Elliott Wave Full Fractal System v2.0Elliott Wave Full Fractal System v2.0 – Q.C. FINAL (Guaranteed R/R)
Elliott Wave Full Fractal System is a multi-timeframe wave engine that automatically labels Elliott impulses and ABC corrections, then builds a rule-based, ATR-driven risk/reward framework around the “W3–W4–W5” leg.
“Guaranteed R/R” here means every order is placed with a predefined stop-loss and take-profit that respect a minimum Reward:Risk ratio – it does not mean guaranteed profits.
Core Idea
This strategy turns a full fractal Elliott Wave labelling engine into a systematic trading model.
It scans fractal pivots on three wave degrees (Primary, Intermediate, Minor) to detect 5-wave impulses and ABC corrections.
A separate “Trading Degree” pivot stream, filtered by a 200-EMA trend filter and ATR-based dynamic pivots, is then used to find W4 pullback entries with a minimum, user-defined Reward:Risk ratio.
Default Properties & Risk Assumptions
The backtest uses realistic but conservative defaults:
// Default properties used for backtesting
strategy(
"Elliott Wave Full Fractal System - Q.C. FINAL (Guaranteed R/R)",
overlay = true,
initial_capital = 10000, // realistic account size
default_qty_type = strategy.percent_of_equity,
default_qty_value = 1, // 1% risk per trade
commission_type = strategy.commission.cash_per_contract,
commission_value = 0.005, // example stock commission
slippage = 0 // see notes below
)
Account size: 10,000 (can be changed to match your own account).
Position sizing: 1% of equity per trade to keep risk per idea sustainable and aligned with TradingView’s recommendations.
Commission: 0.005 cash per contract/share as a realistic example for stock trading.
Slippage: set to 0 in code for clarity of “pure logic” backtesting. Real-life trading will experience slippage, so users should adjust this according to their market and broker.
Always re-run the backtest after changing any of these values, and avoid using high risk fractions (5–10%+) as that is rarely sustainable.
1. Full Fractal Wave Engine
The script builds and maintains four pivot streams using ATR-adaptive fractals:
Primary Degree (Macro Trend):
Captures the large swings that define the major trend. Labels ①–⑤ and ⒶⒷⒸ using blue “Circle” labels and thicker lines.
Intermediate Degree (Trading Degree):
Captures the medium swings (swing-trading horizon). Uses teal labels ( (1)…(5), (A)(B)(C) ).
Minor Degree (Micro Structure):
Tracks short-term swings inside the larger waves. Uses red roman numerals (i…v, a b c).
ABC Corrections (Optional):
When enabled, the engine tries to detect standard A–B–C corrective structures that follow a completed 5-wave impulse and plots them with dashed lines.
Each degree uses a dynamic pivot lookback that expands when ATR is above its EMA, so the system naturally requires “stronger” pivots in volatile environments and reacts faster in quiet conditions.
2. Theory Rules & Strict Mode
Normal Mode: More permissive detection. Designed to show more wave structures for educational / exploratory use.
Strict Mode: Enforces key Elliott constraints:
Wave 3 not shorter than waves 1 and 5.
No invalid W4 overlap with W1 (for standard impulses).
ABC Logic: After a confirmed bullish impulse, the script expects a down-up-down corrective pattern (A,B,C). After a bearish impulse, it looks for up-down-up.
3. Trend Filter & Pivots
EMA Trend Filter: A configurable EMA (default 200) is used as a non-wave trend filter.
Price above EMA → Only long setups are considered.
Price below EMA → Only short setups are considered.
ATR-Adaptive Pivots: The pivot engine scales its left/right bars based on current ATR vs ATR EMA, making waves and trading pivots more robust in volatile regimes.
4. Dynamic Risk Management (Guaranteed R/R Engine)
The trading engine is designed around risk, not just pattern recognition:
ATR-Based Stop:
Stop-loss is placed at:
Entry ± ATR × Multiplier (user-configurable, default 2.0).
This anchors risk to current volatility.
Minimum Reward:Risk Ratio:
For each setup, the script:
Computes the distance from entry to stop (risk).
Projects a take-profit target at risk × min_rr_ratio away from entry.
Only accepts the setup if risk is positive and the required R:R ratio is achievable.
Result: Every order is created with both TP and SL at a predefined distance, so each trade starts with a known, minimum Reward:Risk profile by design.
“Guaranteed R/R” refers exclusively to this order placement logic (TP/SL geometry), not to win-rate or profitability.
5. Trading Logic – W3–W4–W5 Pattern
The Trading pivot stream (separate from visual wave degrees) looks for a simple but powerful pattern:
Bullish structure:
Sequence of pivots forms a higher-high / higher-low pattern.
Price is above the EMA trend filter.
A strong “W3” leg is confirmed with structure rules (optionally stricter in Strict mode).
Entry (Long – W4 Pullback):
The “height” of W3 is measured.
Entry is placed at a configurable Fibonacci pullback (default 50%) inside that leg.
ATR-based stop is placed below entry.
Take-profit is projected to satisfy min Reward:Risk.
Bearish structure:
Mirrored logic (lower highs/lows, price below EMA, W3 down, W4 retrace up, W5 continuation down).
Once a valid setup is found, the script draws a colored box around the entry zone and a label describing the type of signal (“LONG SETUP” or “SHORT SETUP”) with the suggested limit price.
6. Orders & Execution
Entry Orders: The strategy uses limit orders at the computed W4 level (“Sniper Long” or “Sniper Short”).
Exits: A single strategy.exit() is attached to each entry with:
Take-profit at the projected minimum R:R target.
Stop-loss at ATR-based level.
One Trade at a Time: New setups are only used when there is no open position (strategy.opentrades == 0) to keep the logic clear and risk contained.
7. Visual Guide on the Chart
Wave Labels:
Primary: ①,②,③,④,⑤, ⒶⒷⒸ
Intermediate: (1)…(5), (A)(B)(C)
Minor: i…v, a b c
Trend EMA: Single blue EMA showing the dominant trend.
Setup Boxes:
Green transparent box → long entry zone.
Red transparent box → short entry zone.
Labels: “LONG SETUP / SHORT SETUP” labels mark the proposed limit entry with price.
8. How to Use This Strategy
Attach the strategy to your chart
Choose your market (stocks, indices, FX, crypto, futures, etc.) and timeframe (for example 1h, 4h, or Daily). Then add the strategy to the chart from your Scripts list.
Start with the default settings
Leave all inputs on their defaults first. This lets you see the “intended” behaviour and the exact properties used for the published backtest (account size, 1% risk, commission, etc.).
Study the wave map
Zoom in and out and look at the three wave degrees:
Blue circles → Primary degree (big picture trend).
Teal (1)…(5) → Intermediate degree (swing structure).
Red i…v → Minor degree (micro waves).
Use this to understand how the engine is interpreting the Elliott structure on your symbol.
Watch for valid setups
Look for the coloured boxes and labels:
Green box + “LONG SETUP” label → potential W4 pullback long in an uptrend.
Red box + “SHORT SETUP” label → potential W4 pullback short in a downtrend.
Only trades in the direction of the EMA trend filter are allowed by the strategy.
Check the Reward:Risk of each idea
For each setup, inspect:
Limit entry price.
ATR-based stop level.
Projected take-profit level.
Make sure the minimum Reward:Risk ratio matches your own rules before you consider trading it.
Backtest and evaluate
Open the Strategy Tester:
Verify you have a decent sample size (ideally 100+ trades).
Check drawdowns, average trade, win-rate and R:R distribution.
Change markets and timeframes to see where the logic behaves best.
Adapt to your own risk profile
If you plan to use it live:
Set Initial Capital to your real account size.
Adjust default_qty_value to a risk level you are comfortable with (often 0.5–2% per trade).
Set commission and slippage to realistic broker values.
Re-run the backtest after every major change.
Use as a framework, not a signal machine
Treat this as a structured Elliott/R:R framework:
Filter signals by higher-timeframe trend, major S/R, volume, or fundamentals.
Optionally hide some wave degrees or ABC labels if you want a cleaner chart.
Combine the system’s structure with your own trade management and discretion.
Best Practices & Limitations
This is an approximate Elliott Wave engine based on fractal pivots. It does not replace a full discretionary Elliott analysis.
All wave counts are algorithmic and can differ from a manual analyst’s interpretation.
Like any backtest, results depend heavily on:
Symbol and timeframe.
