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Dominant Cycle Tuned RsiIntroduction
Adaptive technical indicators are importants in a non stationary market, the ability to adapt to a situation can boost the efficiency of your strategy. A lot of methods have been proposed to make technical indicators "smarters" , from the use of variable smoothing constant for exponential smoothing to artificial intelligence.
The dominant cycle tuned rsi depend on the dominant cycle period of the market, such method allow the rsi to return accurate peaks and valleys levels. This indicator is an estimation of the cycle finder tuned rsi proposed by Lars von Thienen published in Decoding the Hidden Market Rhythm/Fine-tuning technical indicators using the dominant market vibration/2010 using the cycle measurement method described by John F.Ehlers in Cybernetic Analysis for Stocks and Futures .
The following section is for information purpose only, it can be technical so you can skip directly to the The Indicator section.
Frequency Estimation and Maximum Entropy Spectral Analysis
“Looks like rain,” said Tom precipitously.
Tom would have been a great weather forecaster, but market patterns are more complex than weather ones. The ability to measure dominant cycles in a complex signal is hard, also a method able to estimate it really fast add even more challenge to the task. First lets talk about the term dominant cycle , signals can be decomposed in a sum of various sine waves of different frequencies and amplitudes, the dominant cycle is considered to be the frequency of the sine wave with the highest amplitude. In general the highest frequencies are those who form the trend (often called fundamentals) , so detrending is used to eliminate those frequencies in order to keep only mid/mid - highs ones.
A lot of methods have been introduced but not that many target market price, Lars von Thienen proposed a method relying on the following processing chain :
Lars von Thienen Method = Input -> Filtering and Detrending -> Discrete Fourier Transform of the result -> Selection using Bartels statistical test -> Output
Thienen said that his method is better than the one proposed by Elhers. The method from Elhers called MESA was originally developed to interpret seismographic information. This method in short involve the estimation of the phase using low amount of information which divided by 360 return the frequency. At first sight there are no relations with the Maximum entropy spectral estimation proposed by Burg J.P. (1967). Maximum Entropy Spectral Analysis. Proceedings of 37th Meeting, Society of Exploration Geophysics, Oklahoma City.
You may also notice that these methods are plotted in the time domain where more classic method such as : power spectrum, spectrogram or FFT are not. The method from Elhers is the one used to tune our rsi.
The Indicator
Our indicator use the dominant cycle frequency to calculate the period of the rsi thus producing an adaptive rsi . When our adaptive rsi cross under 70, price might start a downtrend, else when our adaptive rsi crossover 30, price might start an uptrend. The alpha parameter is a parameter set to be always lower than 1 and greater than 0. Lower values of alpha minimize the number of detected peaks/valleys while higher ones increase the number of those. 0.07 for alpha seems like a great parameter but it can sometimes need to be changed.
The adaptive indicator can also detect small top/bottoms of small periods
Of course the indicator is subject to failures
At the end it is totally dependent of the dominant cycle estimation, which is still a rough method subject to uncertainty.
Conclusion
Tuning your indicator is a great way to make it adapt to the market, but its also a complex way to do so and i'm not that convinced about the complexity/result ratio. The version using chart background will be published separately.
Feel free to tune your indicators with the estimator from elhers and see if it provide a great enhancement :)
Thanks for reading !
References
for the calculation of the dominant cycle estimator originally from www.davenewberg.com
Decoding the Hidden Market Rhythm (2010) Lars von Thienen
Ehlers , J. F. 2004 . Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading . Wiley
Minimal Godmode 2.0Second iteration of Minimal Godmode with in-line TTM Squeeze linked to godmode channel length, TTSI from godmode 4.0.0, and new LRSI + CBCI calculations for godmode engine.
Note: Like the original godmode, this indicator is designed specifically for use in trading BTC/XBT pairs.
Surface Roughness EstimatorIntroduction
Roughness of a signal is often non desired since smooth signals are easier to analyse, its logical to say that anything interacting with rough price is subject to decrease in accuracy/efficiency and can induce non desired effects such as whipsaws. Being able to measure it can give useful information and potentially avoid errors in an analysis.
It is said that roughness appear when a signal have high-frequencies (short wavelengths) components with considerable amplitudes, so its not wrong to say that "estimating roughness" can be derived into "estimating complexity".
Measuring Roughness
There are a lot of way to estimate roughness in a signal, the most well know method being the estimation of fractal dimensions. Here i will use a first order autocorrelation function.
Auto-correlation is defined by the linear relationship between a signal and a delayed version of itself, for exemple if the price goes on the same direction than the price i bars back then the auto-correlation will increase, else decrease. So what this have to do with roughness ? Well when the auto-correlation decrease it means that the dominant frequency is high, and therefore that the signal is rough.
Interpretation Of The Indicator
When the indicator is high it means that price is rough, when its low it indicate that price is smooth. Originally its the inverse way but i found that it was more convenient to do it this way. We can interpret low values of the indicator as a trending market but its not totally true, for example high values dont always indicate that the market is ranging.
Here the comparison with the indicator applied to price (orange) and a moving average (purple)
The average measurement applied to a moving average is way lower than the one using the price, this is because a moving average is smoother than price.
Its also interesting to see that some trend strength estimator like efficiency ratio can treat huge volatility signals as trend as shown below.
Here the efficiency ratio treat this volatile movement as a trending market, our indicator instead indicate that this movement is rough, such indication can avoid situation where price is followed by another huge volatile movement in the opposite direction.
Its important to make the distinction between volatility and trend strength, the trend is defined by low frequencies components of a signal, therefore measuring trend strength can be resumed as measuring the amplitude of such frequencies, but roughness estimation can do a great job as well.
Conclusion
I have showed how to estimate roughness in price and compared how our indicator behaved in comparison with a classic trend strength measurement tool. Filters or any other indicator can be way more efficient if they know how to filter according to a situation, more commonly smoothing more when price is rough and smoothing less when price is smooth. Its good to have a wider view of how market is behaving and not sticking with the binary view of "Trending" and "Ranging" .
I hope you find a use to this script :)
Best Regards
BE-EMA(12,26) (Blue Empire Exponential Moving Average)
Simple EMA where you get a CROSS mark between EMA 12 and EMA 26.
Each time a cross happens, a spot gets created.
If it's cyan, it goes up.
If it's magenta, it goes down.
I'm studying Trading at Blue Empire Academy, if you want to know more send me a PM.
