling feature allows for easier navigation through historical data, enabling both more historical spread bars to be viewed and more historical VSA pattern labels being displayed without requiring using the bar replay tool. Please note that this indicator’s auto-scaling feature recalculates the visible bars on the chart, causing the indicator to reload whenever the chart is moved.
Auto-scaled spread bars have two display options (set via 'Spread Bars Method' setting):
Lines: a bar lookback limit of 500 bars.
Polylines: no bar lookback limit as only plotted on visible bars on chart, which uses multiple polylines are used.
█ Simple Explanation:
The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities.
█ Laws of Volume Spread Analysis (VSA):
The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws:
The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply.
The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend.
The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly.
█ Volume and Spread Analysis Bars:
Display: Volume and spread bars that consist of color coded levels, with the spread bars scaled to match the volume bars. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar.
Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends.
Low Level: Indicates reduced volatility and market interest.
Normal Level: Reflects typical market activity and volatility.
High Level: Indicates increased activity and volatility.
Ultra Level: Identifies extreme levels of activity and volatility.
This illustrates the appearance of Volume and Spread bars when scaled and plotted together:
█ Forecasting Capabilities:
Display: Forecasted volume and spread levels using predictive models.
Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear.
Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close.
Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion.
Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra).
The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels:
█ VSA Patterns:
Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data.
Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns.
Down Thrust
Selling Climax
No Effort ➤ Bearish Result
Bearish Effort ➤ No Result
Inverse Down Thrust
Failed Selling Climax
Bull Outside Reversal
End of Falling Market (Bag Holder)
Pseudo Down Thrust
No Supply
Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns.
Up Thrust
Buying Climax
No Effort ➤ Bullish Result
Bullish Effort ➤ No Result
Inverse Up Thrust
Failed Buying Climax
Bear Outside Reversal
End of Rising Market (Bag Seller)
Pseudo Up Thrust
No Demand
Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal.
Quiet Doji
Balanced Doji
Strong Doji
Quiet Spinning Top
Balanced Spinning Top
Strong Spinning Top
Quiet High Wave
Balanced High Wave
Strong High Wave
Consolidation
Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently.
Bull Pin Bar
Bear Pin Bar
Doji
Spinning Top
High Wave
Consolidation
This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern:
█ Alerts:
VSA Pattern Alerts: Notifications for identified VSA patterns at bar close.
Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra).
Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed.
█ Inputs and Settings:
Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels).
Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None).
Price Bar Colors: Options to color price bars based on VSA patterns and volume levels.
Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars.
Forecast: Configure forecast display and prediction details for volume and spread.
Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis.
Moving Average: Set volume and spread moving average settings.
VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral).
Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave).
Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars.
More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes.
Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels.
█ Usage:
The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
Intelle_city - World Cycle - Ath & Atl - Logarithmic - Strategy.Overview
Indicators: Strategy !
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for a buy-sell strategy; there is also a signal indicator from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Strategy - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для стратегии покупок продаж, есть также и сигнальный от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Strategy – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator ist für eine Kauf-Verkaufs-Strategie konzipiert; es gibt auch einen Signalindikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
intellect_city - World Cycle - Ath & Atl - Logarithmic - Signal.Indicator Overview
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for signal purchases of sales, there is also a strategic one from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для сигнальных покупок продаж, есть также и стратегический от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Signal – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator dient zur Signalisierung von Käufen oder Verkäufen, es gibt auch einen strategischen Indikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Intellect_city - World Cycle - Ath - Timeframe 1D and 1WIndicator Overview
The Pi Cycle Top Indicator has historically been effective in picking out the timing of market cycle highs within 3 days.
It uses the 111 day moving average (111DMA) and a newly created multiple of the 350 day moving average, the 350DMA x 2.
Note: The multiple is of the price values of the 350DMA, not the number of days.
For the past three market cycles, when the 111DMA moves up and crosses the 350DMA x 2 we see that it coincides with the price of Bitcoin peaking.