Sample size (more trades are better).
Realistic commission/slippage settings.
The 0-slippage default is chosen only to show the “raw logic”. In real markets, slippage can significantly impact performance.
No strategy wins all the time. Losing streaks and drawdowns will still occur even with a strict R:R framework.
Disclaimer
This script is for educational and research purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance, whether real or simulated, is not indicative of future results. Always test on multiple symbols/timeframes, use conservative risk, and consult your financial advisor before trading live capital.
Cycleanalysis
RSI cyclic smoothed ProCyclic Smoothed Relative Strength Indicator - Pro Version
The cyclic smoothed RSI indicator is an enhancement of the classic RSI, adding
additional smoothing according to the market vibration,
adaptive upper and lower bands according to the cyclic memory and
using the current dominant cycle length as input for the indicator.
The cRSI is used like a standard indicator. The chart highlights trading signals where the signal line crosses above or below the adaptive lower/upper bands. It is much more responsive to market moves than the basic RSI.
The indicator uses the dominant cycle as input to optimize signal, smoothing and cyclic memory. To get more in-depth information on the cyclic-smoothed RSI indicator, please read Chapter 4 "Fine tuning technical indicators" of the book "Decoding the Hidden Market Rhythm, Part 1" available at your favorite book store.
Info: Pro Version
This is the actively maintained and continuously enhanced edition of my free, open-source indicator “RSI Cyclic Smoothed v2” which was recognized with a TradingView Editors’ Pick. The Pro Version will remain fully up to date with the latest Pine Script standards and will receive ongoing refinements and feature improvements, all while preserving the core logic and intent of the original tool. The legacy version will continue to be available for code review and educational purposes, but it will no longer receive updates. The legacy open-source version is here
Pro Features V1:
1) Leveraging multi-timeframe analysis
Indicator can be used on one chart by using different time frames at the same time. Read more on TradingView here .
2) Scoring feature added for scanning and filtering
This indicator now provides four distinct scoring states for both bullish and bearish conditions, making it fully compatible with the TradingView Screener .
Each score reflects a specific market phase based on RSI behavior, slope, and crossover signals.
Bullish States (Positive Scores)
+1 – Bull Exhaustion: Price is above the upper threshold and still rising (upsloping).
+2 – Bull Fatigue: Price is above the upper threshold but losing momentum (downsloping).
+3 – Bull Exit: A fresh downward crossover has occurred.
+4 – Recent Bull Exit: A downward crossover occurred within the recent lookback window.
Bearish States (Negative Scores)
–1 – Bear Exhaustion: Price is below the lower threshold and still declining (downsloping).
–2 – Bear Fatigue: Price is below the lower threshold but starting to turn upward (upsloping).
–3 – Bear Exit: A fresh upward crossover has occurred.
–4 – Recent Bear Exit: An upward crossover occurred within the recent lookback window.
The scoring states are shown in the indicator status panel when plotting the indicator on the chart. For a Screener run, use a generic cycle length setting.
How to determine the current active cycle length?
You can use the following additional tools to fine-tune the current dominant cycle length:
1. The advanced dyanmic Cycle Spectrum Scanner
2. The free Detremded Market Rhythm Oscillator
Skrip berbayar
Cycle Spectrum AnalyzerCycle Spectrum Indicator — Short Description
This indicator computes a visual Fourier cycle spectrum from the input price data to reveal the market’s dominant cyclical behaviour. The price series is first detrended using a Hodrick–Prescott filter, after which a specialized Fourier analysis variant extracts the cycle components.
The resulting spectrum displays peaks that represent the dominant cycles present in the data, where each peak’s cycle length and amplitude indicate the strength and duration of the underlying rhythm. The most significant peaks are ranked, highlighting the top cycles currently driving market movement. Each detected cycle also includes a phase value, describing the cycle’s position at the most recent bar (e.g., topping, bottoming, rising, falling).
The indicator can be used to:
Identify the top 3 dominant cycles with their length and phase.
Analyze the current market state by interpreting these phases.
Feed the dominant cycle lengths—often half the primary cycle—into other technical indicators for improved parameter tuning.
Project cycles forward to estimate upcoming turning points and anticipate potential trend shifts.
Additional Explanation of the included visual example image
Left Area – The Theoretical “Perfect Cycle”
The left part of the illustration presents a theoretical, perfectly smooth sine-wave cycle. This serves as a reference model to explain the core cycle parameters:
Cycle Length – The full wavelength of one complete oscillation (from trough to trough or peak to peak).
Phase – The current position within that cycle, expressed both numerically and as an easy-to-read text label such as Bottom_Departure, Uptrend_Neutral, Approaching Top, or Top_Departure.
The diagram highlights visually how a cycle progresses through bottoming, rising, peaking, and declining phases, matching the phase descriptions used in the indicator’s output. This helps translate raw phase angles into intuitive market-state labels (e.g., recovery, boom, topping, recession).
Right Area – The Price Series Used for Analysis
On the right, the actual price chart (e.g., Dow Jones Industrial Average) is displayed. This is the dataset from which the Fourier cycle spectrum is computed.
At the bottom of this chart section, a purple bar indicates the amount of historical data included in the cycle analysis. Because Fourier-based methods depend strongly on sample size, this visual cue shows how far back the indicator collected and processed data before generating the spectrum.
Bottom Area – The Cycle Spectrum Output Pane
The lower pane contains the Cycle Spectrum Analyzer output:
It displays the cycle spectrum at the most recent bar, where each green peak corresponds to a detected cycle.
Peak height = amplitude (strength) of the cycle
Peak position (horizontal) = dominant cycle length
The largest peaks represent the strongest cycles currently present in the detrended price series.
Next to the spectrum, a ranked table lists the Top 3 dominant cycles, showing:
Rank (1 = strongest)
Cycle Length (in bars)
Phase Description (interpreting where that cycle is right now)
This concise summary allows users to quickly understand:
Which cycles are strongest,
How long they are,
And whether they are currently bottoming, topping, rising, or falling.
How the Indicator Works & How It Can Be Adjusted
Calculation Only at the Last Bar
The indicator performs its full Fourier-based cycle decomposition exclusively on the most recent bar. This ensures that the spectrum always reflects the current market state without repeatedly recalculating historical spectra. The result is an efficient, real-time snapshot of the dominant cycles influencing the price at the latest point in time.
Works on Any Symbol and Any Timeframe
Because the analysis operates directly on the provided price series, the indicator is compatible with all markets and all timeframes—stocks, indices, forex, crypto, futures, and intraday charts alike.
The detected cycle lengths always refer to the selected chart’s bar interval (e.g., 240-bar cycle on a 1h chart ≈ 240 hours; same cycle on a daily chart ≈ 240 days).
Adjustable Historical Lookback (Default: 1100 Bars)
The accuracy of cycle detection depends on the amount of historical data used. The indicator provides a parameter allowing you to specify how many past bars should be included in the Fourier calculation.
Standard value: 1100 bars
Increasing the lookback allows detection of longer cycles, but may dilute short-term characteristics.
Decreasing it focuses on shorter and medium-term cycles, increasing responsiveness but reducing visibility of long-duration rhythms.
By tuning this lookback parameter and choosing an appropriate timeframe, traders can adapt the cycle spectrum to match their analytical style—short-term, medium-term, or long-term cycle interpretation.
Skrip berbayar
Blockchain Fundamentals: PPT [CR]Blockchain Fundamentals: PPT
A proprietary market positioning indicator that analyzes price behavior using percentile-based statistical methods. The PPT (Percentile Position Transform) provides a normalized oscillator view of market conditions, helping traders identify potential trend exhaustion and reversal zones through multi-timeframe statistical analysis.
█ FEATURES
Dual Signal Lines
The indicator plots two distinct signals:
- White Line — Primary signal representing the normalized, smoothed market position. This is the main signal used for trading decisions.
- Red Line — Raw statistical measurement before final normalization. Useful for identifying divergences and signal development.
Background Coloring
Dynamic background colors provide at-a-glance market context:
- Green Background — Indicates bullish positioning when the primary signal exceeds the buffer threshold.
- Red Background — Indicates bearish positioning when the primary signal falls below the buffer threshold.
- Gray Background — Neutral zone where no clear directional bias is present.
Flip Buffer
An adjustable threshold system designed to reduce noise and false signals:
- Enable Flip Buffer — Toggle the buffer system on or off.
