VFI - Volume Flow Indicator [UTS]The Volume Flow Indicator (VFI) indicator was first introduced in my June 2004 and is is based on the popular On Balance Volume (OBV) but with three very important modifications:
Unlike the OBV, indicator values are no longer meaningless. Positive readings are bullish and negative bearish.
The calculation is based on the day's median instead of the closing price.
A volatility threshold takes into account minimal price changes and another threshold eliminates excessive volume.
The indicator takes into account only the latest 6 month volume action and not the entire data loaded in the chart.
General Usage
A simplified interpretation of the VFI is that values above zero indicate a bullish state and the crossing of the zero line is the trigger or buy signal.
The strongest signal with all money flow indicators is of course divergence.
The classic form of divergence is when the indicator refuses to follow the price action and makes lower highs while price makes higher highs (negative divergence). If price reaches a new low but the indicator fails to do so, then price probably traveled lower than it should have. In this instance, you have positive divergence.
Default settings
130 VFI Length
0.2 Coef
2.5 Volume cutoff
3 Smoothing Period
Further setting examples can be found on www.precisiontradingsystems.com
Trend Visualisation
Optional Setting:
If the trend direction is DOWN the moving average is painted red. If the trend direction is UP the moving average is painted in green.
If the movement is FLAT then the color is grey.
Moving Averages
4 different types of Moving Averages are available for both FVI and the optional Moving Average of the FVI.
ALMA (Arnaud Legoux Moving Average)
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
WMA (Weighted Moving Average)
Notes
This indicator is using the exact formula from mkatsanos.com where EMA has been taken as default value for FVI smoothing calculation.
In den Scripts nach "Exponential Moving Average" suchen
General Filter Estimator-An Experiment on Estimating EverythingIntroduction
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA , who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something more flexible and less complex with the ability to approximate any filter output. Its possible, but the methods to do so are not something that pinescript can do, we have to use another base for our estimation using coefficients, so i inspired myself from the alpha-beta filter and i started writing the code.
Calculation and The Estimation Coefficients
Simplicity is the key word, its also my signature style, if i want something good it should be simple enough, so my code look like that :
p = length/beta
a = close - nz(b ,close)
b = nz(b ,close) + a/p*gamma
3 line, 2 function, its a good start, we could put everything in one line of code but its easier to see it this way. length control the smoothing amount of the filter, for any filter f(Period) Period should be equal to length and f(Period) = p , it would be inconvenient to have to use a different length period than the one used in the filter we want to estimate (imagine our estimation with length = 50 estimating an ema with period = 100) , this is where the first coefficients beta will be useful, it will allow us to leave length as it is. In general beta will be greater than 1, the greater it will be the less lag the filter will have, this coefficient will be useful to estimate low lagging filters, gamma however is the coefficient who will estimate lagging filters, in general it will range around .
We can get loose easily with those coefficients estimation but i will leave a coefficients table in the code for estimating popular filters, and some comparison below.
Estimating a Simple Moving Average
Of course, the boxcar filter, the running mean, the simple moving average, its an easy filter to use and calculate.
For an SMA use the following coefficients :
beta = 2
gamma = 0.5
Our filter is in red and the moving average in white with both length at 50 (This goes for every comparison we will do)
Its a bit imprecise but its a simple moving average, not the most interesting thing to estimate.
Estimating an Exponential Moving Average
The ema is a great filter because its length times more computing efficient than a simple moving average. For the EMA use the following coefficients :
beta = 3
gamma = 0.4
N.B : The EMA is rougher than the SMA, so it filter less, this is why its faster and closer to the price
Estimating The Hull Moving Average
Its a good filter for technical analysis with tons of use, lets try to estimate it ! For the HMA use the following coefficients :
beta = 4
gamma = 0.85
Looks ok, of course if you find better coefficients i will test them and actualize the coefficient table, i will also put a thank message.
Estimating a LSMA
Of course i was gonna estimate it, but this time this estimation does not have anything a lsma have, no moving average, no standard deviation, no correlation coefficient, lets do it.
For the LSMA use the following coefficients :
beta = 3.5
gamma = 0.9
Its far from being the best estimation, but its more efficient than any other i previously made.
Estimating the Quadratic Least Square Moving Average
I doubted about this one but it can be approximated as well. For the QLSMA use the following coefficients :
beta = 5.25
gamma = 1
Another ok estimate, the estimate filter a bit more than needed but its ok.
Jurik Moving Average
Its far from being a filter that i like and its a bit old. For the comparison i will use the JMA provided by @everget described in this article : c.mql5.com
For the JMA use the following coefficients :
for phase = 0
beta = pow*2 (pow is a parameter in the Jma)
gamma = 0.5
Here length = 50, phase = 0, pow = 5 so beta = 10
Looks pretty good considering the fact that the Jma use an adaptive architecture.
Discussion
I let you the task to judge if the estimation is good or not, my motivation was to estimate such filters using the less amount of calculations as possible, in itself i think that the code is quite elegant like all the codes of IIR filters (IIR Filters = Infinite Impulse Response : Filters using recursion) .
It could be possible to have a better estimate of the coefficients using optimization methods like the gradient descent. This is not feasible in pinescript but i could think about it using python or R.
Coefficients should be dependant of length but this would lead to a massive work, the variation of the estimation using fixed coefficients when using different length periods is just ok if we can allow some errors of precision.
I dont think it should be possible to estimate adaptive filter relying a lot on their adaptive parameter/smoothing constant except by making our coefficients adaptive (gamma could be)
So at the end ? What make a filter truly unique ? From my point of sight the architecture of a filter and the problem he is trying to solve is what make him unique rather than its output result. If you become a signal, hide yourself into noise, then look at the filters trying to find you, what a challenging game, this is why we need filters.
Conclusion
I wanted to give a simple filter estimator relying on two coefficients in order to estimate both lagging and low-lagging filters. I will try to give more precise estimate and update the indicator with new coefficients.
Thanks for reading !
Madrid Trend SpotterThis study shows a pair of colored moving averages filled with the color of the direction of the trend.
This study calculates the moving averages with standard or exponential M.A.'s. By default it uses a couple of fast exponential moving average pair (5,13) with the closing price as the source.
Parameters:
source
fast MA length
slow MA Length
type of moving average
Standardized Cumulative Deltas [LuxAlgo]The Standardized Cumulative Deltas tool allows traders to compare the cumulative standardized open-close difference for up to 10 different tickers, allowing them to visualize the general sentiment for all selected tickers.
These results allow the construction of two areas showing the average or extreme bullish and bearish cumulative change for all enabled tickers, providing a summarized view of the overall ticker group sentiment.
🔶 USAGE
This tool is meant to give a full picture of the individuals and/or overall selected tickers, and unlike classical indicators, the displayed series of values is not meant to be directly interpreted over time.
Given the selected lookback period, a majority of observations being above 0 indicate an overall bullish market for the asset.
By default, the auto lookback period feature is enabled, allowing the tool to use all the visible bars for its calculations. Traders can also set the lookback period manually. The above chart uses a fixed lookback period of 500.
Up to 10 tickers can be used. While major cryptocurrencies are set by default, the users can set a specific basket of assets, such as US equities, forex pairs, commodities, etc.
🔹 Densities
The provided areas, here called densities, can be used to get an overall sentiment of the selected tickers. The upper density (bullish) processes positive deltas, while the lower one (bearish) processes negative ones.
Interpretation is subject to the selected "Density Mode".
Average: Densities track the average bullish/bearish cumulative deltas for the selected tickers. For example, a more prominent bullish density would indicate that, on average, cumulative deltas were positive across the tickers.
Envelope: Densities track the extreme values made by bullish/bearish cumulative deltas for the selected tickers. Here, a more prominent density would indicate more volatile bullish/bearish movements, depending on the density.