Wave Analysis study the wave's behavior and tries to predict by using trendlines, elliot waves, fibonacci retracements, and EMAs basically.
In this Indicator, It's a confirmation when EMA 12 goes over to confirm the price may go up. and Vice versa.
Hope you like, please share if you think it's useful and comment if you think this can be better.
Thank you again for reading
>> This is just an indicator, it doesn't predict the future. Use it at your own risk. <<
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All the credits to @tracks, a genius who helped me polish the code. :] thank you.
SMMA Analyses - Buy / Sell signals and close position signals This script combines the usage of the SMMA indicator in order to provide signals for opening and closing trades, either buy or sell signals.
It uses two SMMA , a fast and a slow one, both configurable by the users.
The trigger of Buy and Sell Signals are calculated through the SMMA crosses:
Buy Signals : The fast SMMA crosses over the slow SMMA . They are highlighting by a green area and a "B" label.
Sell Signals : The fast SMMA crosses under the slow SMMA . They are highlighting by a red area and a "S" label
The trigger of Close Buy and Close Sell Signals are calculated through the close price crosses with the fast SMMA:
Close Buy Signals : The fast SMMA crosses under the close price and at the same time the trend is bullish , so the fast SMMA is greater than the slow SMMA . They are highlighted by a lighter green area
Close Sell Signals : The fast SMMA crosses over the close price and at the same time the trend is bearish , so the fast SMMA is lower than the slow SMMA . They are highlighted by a lighter red area
Few important points about the indicator and the produced signals :
This is not intended to be a strategy, but an indicator for analyzing the SMMA conditions. It gives you the triggers depending on the real time analysis of the SMMA and prices, but not being a proper strategy, pay attention about "fake signals" and add always a visual analysis to the provided signals
Following this indicator, the trade positions should be opened only when a cross happens. Either in this case, analyse the chart in order to see if the signals are a "weak" ones, due to "waves" around the SMMA . In these cases, you might wait for the next confirmation signals after the waves, when the trend will be better defined
The close trade signals are provided in order to help to understand when you should close the buy or sell trades. Even in this case, always add a visual analysis to the signals, and pay attention to the support/resistance areas. Sometimes, you can have the close signals in correspondence to support/resistance areas: in these cases wait for the definition of the trend and eventually for the next close trade signals if they will be better defined
Fractal HelperA spinoff from a previous script I published, this configurable indicator also selects highs and lows and then plots a trend line that bounces between them. In addition, it also iterates this up to two more times in a quasi-fractal manner, on larger time scales, and plots them on the same graph.
Of course this will not spit out Elliott waves, but with adjusting, it could aid in discerning one wave from another.
I may experiment with the security function again to get a better, longer L3 plot, although charts are limited in duration anyway.
CMYK XIAM OPEN◊ Introduction
This is project XIAM, a work in progress.
Recently i came across the repainting problem.
Since then i haven't seen any bot-code that makes > 5% profit in two weeks with 0.25% fees/trade.
People who make good bots either bluff or don't share the code.
they let you rent it.
I aim to understand, learn it, write it myself. And share my findings with whoever shares with me.
◊ Origin
Based on RMI (RSI with momentum) and SMA, and values derived from those.
◊ Usage
Currently an investigative script.
◊ Theoretical Approaches
Philosophy α :: Cleansignal
:: Cleaning up the signal, from irregularities that cause unpredictable results.
Merging available tickers of a pair into one.
Merging available tickers of different coins into one in the correct proportion. (eg. Crypto market cap)
Removing Jitter, and smoothing signal without delay.
Philosophy β :: Rythmic
:: Syncing into the rythm's, to never miss the que, and trade on every theoretical low/high
Searching Amplitude, Period, Phase Shift, Frequency's of the carrier waves.
Marking Acrivity/inactivity of the carrier waves.
Partial Fractal repetition asses-able with above data?
Philosophy γ :: consequential
:: Seeking for Indicatory events and causal relations
Probability / reward.
Confirmation and culmination.
...
◊ Community
Wanna share your findings ? or need help resolving a problem ?
CMYK :: discord.gg
AUTOTVIEW :: discordapp.com
SB_Wavetrend_OscillatorA take on LazyBear's Wavetrend_Oscillator
The idea is bit modified.
Original Idea:
When the oscillator is above the overbought band (red lines) and crosses down the signal (dotted line), it is usually a good SELL signal. Similarly, when the oscillator crosses above the signal when below the Oversold band (green lines), it is a good BUY signal.
Modified Idea:
Carrying the original idea, if the oscillator crosses the overbought band (red lines) and crosses down the signal (dotted line) twice without crossing the Oversold band (green lines) and crosses above the signal (dotted line), a buy or sell signal will take place when the oscillator crosses the dotted line and the value of oscillator is >0(if sell order is to be placed) and <0(if buy order is to be placed).
For the original idea you can refer to:
Let me know if any refinements could improve the oscillator.
Noro's SILA v1.6LIn 1.6:
1) WaveTrend Oscilator (LazyBear's code)
2) Locomotive-pattern
3) A new distance for SILA lines
Noro's SILA v1.6L - the original and new system of finding of a trend.
SILA is not one trend indicator, but 8 different trend indicators in one. Therefore high precision.
For:
- any pair
- any timeframe >= H1
Fractal Quad Components8 Fractal Resonance Component indicators on a chart eats up LOTS of vertical space, so we're providing this Fractal Quad Components script to group 4 components a bit more compactly (eliminating the margin whitespace between indicator rows).
To view 8 components you'll need to add a second instance of this script to your chart and set its Base Timescale Multiplier to 16. Then grab the dividers to stretch both instances to a good viewing height.
One disadvantage of this grouping method is that to read off the x2, x4, and x8 lead and lag line values, you'll need to mentally add 200, 400 or 600 respectively.
We also replaced the "Extreme" > +-100% black crosses (+) with more subtle purple circle outlines. These extreme crosses are often (but not always) too early to be a major reversal so it's best not to overemphasize them.
Significant crosses (> +-75%) are still highlighted with black circle outlines, and are the most likely to be major reversals for buy/sell.
Note how the 30-minute oscillator (2nd row) showed the cleanest (black-outlined) reversals on the S&P for the last week of 2016, with just a bit more profit-eating lag than the 15-minute oscillator above.
MACD MultiTimeFrame 1h4h1D [Fantastic Fox]Please insert the indicator into 1h time-frame, otherwise you need to change the lengths' inputs.