- Buffer Size — Adjustable threshold level (default -0.1) that determines when background colors change. Higher values reduce sensitivity; lower values increase responsiveness.
Reference Levels
Three horizontal reference lines provide context:
- Center line at 0 — Neutral market position.
- Upper dashed line at +1 — Extreme bullish positioning threshold.
- Lower dashed line at -1 — Extreme bearish positioning threshold.
█ HOW TO USE
Signal Interpretation
The indicator operates as a mean-reversion oscillator within a normalized range:
1 — Values approaching +1 suggest extended bullish conditions where price may be overextended relative to recent history.
2 — Values approaching -1 suggest extended bearish conditions where price may be oversold relative to recent history.
3 — Crosses of the center line (0) indicate shifts in the underlying statistical trend.
Trading Applications
While specific trading strategies will vary by individual approach and market conditions:
- Consider the extremes (+1 and -1 levels) as potential areas of interest for mean-reversion setups.
- Background color changes can help identify when market positioning shifts from one regime to another.
- Divergences between the white and red lines may provide early warning of potential trend changes.
- The buffer zone (gray background) represents areas where market positioning is relatively neutral.
█ LIMITATIONS
- The indicator requires sufficient historical data to function properly. In assets with limited price history, the statistical measurements may be less reliable during early data periods.
- As a percentile-based system, the indicator is relative to recent history. Changing market regimes may require interpretation adjustments.
- Not designed for high-frequency or scalping strategies due to its daily data dependency.
- Background colors are visual aids and should not be used as standalone trading signals without additional confirmation.
█ NOTES
This indicator is part of the Blockchain Fundamentals suite and represents proprietary research into statistical market positioning analysis.
Users should experiment with the buffer settings to match their risk tolerance and trading style. More conservative traders may prefer larger buffer values to reduce signal frequency, while active traders might benefit from smaller buffers that provide earlier warnings.
Trend Catcher - Alpha v2 - by Crypto_Dan_CroIf you want to get this indicator, contact me on
X handle: @crypto_dan_cro
What is Trend Catcher v2?
This is the only indicator you need ;)
This indicator is a proprietary market analysis system designed to identify high-probability trading zones by synchronizing multiple layers of market structure, momentum behaviour and cyclical dynamics.
It dynamically adapts to changing market conditions by evaluating:
- macro trend alignment
- structural price positioning
- momentum acceleration & deceleration
- volatility-based reaction zones
- cycle maturity levels
The system filters out low-quality setups and highlights only areas where multiple hidden conditions align, providing:
- trend continuation signals
- structural shift detection
- cycle-based expansion targets
- adaptive support & resistance mapping
Rather than reacting to price alone, the indicator anticipates areas where market psychology historically shifts, allowing traders to position themselves ahead of major moves.
Core philosophy:
This tool does not attempt to predict the market — it tracks the underlying pressure points where probability favours expansion or exhaustion.
It functions as:
- a trend alignment engine
- a cycle decoder
- a volatility interpreter
- a structure validation system
What it gives the user:
- Clear visual guidance without overloading the chart
- Objective market context independent of emotion
- Early trend recognition
- Cycle-aware price targeting
- Decision zones instead of random entries
Ideal for:
- traders who trade structure, not noise
- investors who respect market cycles
- strategists focused on probability over prediction
- disciplined entries & exits
In short:
It is a market interpretation framework built for traders who think two steps ahead.
Contains:
1. Higher Timeframe mode (Monthly / Weekly) on all timeframes
2. Current Chart Timeframe mode
3. Global Trend via BTC MACD
4. SMA
5. EMA
6. BO (Break Out), BD (Break Down) signals
7. TOP & BOTTOM Detection
8. Support & Resistance Zones
9. RSI confirmation
10. Smart Info Panel (Global trend, MACD, SMA, EMA, RSI statuses - Bull, Bear, Neutral)
11. Monthly timeframe (Fibbonaci Retracement levels)
12. Monthly timeframe (all Cycle tops, and Cycle bottoms)
Crypto markets are volatile, if you choose to use this indicator for trading, you are doing it on your own. Crypto_dan_cro is not responsible for any profits or losses created by using this Indicator.
Pi Cycle BTC Top + Pre-Alert BandsPi Cycle BTC Top + Pre-Alert Bands is an advanced implementation of the classic Pi Cycle Top model, designed for Bitcoin cycle analysis on higher timeframes (especially 1D BTCUSD/BTCUSD·INDEX).
The original Pi Cycle Top uses two moving averages:
• 111-day SMA (short MA)
• 350-day SMA ×2 (long MA)
A Pi Top is signaled when the 111 SMA crosses above the 350×2 SMA. Historically, this has occurred near major BTC cycle highs.
This script extends that idea with a 3-step early-warning sequence:
• Pi Green – early compression: short/long MA ratio crosses upward into the green band (convergence from below is required).
• Pi Yellow – mid-cycle warning: only fires if a valid Green has already occurred in the same cycle.
• Pi Cycle Top – final top: the classic Pi Cycle cross, limited to one top signal per cycle. After a top, no new Yellow or Top signals can appear until a new Green event starts the next cycle.
Background shading shows the active phase (Green / Yellow / late-cycle zone), so you can see at a glance where BTC is within its Pi-based macro structure.
All logic is non-repainting: request.security() uses lookahead_off and no future data is accessed.
Typical use
This indicator is intended as a macro-cycle timing and risk-awareness tool, not a stand-alone entry system. Many traders use it to:
• Watch for Pi Green as the start of a potential late-cycle advance.
• Treat Pi Yellow as a rising-risk environment and tighten risk management.
• Use the Pi Cycle Top as a historical high-risk zone where large profit-taking or hedging may be considered.
Always combine this with your own analysis (trend, volume, on-chain, macro) before making decisions.
How to set alerts
Add the indicator to your chart (1D BTCUSD or BTCUSD·INDEX recommended).
Click Alerts → Condition → Pi Cycle BTC Top + Pre-Alert Bands.
Choose one of:
• Pi Cycle – Green Pre-Alert (early convergence)
• Pi Cycle – Yellow Pre-Alert (after Green only)
• Pi Cycle – TOP (Single per Cycle, after Green)
Use “Once per bar close” for higher-timeframe reliability.
Disclaimer
This tool is for educational and analytical purposes only. The Pi Cycle concept is based on historical behavior and does not guarantee future results. This is not financial advice; always do your own research and manage risk appropriately.
Gann Square of 144 (Master Price & Time)🔹 What this tool does
Draws a 144-unit square in price & time (0 → 144)
Plots all key horizontal & vertical levels:
0, 18, 36, 48, 54, 72, 90, 96, 108, 126, 144
Highlights the main 1/2 level (72) as thick midline
Marks 1/3 and 2/3 (48 & 96) as special harmonic levels
Draws internal diagonals (0–144, 144–0 and sub-squares)
Plots an 8-ray Gann fan from the 0-point (0 → 36 / 72 / 108 / 144 etc.)
Keeps price–time ratio consistent inside the box:
the 1×1 angle has a fixed slope = price_per_bar
The idea: once the square is calibrated to a major swing, you can study how price respects these angles and harmonic zones over time.
🔧 Inputs & how to set it up correctly
Choose your timeframe
Works best on Daily and Weekly charts.
Use one timeframe consistently when calibrating the square.
Start offset (bars back)
Start offset (bars back) shifts the whole square left/right.
Increase the value to move the square further into the past, decrease it to move it closer to the current bars.
Box width (bars)
Box width (bars) = how many bars the square spans horizontally.
Bigger value = projects the structure further into the future.
Example: 288 bars ≈ 2×144 units in time, 720 bars for longer-term projection, etc.
Bottom price
Bottom price is your 0-level in price.
Usually set this to a major swing low (cycle low, bear market low, important pivot).
The bottom-left corner of the square conceptually sits at:
(start_offset_bar, bottom_price)
Price per bar (slope 1×1) (if your version has this input)
This defines the slope of the 1×1 angle (main Gann angle).
Recommended way to set it:
Pick a major impulsive move from Swing Low → Swing High.
Measure:
Price range = High − Low
Number of bars between them.
Compute:
price_per_bar = price_range / number_of_bars
Use that as your 1×1 value in the input.
Now the main diagonal from 0 to 144 represents the true Gann 1×1 for that swing.
Important: The 1×1 angle is mathematically correct (price-per-bar), even if it does not always look like a perfect 45° line visually in TradingView due to chart scaling.