🔹 Dashboard
The tool features a dashboard with active tickers and their respective colors for traders' convenience.
🔶 DETAILS
🔹 Densities
Densities are obtained by applying a forward-backward exponential moving average on the average, or the highest/lowest cumulative series, depending on the selected Density Mode.
The resulting densities are smoothed by the "Smoothing" parameter located in the Settings panel, with higher values returning smoother envelopes with less variability.
Do note that the smoothing method used here is subject to repainting.
🔶 SETTINGS
Lookback: Select the lookback period and enable/disable the Auto Lookback feature
Tickers: Enable/disable and select up to 10 tickers and their colors
Density Mode: Determine how densities are calculated
🔹 Dashboard
Show Dashboard: Enable/disable the dashboard
Position: Select the dashboard position
Size: Select the dashboard size
🔹 Style
Density: Enable/disable the density areas
Bullish Density: Select the color of the top density area
Bearish Density: Select the color of the bottom density area
Smoothing: Select the smoothing constant for the EMA calculation
Uptrick: Z-Trend BandsOverview
Uptrick: Z-Trend Bands is a Pine Script overlay crafted to capture high-probability mean-reversion opportunities. It dynamically plots upper and lower statistical bands around an EMA baseline by converting price deviations into z-scores. Once price moves outside these bands and then reenters, the indicator verifies that momentum is genuinely reversing via an EMA-smoothed RSI slope. Signal memory ensures only one entry per momentum swing, and traders receive clear, real-time feedback through customizable bar-coloring modes, a semi-transparent fill highlighting the statistical zone, concise “Up”/“Down” labels, and a live five-metric scoring table.
Introduction
Markets often oscillate between trending and reverting, and simple thresholds or static envelopes frequently misfire when volatility shifts. Standard deviation quantifies how “wide” recent price moves have been, and a z-score transforms each deviation into a measure of how rare it is relative to its own history. By anchoring these bands to an exponential moving average, the script maintains a fluid statistical envelope that adapts instantly to both calm and turbulent regimes. Meanwhile, the Relative Strength Index (RSI) tracks momentum; smoothing RSI with an EMA and observing its slope filters out erratic spikes, ensuring that only genuine momentum flips—upward for longs and downward for shorts—qualify.
Purpose
This indicator is purpose-built for short-term mean-reversion traders operating on lower–timeframe charts. It reveals when price has strayed into the outer 5 percent of its recent range, signaling an increased likelihood of a bounce back toward fair value. Rather than firing on price alone, it demands that momentum follow suit: the smoothed RSI slope must flip in the opposite direction before any trade marker appears. This dual-filter approach dramatically reduces noise-driven, false setups. Traders then see immediate visual confirmation—bar colors that reflect the latest signal and age over time, clear entry labels, and an always-visible table of metric scores—so they can gauge both the validity and freshness of each signal at a glance.
Originality and Uniqueness
Uptrick: Z-Trend Bands stands apart from typical envelope or oscillator tools in four key ways. First, it employs fully normalized z-score bands, meaning ±2 always captures roughly the top and bottom 5 percent of moves, regardless of volatility regime. Second, it insists on two simultaneous conditions—price reentry into the bands and a confirming RSI slope flip—dramatically reducing whipsaw signals. Third, it uses slope-phase memory to lock out duplicate signals until momentum truly reverses again, enforcing disciplined entries. Finally, it offers four distinct bar-coloring schemes (solid reversal, fading reversal, exceeding bands, and classic heatmap) plus a dynamic scoring table, rather than a single, opaque alert, giving traders deep insight into every layer of analysis.
Why Each Component Was Picked
The EMA baseline was chosen for its blend of responsiveness—weighting recent price heavily—and smoothness, which filters market noise. Z-score deviation bands standardize price extremes relative to their own history, adapting automatically to shifting volatility so that “extreme” always means statistically rare. The RSI, smoothed with an EMA before slope calculation, captures true momentum shifts without the false spikes that raw RSI often produces. Slope-phase memory flags prevent repeated alerts within a single swing, curbing over-trading in choppy conditions. Bar-coloring modes provide flexible visual contexts—whether you prefer to track the latest reversal, see signal age, highlight every breakout, or view a continuous gradient—and the scoring table breaks down all five core checks for complete transparency.
Features
This indicator offers a suite of configurable visual and logical tools designed to make reversal signals both robust and transparent:
Dynamic z-score bands that expand or contract in real time to reflect current volatility regimes, ensuring the outer ±zThreshold levels always represent statistically rare extremes.
A smooth EMA baseline that weights recent price more heavily, serving as a fair-value anchor around which deviations are measured.
EMA-smoothed RSI slope confirmation, which filters out erratic momentum spikes by first smoothing raw RSI and then requiring its bar-to-bar slope to flip before any signal is allowed.
Slope-phase memory logic that locks out duplicate buy or sell markers until the RSI slope crosses back through zero, preventing over-trading during choppy swings.
Four distinct bar-coloring modes—Reversal Solid, Reversal Fade, Exceeding Bands, Classic Heat—plus a “None” option, so traders can choose whether to highlight the latest signal, show signal age, emphasize breakout bars, or view a continuous heat gradient within the bands.
A semi-transparent fill between the EMA and the upper/lower bands that visually frames the statistical zone and makes extremes immediately obvious.
Concise “Up” and “Down” labels that plot exactly when price re-enters a band with confirming momentum, keeping chart clutter to a minimum.
A real-time, five-metric scoring table (z-score, RSI slope, price vs. EMA, trend state, re-entry) that updates every two bars, displaying individual +1/–1/0 scores and an averaged Buy/Sell/Neutral verdict for complete transparency.
Calculations
Compute the fair-value EMA over fairLen bars.
Subtract that EMA from current price each bar to derive the raw deviation.
Over zLen bars, calculate the rolling mean and standard deviation of those deviations.
Convert each deviation into a z-score by subtracting the mean and dividing by the standard deviation.
Plot the upper and lower bands at ±zThreshold × standard deviation around the EMA.
Calculate raw RSI over rsiLen bars, then smooth it with an EMA of length rsiEmaLen.
Derive the RSI slope by taking the difference between the current and previous smoothed RSI.
Detect a potential reentry when price exits one of the bands on the prior bar and re-enters on the current bar.
Require that reentry coincide with an RSI slope flip (positive for a lower-band reentry, negative for an upper-band reentry).
On first valid reentry per momentum swing, fire a buy or sell signal and set a memory flag; reset that flag only when the RSI slope crosses back through zero.
For each bar, assign scores of +1, –1, or 0 for the z-score direction, RSI slope, price vs. EMA, trend-state, and reentry status.
Average those five scores; if the result exceeds +0.1, label “Buy,” if below –0.1, label “Sell,” otherwise “Neutral.”
Update bar colors, the semi-transparent fill, reversal labels, and the scoring table every two bars to reflect the latest calculations.
How It Actually Works
On each new candle, the EMA baseline and band widths update to reflect current volatility. The RSI is smoothed and its slope recalculated. The script then looks back one bar to see if price exited either band and forward to see if it reentered. If that reentry coincides with an appropriate RSI slope flip—and no signal has yet been generated in that swing—a concise label appears. Bar colors refresh according to your selected mode, and the scoring table updates to show which of the five conditions passed or failed, along with the overall verdict. This process repeats seamlessly at each bar, giving traders a continuous feed of disciplined, statistically filtered reversal cues.
Inputs
All parameters are fully user-configurable, allowing you to tailor sensitivity, lookbacks, and visuals to your trading style:
EMA length (fairLen): number of bars for the fair-value EMA; higher values smooth more but lag further behind price.
Z-Score lookback (zLen): window for calculating the mean and standard deviation of price deviations; longer lookbacks reduce noise but respond more slowly to new volatility.