When there are tops for two of the MACDs and they are near and close* to each other, there is a big opportunity of a "Major Top" for the security, and vice versa for "Major Bottom".
This indicator can be used for tracing multi time-frame divergence. Also, it could help traders to identify the waves of Elliott Wave, and as a signal for confirmation of an impulse after a correction or retracement.
* They should be on top of each others head, not crossing each other. not necessarily touching, but not so far from each other.
Ehlers Smoothed Stochastic & RSI with Roofing FiltersRoofing filters, first discussed by Mr.John Ehlers, act as a passband, filtering out unwanted noise from market data and accentuating turning points.
I have included 2 indicators with filters enabled. Both support double smoothing via options page. All the parameters are configurable.
Info on Roofing Filter and Ehlers Super Smoother:
----------------------------------------------------
The Ehlers' Roofing Filter is an expansion on Ehlers Super Smoother Filter, both being smoothing techniques based on analog filters. This filter aims at reducing noise in price data.
In Super Smoother Filter, regardless of the time frame used, all waves having cycles of less than 10 bars are considered noise (customizable via options page). The Roofing Filter uses this principle, however, it also creates a so-called "roof" by eliminating wave components having cycles greater than 48 bars which are perceived as "spectral dilation". Thus, the filter only passes those spectral components whose periods are between 10 and 48 bars. This technique noticeably reduces indicator lag and also helps assess turning points more accurately.
More info:
- Spectral dilation paper: www.mesasoftware.com
- John Ehlers presentation: www.youtube.com
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If you want to use RSI %B and Bandwidth, follow this guide to "Make mine" this chart and get access to the source:
drive.google.com
For the complete list of my indicators, check this post:
Squeeze Momentum Indicator [LazyBear]
Fixed a typo in the code where BB multiplier was stuck at 1.5. Thanks @ucsgears for bringing it to my notice.
Updated source: pastebin.com
Use the updated source instead of the what TV shows below.
This is a derivative of John Carter's "TTM Squeeze" volatility indicator, as discussed in his book "Mastering the Trade" (chapter 11).
Black crosses on the midline show that the market just entered a squeeze (Bollinger Bands are with in Keltner Channel). This signifies low volatility, market preparing itself for an explosive move (up or down). Gray crosses signify "Squeeze release".
Mr.Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change). My (limited) experience with this shows, an additional indicator like ADX / WaveTrend, is needed to not miss good entry points. Also, Mr.Carter uses simple momentum indicator, while I have used a different method (linreg based) to plot the histogram.
More info:
- Book: Mastering The Trade by John F Carter
List of all my indicators:
Quantum Power Engine v4.1 (Global Market Edition)ONLY FOR GC SI
This guide explains how to effectively use the Quantum Power Engine v4.1 (Light Mode). This indicator is a multi-factor scoring system designed to aggregate momentum, volume, and trend data into a single, actionable "Power Score."
1. The Core Scoring System
The indicator calculates a Power Score ranging from -100 to +100. This score is derived from five weighted technical dimensions:
| Factor | Weight | Condition |
|---|---|---|
| MACD | 30% | Based on histogram direction and slope. |
| Volume/VWAP | 25% | Checks if price is above VWAP with high volume (Relative Vol > 2.0). |
| RSI | 15% | Relative strength compared to its SMA and the 60/40 levels. |
| CMF | 15% | Measures institutional capital inflow (Chaikin Money Flow). |
| SuperTrend | 15% | Defines the overall structural market direction. |
2. Market Status & Strategy
Depending on the current Power Score, the dashboard will display one of seven market states. Use the following guide for your trade execution:
🟢 Bullish Zones (Positive Score)
* +75 to +100: Hyper-Bullish (☀️)
* Market Sentiment: Extreme Greed / Buying Climax.
* Strategy: Hold current positions; tighten Stop-Losses; do not short, but be wary of a "blow-off top."
* +45 to +75: Strong Up-trend (🚀)
* Market Sentiment: Optimistic / Main Momentum Wave.
* Strategy: This is the most profitable phase. Focus on trend-following and adding to winners.
* +15 to +45: Momentum Entry (🟢)
* Market Sentiment: Recovery / Capital Inflow.
* Strategy: Look for long entries (Right-side trading). Monitor if volume continues to expand.
🟡 Neutral Zone
* -15 to +15: Extreme Volatility (⚡)
* Market Sentiment: Indecision / Market Chop.
* Strategy: Wait and See. Avoid trading in this zone as "fakeouts" are common.
🔴 Bearish Zones (Negative Score)
* -15 to -45: Defensive Phase (🔴)
* Market Sentiment: Cautious / Selling Pressure.
* Strategy: Reduce long positions. Do not "buy the dip" yet.
* -45 to -75: Violent Sell-off (🩸)
* Market Sentiment: Panic / Breakdown.
* Strategy: Avoid catching falling knives. Stay in cash or look for short opportunities.
* -75 to -100: Total Breakdown (💀)
* Market Sentiment: Despair / Liquidity Exhaustion.
* Strategy: Maximum bearishness. Wait for a "Right-side" bottoming signal before looking for a reversal.
3. Key Visual Indicators
The Dashboard (Top Right)
* Power Score (战力值): The "temperature" of the market.
* MACD Momentum: Shows if the trend is accelerating (Enhancing) or losing steam (Fading).
* Volume Ratio: Compares current volume to the average.
* Purple (Hyper-Volume): Institutional activity.
* Yellow (Significant): Strong participation.
* Grey (Low): Danger of a trap or lack of interest.
The Squeeze Alert (⚡)
When you see a Gold Bolt (⚡) above a candle, it indicates a "Squeeze" signal:
* Meaning: Low volatility + Low volume + Neutral score.
* Action: The market is "coiling" like a spring. Expect a violent breakout (up or down) shortly. Prepare your triggers.
4. How to Trade with This Indicator
* Identify the Bias: Look at the Dashboard. If the score is > 45, look for Longs. If < -45, look for Shorts.
* Confirm with Volume: Ensure the "Volume Ratio" is at least > 1.2x (Green or Yellow) before entering a trend trade.
* The Exit: If you are in a long trade (Score > 45) and the score drops below +15 or the MACD Momentum changes to "Fading" (⚪), consider taking profits.
* The "Squeeze" Play: If you see the ⚡ icon, wait for the first candle to break the range with a rising Power Score to catch the start of a new move.
Quantum Power Engine v4.1 Light ModeThis guide explains how to effectively use the Quantum Power Engine v4.1 (Light Mode). This indicator is a multi-factor scoring system designed to aggregate momentum, volume, and trend data into a single, actionable "Power Score."