📖 How to read the Square of 144
Horizontal levels
0 = anchor price (bottom)
18, 36, 48, 54, 72, 90, 96, 108, 126, 144 = key price harmonics
72 (1/2) often acts as major support/resistance
48 & 96 (1/3 and 2/3) are strong “vibration” levels
Vertical levels
Same units but in time (bars).
When important pivots in price occur near these verticals, you get time–price confluence.
Midlines (1/2)
The thick horizontal and vertical lines at 72 mark the center of the square.
Crossings around these often signal important cycle turns.
1/3 & 2/3 zones (48–54 and 90–96)
These narrow bands are powerful reversal / decision zones.
Price often reacts strongly there or accelerates if they break.
Gann fan from 0-point
These rays represent major trends:
1×1 equivalent (main diagonal)
Faster & slower angles (e.g. 2×1, 1×2, etc depending on configuration)
If price breaks one fan angle cleanly, it often “falls” or “climbs” toward the next one.
🎯 Practical use cases
Project future support/resistance zones based on a major low.
See where price is in the square: early in the cycle (0–36), mid (around 72), or late (108–144).
Watch how price respects:
midlines (72),
1/3 and 2/3 bands (48–54, 90–96),
and the fan angles from 0.
Combine with your own price action / Fibonacci / trend tools – this is not a signal generator, but a time–price map.
⚠️ Notes & limitations
This tool is for educational & analytical purposes only.
It does not generate buy/sell signals.
Visual 45° angles in TradingView can change when you zoom or rescale the chart.
→ The script keeps the internal price-per-bar logic stable, even if the drawing looks steeper/flatter when zooming.
Always confirm zones with price action, volume, and higher timeframe context.
Gann Dynamic Levels [SmartFoxy]# 🌌 Gann Dynamic Levels
Gann Dynamic Levels is a dynamic Gann-based framework that calculates proportional and exponential levels using customizable methods — including planetary ratios.
Perfect for traders focused on cycles , ratios , and harmonic structures .
Inspired by the geometric and harmonic principles of W.D. Gann , this multifunctional tool automatically plots time–price projection levels based on user-defined anchor points.
It combines multiple calculation techniques to capture both linear and exponentia l market symmetries.
The indicator adapts dynamically to price movement, helping traders identify potential reversal zones , time clusters , and harmonic expansions derived from proportional and planetary relationships.
---
## ⚙️ Core Features
Five Calculation Methods — Linear, ratio-based, geometric, and exponential spacing for multi-perspective analysis.
Planetary Scaling Mode — Optional mode based on astronomical distances (Titius–Bode Law), adding an astronomical dimension to level spacing.
Adaptive Offset Control — Shifts all projected levels left or right proportionally without changing their internal spacing.
Automatic Label Management — Dynamically updates or reuses labels for better clarity and improved chart performance.
Custom Styling — Full control over colors, widths, label positions, and line styles for each method.
---
## 🌐 Purpose
Designed for traders who combine Gann theory , harmonic ratios , and cyclical timing to visualize equilibrium zones and future market symmetry.
Whether used for short-term timing or long-term structural projections, Gann Dynamic Levels provides an adaptive, geometry-based framework for interpreting market behavior.
---
## 📘 How to Use
When first applied, the indicator prompts you to place two points on the chart — for example, at the start and end of a significant price range.
The indicator calculates the number of bars between these two points, known as Delta .
Delta serves as the base unit for all calculations in Methods #1–#5 .
The computed results are displayed in Table 1 , which can be toggled using the parameter “📱 Show Gann Levels Table”.
You can reset or reposition the initial points in two ways:
Drag the existing points to new positions on the chart.
Hover over the indicator name, click ⦁⦁⦁ (More) → select “ Reset Points ”, then set new reference points.
---
## ⚙️ Method Logic
Classic – Evenly spaced levels based on the base Delta value. Ideal for identifying key support and resistance zones.
Coefficient (Coeff) – Scales Delta by fractional or whole-number coefficients for proportional level spacing.
Rounded – Rounds each calculated level to the nearest significant price value to align with major zones.
Subtractive – Generates levels by subtracting multiples of Delta from a reference point, emphasizing retracement-type structures.
Exponential – Applies an exponential growth model (10a = 4 + 3×2ⁿ) to project dynamic, non-linear level expansion.
Planetary – Uses the average distances of planets from the Sun (in Astronomical Units, AU ) as ratio multipliers to create harmonic projections.
Planetary distances can be customized in the user settings.
Data for Method #6 (Planetary) is displayed in Table 2 , toggled via “ 🪐 Show Planetary Table. ”
---
## ➡️ Additional Feature
Offset – Shifts all Gann levels horizontally (left or right) without changing their spacing.
Useful for visually aligning levels with key market structures.
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### 🧭 Summary
A multi-method Gann framework combining geometric, harmonic, and planetary ratios for dynamic level projection and cycle analysis.
Market Regime IndexThe Market Regime Index is a top-down macro regime nowcasting tool that offers a consolidated view of the market’s risk appetite. It tracks 32 of the world’s most influential markets across asset classes to determine investor sentiment by applying trend-following signals to each independent asset. It features adjustable parameters and a built-in alert system that notifies investors when conditions transition between Risk-On and Risk-Off regimes. The selected markets are grouped into equities (7), fixed income (9), currencies (7), commodities (5), and derivatives (4):
Equities = S&P 500 E-mini Index Futures, Nasdaq-100 E-mini Index Futures, Russell 2000 E-mini Index Futures, STOXX Europe 600 Index Futures, Nikkei 225 Index Futures, MSCI Emerging Markets Index Futures, and S&P 500 High Beta (SPHB)/Low Beta (SPLV) Ratio.
Fixed Income = US 10Y Treasury Yield, US 2Y Treasury Yield, US 10Y-02Y Yield Spread, German 10Y Bund Yield, UK 10Y Gilt Yield, US 10Y Breakeven Inflation Rate, US 10Y TIPS Yield, US High Yield Option-Adjusted Spread, and US Corporate Option-Adjusted Spread.
Currencies = US Dollar Index (DXY), Australian Dollar/US Dollar, Euro/US Dollar, Chinese Yuan/US Dollar, Pound Sterling/US Dollar, Japanese Yen/US Dollar, and Bitcoin/US Dollar.
Commodities = ICE Brent Crude Oil Futures, COMEX Gold Futures, COMEX Silver Futures, COMEX Copper Futures, and S&P Goldman Sachs Commodity Index (GSCI) Futures.
Derivatives = CBOE S&P 500 Volatility Index (VIX), ICE US Bond Market Volatility Index (MOVE), CBOE 3M Implied Correlation Index, and CBOE VIX Volatility Index (VVIX)/VIX.
All assets are directionally aligned with their historical correlation to the S&P 500. Each asset contributes equally based on its individual bullish or bearish signal. The overall market regime is calculated as the difference between the number of Risk-On and Risk-Off signals divided by the total number of assets, displayed as the percentage of markets confirming each regime. Green indicates Risk-On and occurs when the number of Risk-On signals exceeds Risk-Off signals, while red indicates Risk-Off and occurs when the number of Risk-Off signals exceeds Risk-On signals.
Bullish Signal = (Fast MA – Slow MA) > (ATR × ATR Margin)
Bearish Signal = (Fast MA – Slow MA) < –(ATR × ATR Margin)
Market Regime = (Risk-On signals – Risk-Off signals) ÷ Total assets
This indicator is designed with flexibility in mind, allowing users to include or exclude individual assets that contribute to the market regime and adjust the input parameters used for trend signal detection. These parameters apply to each independent asset, and the overall regime signal is smoothed by the signal length to reduce noise and enhance reliability. Investors can position according to the prevailing market regime by selecting factors that have historically outperformed under each regime environment to minimise downside risk and maximise upside potential:
Risk-On Equity Factors = High Beta > Cyclicals > Low Volatility > Defensives.
Risk-Off Equity Factors = Defensives > Low Volatility > Cyclicals > High Beta.
Risk-On Fixed Income Factors = High Yield > Investment Grade > Treasuries.
Risk-Off Fixed Income Factors = Treasuries > Investment Grade > High Yield.
Risk-On Commodity Factors = Industrial Metals > Energy > Agriculture > Gold.
Risk-Off Commodity Factors = Gold > Agriculture > Energy > Industrial Metals.
Risk-On Currency Factors = Cryptocurrencies > Foreign Currencies > US Dollar.