Z-Score threshold (zThreshold): number of standard deviations defining the upper and lower bands; common default is 2.0 for roughly the outer 5 percent of moves.
Source (src): choice of price series (close, hl2, etc.) used for EMA, deviation, and RSI calculations.
RSI length (rsiLen): period for raw RSI calculation; shorter values react faster to momentum changes but can be choppier.
RSI EMA length (rsiEmaLen): period for smoothing raw RSI before taking its slope; higher values filter more noise.
Bar coloring mode (colorMode): select from None, Reversal Solid, Reversal Fade, Exceeding Bands, or Classic Heat to control how bars are shaded in relation to signals and band positions.
Show signals (showSignals): toggle on-chart “Up” and “Down” labels for reversal entries.
Show scoring table (enableTable): toggle the display of the five-metric breakdown table.
Table position (tablePos): choose which corner (Top Left, Top Right, Bottom Left, Bottom Right) hosts the scoring table.
Conclusion
By merging a normalized z-score framework, momentum slope confirmation, disciplined signal memory, flexible visuals, and transparent scoring into one Pine Script overlay, Uptrick: Z-Trend Bands offers a powerful yet intuitive tool for intraday mean-reversion trading. Its adaptability to real-time volatility and multi-layered filter logic deliver clear, high-confidence reversal cues without the clutter or confusion of simpler indicators.
Disclaimer
This indicator is provided solely for educational and informational purposes. It does not constitute financial advice. Trading involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. Always conduct your own testing and apply careful risk management before trading live.
Forexsom MA Crossover SignalsA Trend-Following Trading Indicator for TradingView
Overview
This indicator plots two moving averages (MA) on your chart and generates visual signals when they cross, helping traders identify potential trend reversals. It is designed to be simple yet effective for both beginners and experienced traders.
Key Features
✅ Dual Moving Averages – Plots a Fast MA (default: 9-period) and a Slow MA (default: 21-period)
✅ Customizable MA Types – Choose between EMA (Exponential Moving Average) or SMA (Simple Moving Average)
✅ Clear Buy/Sell Signals – Displays "BUY" (green label) when the Fast MA crosses above the Slow MA and "SELL" (red label) when it crosses below
✅ Alerts – Get notified when new signals appear (compatible with TradingView alerts)
✅ Clean Visuals – Easy-to-read moving averages with adjustable colors
How It Works
Bullish Signal (BUY) → Fast MA crosses above Slow MA (suggests uptrend)
Bearish Signal (SELL) → Fast MA crosses below Slow MA (suggests downtrend)
Best Used For
✔ Trend-following strategies (swing trading, day trading)
✔ Confirming trend reversals
✔ Filtering trade entries in combination with other indicators
Customization Options
Adjust Fast & Slow MA lengths
Switch between EMA or SMA for smoother or more responsive signals
Why Use This Indicator?
Simple & Effective – No clutter, just clear signals
Works on All Timeframes – From scalping (1M, 5M) to long-term trading (4H, Daily)
Alerts for Real-Time Trading – Never miss a signal
CCT Pi Cycle Top/BottomPi Cycle Top/bottom: The Ultimate Market Cycle Indicator
Introduction
The Pi Cycle Top/bottom Indicator is one of the most reliable tools for identifying Bitcoin market cycle peaks and bottoms. Its effectiveness lies in the strategic combination of moving averages that historically align with major market cycle reversals. Unlike traditional moving average crossovers, this indicator applies an advanced iterative approach to pinpoint price extremes with higher accuracy.
This version, built entirely with Pine Script™ v6, introduces unprecedented precision in detecting both the Pi Cycle Top and Pi Cycle Bottom, eliminating redundant labels, optimizing visual clarity, and ensuring the indicator adapts dynamically to evolving market conditions.
What is the Pi Cycle Theory?
The Pi Cycle Top and Pi Cycle Bottom were originally introduced based on a simple yet profound discovery: key moving average crossovers consistently align with macro market tops and bottoms.
Pi Cycle Top: The crossover of the 111-day Simple Moving Average (SMA) and the 350-day SMA multiplied by 2 has historically signaled market tops with astonishing accuracy.
Pi Cycle Bottom: The intersection of the 150-day Exponential Moving Average (EMA) and the 471-day SMA has repeatedly marked significant market bottoms.
While traditional moving average strategies often suffer from lag and false signals, the Pi Cycle Indicator enhances accuracy by applying a range-based scanning methodology, ensuring that only the most critical reversals are detected.
How This Indicator Works
Unlike basic moving average crossovers, this script introduces a unique iteration process to refine the detection of Pi Cycle points. Here’s how it works:
Detecting Crossovers:
Identifies the Golden Cross (bullish crossover) and Death Cross (bearish crossover) for both the Pi Cycle Top and Pi Cycle Bottom.
Iterating Through the Cycle:
Instead of plotting a simple crossover point, this script scans the range between each Golden and Death Cross to identify the absolute lowest price (Pi Cycle Bottom) and highest price (Pi Cycle Top) within that cycle.
Precision Labeling:
The indicator dynamically adjusts label positioning:
If the price at the crossover is below the fast moving average → the label is placed on the moving average with a downward pointer.
If the price is above the fast moving average → the label is placed below the candle with an upward pointer.
This ensures optimal visibility and prevents misleading signal placement.
Advanced Pine Script v6 Features:
Labels and moving average names are only shown on the last candle, reducing chart noise while maintaining clarity.
Offers full user customization, allowing traders to toggle:
Pi Cycle Top & Bottom visibility
Moving average labels
Crossover labels
Why This Indicator is Superior
This script is not just another moving average crossover tool—it is a market cycle tracker designed for long-term investors and analysts who seek:
✔ High-accuracy macro cycle identification
✔ Elimination of false signals using an iterative range-based scan
✔ Automatic detection of market extremes without manual adjustments
✔ Optimized visuals with smart label positioning
✔ First-of-its-kind implementation using Pine Script™ v6 capabilities
How to Use It?
Bull Market Tops:
When the Pi Cycle Top indicator flashes, consider the potential for a market cycle peak.
Historically, Bitcoin has corrected significantly after these signals.
Bear Market Bottoms:
When the Pi Cycle Bottom appears, it suggests a macro accumulation phase.
These signals have aligned perfectly with historical cycle bottoms.
Final Thoughts
The Pi Cycle Top/bottom Indicator is a must-have tool for traders, investors, and analysts looking to anticipate long-term trend reversals with precision. With its refined methodology, superior label positioning, and cutting-edge Pine Script™ v6 optimizations, this is the most reliable version ever created.
OrangeCandle 4EMA 55 + Fib Bands + SignalsThe script is a TradingView indicator that combines three popular technical analysis tools: Exponential Moving Averages (EMAs), Fibonacci bands, and buy/sell signals based on these indicators. Here’s a breakdown of its features:
1. EMA Settings and Calculation:
The script calculates and plots several Exponential Moving Averages (EMAs) on the chart with different lengths:
Short-term EMAs: EMA 9, EMA 13, EMA 21, and EMA 55 (used for tracking short-term price trends).
Long-term EMAs: EMA 100 and EMA 200 (used to analyze longer-term trends).
These EMAs are plotted with different colors to visually distinguish between the short-term and long-term trends.
2. Fibonacci Bands:
The script calculates Fibonacci Bands based on the Average True Range (ATR) and a Simple Moving Average (SMA).
Fibonacci factors (1.618, 2.618, 4.236, 6.854, and 11.090) are used to determine the upper and lower bounds of five Fibonacci bands.
Upper Fibonacci Bands (e.g., fib1u, fib2u) represent resistance levels.
Lower Fibonacci Bands (e.g., fib1l, fib2l) represent support levels.
These bands are plotted with different colors for each level, helping traders identify potential price reversal zones.