1. The Core Scoring System
The indicator calculates a Power Score ranging from -100 to +100. This score is derived from five weighted technical dimensions:
| Factor | Weight | Condition |
|---|---|---|
| MACD | 30% | Based on histogram direction and slope. |
| Volume/VWAP | 25% | Checks if price is above VWAP with high volume (Relative Vol > 2.0). |
| RSI | 15% | Relative strength compared to its SMA and the 60/40 levels. |
| CMF | 15% | Measures institutional capital inflow (Chaikin Money Flow). |
| SuperTrend | 15% | Defines the overall structural market direction. |
2. Market Status & Strategy
Depending on the current Power Score, the dashboard will display one of seven market states. Use the following guide for your trade execution:
🟢 Bullish Zones (Positive Score)
* +75 to +100: Hyper-Bullish (☀️)
* Market Sentiment: Extreme Greed / Buying Climax.
* Strategy: Hold current positions; tighten Stop-Losses; do not short, but be wary of a "blow-off top."
* +45 to +75: Strong Up-trend (🚀)
* Market Sentiment: Optimistic / Main Momentum Wave.
* Strategy: This is the most profitable phase. Focus on trend-following and adding to winners.
* +15 to +45: Momentum Entry (🟢)
* Market Sentiment: Recovery / Capital Inflow.
* Strategy: Look for long entries (Right-side trading). Monitor if volume continues to expand.
🟡 Neutral Zone
* -15 to +15: Extreme Volatility (⚡)
* Market Sentiment: Indecision / Market Chop.
* Strategy: Wait and See. Avoid trading in this zone as "fakeouts" are common.
🔴 Bearish Zones (Negative Score)
* -15 to -45: Defensive Phase (🔴)
* Market Sentiment: Cautious / Selling Pressure.
* Strategy: Reduce long positions. Do not "buy the dip" yet.
* -45 to -75: Violent Sell-off (🩸)
* Market Sentiment: Panic / Breakdown.
* Strategy: Avoid catching falling knives. Stay in cash or look for short opportunities.
* -75 to -100: Total Breakdown (💀)
* Market Sentiment: Despair / Liquidity Exhaustion.
* Strategy: Maximum bearishness. Wait for a "Right-side" bottoming signal before looking for a reversal.
3. Key Visual Indicators
The Dashboard (Top Right)
* Power Score (战力值): The "temperature" of the market.
* MACD Momentum: Shows if the trend is accelerating (Enhancing) or losing steam (Fading).
* Volume Ratio: Compares current volume to the average.
* Purple (Hyper-Volume): Institutional activity.
* Yellow (Significant): Strong participation.
* Grey (Low): Danger of a trap or lack of interest.
The Squeeze Alert (⚡)
When you see a Gold Bolt (⚡) above a candle, it indicates a "Squeeze" signal:
* Meaning: Low volatility + Low volume + Neutral score.
* Action: The market is "coiling" like a spring. Expect a violent breakout (up or down) shortly. Prepare your triggers.
4. How to Trade with This Indicator
* Identify the Bias: Look at the Dashboard. If the score is > 45, look for Longs. If < -45, look for Shorts.
* Confirm with Volume: Ensure the "Volume Ratio" is at least > 1.2x (Green or Yellow) before entering a trend trade.
* The Exit: If you are in a long trade (Score > 45) and the score drops below +15 or the MACD Momentum changes to "Fading" (⚪), consider taking profits.
* The "Squeeze" Play: If you see the ⚡ icon, wait for the first candle to break the range with a rising Power Score to catch the start of a new move.
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
This Pine Script v6 strategy is designed for cryptocurrency markets operating on 5-minute and faster timeframes. It combines volatility regime detection, multi-path signal confirmation, and adaptive risk management to identify momentum-based trading opportunities in perpetual futures markets.
Core Design Principles
The strategy addresses three challenges specific to cryptocurrency trading:
24/7 market operation without session boundaries requires continuous monitoring and execution logic
Volatility regimes shift rapidly, demanding adaptive stop and target calculations
Tick-level responsiveness is critical for capturing momentum moves before they complete
Strategy Architecture
1. Signal Generation Stack
The strategy uses multiple technical indicators calibrated for cryptocurrency momentum:
MACD with parameters 8/21/5 (fast/slow/signal) optimized for crypto acceleration phases
EMA ribbon using 8/21/34 periods with slope analysis to assess trend structure
Volume impulse detection combining SMA baseline, standard deviation, and z-score filtering
RSI (21 period) and MFI (21 period) for momentum confirmation
Bollinger Bands and Keltner Channels for squeeze detection
2. Volatility Regime Classification
The strategy normalizes ATR as a percentage of price and classifies market conditions into three regimes:
Compression (< 0.8% ATR): Reduced position sizing, tighter stops (1.05x ATR), lower profit targets (1.6x ATR)
Expansion (0.8% - 1.6% ATR): Standard risk parameters, balanced risk-reward (1.55x stop, 2.05x target)
Velocity (> 1.6% ATR): Wider stops (2.1x ATR), amplified targets (2.8x ATR), tighter trailing offsets
ATR is calculated over 21 periods and smoothed with a 13-period EMA to reduce noise from wicks.
3. Multi-Path Entry System
Four independent signal pathways contribute to a composite strength score (0-100):
Trend Break (30 points): Requires EMA ribbon alignment, positive slope, and structure breakout above/below recent highs/lows
Momentum Surge (30 points): MACD histogram exceeds adaptive baseline, MACD line crosses signal, RSI/MFI above/below thresholds, with volume impulse confirmation
Squeeze Release (25 points): Bollinger Bands compress inside Keltner Channels, then release with momentum bias
Micro Pullback (15 points): Shallow retracements within trend structure that reset without breaking support/resistance
Additional scoring modifiers:
Volume impulse: +5 points when present, -5 when absent
Regime bonus: +5 in velocity, -2 in compression
Cycle bias: +5 when aligned, -5 when counter-trend
Trades only execute when the composite score reaches the minimum threshold (default: 55) and all filters agree.