Risk-Off Currency Factors = US Dollar > Foreign Currencies > Cryptocurrencies.
In summary, the Market Regime Index is a comprehensive macro risk-management tool that identifies the current market regime and helps investors align portfolio risk with the market’s underlying risk appetite. Its intuitive, color-coded design makes it an indispensable resource for investors seeking to navigate shifting market conditions and enhance risk-adjusted performance by selecting factors that have historically outperformed. While it has proven historically valuable, asset-specific characteristics and correlations evolve over time as market dynamics change.
Cycle-Synced Channel Breakout📌 Cycle-Synced Channel Breakout – Detect Breakouts Confirmed by Candles and Momentum Cycles
📖 Overview
The Cycle-Synced Channel Breakout indicator is a precision breakout detection tool that combines the power of:
• Adaptive Keltner Channels
• Dominant Cycle Period Analysis (Ehlers-inspired)
• Candlestick Pattern Recognition (Engulfing)
This multi-layered approach helps identify true breakout opportunities by filtering out noise and false signals, making it ideal for swing traders and intraday traders seeking high-probability directional moves.
⚙️ How It Works
1. Keltner Channel Envelope
A dynamic volatility channel based on the EMA and ATR defines the upper and lower bounds of price movement.
2. Engulfing Candle Detection
The script detects strong bullish and bearish engulfing patterns, which often signal trend reversals or momentum continuations.
3. Dominant Cycle Momentum (Ehlers-inspired)
Using a smoothed power oscillator derived from a detrended price series, the indicator assesses whether momentum is accelerating during the breakout — filtering out weak moves.
4. Signal Confirmation Logic
A signal is only shown when:
• An engulfing pattern is detected, and
• Price breaks out of the Keltner Channel, and
• Momentum (cycle power) is rising
5. Visual Feedback
• Breakout signals are plotted with “BUY” or “SELL” labels
• Faded green/red background highlights confirmed breakouts
• Optional display of engulfing candles with triangle markers
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🛠️ Key Features
• ✅ Adaptive Keltner Channels
• ✅ Bullish/Bearish Engulfing Candle Recognition
• ✅ Ehlers-style Cycle Momentum Confirmation
• ✅ Background highlights for confirmed breakouts
• ✅ Optional candle pattern visualization
• ✅ Lightweight and Pine v6 compatible
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🧪 Inputs
• Keltner Length – EMA period for channel basis
• Multiplier – Multiplied with ATR to determine band width
• Cycle Lookback – Used to calculate smoothed cycle power
• Show Engulfing Candles? – Toggles candlestick signals
• Show Breakout Signals? – Toggles breakout labels and backgrounds
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🧠 How to Use
• Look for “BUY” or “SELL” labels when:
• An engulfing candle breaks through the Keltner Channel
• Cycle momentum confirms strength behind the move
• The background color will faintly highlight the breakout direction.
• Use in combination with other trend or volume indicators for added confluence.
🔒 Notes
• This indicator is not repainting.
• It is designed for educational and research purposes only.
• Works across all timeframes and asset classes (stocks, crypto, forex, etc.)
Estimated Manipulation Movement Signal [AlgoPoint]Follow the Footprints of Whale Movements That Drive the Market
Overview
The market is not always driven by natural supply and demand. Large players—often called "whales" or institutions—can create artificial price movements to trigger stop-losses, induce panic or FOMO, and build their large positions at favorable prices. These events are known as "stop hunts" or "liquidity grabs."
The EMMS indicator is a specialized tool designed to detect these specific moments of potential market manipulation. It does not follow trends in a traditional sense; instead, it identifies high-probability reversal points created by the calculated actions of Smart Money trapping other market participants.
How It Works: The 3-Module Logic
The indicator uses a multi-stage confirmation process to identify a potential stop hunt:
1. Anomaly Detection: The engine first scans the chart for "Anomaly Candles." These are candles with unusually high volume and a very long wick relative to their body. This combination signals a sudden, forceful, and potentially unnatural price push.
2. Liquidity Zone Detection: The indicator automatically identifies and tracks recent significant swing highs and lows. These levels are considered "Liquidity Zones" because they are areas where a large number of stop-loss orders are likely clustered. These are the "hunting grounds" for whales.
3. The Stop Hunt Signal: A final signal is generated only when these two events align in a specific sequence:
An Anomaly Candle (high volume, long wick) spikes through a previously identified Liquidity Zone.
The same candle then reverses, closing back inside the previous price range.
This sequence confirms that the move was likely a "trap" designed to engineer liquidity, and a reversal in the opposite direction is now highly probable.
How to Interpret & Use This Indicator
BUY Signal: A BUY signal appears after a sharp price drop that pierces a recent swing low (taking out the stops of long positions) and then aggressively reverses to close higher. This suggests that Smart Money has absorbed the panic selling they just induced. The signal indicates a potential move UP.
SELL Signal: A SELL signal appears after a sharp price spike that pierces a recent swing high (taking out the stops of short positions) and then aggressively reverses to close lower. This suggests that Smart Money has sold into the FOMO buying they just created. The signal indicates a potential move DOWN.
This indicator is best used as a high-probability confirmation tool, ideally in conjunction with your understanding of the overall market trend and structure.
Cyclic Reversal Engine [AlgoPoint]Overview
Most indicators focus on price and momentum, but they often ignore a critical third dimension: time. Markets move in rhythmic cycles of expansion and contraction, but these cycles are not fixed; they speed up in trending markets and slow down in choppy conditions.
The Cyclic Reversal Engine is an advanced analytical tool designed to decode this rhythm. Instead of relying on static, lagging formulas, this indicator learns from past market behavior to anticipate when the current trend is statistically likely to reach its exhaustion point, providing high-probability reversal signals.
It achieves this by combining a sophisticated time analysis with a robust price-action confirmation.
How It Works: The Core Logic
The indicator operates on a multi-stage process to identify potential turning points in the market.
1. Market Regime Analysis (The Brain): Before analyzing any cycles, the indicator first diagnoses the current "personality" of the market. Using a combination of the ADX, Choppiness Index, and RSI, it classifies the market into one of three primary regimes:
- Trending: Strong, directional movement.
- Ranging: Sideways, non-directional chop.
- Reversal: An over-extended state (overbought/oversold) where a turn is imminent.
2. Adaptive Cycle Learning (The "Machine Learning" Aspect): This is the indicator's smartest feature. It constantly analyzes past cycles by measuring the bar-count between significant swing highs and swing lows. Crucially, it learns the average cycle duration for each specific market regime. For example, it learns that "in a strong trending market, a new swing low tends to occur every 35 bars," while "in a ranging market, this extends to 60 bars."
3. The Countdown & Timing Signal: The indicator identifies the last major swing high or low and starts a bar-by-bar countdown. Based on the current market regime, it selects the appropriate learned cycle length from its memory. When the bar count approaches this adaptive target, the indicator determines that a reversal is "due" from a timing perspective.
4. Price Confirmation (The Trigger): A signal is never generated based on timing alone. Once the timing condition is met (the cycle is "due"), the indicator waits for a final price-action confirmation. The default confirmation is the RSI entering an extreme overbought or oversold zone, signaling momentum exhaustion. The signal is only triggered when Time + Price Confirmation align.
How to Use This Indicator
- The Dashboard: The panel in the bottom-right corner is your command center.
- Market Regime: Shows the current market personality analyzed by the engine.
- Adaptive Cycle / Bar Count: This is the core of the indicator. It shows the target cycle length for the current regime (e.g., 50) and the current bar count since the last swing point (e.g., 45). The background turns orange when the bar count enters the "due zone," indicating that you should be on high alert for a reversal.
- BUY/SELL Signals: A label appears on the chart only when the two primary conditions are met:
The timing is right (Bar Count has reached the Adaptive Cycle target).
The price confirms exhaustion (RSI is in an extreme zone).
A BUY signal suggests a downtrend cycle is likely complete, and a SELL signal suggests an uptrend cycle is likely complete.
Key Settings
- Pivot Lookback: Controls the sensitivity of the swing point detection. Higher values will identify more significant, longer-term cycles.
- Market Regime Engine: The ADX, Choppiness, and RSI settings can be fine-tuned to adjust how the indicator classifies the market's personality.
- Require Price Confirmation: You can toggle the RSI confirmation on or off. It is highly recommended to keep it enabled for higher-quality signals.