3. Buy and Sell Signals:
Long Condition: A buy signal occurs when the price crosses above the EMA 55 (long-term trend indicator) and is above the lower Fibonacci band (support zone).
Short Condition: A sell signal occurs when the price crosses below the EMA 55 and is below the upper Fibonacci band (resistance zone).
These conditions trigger visual signals on the chart (green arrow for long, red arrow for short).
4. Alerts:
The script includes alert conditions to notify the trader when a long or short signal is triggered based on the crossover of price and EMA 55 near the Fibonacci support or resistance levels.
Long Entry Alert: Triggers when the price crosses above the EMA 55 and is near a Fibonacci support level.
Short Entry Alert: Triggers when the price crosses below the EMA 55 and is near a Fibonacci resistance level.
5. Visualization:
EMAs are plotted with distinct colors:
EMA 9 is aqua,
EMA 13 is purple,
EMA 21 is orange,
EMA 55 is blue (with thicker line width for emphasis),
EMA 100 is gray,
EMA 200 is black.
Fibonacci bands are plotted with different colors for each level:
Fib Band 1 (upper and lower) in white,
Fib Band 2 in green (upper) and red (lower),
Fib Band 3 in green (upper) and red (lower),
Fib Band 4 in blue (upper) and orange (lower),
Fib Band 5 in purple (upper) and yellow (lower).
Summary:
This script provides a comprehensive strategy for analyzing the market with multiple EMAs for trend detection, Fibonacci bands for support/resistance, and signals based on price action in relation to these indicators. The combination of these tools can assist traders in making more informed decisions by providing potential entry and exit points on the chart.
Cumulative New Highs - New Lows IndicatorThis indicator is designed to track market momentum by calculating and plotting the cumulative sum of 52 weeks High-Low for different indices, alongside a customizable moving average.
Index Selection:
Users can choose from multiple indices, including:
Total Stock Market (default)
NYSE Composite
Nasdaq Composite
S&P 500
Nasdaq 100
Russell 2000
Moving Average Customization:
The script allows you to select between a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) for smoothing the cumulative data. The window length of the moving average is also adjustable, letting you tailor the sensitivity of the trend analysis.
Dynamic Background Plotting:
With the background plot option enabled, the indicator changes the chart's background color dynamically:
Green: When the cumulative sum is above its moving average, suggesting bullish momentum.
Red: When it is below the moving average, indicating bearish conditions.
Visual Representation:
Two key lines are plotted:
Cumulative Index Line: Displayed in a subtle blue, representing the aggregated market movement.
Moving Average Line: Shown in an orange tone, offering a smoothed perspective that aids in identifying trend shifts.
Inspiration:
I took inspiration from the indicator made by YoxTrades (I can't put links, but you can check their profile) and added a few features I wanted on top of it.
Weekly MA SuiteThe Weekly MA Suite is a multi-layered moving average indicator designed for traders and investors who analyze market trends across weekly and long-term timeframes. It combines three critical trend layers—short-term (1W EMA/VWMA), mid-term (30W EMA/VWMA), and long-term (200W HMA)—providing clear insights into market momentum, structure, and cycle trends.
This indicator is ideal for:
✅ Swing traders looking for weekly momentum shifts
✅ Position traders tracking multi-week to multi-month trends
✅ Long-term investors monitoring macro market cycles
Each layer has customizable colors, transparency, and visibility toggles, ensuring traders can tailor the indicator to their specific needs.
📊 Breakdown of Components
🔹 Short-Term Trend (1W EMA/VWMA Ribbon – Top Layer)
Purpose: Captures weekly momentum and volume dynamics
• 1W EMA (Exponential Moving Average) reacts quickly to price changes
• 1W VWMA (Volume-Weighted Moving Average) accounts for volume to confirm trend strength
• Ribbon fill highlights the divergence between price-based momentum (EMA) and volume-weighted trends (VWMA), making trend shifts easier to spot
Usage:
• If the 1W EMA is above the 1W VWMA, momentum is strong and price is trending higher with support from volume
• If the EMA crosses below the VWMA, it may indicate weakening trend strength or distribution
• A widening ribbon suggests increasing momentum, while a narrowing ribbon signals potential consolidation or reversal
🔸 Mid-Term Trend (30W EMA/VWMA Ribbon – Middle Layer)
Purpose: Provides insight into the broader market structure over multiple months
• 30W EMA represents the dominant trend direction over roughly half a year
• 30W VWMA smooths this trend while weighting price by trading volume
• Ribbon fill allows for a visual representation of how volume impacts trend direction
Usage:
• A bullish trend is confirmed when price remains above the 30W EMA, with the ribbon widening in an uptrend
• A bearish shift occurs when the 30W EMA crosses below the 30W VWMA, signaling weakening demand
• If the ribbon narrows or twists frequently, the market may be in a choppy, range-bound phase
🔻 Long-Term Trend (200W HMA – Background Layer)
Purpose: Identifies major market cycles and deep trend shifts
• The 200W Hull Moving Average (HMA) is a long-term smoothing tool that reduces lag while maintaining trend clarity
• Unlike traditional moving averages, the HMA reacts faster to trend changes without excessive noise
Usage:
• When price is above the 200W HMA, the broader trend remains bullish, even during short-term corrections
• A cross below the 200W HMA may indicate a macro downtrend or deep market cycle shift
• Long-term investors can use this as a dynamic support or resistance zone
🎯 How to Use the Weekly MA Suite for Trading
📅 Identifying Market Phases
• In strong uptrends, the 1W EMA and 30W EMA will be aligned above their VWMA counterparts, with price well above the 200W HMA
• In sideways markets, the ribbons will frequently narrow or cross, signaling indecision
• In bear markets, price will typically trade below the 30W EMA, with the 200W HMA acting as a long-term resistance
📈 Entry and Exit Strategies
• A bullish trade setup occurs when the 1W EMA crosses above the 1W VWMA while the 30W EMA holds above the 30W VWMA, confirming multi-timeframe momentum
• A bearish setup is confirmed when the 1W EMA crosses below the 1W VWMA and price is also trending below the 30W EMA
• The 200W HMA can be used as a trend filter—staying long when price is above it and avoiding longs when price is below
🚦 Customizing for Your Trading Style
• Scalpers can focus on the 1W ribbon for faster trend shifts
• Swing traders can use the 30W ribbon for trend-following entries and exits
• Long-term investors should watch price action relative to the 200W HMA for market cycle positioning
🔧 Final Thoughts
The Weekly MA Suite simplifies multi-timeframe analysis by layering key moving averages in an intuitive and structured format. By combining short, medium, and long-term trend indicators, traders can confidently navigate market conditions and improve decision-making. Whether trading weekly trends or monitoring multi-year cycles, this tool provides a clear visual framework to enhance market insights.
Smoothed EMA LinesThe "Smoothed EMA Lines" script is a technical analysis tool designed to help traders identify trends and potential support/resistance levels in financial markets. The script plots exponential moving averages (EMAs) of the closing price for five commonly used time periods: 8, 13, 21, 55, and 200.
Key features of the script include:
Overlay: The EMAs are plotted directly on the price chart, making it easy to analyze the relationship between the moving averages and price action.
Smoothing: The script applies an additional smoothing function to each EMA, using a simple moving average (SMA) of a user-defined length. This helps to reduce noise and provide a clearer picture of the trend.
Customizable lengths: Users can easily adjust the length of each EMA and the smoothing period through the script's input parameters.
Color-coded plots: Each EMA is assigned a unique color (8: blue, 13: green, 21: orange, 55: red, 200: purple) for easy identification on the chart.
Traders can use the "Smoothed EMA Lines" script to:
Identify the overall trend direction (bullish, bearish, or neutral) based on the arrangement of the EMAs.
Spot potential support and resistance levels where the price may interact with the EMAs.