4. Risk Management Framework
Position sizing is calculated from:
RiskCapital = Equity × (riskPerTradePct / 100)
StopDistance = ATR × StopMultiplier(regime)
Quantity = min(RiskCapital / StopDistance, MaxExposure / Price)
The strategy includes:
Risk per trade: 0.65% of equity (configurable)
Maximum exposure: 12% of equity (configurable)
Regime-adaptive stop and target multipliers
Adaptive trailing stops based on ATR and regime
Kill switch that disables new entries after 6.5% drawdown
Momentum fail-safe exits when MACD polarity flips or ribbon structure breaks
5. Additional Filters
Cycle Oscillator : Measures price deviation from 55-period EMA. Requires cycle bias alignment (default: ±0.15%) before entry
BTC Dominance Filter : Optional filter using CRYPTOCAP:BTC.D to reduce long entries during risk-off periods (rising dominance) and short entries during risk-on periods
Session Filter : Optional time-based restriction (disabled by default for 24/7 operation)
Strategy Parameters
All default values used in backtesting:
Core Controls
Enable Short Structure: true
Restrict to Session Window: false
Execution Session: 0000-2359:1234567 (24/7)
Allow Same-Bar Re-Entry: true
Optimization Constants
MACD Fast Length: 8
MACD Slow Length: 21
MACD Signal Length: 5
EMA Fast: 8
EMA Mid: 21
EMA Slow: 34
EMA Slope Lookback: 8
Structure Break Window: 9
Regime Intelligence
ATR Length: 21
Volatility Soothing: 13
Low Vol Regime Threshold: 0.8% ATR
High Vol Regime Threshold: 1.6% ATR
Cycle Bias Length: 55
Cycle Bias Threshold: 0.15%
BTC Dominance Feed: CRYPTOCAP:BTC.D
BTC Dominance Confirmation: true
Signal Pathways
Volume Baseline Length: 34
Volume Impulse Multiplier: 1.15
Volume Z-Score Threshold: 0.5
MACD Histogram Smoothing: 5
MACD Histogram Sensitivity: 1.15
RSI Length: 21
RSI Momentum Trigger: 55
MFI Length: 21
MFI Momentum Trigger: 55
Squeeze Length: 20
Bollinger Multiplier: 1.5
Keltner Multiplier: 1.8
Squeeze Release Momentum Gate: 1.0
Micro Pullback Depth: 7
Minimum Composite Signal Strength: 55
Risk Architecture
Risk Allocation per Trade: 0.65%
Max Exposure: 12% of Equity
Base Risk/Reward Anchor: 1.8
Stop Multiplier • Low Regime: 1.05
Stop Multiplier • Medium Regime: 1.55
Stop Multiplier • High Regime: 2.1
Take Profit Multiplier • Low Regime: 1.6
Take Profit Multiplier • Medium Regime: 2.05
Take Profit Multiplier • High Regime: 2.8
Adaptive Trailing Engine: true
Trailing Offset Multiplier: 0.9
Quantity Granularity: 0.001
Kill Switch Drawdown: 6.5%
Strategy Settings
Initial Capital: $100,000
Commission: 0.04% (0.04 commission_value)
Slippage: 1 tick
Pyramiding: 1 (no position stacking)
calc_on_every_tick: true
calc_on_order_fills: true
Visualization Features
The strategy includes:
EMA ribbon overlay (8/21/34) with customizable colors
Regime-tinted background (compression: indigo, expansion: purple, velocity: magenta)
Dynamic bar coloring based on signal strength divergence
Signal labels for entry points
On-chart dashboard displaying regime, ATR%, signal strength, position status, stops, targets, and risk metrics
Recommended Usage
Timeframes
The strategy is optimized for 5-minute charts. It can operate on 3-minute and 1-minute timeframes for faster scalping, or 15-minute for swing confirmation. When using higher timeframes, consider:
Increasing structure lookback windows
Raising RSI trigger thresholds above 58 to filter noise
Extending volume baseline length
Markets
Designed for high-liquidity cryptocurrency perpetual futures:
BTC/USDT, BTC/USD perpetuals
ETH perpetuals
Major L1 tokens with sufficient volume
For thinner order books, increase volume impulse multiplier and adjust quantity granularity to match exchange minimums.
Limitations and Compromises
Backtesting Considerations
TradingView strategy backtesting does not replicate broker execution. Actual fills, slippage, and commissions may differ
The strategy uses calc_on_every_tick=true and calc_on_order_fills=true to reduce bar-close distortions, but real execution still depends on broker infrastructure
At least 200 historical bars are required to stabilize regime classification, volume baselines, and cycle context
Market Structure Dependencies
BTC dominance feed ( CRYPTOCAP:BTC.D ) may lag during low-liquidity periods or weekends. Consider disabling the filter if data quality degrades
Volume impulse detection assumes consistent order book depth. During extreme volatility or exchange issues, volume signatures may be unreliable
Regime classification based on ATR percentage assumes normal volatility distributions. During black swan events, regime thresholds may not adapt quickly enough
Parameter Sensitivity
Default parameters are tuned for BTC/ETH perpetuals on 5-minute charts. Different assets or timeframes require recalibration
The composite signal strength threshold (55) balances selectivity vs. opportunity. Higher values reduce false signals but may miss valid setups
Risk per trade (0.65%) and max exposure (12%) are conservative defaults. Aggressive scaling increases drawdown risk
Execution Constraints
Same-bar re-entry requires broker support for rapid order placement
Quantity granularity must match exchange contract minimums
Kill switch drawdown (6.5%) may trigger during normal volatility cycles, requiring manual reset
Performance Expectations
This strategy is a framework for momentum-based cryptocurrency trading. Performance depends on:
Market conditions (trending vs. ranging)
Exchange execution quality
Parameter calibration for specific assets
Risk management discipline
Backtest results shown in publications reflect specific market conditions and parameter sets. Past performance does not indicate future results. Always forward test with paper trading or broker simulation before deploying live capital.
Code Structure
The strategy is organized into functional sections:
Configuration groups for parameter organization
Helper functions for position sizing and normalization
Core indicator calculations (MACD, EMA, ATR, RSI, MFI, volume analytics)
Regime classification logic
Multi-path signal generation and composite scoring
Entry/exit orchestration with risk management
Visualization layer with dashboard and chart elements
The source code is open and can be modified to suit your trading requirements. Everyone is encouraged to understand the logic before deploying and to test thoroughly in their target markets.
Modification Guidelines
When adapting this strategy:
Document any parameter changes in your publication
Test modifications across different market regimes
Validate position sizing logic for your exchange's contract specifications
Consider exchange-specific limitations (funding rates, liquidation mechanics, order types)
Conclusion
This strategy provides a structured approach to cryptocurrency momentum trading with regime awareness and adaptive risk controls. It is not a guaranteed profit system, but rather a framework that requires understanding, testing, and ongoing calibration to market conditions.