Multi-Asset Trend Background [SwissAlgo]Multi-Asset Trend Background
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Purpose
This indicator colors the chart background green (uptrend) or red (downtrend) to show the broad phases of a selected asset or ratio (for example SP500, or Gold), regardless of the current ticker on the chart (for example BTC).
The aim is not to generate signals, but to show when the selected asset (such as SP500 or Gold) was in a sustained uptrend or downtrend, so you can compare another chart (for example BTC) against that backdrop.
It helps frame price action in context, highlighting how macro drivers often align with or diverge from other markets.
From mid-2016 to late-2017, the SP500 was in a clear uptrend — Bitcoin rallied strongly in the same period, showing alignment between equities and crypto risk-taking.
When Gold trended higher, the SP500 often weakened, reflecting their tendency to move inversely in longer cycles.
As HYG/TLT turned down in early 2020, QQQ also struggled — illustrating how credit risk appetite is linked to equity performance.
During periods of DXY strength, Gold frequently showed the opposite trend, consistent with the historical dollar–gold relationship.
When RSP/SPY trended down, rallies in the S&P 500 were driven by a narrow group of large-cap stocks, while a rising ratio indicated broad market participation.
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Why it May Help You
Provides context for asset correlations.
Helps identify whether a chart is moving with or against its macro environment.
Useful for cycle mapping and historical study of market phases.
Filters noise and emphasizes established trends rather than short swings.
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How it Works
You select an asset or ratio from a dropdown.
The script calculates a mid-term moving average, then measures its slope, slope change, and slope acceleration to quantify the trend’s direction and consistency.
A longer-term moving average filter defines whether the long-term backdrop is bullish or bearish.
Background Coloring rules:
Green = slope strongly positive in line with long-term uptrend, or downtrend showing constructive reversal signs.
Red = slope strongly negative in line with long-term downtrend, or uptrend showing weakening slope.
No shading = neutral or mixed conditions.
This slope-based approach avoids the limitations of simple MA crosses, aiming to capture broad, consistent trend phases across different assets, with a mid/long-term view.
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Assets You Can Select
EQUITIES – good reference to gauge risk appetite in financial markets
SP500 = broad benchmark. Uptrend = strength in US equities signalling risk-on conditions; downtrend = weakness, risk-off market phase.
NASDAQ = tech and growth stocks. Uptrend = technology/growth leadership, risk appetite; downtrend = tech underperformance and fading risk appetite.
DOW = industrial and value stocks. Uptrend = industrial/value strength/economic strength; downtrend = weakness in traditional sectors and potential economic downturn.
RUSSELL2000 = small caps. Uptrend = typical in risk-on environments and FOMO; downtrend = small-cap underperformance, "flight to safety".
COMMODITIES – proxies for inflation, industry, and safe-haven demand.
GOLD = safe-haven. Uptrend = defensive demand rising/risk-off/inflation fears; downtrend = weaker demand for safety.
SILVER = partly industrial, partly safe-haven. Uptrend = stronger industrial cycle, or precious metals demand and risk appetite.
COPPER = industrial barometer. Uptrend = stronger industrial activity; downtrend = economic slowdown concerns.
CRUDE OIL = energy prices. Uptrend = rising energy/inflation pressures; downtrend = weaker demand or supply relief.
NATURAL GAS = volatile energy prices. Uptrend = higher energy costs and inflation pressure; downtrend = easing energy conditions.
BONDS / FX – monetary policy, credit, and risk appetite signals.
TLT = long-term US bonds. Uptrend = falling yields (bond demand)/flight to safety; downtrend = rising yields (risk on)
HYG = high-yield credit. Uptrend = strong credit appetite; downtrend = risk aversion in credit markets.
DXY = US dollar index. Uptrend = dollar strength (weaker EUR, GBP, SEK, etc); downtrend = dollar weakness.
USDJPY = carry trade proxy. Uptrend = stronger USD vs JPY (risk appetite); downtrend = JPY strength (risk-off).
CHFUSD = Swiss franc. Uptrend = franc strength (defensive flow); downtrend = franc weakness.
YIELD INVERSION = US10Y–US02Y. Uptrend = curve steepening; downtrend = inversion deepening (higher recession risk).
HOME BUILDERS = US housing sector. Uptrend = housing sector strength (risk on); downtrend = weakness (risk off).
EURUSD = euro vs dollar. Uptrend = euro strength (risk appetite); downtrend = euro weakness (risk aversion).
CRYPTO – digital asset benchmarks.
BITCOIN = digital gold. Uptrend = BTC strength; downtrend = BTC weakness.
CRYPTO_TOTAL = entire crypto market cap. Uptrend = broad crypto growth; downtrend = contraction.
CRYPTO_ALTS = altcoin market cap. Uptrend = altcoin expansion (often “alt season”); downtrend = contraction.
RATIOS – relative measures to extract macro signals.
COPPER/BTC = compares industrial cycle vs Bitcoin cycle. Uptrend = copper outperforming BTC; downtrend = BTC outperforming copper. Seems aligned with BTC macro tops and bottoms in the mid/long run.
RSP/SPY = market breadth (equal-weight vs cap-weighted). Uptrend = strong broad participation in market growth; downtrend = narrow leadership (fewer stocks leading the growth).
PCE/CPI = Fed’s inflation measure (PCE) vs consumer perceived inflation (CPI). Uptrend = PCE rising faster than CPI; downtrend = CPI running hotter than PCE. Fluctuates around 1; values above 1 may indicate hawkish Fed stands, values < 1 may indicate more dovish Fed stands.
HYG/TLT = credit vs bonds. Uptrend = risk appetite (high-yield outperforming long-term
treasury bonds); downtrend = risk aversion.
GOLD/SILVER = defensive vs cyclical metals. Uptrend = gold outperforming (risk-off tilt); downtrend = silver outperforming (risk-on tilt).
EURUSD/BTC = fiat vs crypto. Uptrend = EUR strengthening vs BTC; downtrend = BTC strengthening vs EUR. In general, the BTC trend is aligned EUR/USD trend.
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Limitations
Trend detection may lag by design to reduce noise.
Ratios rely on the availability and session rules of their components.
Background colors update on bar close; intra-bar values may differ.
Parameters are fixed and may not suit all assets equally.
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Disclaimer
This script is for educational and research purposes only. It does not provide financial advice or trade recommendations. Historical trend alignment does not guarantee future outcomes. Use with additional independent analysis.
Crypto Flows [ETF|On-chain]The surge in Bitcoin and Ethereum spot ETFs has transformed how crypto is held and traded. By mid‑2025, U.S. spot Bitcoin ETFs already controlled roughly 1.28 million BTC, or about 6.5 percent of the circulating supply (Fosque, 2025). This accumulation has coincided with sharp price rallies and signals that regulated vehicles are absorbing a meaningful share of supply (Fosque, 2025; Wright, 2025). At the same time, on‑chain analytics show that exchange flows still influence markets: large inflows to exchanges often precede sell‑offs, whereas withdrawals to private wallets signal accumulation and reduced sell pressure (Singh, 2024; CryptoQuant, 2024). IntoTheBlock’s large‑holder inflow indicator even notes that spikes in whale buying frequently mark major bottoms (IntoTheBlock, 2022). I wanted to weave these pieces together, so I created this indicator.
Essence and logic
The script draws from two data streams: net flows into ETFs and net on‑chain flows from large holders, both scaled by the asset’s circulating market cap. ETF flows are aggregated across the ten largest INDEX:BTCUSD Bitcoin ETFs, the ten largest Ethereum INDEX:ETHUSD ETFs and the first CRYPTOCAP:SOL Solana ETF; each fund has its own checkbox and colour selection. On‑chain data uses IntoTheBlock’s large‑holder inflows and outflows, with dozens of coins available( CRYPTO:XRPUSD CRYPTOCAP:AVAX CRYPTOCAP:ADA CRYPTOCAP:LINK CRYPTO:DOGEUSD CRYPTOCAP:OTHERS ; if your coin isn’t shown in the dropdown you can manually enter its symbol. For each component, daily flows are converted into either a Z‑score or, by default, a percent‑of‑market‑cap series; users choose the weighting between ETF and on‑chain signals. These weighted series are summed into a composite, smoothed, and then two moving averages (a fast and a slow one) are applied to define bullish or bearish regimes. Because ETFs are a recent phenomenon, the early part of the composite is dominated by on‑chain flows; as ETF history lengthens, the fund‑flow component will become more influential. Trade signals are generated via moving‑average crossovers and optional dip triggers, and a trend table summarises current values and directions.