Look for crossovers between EMAs as potential entry or exit signals.
Combine the EMA analysis with other technical indicators and price action patterns for a more comprehensive trading strategy.
The "Smoothed EMA Lines" script provides a clear, customizable, and easy-to-interpret visualization of key exponential moving averages, helping traders make informed decisions based on trend analysis.
EMA Alignment & Spread Monitor (Sang Youn)Overview
The EMA Alignment & Spread Monitor is a dynamic trading script designed to monitor EMA (Exponential Moving Average) alignments, track spread deviations, and provide real-time alerts when significant conditions are met. This script allows traders to customize their EMA periods, analyze market trends based on EMA positioning, and receive visual and audio alerts when key spread conditions occur.
🔹 Key Features
✅ Customizable EMA Periods – Users can input their own EMA lengths to adapt the script to various market conditions. (Default: 5, 10, 20, 60, 120)
✅ EMA Alignment Detection – Identifies bullish alignment (all EMAs in ascending order) and bearish alignment (all EMAs in descending order).
✅ Spread Calculation & Monitoring – Computes the spread difference between each EMA and tracks the average spread over a user-defined period.
✅ Deviation Alerts – Notifies traders when:
Bullish Trend: The spread exceeds its average, indicating a potential strong uptrend.
Bearish Trend: The spread falls below its average, signaling a possible downtrend.
✅ Chart Annotations – Displays 📈 (green triangle) when bullish spread exceeds average and 📉 (red triangle) when bearish spread drops below average for easy visualization.
✅ Real-time Alerts – Sends alerts when spread conditions are met, helping traders react to market shifts efficiently.
✅ Spread Histogram – Visual representation of bullish and bearish spread levels for trend analysis.
🔹 How It Works
1️⃣ Set your EMA periods in the script settings (default: 5, 10, 20, 60, 120).
2️⃣ Define the spread average calculation length (default: 50 candles).
3️⃣ The script tracks EMA alignment to determine bullish or bearish trends.
4️⃣ If the spread deviates significantly from its average, the script:
Places a 📈 green triangle above candles in a bullish trend when spread > average.
Places a 📉 red triangle below candles in a bearish trend when spread < average.
Triggers an alert for timely decision-making.
5️⃣ Use the histogram & real-time alerts to stay ahead of market movements.
MA Deviation with Volatility ThresholdsPrice Deviation from MA with Dynamic Thresholds - TradingView Script Description
Overview
The Price Deviation from Moving Average (MA) with Dynamic Thresholds indicator is designed to measure and visualize how far the current price deviates from a chosen moving average (SMA or EMA) in percentage terms. It provides traders with valuable insights into whether the asset is significantly overbought or oversold relative to its historical mean.
One of the standout features of this indicator is its ability to dynamically adjust overbought and oversold thresholds based on historical volatility, making it more adaptable across different asset classes and market conditions.
Key Features
✅ Customizable Moving Average
Choose between Simple Moving Average (SMA) or Exponential Moving Average (EMA).
Adjustable MA period (default: 200).
Select the timeframe for the MA calculation (default: Daily).
✅ Percentage-Based Deviation Measurement
Measures how much the price has deviated from the selected moving average in percentage terms.
Helps to identify extreme price movements relative to historical trends.
✅ Static & Dynamic Overbought/Oversold Thresholds
Static Thresholds: Users can set fixed percentage levels for overbought and oversold conditions (default: ±20%).
Dynamic Thresholds (enabled by default): Automatically adjust based on historical volatility.
Uses standard deviation of price changes over a specified period (default: 200 candles).
Thresholds are calculated as volatility × a user-defined multiplier (default: 10).
✅ Visual Enhancements
Background Highlighting:
Red when the price exceeds the overbought threshold.
Green when the price drops below the oversold threshold.
Area Chart Representation: The deviation is plotted as a filled orange area (30% opacity) to enhance visual clarity.
Zero Line in Yellow: Helps in quickly identifying when the price is near the moving average.
How to Use
📌 Trend Confirmation & Mean Reversion Trading:
If the deviation is consistently positive, it indicates an uptrend, while negative values suggest a downtrend.
If the price significantly deviates from the MA and enters the overbought/oversold zone, a potential mean reversion opportunity may arise.
📌 Volatility-Adaptive Thresholds:
When enabled, dynamic thresholds help to adjust for different asset volatilities.
Suitable for traders dealing with assets that exhibit varying levels of price fluctuations.
📌 Combining with Other Indicators:
Works well with RSI, Bollinger Bands, and MACD to confirm trend strength or potential reversals.
Can be used in conjunction with support & resistance levels for added confirmation.
Customization Options
Moving Average Type: SMA or EMA.
Moving Average Period & Timeframe Selection.
Static Overbought/Oversold Levels.
Dynamic Thresholds:
Toggle ON/OFF.
Set the Lookback Period for volatility calculation.
Adjust the Volatility Multiplier for fine-tuning threshold sensitivity.
Why Use This Indicator?
🔹 Adaptive to Different Markets: Works with stocks, forex, crypto, commodities, and indices.
🔹 Useful for Both Trend-Following & Mean Reversion Strategies.
🔹 Volatility-Based Adjustments Ensure Market-Relevant Thresholds.
🔹 Enhances Market Awareness by Identifying Extreme Price Deviations.
Final Thoughts
The Price Deviation from MA with Dynamic Thresholds indicator is a powerful tool for traders who want to gauge price extremes and identify potential turning points in the market. With both static and dynamic threshold options, it can be tailored to different trading styles and asset behaviors.
💡 Tip: Experiment with different MA types, periods, and volatility multipliers to find settings that best suit your preferred trading strategy. 🚀
[SHORT ONLY] Consecutive Bars Above MA Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above MA Strategy" is a contrarian trading system aimed at exploiting overextended bullish moves in stocks and ETFs. It monitors the number of consecutive bars that close above a chosen short-term moving average (which can be either a Simple Moving Average or an Exponential Moving Average). Once the count reaches a preset threshold and the current bar’s close exceeds the previous bar’s high within a designated trading window, a short entry is initiated. An optional EMA filter further refines entries by requiring that the current close is below the 200-period EMA, helping to ensure that trades are taken in a bearish environment.
█ HOW ARE THE CONSECUTIVE BULLISH COUNTS CALCULATED?
The strategy utilizes a counter variable, `bullCount`, to track consecutive bullish bars based on their relation to the short-term moving average. Here’s how the count is determined:
Initialize the Counter
The counter is initialized at the start:
var int bullCount = na
Bullish Bar Detection
For each bar, if the close is above the selected moving average (either SMA or EMA, based on user input), the counter is incremented:
bullCount := close > signalMa ? (na(bullCount) ? 1 : bullCount + 1) : 0
Reset on Non-Bullish Condition
If the close does not exceed the moving average, the counter resets to zero, indicating a break in the consecutive bullish streak.
█ SIGNAL GENERATION
1. SHORT ENTRY
A short signal is generated when:
The number of consecutive bullish bars (i.e., bars closing above the short-term MA) meets or exceeds the defined threshold (default: 3).
The current bar’s close is higher than the previous bar’s high.
The signal occurs within the specified trading window (between Start Time and End Time).
Additionally, if the EMA filter is enabled, the entry is only executed when the current close is below the 200-period EMA.
2. EXIT CONDITION
An exit signal is triggered when the current close falls below the previous bar’s low, prompting the strategy to close the short position.
█ ADDITIONAL SETTINGS
Threshold: The number of consecutive bullish bars required to trigger a short entry (default is 3).
Trading Window: The Start Time and End Time inputs define when the strategy is active.
Moving Average Settings: Choose between SMA and EMA, and set the MA length (default is 5), which is used to assess each bar’s bullish condition.
EMA Filter (Optional): When enabled, this filter requires that the current close is below the 200-period EMA, supporting entries in a downtrend.