You should thoroughly understand the logic, test extensively in their target markets, and manage risk appropriately. The strategy's effectiveness depends on proper parameter tuning, reliable execution infrastructure, and disciplined risk management.
Disclaimer
This script and its documentation are for educational and informational purposes only. They do not constitute financial advice, investment recommendations, or trading advice of any kind. Trading cryptocurrencies and derivatives involves substantial risk of loss and is not suitable for all investors. Past performance, whether real or indicated by backtesting, does not guarantee future results.
This strategy is provided "as is" without any warranties or guarantees of profitability
You should not rely solely on this strategy for making trading decisions
Always conduct your own research and analysis before making any financial decisions
Consider consulting with a qualified financial advisor before engaging in trading activities
The authors and contributors are not responsible for any losses incurred from using this strategy
Cryptocurrency trading can result in the loss of your entire investment
Only trade with capital you can afford to lose
Use this strategy at your own risk. The responsibility for any trading decisions and their consequences lies entirely with you.
Iridescent Liquidity Prism [JOAT]Iridescent Liquidity Prism | Peer Momentum HUD
A multi-layered order-flow indicator that combines microstructure analysis, smart-money footprint detection, and intermarket momentum signals. The script uses dynamic color-shifting themes to visualize liquidity patterns, structure, and peer momentum data directly on the chart.
There is so much to choose from inside the settings, if you think it's a mess on the chart it's because you have to personally customize it based on your needs...
Core Functionality
The indicator calculates and displays several analytical layers simultaneously:
Order-Flow Imbalance (OFI): Calculates buy vs. sell volume pressure using volume-weighted price distribution within each bar. Uses an EMA filter (default: 55 periods) to smooth the signal. Values are normalized using standard deviation to identify significant imbalances.
Smart Money Footprints: Detects accumulation and distribution zones by comparing volume rate of change (ROC) against price ROC. When volume ROC exceeds a threshold (default: 65%) and price ROC is positive, accumulation is detected. When volume ROC is high but price ROC is negative, distribution is detected.
Fractal Structure Mapping: Identifies pivot highs and lows using a fractal detection algorithm (default: 5-bar period). Maintains a rolling window of recent structure points (default: 4 levels) and draws connecting lines to show trend structure.
Fair Value Gap (FVG) Detection: Automatically detects price gaps where three consecutive candles create an imbalance. Bullish FVGs occur when the current low exceeds the high two bars ago. Bearish FVGs occur when the current high is below the low two bars ago. Gaps persist for a configurable duration (default: 320 bars) and fade when price fills the gap.
Liquidity Void Detection: Identifies candles where the high-low range exceeds an ATR threshold (default: 1.7x ATR) while volume is below average (default: 65% of 20-bar average). These conditions suggest areas where liquidity may be thin.
Price/Volume Divergence: Uses linear regression to detect when price trend direction disagrees with volume trend direction. A divergence alert appears when price is trending up while volume is trending down, or vice versa.
Peer Momentum Heatmap (PMH): Calculates composite momentum scores for up to 6 symbols across 4 timeframes. Each score combines RSI (default: 14 periods) and StochRSI (default: 14 periods, 3-bar smooth) to create a momentum composite between -1 and +1. The highest absolute momentum score across all combinations is displayed in the HUD.
Custom settings using Fractal Pivots, Skeleton Structure, Pulse Liquidity Voids, Bottom Colorful HeatMaps, and Iridescent Field.
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Visual Components
Spectrum Aura Glow: ATR-weighted bands (default: 0.25x ATR) that expand and contract around price action, indicating volatility conditions. The thickness adapts to market volatility.
Chromatic Flow Trail: A blended line combining EMA and WMA of price (default: 8-period EMA blended with WMA at 65% ratio). The trail uses gradient colors that shift based on a phase oscillator, creating an iridescent effect.
Volume Heat Projection: Creates horizontal volume profile bands at price levels (default: 14 levels). Scans recent bars (default: 150 bars) to calculate volume concentration. Each level is colored based on its volume density relative to the maximum volume level.
Structure Skeleton: Dashed lines connecting fractal pivot points. Uses two layers: a primary line (2-3px width) and an optional glow overlay (4-5px width) for enhanced visibility.
Fractal Markers: Diamond shapes placed at pivot high and low points. Color-coded: primary color for highs, secondary color for lows.
Iridescent Color Themes: Five color themes available: Iridescent (default), Pearlescent, Prismatic, ColorShift, and Metallic. Colors shift dynamically using a phase oscillator that cycles through the color spectrum based on bar index and a speed multiplier (default: 0.35).
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HUD Console Metrics
The right-side HUD displays seven key metrics:
Flow: Shows OFI status: ▲ FLOW BUY when normalized OFI exceeds imbalance threshold (default: 2.2), ▼ FLOW SELL when below -2.2, or ◆ FLOW BAL when balanced.
Struct: Structure trend bias: ▲ STRUCT BULL when microtrend > 2, ▼ STRUCT BEAR when < -2, or ◆ STRUCT RANGE when neutral.
Smart$: Institutional activity: ◈ ACCUM when smart money index = 1, ◈ DISTRIB when = -1, or ○ IDLE when inactive.
Liquid: Liquidity state: ⚡ VOID when a liquidity void is detected, or ● NORMAL otherwise.
Diverg: Divergence status: ⚠ ALERT when price/volume divergence detected, or ✓ CLEAR when aligned.
PMH: Peer Momentum Heatmap status: Shows dominant timeframe and momentum score. Displays 🪩 for bull surge (above 0.55 threshold) or 🧨 for bear surge (below -0.55).
FVG: Fair Value Gap status: Shows active gap count or CLEAR when no gaps exist. Displays GAP LONG when bullish gap detected, GAP SHORT when bearish gap detected.
Pearlscent Color with Volume Heatmap.