Why these components?
ETF flows reflect institutional adoption and supply absorption. Funds such as IBIT already hold about 744 000 BTC (roughly 3.3 percent of total supply), and cumulative ETF holdings have been growing faster than new coins are mined (Wright, 2025). Net inflows into these vehicles have tended to accompany rising prices and signal long‑horizon capital (Fosque, 2025). On‑chain flows, meanwhile, capture exchange liquidity dynamics. High inflows to exchanges often indicate that investors are preparing to sell, increasing tradable supply (Singh, 2024; CryptoQuant, 2024). Outflows into self‑custody suggest accumulation and reduced sell pressure, providing a bullish signal (Singh, 2024; CryptoQuant, 2024). IntoTheBlock points out that spikes in large‑holder inflows—whales moving coins into cold storage—have historically preceded price bottoms (IntoTheBlock, 2022). By weighting and standardising these flows relative to market cap, the composite aims to offer a more objective lens on risk‑on versus risk‑off regimes than price alone.
Limitations and outlook
ETFs a pretty new, so the data history is short. The list of tracked funds is currently limited to U.S. and European products; adding Asian or Canadian vehicles could provide a fuller picture. On‑chain flows can be noisy and occasionally give conflicting signals, and large‑holder data is not available for every crypto asset. The ETF and on‑chain components are also correlated through market cap, so equal weighting may amplify common trends. As macro conditions evolve and ETF redemption mechanisms change, the usefulness of fund flows could vary. I see this indicator as one tool among many, and I’m considering adding stablecoin flows, derivatives funding rates, or halving‑cycle adjustments. Suggestions are welcome.
Personal note
I’m a student who enjoys exploring the intersection of macro flows, on‑chain analytics and market psychology. This script is free to use. You can enable or disable each component, adjust weights, change the display mode and lookback, and select individual ETF tickers. If it brings you value, feel free to follow my work or reach out with feedback. I appreciate your support. Please remember that this indicator is for educational purposes and not investment advice. I built this indicator in addition to my Liquidity indicator, where I use Global M2, the yield curve, and the high-yield spread to define risk-on/risk-off regimes. If you are interested, you can find it here:
References
CryptoQuant Team. (2024). Exchange in/outflow and netflow user guide.
Fosque, J. (2025). Bitcoin ETFs pull $17.8 billion in 90 days as price surges past $118 K. The Digital Chamber.
IntoTheBlock. (2022). Large holders inflow indicator description.
Singh, O. (2024). Crypto exchange inflows and outflows explained: What they reveal about market trends. CCN.
Wright, L. (2025). Bitcoin ETFs to lock up 1.5 million BTC by New Year as supply squeeze tightens grip. CryptoSlate.
MERV: Market Entropy & Rhythm Visualizer [BullByte]The MERV (Market Entropy & Rhythm Visualizer) indicator analyzes market conditions by measuring entropy (randomness vs. trend), tradeability (volatility/momentum), and cyclical rhythm. It provides traders with an easy-to-read dashboard and oscillator to understand when markets are structured or choppy, and when trading conditions are optimal.
Purpose of the Indicator
MERV’s goal is to help traders identify different market regimes. It quantifies how structured or random recent price action is (entropy), how strong and volatile the movement is (tradeability), and whether a repeating cycle exists. By visualizing these together, MERV highlights trending vs. choppy environments and flags when conditions are favorable for entering trades. For example, a low entropy value means prices are following a clear trend line, whereas high entropy indicates a lot of noise or sideways action. The indicator’s combination of measures is original: it fuses statistical trend-fit (entropy), volatility trends (ATR and slope), and cycle analysis to give a comprehensive view of market behavior.
Why a Trader Should Use It
Traders often need to know when a market trend is reliable vs. when it is just noise. MERV helps in several ways: it shows when the market has a strong direction (low entropy, high tradeability) and when it’s ranging (high entropy). This can prevent entering trend-following strategies during choppy periods, or help catch breakouts early. The “Optimal Regime” marker (a star) highlights moments when entropy is very low and tradeability is very high, typically the best conditions for trend trades. By using MERV, a trader gains an empirical “go/no-go” signal based on price history, rather than guessing from price alone. It’s also adaptable: you can apply it to stocks, forex, crypto, etc., on any timeframe. For example, during a bullish phase of a stock, MERV will turn green (Trending Mode) and often show a star, signaling good follow-through. If the market later grinds sideways, MERV will shift to magenta (Choppy Mode), warning you that trend-following is now risky.
Why These Components Were Chosen
Market Entropy (via R²) : This measures how well recent prices fit a straight line. We compute a linear regression on the last len_entropy bars and calculate R². Entropy = 1 - R², so entropy is low when prices follow a trend (R² near 1) and high when price action is erratic (R² near 0). This single number captures trend strength vs noise.
Tradeability (ATR + Slope) : We combine two familiar measures: the Average True Range (ATR) (normalized by price) and the absolute slope of the regression line (scaled by ATR). Together they reflect how active and directional the market is. A high ATR or strong slope means big moves, making a trend more “tradeable.” We take a simple average of the normalized ATR and slope to get tradeability_raw. Then we convert it to a percentile rank over the lookback window so it’s stable between 0 and 1.
Percentile Ranks : To make entropy and tradeability values easy to interpret, we convert each to a 0–100 rank based on the past len_entropy periods. This turns raw metrics into a consistent scale. (For example, an entropy rank of 90 means current entropy is higher than 90% of recent values.) We then divide by 100 to plot them on a 0–1 scale.
Market Mode (Regime) : Based on those ranks, MERV classifies the market:
Trending (Green) : Low entropy rank (<40%) and high tradeability rank (>60%). This means the market is structurally trending with high activity.
Choppy (Magenta) : High entropy rank (>60%) and low tradeability rank (<40%). This is a mostly random, low-momentum market.
Neutral (Cyan) : All other cases. This covers mixed regimes not strongly trending or choppy.
The mode is shown as a colored bar at the bottom: green for trending, magenta for choppy, cyan for neutral.
Optimal Regime Signal : Separately, we mark an “optimal” condition when entropy_norm < 0.3 and tradeability > 0.7 (both normalized 0–1). When this is true, a ★ star appears on the bottom line. This star is colored white when truly optimal, gold when only tradeability is high (but entropy not quite low enough), and black when neither condition holds. This gives a quick visual cue for very favorable conditions.
What Makes MERV Stand Out
Holistic View : Unlike a single-oscillator, MERV combines trend, volatility, and cycle analysis in one tool. This multi-faceted approach is unique.
Visual Dashboard : The fixed on-chart dashboard (shown at your chosen corner) summarizes all metrics in bar/gauge form. Even a non-technical user can glance at it: more “█” blocks = a higher value, colors match the plots. This is more intuitive than raw numbers.
Adaptive Thresholds : Using percentile ranks means MERV auto-adjusts to each market’s character, rather than requiring fixed thresholds.
Cycle Insight : The rhythm plot adds information rarely found in indicators – it shows if there’s a repeating cycle (and its period in bars) and how strong it is. This can hint at natural bounce or reversal intervals.
Modern Look : The neon color scheme and glow effects make the lines easy to distinguish (blue/pink for entropy, green/orange for tradeability, etc.) and the filled area between them highlights when one dominates the other.
Recommended Timeframes
MERV can be applied to any timeframe, but it will be more reliable on higher timeframes. The default len_entropy = 50 and len_rhythm = 30 mean we use 30–50 bars of history, so on a daily chart that’s ~2–3 months of data; on a 1-hour chart it’s about 2–3 days. In practice:
Swing/Position traders might prefer Daily or 4H charts, where the calculations smooth out small noise. Entropy and cycles are more meaningful on longer trends.
Day trader s could use 15m or 1H charts if they adjust the inputs (e.g. shorter windows). This provides more sensitivity to intraday cycles.
Scalpers might find MERV too “slow” unless input lengths are set very low.
In summary, the indicator works anywhere, but the defaults are tuned for capturing medium-term trends. Users can adjust len_entropy and len_rhythm to match their chart’s volatility. The dashboard position can also be moved (top-left, bottom-right, etc.) so it doesn’t cover important chart areas.
How the Scoring/Logic Works (Step-by-Step)
Compute Entropy : A linear regression line is fit to the last len_entropy closes. We compute R² (goodness of fit). Entropy = 1 – R². So a strong straight-line trend gives low entropy; a flat/noisy set of points gives high entropy.