█ PERFORMANCE OVERVIEW
This strategy is designed for stocks and ETFs and can be applied across various timeframes.
It seeks to capture mean reversion by shorting after a series of bullish bars suggests an overextended move.
The approach employs a contrarian short entry by waiting for a breakout (close > previous high) following consecutive bullish bars.
The adjustable moving average settings and optional EMA filter allow for further optimization based on market conditions.
Comprehensive backtesting is recommended to fine-tune the threshold, moving average parameters, and filter settings for optimal performance.
ATR Trailing Stop by GideonMATR Trailing Stop Indicator
This ATR Trailing Stop Indicator is designed for traders who wish to enhance their exit strategies by leveraging volatility-based stops. It offers a systematic approach to trend management and risk control, enabling traders to capture extended trends while protecting their capital during market reversals. Works on Indian Indices as well.
Overview:
The ATR Trailing Stop indicator is a dynamic trend-following tool that adjusts stop levels based on market volatility. By incorporating the Average True Range (ATR), the indicator provides a flexible exit strategy that adapts to changing market conditions, helping traders lock in profits during trends and limit losses during reversals.
How It Works:
True Range and ATR Calculation:
The indicator first calculates the True Range (TR) for each bar, defined as the maximum of:
The difference between the high and low,
The absolute difference between the high and the previous close, and
The absolute difference between the low and the previous close.
Using the TR values, the ATR is computed over a user-defined period (default is 14 bars) with an option to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the smoothing method.
Trailing Stop Determination:
Two potential stop levels are calculated:
For an uptrend, the stop is determined as:
Stop = Close – (Multiplier × ATR)
For a downtrend, the stop is:
Stop = Close + (Multiplier × ATR)
The indicator maintains a persistent trailing stop that dynamically adjusts:
In an uptrend, the trailing stop only moves upward (or remains flat) to secure gains.
In a downtrend, it only moves downward, thereby protecting the position from excessive losses.
A reversal in trend is identified when the price crosses the trailing stop level, at which point the indicator flips the trend and resets the stop level accordingly.
Rationale:
Utilizing the ATR for trailing stops ensures that the stop levels are directly influenced by market volatility. This dynamic adjustment helps accommodate the natural price fluctuations of the market, providing a more adaptive risk management tool compared to fixed stop-loss levels. The approach is particularly useful in volatile markets where traditional static stops might be triggered prematurely.
Customization:
Key parameters that can be adjusted include:
ATR Period: The number of bars used to calculate the ATR.
ATR Multiplier: The factor that determines how far the trailing stop is set from the current price.
Smoothing Method: Option to choose between SMA and EMA for ATR calculation, allowing traders to tailor the sensitivity of the indicator to their specific trading style.
Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
TVMC - Composite Indicator with Technical RatingsDescription:
The TVMC (Trend, Volume, Momentum, Composite) indicator is a powerful multi-component tool designed to provide traders with a comprehensive understanding of market conditions. By combining four essential technical analysis components—trend, momentum, volume, and volatility—this indicator offers clear and actionable insights to assist in decision-making.
Key Features:
1. Trend Component (TC):
* Based on MACD (Moving Average Convergence Divergence), this component analyzes the relationship between two exponential moving averages (fast and slow) to determine the prevailing market trend.
* The MACD signal is normalized to a range of -1 to +1 for consistency and clarity.
2. Momentum Component (MC):
* Utilizes RSI (Relative Strength Index) to measure the strength and speed of price movements.
* This component highlights overbought or oversold conditions, which may indicate potential market reversals.
3. Volume Confirmation (VC):
* Compares the current trading volume to its moving average over a specified period.
* High volume relative to the average confirms the validity of the current trend.
4. Volatility Filter (VF):
* Uses ATR (Average True Range) to gauge market volatility.
* Adjusts and smooths signals to reduce noise during periods of high volatility.
5. Technical Ratings Integration:
* Incorporates TradingView’s Technical Ratings, allowing users to validate signals using moving averages, oscillators, or a combination of both.
* Users can choose their preferred source of ratings for enhanced signal confirmation.
How It Works:
The TVMC indicator combines the weighted contributions of the Trend, Momentum, and Volume components, further refined by the Volatility Filter. Each component plays a specific role:
* Trend: Identifies whether the market is bullish, bearish, or neutral.
* Momentum: Highlights the strength of price action.
* Volume: Confirms whether the current price action is supported by sufficient trading activity.
* Volatility: Filters out excessive noise in volatile market conditions, providing a smoother and more reliable output.
Visualization:
1. Bullish Signals:
* The indicator line turns green and remains above the zero line, indicating upward momentum.
2. Bearish Signals:
* The indicator line turns red and falls below the zero line, signaling downward momentum.
3. Neutral Signals:
* The line is orange and stays near zero, indicating a lack of strong trend or momentum.
4. Zones:
* Horizontal lines at +30 and -30 mark strong bullish and bearish zones, respectively.
* A zero line is included for clear separation between bullish and bearish signals.
Recommended Usage:
* Best Timeframes: The indicator is optimized for higher timeframes such as 4-hour (H4) and daily (D1) charts.
* Trading Style: Suitable for swing and positional trading.
* Customization: The indicator allows users to adjust all major parameters (e.g., MACD, RSI, volume, and ATR settings) to fit their trading preferences.
Customization Options:
* Adjustable weights for Trend, Momentum, and Volume components.
* Fully configurable settings for MACD, RSI, Volume SMA, and ATR periods.
* Timeframe selection for multi-timeframe analysis.
Important Notes:
1. Originality: The TVMC indicator combines multiple analysis methods into a unique framework. It does not replicate or minimally modify existing indicators.
2. Transparency: The description is detailed enough for users to understand the methodology without requiring access to the code.
3. Clarity: The indicator is explained in a way that is accessible even to users unfamiliar with complex technical analysis tools.
Compliance with TradingView Rules:
* The indicator is written in Pine Script version 5, adhering to TradingView’s language standards.
* The description is written in English to ensure accessibility to the global community, with a clear explanation of all components and functionality.
* No promotional content, links, or unrelated references are included.
* The chart accompanying the indicator is clean and demonstrates its intended use clearly, with no additional indicators unless explicitly explained.
PDF-MA Supertrend [BackQuant]PDF-MA Supertrend
The PDF-MA Supertrend combines the innovative Probability Density Function (PDF) smoothing with the widely popular Supertrend methodology, creating a robust tool for identifying trends and generating actionable trading signals. This indicator is designed to provide precise entries and exits by dynamically adapting to market volatility while visualizing long and short opportunities directly on the chart.
Core Feature: PDF Smoothing
At the foundation of this indicator is the PDF smoothing technique, which applies a Probability Density Function to calculate a smoothed moving average. This method allows the indicator to assign adaptive weights to data points, making it responsive to market changes without overreacting to short-term volatility.
Key parameters include:
Variance: Controls the spread of the PDF weighting. A smaller variance results in sharper responses, while a larger variance smooths out the curve.
Mean: Shifts the PDF’s center, allowing traders to tweak how weights are distributed around the data points.
Smoothing Method: Offers the choice between EMA (Exponential Moving Average) and SMA (Simple Moving Average) for blending the PDF-smoothed data with traditional moving average methods.
By combining these parameters, the PDF smoothing creates a moving average that effectively captures underlying trends.
Supertrend: Adaptive Trend and Volatility Tracking
The Supertrend is a well-known volatility-based indicator that dynamically adjusts to market conditions using the ATR (Average True Range). In this script, the PDF-smoothed moving average acts as the price input, making the Supertrend calculation more adaptive and precise.
Key Supertrend Features:
ATR Period: Determines the lookback period for calculating market volatility.