It is also interesting to note that 350 / 111 is 3.153, which is very close to Pi = 3.142. In fact, it is the closest we can get to Pi when dividing 350 by another whole number.
It once again demonstrates the cyclical nature of Bitcoin price action over long time frames. However, in this instance, it does so with a high degree of accuracy over Bitcoin's adoption phase of growth.
Bitcoin Price Prediction Using This Tool
The Pi Cycle Top Indicator forecasts the cycle top of Bitcoin’s market cycles. It attempts to predict the point where Bitcoin price will peak before pulling back. It does this on major high time frames and has picked the absolute tops of Bitcoin’s major price moves throughout most of its history.
How It Can Be Used
Pi Cycle Top is useful to indicate when the market is very overheated. So overheated that the shorter-term moving average, which is the 111-day moving average, has reached an x2 multiple of the 350-day moving average. Historically, it has proved advantageous to sell Bitcoin around this time in Bitcoin's price cycles.
It is also worth noting that this indicator has worked during Bitcoin's adoption growth phase, the first 15 years or so of Bitcoin's life. With the launch of Bitcoin ETF's and Bitcoin's increased integration into the global financial system, this indicator may cease to be relevant at some point in this new market structure.
Volume Spread Analysis [TANHEF]Volume Spread Analysis: Understanding Market Intentions through the Interpretation of Volume and Price Movements.
█ Simple Explanation:
The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities.
█ Laws of Volume Spread Analysis (VSA):
The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws:
The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply.
The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend.
The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly.
█ Volume and Spread Analysis Bars:
Display: Volume and/or spread bars that consist of color coded levels. If both of these are displayed, the number of spread bars can be limited for visual appeal and understanding, with the spread bars scaled to match the volume bars. While automatic calculation of the number of visual bars for auto scaling is possible, it is avoided to prevent the indicator from reloading whenever the number of visual price bars on the chart is adjusted, ensuring uninterrupted analysis. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar.
Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends.
Low Level: Indicates reduced volatility and market interest.
Normal Level: Reflects typical market activity and volatility.
High Level: Indicates increased activity and volatility.
Ultra Level: Identifies extreme levels of activity and volatility.
This illustrates the appearance of Volume and Spread bars when scaled and plotted together:
█ Forecasting Capabilities:
Display: Forecasted volume and spread levels using predictive models.
Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear.
Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close.
Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion.
Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra).
The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels:
█ VSA Patterns:
Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data.
Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns.
Down Thrust
Selling Climax
No Effort → Bearish Result
Bearish Effort → No Result
Inverse Down Thrust
Failed Selling Climax
Bull Outside Reversal
End of Falling Market (Bag Holder)
Pseudo Down Thrust
No Supply
Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns.
Up Thrust
Buying Climax
No Effort → Bullish Result
Bullish Effort → No Result
Inverse Up Thrust
Failed Buying Climax
Bear Outside Reversal
End of Rising Market (Bag Seller)
Pseudo Up Thrust
No Demand
Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal.
Quiet Doji
Balanced Doji
Strong Doji
Quiet Spinning Top
Balanced Spinning Top
Strong Spinning Top
Quiet High Wave
Balanced High Wave
Strong High Wave
Consolidation
Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently.
Bull Pin Bar
Bear Pin Bar
Doji
Spinning Top
High Wave
Consolidation
This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern:
█ Alerts:
VSA Pattern Alerts: Notifications for identified VSA patterns at bar close.
Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra).
Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed.
█ Inputs and Settings:
Display Volume and/or Spread: Choose between displaying volume bars, spread bars, or both with different lookback periods.
Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels).
Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None).
Price Bar Colors: Options to color price bars based on VSA patterns and volume levels.
Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars.
Forecast: Configure forecast display and prediction details for volume and spread.
Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis.
Moving Average: Set volume and spread moving average settings.
VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral).
Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave).
Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars.
More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes.
Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels.