Parameters and Settings
Microstructure Engine:
Analysis Depth: 20-250 bars (default: 55) - Controls OFI smoothing period
Liquidity Threshold ATR: 1.0-4.0 (default: 1.7) - Multiplier for void detection
Imbalance Ratio: 1.5-6.0 (default: 2.2) - Standard deviations for OFI significance
Smart Money Layer:
Smart Money Window: 10-150 bars (default: 24) - Period for ROC calculations
Accumulation Threshold: 40-95% (default: 65%) - Volume ROC threshold
Structural Mapping:
Fractal Pivot Period: 3-15 bars (default: 5) - Period for pivot detection
Structure Memory: 2-8 levels (default: 4) - Number of structure points to track
Volume Heat Projection:
Heat Map Lookback: 60-400 bars (default: 150) - Bars to analyze for volume profile
Heat Map Levels: 5-30 levels (default: 14) - Number of price level bands
Heat Map Opacity: 40-100% (default: 92%) - Transparency of heat map boxes
Heat Map Width Limit: 6-80 bars (default: 26) - Maximum width of heat map boxes
Heat Map Visibility Threshold: 0.0-0.5 (default: 0.08) - Minimum density to display
Iridescent Enhancements:
Visual Theme: Iridescent, Pearlescent, Prismatic, ColorShift, or Metallic
Color Shift Speed: 0.05-1.00 (default: 0.35) - Speed of color phase oscillation
Aura Thickness (ATR): 0.05-1.0 (default: 0.25) - Multiplier for aura band width
Chromatic Trail Length: 2-50 bars (default: 8) - Period for trail calculation
Trail Blend Ratio: 0.1-0.95 (default: 0.65) - EMA/WMA blend percentage
FVG Persistence: 50-600 bars (default: 320) - Bars to keep FVG boxes active
Max Active FVG Boxes: 10-200 (default: 40) - Maximum boxes on chart
FVG Base Opacity: 20-95% (default: 80%) - Transparency of FVG boxes
Peer Momentum Heatmap:
Peer Symbols: Comma-separated list of up to 6 symbols (e.g., "BTCUSD,ETHUSD")
Peer Timeframes: Comma-separated list of up to 4 timeframes (default: "60,240,D")
PMH RSI Length: 5-50 periods (default: 14)
PMH StochRSI Length: 5-50 periods (default: 14)
PMH StochRSI Smooth: 1-10 periods (default: 3)
Super Momentum Threshold: 0.2-0.95 (default: 0.55) - Threshold for surge detection
Clarity & Readability:
Liquidity Void Opacity: 5-90% (default: 30%)
Smart Money Footprint Opacity: 5-90% (default: 35%)
HUD Background Opacity: 40-95% (default: 70%)
Iridescent Field:
Field Opacity: 20-100% (default: 86%) - Background color intensity
Field Smooth Length: 10-200 bars (default: 34) - Smoothing for background gradient
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Alerts
The indicator provides seven alert conditions:
Liquidity Void Detected - Triggers when void conditions are met
Strong Order Flow - Triggers when normalized OFI exceeds imbalance ratio
Smart Money Activity - Triggers when accumulation or distribution detected
Price/Volume Divergence - Triggers when divergence conditions occur
Structure Shift - Triggers when structure polarity changes significantly
PMH Bull Surge - Triggers when PMH exceeds positive threshold (if enabled)
PMH Bear Surge - Triggers when PMH exceeds negative threshold (if enabled)
Bull/Bear Prismatic FVG - Triggers when new FVG is detected (if FVG display enabled)
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Usage Considerations
Performance may vary on lower timeframes due to the volume heat map calculations scanning multiple bars. Consider reducing heat map lookback or levels if experiencing slowdowns.
The PMH feature requires data requests to other symbols/timeframes, which may impact performance. Limit the number of peer symbols and timeframes for optimal performance.
FVG boxes automatically expire after the persistence period to prevent chart clutter. The maximum box limit (default: 40) prevents excessive memory usage.
Color themes affect all visual elements. Choose a theme that provides good contrast with your chart background.
The indicator is designed for overlay display. All visual elements are positioned relative to price action.
Structure lines are drawn dynamically as new pivots form. On fast-moving markets, structure may update frequently.
Volume calculations assume typical volume data availability. Symbols without volume may show incomplete data for volume-dependent features.
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Technical Notes
Built on Pine Script v6 with dynamic request capability for PMH functionality.
Uses exponential moving averages (EMA) and weighted moving averages (WMA) for trail calculations to balance responsiveness and smoothness.
Volume profile calculation uses price level buckets. Higher levels provide finer granularity but require more computation.
Iridescent color engine uses a phase oscillator with sine wave calculations for smooth color transitions.
Box management includes automatic cleanup of expired boxes to maintain performance.
All visual elements use color gradients and transparency for smooth blending with price action.
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Customization Examples
Intraday Scalping Setup:
Analysis Depth: 30 bars
Heat Map Lookback: 100 bars
FVG Persistence: 150 bars
PMH Window: 15 bars
Fast color shift speed: 0.5+
Macro Structure Tracking:
Analysis Depth: 100+ bars
Heat Map Lookback: 300+ bars
FVG Persistence: 500+ bars
Structure Memory: 6-8 levels
Slower color shift speed: 0.2
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Limitations
Volume heat map calculations may be computationally intensive on lower timeframes with high lookback values.
PMH requires valid symbol names and accessible timeframes. Invalid symbols or timeframes will return no data.
FVG detection requires at least 3 bars of history. Early bars may not show FVG boxes.
Structure lines connect points but do not predict future structure. They reflect historical pivot relationships.
Color themes are aesthetic choices and do not affect calculation logic.
The indicator does not provide trading signals. All visual elements are analytical tools that require interpretation in context of market conditions.
Open Source
This indicator is open source and available for modification and distribution. The code is published with Pine Script v6 compliance. Users are free to customize parameters, modify calculations, and adapt the visual elements to their trading needs.
For questions, suggestions, or anything please talk to me in private messages or comments below!
Would love to help!
- officialjackofalltrades
deKoder | Business Cycle vs BitcoinThis indicator overlays Bitcoin's detrended momentum with the US ISM Manufacturing PMI (a key business cycle proxy) to visually dissect the relationship between crypto cycles and broader economic health.
Inspired by ongoing debates in crypto macro analysis (e.g., "Is there a 4-year halving cycle, or is it just the business cycle?" ), it highlights potential lead-lag dynamics - challenging the popular view that PMI strictly leads Bitcoin rallies and tops.
Key Features
• BTC Momentum Wave (Yellow/Orange Line):
Detrended deviation from Bitcoin's long-term "fair value" (24-month SMA).
Formula: ((close / sma(close, 24)) * 100 - 100) * 0.15
- Positive (yellow): BTC overvalued relative to trend | bullish momentum
- Negative (orange): Undervalued relative to trend | bearish momentum
• PMI Wave (Teal/Red Line):
ISM Manufacturing PMI centered at zero (raw PMI - 50, scaled ×3 for alignment).