Factor: Multiplies the ATR to set the distance between the Supertrend and the price. A higher factor creates wider bands, filtering out smaller price movements, while a lower factor captures tighter trends.
Dynamic Direction: The Supertrend flips its direction based on price interactions with the calculated upper and lower bands:
Uptrend : When the price is above the Supertrend, the direction turns bullish.
Downtrend : When the price is below the Supertrend, the direction turns bearish.
This combination of PDF smoothing and Supertrend calculation ensures that trends are detected with greater accuracy, while volatility filters out market noise.
Long and Short Signal Generation
The PDF-MA Supertrend generates actionable trading signals by detecting transitions in the trend direction:
Long Signal (𝕃): Triggered when the trend transitions from bearish to bullish. This is visually represented with a green triangle below the price bars.
Short Signal (𝕊): Triggered when the trend transitions from bullish to bearish. This is marked with a red triangle above the price bars.
These signals provide traders with clear entry and exit points, ensuring they can capitalize on emerging trends while avoiding false signals.
Customizable Visualization Options
The indicator offers a range of visualization settings to help traders interpret the data with ease:
Show Supertrend: Option to toggle the visibility of the Supertrend line.
Candle Coloring: Automatically colors candlesticks based on the trend direction:
Green for long trends.
Red for short trends.
Long and Short Signals (𝕃 + 𝕊): Displays long (𝕃) and short (𝕊) signals directly on the chart for quick identification of trade opportunities.
Line Color Customization: Allows users to customize the colors for long and short trends.
Alert Conditions
To ensure traders never miss an opportunity, the PDF-MA Supertrend includes built-in alerts for trend changes:
Long Signal Alert: Notifies when a bullish trend is identified.
Short Signal Alert: Notifies when a bearish trend is identified.
These alerts can be configured for real-time notifications via SMS, email, or push notifications, making it easier to stay updated on market movements.
Suggested Parameter Adjustments
The indicator’s effectiveness can be fine-tuned using the following guidelines:
Variance:
For low-volatility assets (e.g., indices): Use a smaller variance (1.0–1.5) for smoother trends.
For high-volatility assets (e.g., cryptocurrencies): Use a larger variance (1.5–2.0) to better capture rapid price changes.
ATR Factor:
A higher factor (e.g., 2.0) is better suited for long-term trend-following strategies.
A lower factor (e.g., 1.5) captures shorter-term trends.
Smoothing Period:
Shorter periods provide more reactive signals but may increase noise.
Longer periods offer stability and better alignment with significant trends.
Experimentation is encouraged to find the optimal settings for specific assets and trading strategies.
Trading Applications
The PDF-MA Supertrend is a versatile indicator suited to a variety of trading approaches:
Trend Following : Use the Supertrend line and signals to follow market trends and ride sustained price movements.
Reversal Trading : Spot potential trend reversals as the Supertrend flips direction.
Volatility Analysis : Adjust the ATR factor to filter out minor price fluctuations or capture sharp movements.
Final Thoughts
The PDF-MA Supertrend combines the precision of Probability Density Function smoothing with the adaptability of the Supertrend methodology, offering traders a powerful tool for identifying trends and volatility. With its customizable parameters, actionable signals, and built-in alerts, this indicator is an excellent choice for traders seeking a robust and reliable system for trend detection and entry/exit timing.
As always, backtesting and incorporating this indicator into a broader strategy are recommended for optimal results.
Rosiz Support 1### Description of the Custom Indicator: MACD + CMF + MOM
This custom indicator combines three powerful technical analysis tools: **MACD (Moving Average Convergence Divergence)**, **CMF (Chaikin Money Flow)**, and **MOM (Momentum)**, to provide a comprehensive view of market trends, momentum, and money flow in a single pane. Here's what each component offers:
---
#### 1. **MACD (Moving Average Convergence Divergence)**
The **MACD** is a trend-following momentum indicator that shows the relationship between two moving averages of an asset’s price.
- **Purpose**: Identifies trend direction and momentum strength.
- **Key Components**:
- **MACD Line**: Difference between the fast and slow exponential moving averages (EMA).
- **Signal Line**: A smoothed moving average of the MACD line, acting as a trigger for buy/sell signals.
- **Histogram**: The difference between the MACD line and the signal line. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
- **Usage**: Look for crossovers (MACD crossing the signal line) to identify potential trend changes.
---
#### 2. **CMF (Chaikin Money Flow)**
The **CMF** measures the volume-weighted average of accumulation and distribution over a specific period. It shows whether money is flowing into or out of an asset.
- **Purpose**: Detects buying or selling pressure based on price and volume.
- **Key Components**:
- **Positive CMF**: Indicates that the asset is being accumulated (buying pressure).
- **Negative CMF**: Indicates that the asset is being distributed (selling pressure).
- **Usage**: Values above 0 suggest bullish strength, while values below 0 suggest bearish strength.
---
#### 3. **MOM (Momentum)**
The **Momentum Indicator** measures the rate of change of an asset's price over a specified period. It helps traders identify the speed of price movements.
- **Purpose**: Highlights the strength and direction of price momentum.
- **Key Components**:
- **Momentum Line**: Positive values indicate upward momentum, while negative values indicate downward momentum.
- **Usage**: A rising momentum line suggests strengthening price trends, while a falling line indicates weakening trends.
---
### Benefits of Combining These Indicators:
1. **Trend Confirmation**: MACD provides a clear picture of trend direction and potential reversals.
2. **Volume-Based Insights**: CMF adds a layer of confirmation by analyzing money flow based on price and volume.
3. **Momentum Analysis**: MOM reveals the speed and strength of price movements, helping traders confirm breakouts or trend exhaustion.
4. **Enhanced Decision-Making**: The combination of these indicators allows traders to make more informed decisions by evaluating different aspects of market behavior in one pane.
---
### How to Use:
- **Identify Trends**: Use MACD to identify overall trend direction and reversals.
- **Confirm Momentum**: Check MOM to validate the strength of the trend.
- **Gauge Buying/Selling Pressure**: Refer to CMF to confirm whether the price movement is backed by accumulation or distribution.
- **Entry/Exit Points**: Look for MACD crossovers, CMF shifts above/below zero, and momentum changes to refine entry and exit strategies.
This powerful tool integrates the strengths of three indicators, making it ideal for traders looking to analyze market conditions holistically and improve their timing and accuracy.
Aura Vibes EMA Ribbon + VStop + SAR + Bollinger BandsThe combination of Exponential Moving Averages (EMA), Volatility Stop (VStop), Parabolic SAR (PSAR), and Bollinger Bands (BB) offers a comprehensive approach to technical analysis, each serving a distinct purpose:
Exponential Moving Averages (EMA): EMAs are used to identify the direction of the trend by smoothing price data. Shorter-period EMAs react more quickly to price changes, while longer-period EMAs provide a broader view of the trend.
Volatility Stop (VStop): VStop is a dynamic stop-loss mechanism that adjusts based on market volatility, typically using the Average True Range (ATR). This allows traders to set stop-loss levels that accommodate market fluctuations, potentially reducing the likelihood of premature stop-outs.
Parabolic SAR (PSAR): PSAR is a trend-following indicator that provides potential entry and exit points by plotting dots above or below the price chart. When the dots are below the price, it suggests an uptrend; when above, a downtrend.
Bollinger Bands (BB): BB consists of a middle band (typically a 20-period simple moving average) and two outer bands set at standard deviations above and below the middle band. These bands expand and contract based on market volatility, helping traders identify overbought or oversold conditions.
Integrating these indicators can enhance trading strategies:
Trend Identification: Use EMAs to determine the prevailing market trend. For instance, a short-term EMA crossing above a long-term EMA may signal an uptrend.
Entry and Exit Points: Combine PSAR and BB to pinpoint potential entry and exit points. For example, a PSAR dot appearing below the price during an uptrend, coinciding with the price touching the lower Bollinger Band, might indicate a buying opportunity.