█ Usage:
The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
Crypto Liquidation Heatmap [LuxAlgo]The Crypto Liquidation Heatmap tool offers real-time insights into the liquidations of the top cryptocurrencies by market capitalization, presenting the current state of the market in a visually accessible format. Assets are sorted in descending order, with those experiencing the highest liquidation values placed at the top of the heatmap.
Additional details, such as the breakdown of long and short liquidation values and the current price of each asset, can be accessed by hovering over individual boxes.
🔶 USAGE
The crypto liquidation heatmap tool provides real-time insights into liquidations across all timeframes for the top 29 cryptocurrencies by market capitalization. The assets are visually represented in descending order, prioritizing assets with the highest liquidation values at the top of the heatmap.
Different colors are used to indicate whether long or short liquidations are dominant for each asset. Green boxes indicate that long liquidations surpass short liquidations, while red boxes indicate the opposite, with short liquidations exceeding long liquidations.
Hovering over each box provides additional details, such as the current price of the asset, the breakdown of long and short liquidation values, and the duration for the calculated liquidation values.
🔶 DETAILS
🔹Crypto Liquidation
Crypto liquidation refers to the process of forcibly closing a trader's positions in the cryptocurrency market. It occurs when a trader's margin account can no longer support their open positions due to significant losses or a lack of sufficient margin to meet the maintenance requirements. Liquidations can be categorized as either a long liquidation or a short liquidation.
A long liquidation occurs when long positions are being liquidated, typically due to a sudden drop in the price of the asset being traded. Traders who were bullish on the asset and had opened long positions will face losses as the market moves against them.
On the other hand, a short liquidation occurs when short positions are being liquidated, often triggered by a sudden spike in the price of the asset. Traders who were bearish on the asset and had opened short positions will face losses as the market moves against them.
🔹Liquidation Data
It's worth noting that liquidation data is not readily available on TradingView. However, we recognize the close correlation between liquidation data, trading volumes, and asset price movements. Therefore, this script analyzes accessible data sources, extracts necessary information, and offers an educated estimation of liquidation data. It's important to emphasize that the presented data doesn't reflect precise quantitative values of liquidations. Traders and analysts should instead focus on observing changes over time and identifying correlations between liquidation data and price movements.
🔶 SETTINGS
🔹Cryptocurrency Asset List
It is highly recommended to select instruments from the same exchange with the same currency to maintain proportional integrity among the chosen assets, as different exchanges may have varying trading volumes.
Supported currencies include USD, USDT, USDC, USDP, and USDD. Remember to use the same currency when selecting assets.
List of Crypto Assets: The default options feature the top 29 cryptocurrencies by market capitalization, currently listed on the Binance Exchange. Please note that only crypto assets are supported; any other asset type will not be processed or displayed. To maximize the utility of this tool, it is crucial to heed the warning message displayed above.
🔹Liquidation Heatmap Settings
Position: Specifies the placement of the liquidation heatmap on the chart.
Size: Determines the size of the liquidation heatmap displayed on the chart.
🔶 RELATED SCRIPTS
Liquidations-Meter
Liquidation-Estimates
Liquidation-Levels
LMACD - Logarithmic MACD Weekly BTC Index [Logue]Logarithmic Moving Average Convergence Divergence (LMACD) Weekly Indicator - The LMACD is a momentum indicator that measures the strength of a trend using 12-period and 26-period moving averages. The weekly LMACD for this indicator is calculated by determining the difference between the log (base 10) of the 12-week and 26-week exponential moving averages. Larger positive numbers indicate a larger positive momentum.
For tops: The default setting for tops is based on decreasing "strength" of BTC tops. A decreasing linear function (trigger = slope * time + intercept) was fit to past cycle tops for this indicator and is used as the default to signal macro tops. The user can change the slope and intercept of the line by changing the slope and/or intercept factor. The user also has the option to indicate tops based on a horizontal line via a settings selection. This line default value is 0.125. This indicator is triggered for a top when the LMACD is above the trigger value.
For bottoms: Bottoms are displayed based on a horizontal line with a default setting of -0.07. The indicator is triggered for a bottom when the LMACD is below the bottom trigger value.