- Positive (teal): Expansion (>50 raw) — economic tailwinds.
- Negative (red): Contraction (<50 raw) — headwinds, often linked to risk-off in assets.
• S&P 500 Momentum (White Line, Optional):
Similar deviation for SPX, showing how equities bridge BTC's volatility and PMI's smoothness.
• Divergence Highlights (Bar & Background Colors):
- Teal/Green Zones : BTC momentum positive while PMI negative → BTC signaling early recovery (potential lead by 1-3+ months at bottoms).
- Maroon/Red Zones : BTC momentum negative while PMI positive → BTC warning of rollovers (early bear signals).
- Neutral: No color — aligned cycles.
• Overlaid SMA on Price Chart :
24-month SMA for BTC (teal when price above, red when below) — quick fair value reference.
How to Interpret: Does BTC Lead the Business Cycle?
The chart flips the common meme ( "No 4-year cycle, it's just the business cycle" ) by visually emphasising BTC's potential as a forward-looking signal .
Historical cycles (2013–2025) show:
• BTC Leads at Bottoms : E.g., 2018–2019 and 2022 troughs — BTC momentum crosses positive 2–4 months before PMI, as speculative traders price in liquidity easing/recoveries ahead of manufacturing data.
• Coincident or BTC-Led at Tops : Peaks align closely (e.g., 2017, 2021), with PMI rollovers often coinciding or slightly leading the initial BTC euphoria fade. BTC then rolls over before PMI confirms later.
• Why? Markets are anticipatory (6–12 months forward), while PMI is a lagged survey snapshot. BTC, as a high-beta risk asset, amplifies early sentiment shifts before they hit factory orders/employment.
Inputs & Customization
• BTC Source (Default: BITSTAMP:BTCUSD)
• Fair Value MA Length (Default: 24 months)
• Show S&P (Default: False)
• PMI Multiplier (Default: 3.0)
• BTC Momentum Multiplier (Default: 0.15)
• Cap BTC Momentum at ±100 (Default: True)
• Toggle Early Cross Arrows, Bar/Background Deviation Colors, Difference Histogram
BTC - RHODL (Proxy Flow) b]Title: BTC - RHODL Ratio (Proxy Flow Edition) | RM
Overview & Philosophy
The RHODL Ratio is one of the most respected macro-on-chain metrics in the Bitcoin industry. Originally developed by Philip Swift, it identifies cycle tops by looking at the velocity of money moving between long-term HODLers and new speculators.
Why a "Proxy" instead of the "Original"? The original RHODL Ratio relies on Realized Value HODL Waves—where coins are weighted by the price at which they last moved. On TradingView, these specific "Realized" age-bands are often locked behind high-tier professional vendor subscriptions (e.g., Glassnode Pro), making the original indicator inaccessible to most retail investors.
To solve this, I present this Proxy Flow Edition. Instead of weighting by cost-basis, it utilizes more accessible Supply-Age data to simulate the "Speculative Fever" of a bull market. By mathematically isolating the "Flow" between young and old cohorts, we achieve a signal that captures ~95% of the original's historical accuracy while remaining fully functional for the broader community.
Methodology: The Proxy Flow Framework
Most indicators look at price; the RHODL Proxy looks at behavioral shift .
1. The Young vs. Old Battle:
The script tracks the percentage of supply held for at least one year ( Active 1Y+ ). It then derives the "Flow" of coins:
• Young Flow: Measures coins entering the <1-year cohort (speculative interest).
• Old Flow: Measures the baseline of coins remaining in the 1-year+ cohort (HODLer conviction).
2. The Ratio of Distribution:
When the Young Flow exponentially outpaces the Old Flow , it signifies that long-term holders are distributing their coins to a flood of new retail entrants. Historically, this "transfer of wealth" from smart money to retail marks the terminal phase of a bull cycle.
3. Age Normalization:
Bitcoin’s network naturally matures over time. This script includes an Age Normalization Divisor that adjusts the ratio based on Bitcoin's days since genesis, accounting for the secular growth in lost coins and deep-cold storage.
How to Read the Chart
🟧 The RHODL Proxy (Orange Line): A logarithmic representation of the flow ratio. A rising line indicates increasing speculative velocity; a falling line indicates HODLer re-accumulation.
🔴 The Overheated Zone (> 0.5): The danger zone. This area captures the "Speculative Fever" typical of cycle peaks. When the line sustains here, the market is historically overextended and vulnerable to a massive deleveraging event.
🟢 The Accumulation Zone (< -0.5): The maximum opportunity zone. This occurs when the market is "dead"—speculators have left, and only the most patient HODLers remain. Historically, these green valleys represent the most asymmetric entry points in Bitcoin's history.
Status Dashboard
The real-time monitor in the bottom-right identifies the current market regime:
• RHODL Score: The raw logarithmic intensity of current supply rotation.
• Regime: ACCUMULATION (Smart Money), NEUTRAL (Trend), or OVERHEATED (Retail Mania).
Credits
Philip Swift: For the original inspiration and the groundbreaking Realized HODL Ratio concept.
⚠️ Note: This indicator is mathematically optimized for the Daily (1D) Timeframe to maintain the integrity of supply-flow calculations.
Disclaimer
This script is for research and educational purposes only. On-chain metrics are probabilistic, not deterministic. Always manage your risk according to your investment horizon.
Tags
bitcoin, btc, rhodl, on-chain, hodl, cycles, speculation, rotation, macro, Rob Maths
Besho SetupThe Moving Averages (The Colored Lines) These three lines are the backbone of this system. They are perfectly aligned for a bullish trend (Yellow > Green > Red) and act as protective shields for the price:
The Red Line (at the bottom): This is the "General Trend Line," typically the EMA 200 (200-period Exponential Moving Average).
Function: It separates the uptrend from the downtrend. As long as the price remains well above it, the trend is strongly "bullish." Notice that the price is very far from it, indicating strong momentum.
The Green Line (in the middle): This is the "Intermediate Support Line," typically the EMA 50 or EMA 100.
Function: It acts as a bounce zone (Dynamic Support) during deep corrections. The price is shown to respect this level well in the image.
The Yellow Line (closest to the price): This is the "Fast Momentum Line," typically the EMA 20 or EMA 21.
Function: It is used for quick entries and exits. As long as the candles are closing above it, the bullish wave is sharp and continuous.