Risk Management: Implement VStop to set adaptive stop-loss levels that adjust with market volatility, providing a buffer against market noise.
By thoughtfully combining these indicators, traders can develop a robust trading system that adapts to various market conditions.
SMA Trend Spectrum [InvestorUnknown]The SMA Trend Spectrum indicator is designed to visually represent market trends and momentum by using a series of Simple Moving Averages (SMAs) to create a color-coded spectrum or heatmap. This tool helps traders identify the strength and direction of market trends across various time frames within one chart.
Functionality:
SMA Calculation: The indicator calculates multiple SMAs starting from a user-defined base period (Starting Period) and increasing by a specified increment (Period Increment). This creates a sequence of moving averages that span from short-term to long-term perspectives.
Trend Analysis: Each segment of the spectrum compares three SMAs to determine the market's trend strength: Bullish (color-coded green) when the current price is above all three SMAs. Neutral (color-coded purple) when the price is above some but not all SMAs. Bearish (color-coded red) when the price is below all three SMAs.
f_col(x1, x2, x3) =>
min = ta.sma(src, x1)
mid = ta.sma(src, x2)
max = ta.sma(src, x3)
c = src > min and src > mid and src > max ? bull : src > min or src > mid or src > max ? ncol : bear
Heatmap Visualization: The indicator plots these trends as a vertical spectrum where each row represents a different set of SMAs, forming a heatmap-like display. The color of each segment in the heatmap directly correlates with market conditions, providing an intuitive view of market sentiment.
Signal Smoothing: Users can choose to smooth the trend signal using either a Simple Moving Average (SMA), Exponential Moving Average (EMA), or leave it as raw data (Signal Smoothing). The length of smoothing can be adjusted (Smoothing Length). The signal is displayed in a scaled way to automatically adjust for the best visual experience, ensuring that the trend is clear and easily interpretable across different chart scales and time frames
Additional Features:
Plot Signal: Optionally plots a line representing the average trend across all calculated SMAs. This line helps in identifying the overall market direction based on the spectrum data.
Bar Coloring: Bars on the chart can be colored according to the average trend strength, providing a quick visual cue of market conditions.
Usage:
Trend Identification: Use the heatmap to quickly assess if the market is trending strongly in one direction or if it's in a consolidation phase.
Entry/Exit Points: Look for shifts in color patterns to anticipate potential trend changes or confirmations for entry or exit points.
Momentum Analysis: The gradient from bearish to bullish across the spectrum can be used to gauge momentum and potentially forecast future price movements.
Notes:
The effectiveness of this indicator can vary based on market conditions, asset volatility, and the chosen SMA periods and increments.
It's advisable to combine this tool with other technical indicators or fundamental analysis for more robust trading decisions.
Disclaimer: Past performance does not guarantee future results. Always use this indicator as part of a broader trading strategy.
three Supertrend EMA Strategy by Prasanna +DhanuThe indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
The indicator described in your Pine Script is a Supertrend EMA Strategy that combines the Supertrend and EMA (Exponential Moving Average) to create a trend-following strategy. Here’s a detailed breakdown of how this indicator works:
1. EMA (Exponential Moving Average):
The EMA is a moving average that places more weight on recent prices, making it more responsive to price changes compared to a simple moving average (SMA). In this strategy, the EMA is used to determine the overall trend direction.
Input Parameter:
ema_length: This is the period for the EMA, set to 50 periods by default. A shorter EMA will respond more quickly to price movements, while a longer EMA is smoother and less sensitive to short-term fluctuations.
How it's used:
If the price is above the EMA, it indicates an uptrend.
If the price is below the EMA, it indicates a downtrend.
2. Supertrend Indicator:
The Supertrend indicator is a trend-following tool based on the Average True Range (ATR), which is a volatility measure. It helps to identify the direction of the trend by setting a dynamic support or resistance level.
Input Parameters:
supertrend_atr_period: The period used for calculating the ATR, set to 10 periods by default.
supertrend_multiplier1: Multiplier for the first Supertrend, set to 3.0.
supertrend_multiplier2: Multiplier for the second Supertrend, set to 2.0.
supertrend_multiplier3: Multiplier for the third Supertrend, set to 1.0.
Each Supertrend line has a different multiplier, which affects its sensitivity to price changes. The ATR period defines how many periods of price data are used to calculate the ATR.
How the Supertrend works:
If the Supertrend value is below the price, the trend is considered bullish (uptrend).
If the Supertrend value is above the price, the trend is considered bearish (downtrend).
The Supertrend will switch between up and down based on price movement and ATR, providing a dynamic trend-following signal.
3. Three Supertrend Lines:
In this strategy, three Supertrend lines are calculated with different multipliers and the same ATR period (10 periods). Each line is more or less sensitive to price changes, and they are plotted on the chart in different colors based on whether the trend is bullish (green) or bearish (red).
Supertrend 1: The most sensitive Supertrend with a multiplier of 3.0.
Supertrend 2: A moderately sensitive Supertrend with a multiplier of 2.0.
Supertrend 3: The least sensitive Supertrend with a multiplier of 1.0.
Each Supertrend line signals a bullish trend when its value is below the price and a bearish trend when its value is above the price.
4. Strategy Rules:
This strategy uses the three Supertrend lines combined with the EMA to generate trade signals.
Entry Conditions:
A long entry is triggered when all three Supertrend lines are in an uptrend (i.e., all three Supertrend lines are below the price), and the price is above the EMA. This suggests a strong bullish market condition.
A short entry is triggered when all three Supertrend lines are in a downtrend (i.e., all three Supertrend lines are above the price), and the price is below the EMA. This suggests a strong bearish market condition.
Exit Conditions:
A long exit occurs when the third Supertrend (the least sensitive one) switches to a downtrend (i.e., the price falls below it).
A short exit occurs when the third Supertrend switches to an uptrend (i.e., the price rises above it).
5. Visualization:
The strategy also plots the following on the chart:
The EMA is plotted as a blue line, which helps identify the overall trend.
The three Supertrend lines are plotted with different colors:
Supertrend 1: Green (for uptrend) and Red (for downtrend).
Supertrend 2: Green (for uptrend) and Red (for downtrend).
Supertrend 3: Green (for uptrend) and Red (for downtrend).
Summary of the Strategy:
The strategy combines three Supertrend indicators (with different multipliers) and an EMA to capture both short-term and long-term trends.
Long positions are entered when all three Supertrend lines are bullish and the price is above the EMA.
Short positions are entered when all three Supertrend lines are bearish and the price is below the EMA.
Exits occur when the third Supertrend line (the least sensitive) signals a change in trend direction.
This combination of indicators allows for a robust trend-following strategy that adapts to both short-term volatility and long-term trend direction. The Supertrend lines provide quick reaction to price changes, while the EMA offers a smoother, more stable trend direction for confirmation.
X4 Moving AverageThe X4 Moving Averages (X4MA) indicator is designed to provide traders with an enhanced view of market trends by combining multiple dimensions of price data. Unlike traditional moving averages that rely solely on closing prices, X4MA integrates high, low, open, and close values for a more nuanced analysis of market movements.
1- High-Low Average (HLAvg):
Captures the market's range during a given period:
HLAvg = (High + Low) / 2
2- Open-Close Average (OCAvg):
Reflects the directional momentum of the price during the same period:
OCAvg = (Open + Close) / 2
3- Combined Average (CMA):
Combines the range (HLAvg) and momentum (OCAvg) for a balanced view of price behavior:
CMA = (HLAvg + OCAvg) / 2
4- Exponential Moving Average (X4MA):
Smooths the combined average using an EMA for better responsiveness to recent price changes while filtering noise:
X4MA = EMA(CMA, Length)