Compute Tradeability : We get ATR over len_entropy bars, normalize it by price (so it’s a fraction of price). We also calculate the regression slope (difference between the predicted close and last close). We scale |slope| by ATR to get a dimensionless measure. We average these (ATR% and slope%) to get tradeability_raw. This represents how big and directional price moves are.
Convert to Percentiles : Each new entropy and tradeability value is inserted into a rolling array of the last 50 values. We then compute the percentile rank of the current value in that array (0–100%) using a simple loop. This tells us where the current bar stands relative to history. We then divide by 100 to plot on .
Determine Modes and Signal : Based on these normalized metrics: if entropy < 0.4 and tradeability > 0.6 (40% and 60% thresholds), we set mode = Trending (1). If entropy > 0.6 and tradeability < 0.4, mode = Choppy (-1). Otherwise mode = Neutral (0). Separately, if entropy_norm < 0.3 and tradeability > 0.7, we set an optimal flag. These conditions trigger the colored mode bars and the star line.
Rhythm Detection : Every bar, if we have enough data, we take the last len_rhythm closes and compute the mean and standard deviation. Then for lags from 5 up to len_rhythm, we calculate a normalized autocorrelation coefficient. We track the lag that gives the maximum correlation (best match). This “best lag” divided by len_rhythm is plotted (a value between 0 and 1). Its color changes with the correlation strength. We also smooth the best correlation value over 5 bars to plot as “Cycle Strength” (also 0 to 1). This shows if there is a consistent cycle length in recent price action.
Heatmap (Optional) : The background color behind the oscillator panel can change with entropy. If “Neon Rainbow” style is on, low entropy is blue and high entropy is pink (via a custom color function), otherwise a classic green-to-red gradient can be used. This visually reinforces the entropy value.
Volume Regime (Dashboard Only) : We compute vol_norm = volume / sma(volume, len_entropy). If this is above 1.5, it’s considered high volume (neon orange); below 0.7 is low (blue); otherwise normal (green). The dashboard shows this as a bar gauge and percentage. This is for context only.
Oscillator Plot – How to Read It
The main panel (oscillator) has multiple colored lines on a 0–1 vertical scale, with horizontal markers at 0.2 (Low), 0.5 (Mid), and 0.8 (High). Here’s each element:
Entropy Line (Blue→Pink) : This line (and its glow) shows normalized entropy (0 = very low, 1 = very high). It is blue/green when entropy is low (strong trend) and pink/purple when entropy is high (choppy). A value near 0.0 (below 0.2 line) indicates a very well-defined trend. A value near 1.0 (above 0.8 line) means the market is very random. Watch for it dipping near 0: that suggests a strong trend has formed.
Tradeability Line (Green→Yellow) : This represents normalized tradeability. It is colored bright green when tradeability is low, transitioning to yellow as tradeability increases. Higher values (approaching 1) mean big moves and strong slopes. Typically in a market rally or crash, this line will rise. A crossing above ~0.7 often coincides with good trend strength.
Filled Area (Orange Shade) : The orange-ish fill between the entropy and tradeability lines highlights when one dominates the other. If the area is large, the two metrics diverge; if small, they are similar. This is mostly aesthetic but can catch the eye when the lines cross over or remain close.
Rhythm (Cycle) Line : This is plotted as (best_lag / len_rhythm). It indicates the relative period of the strongest cycle. For example, a value of 0.5 means the strongest cycle was about half the window length. The line’s color (green, orange, or pink) reflects how strong that cycle is (green = strong). If no clear cycle is found, this line may be flat or near zero.
Cycle Strength Line : Plotted on the same scale, this shows the autocorrelation strength (0–1). A high value (e.g. above 0.7, shown in green) means the cycle is very pronounced. Low values (pink) mean any cycle is weak and unreliable.
Mode Bars (Bottom) : Below the main oscillator, thick colored bars appear: a green bar means Trending Mode, magenta means Choppy Mode, and cyan means Neutral. These bars all have a fixed height (–0.1) and make it very easy to see the current regime.
Optimal Regime Line (Bottom) : Just below the mode bars is a thick horizontal line at –0.18. Its color indicates regime quality: White (★) means “Optimal Regime” (very low entropy and high tradeability). Gold (★) means not quite optimal (high tradeability but entropy not low enough). Black means neither condition. This star line quickly tells you when conditions are ideal (white star) or simply good (gold star).
Horizontal Guides : The dotted lines at 0.2 (Low), 0.5 (Mid), and 0.8 (High) serve as reference lines. For example, an entropy or tradeability reading above 0.8 is “High,” and below 0.2 is “Low,” as labeled on the chart. These help you gauge values at a glance.
Dashboard (Fixed Corner Panel)
MERV also includes a compact table (dashboard) that can be positioned in any corner. It summarizes key values each bar. Here is how to read its rows:
Entropy : Shows a bar of blocks (█ and ░). More █ blocks = higher entropy. It also gives a percentage (rounded). A full bar (10 blocks) with a high % means very chaotic market. The text is colored similarly (blue-green for low, pink for high).
Rhythm : Shows the best cycle period in bars (e.g. “15 bars”). If no calculation yet, it shows “n/a.” The text color matches the rhythm line.
Cycle Strength : Gives the cycle correlation as a percentage (smoothed, as shown on chart). Higher % (green) means a strong cycle.
Tradeability : Displays a 10-block gauge for tradeability. More blocks = more tradeable market. It also shows “gauge” text colored green→yellow accordingly.
Market Mode : Simply shows “Trending”, “Choppy”, or “Neutral” (cyan text) to match the mode bar color.
Volume Regime : Similar to tradeability, shows blocks for current volume vs. average. Above-average volume gives orange blocks, below-average gives blue blocks. A % value indicates current volume relative to average. This row helps see if volume is abnormally high or low.
Optimal Status (Large Row) : In bold, either “★ Optimal Regime” (white text) if the star condition is met, “★ High Tradeability” (gold text) if tradeability alone is high, or “— Not Optimal” (gray text) otherwise. This large row catches your eye when conditions are ripe.
In short, the dashboard turns the numeric state into an easy read: filled bars, colors, and text let you see current conditions without reading the plot. For instance, five blue blocks under Entropy and “25%” tells you entropy is low (good), and a row showing “Trending” in green confirms a trend state.
Real-Life Example
Example : Consider a daily chart of a trending stock (e.g. “AAPL, 1D”). During a strong uptrend, recent prices fit a clear upward line, so Entropy would be low (blue line near bottom, perhaps below the 0.2 line). Volatility and slope are high, so Tradeability is high (green-yellow line near top). In the dashboard, Entropy might show only 1–2 blocks (e.g. 10%) and Tradeability nearly full (e.g. 90%). The Market Mode bar turns green (Trending), and you might see a white ★ on the optimal line if conditions are very good. The Volume row might light orange if volume is above average during the rally. In contrast, imagine the same stock later in a tight range: Entropy will rise (pink line up, more blocks in dashboard), Tradeability falls (fewer blocks), and the Mode bar turns magenta (Choppy). No star appears in that case.
Consolidated Use Case : Suppose on XYZ stock the dashboard reads “Entropy: █░░░░░░░░ 20%”, “Tradeability: ██████████ 80%”, Mode = Trending (green), and “★ Optimal Regime.” This tells the trader that the market is in a strong, low-noise trend, and it might be a good time to follow the trend (with appropriate risk controls). If instead it reads “Entropy: ████████░░ 80%”, “Tradeability: ███▒▒▒▒▒▒ 30%”, Mode = Choppy (magenta), the trader knows the market is random and low-momentum—likely best to sit out until conditions improve.
Example: How It Looks in Action
Screenshot 1: Trending Market with High Tradeability (SOLUSD, 30m)
What it means:
The market is in a clear, strong trend with excellent conditions for trading. Both trend-following and active strategies are favored, supported by high tradeability and strong volume.
Screenshot 2: Optimal Regime, Strong Trend (ETHUSD, 1h)
What it means:
This is an ideal environment for trend trading. The market is highly organized, tradeability is excellent, and volume supports the move. This is when the indicator signals the highest probability for success.
Screenshot 3: Choppy Market with High Volume (BTC Perpetual, 5m)
What it means:
The market is highly random and choppy, despite a surge in volume. This is a high-risk, low-reward environment, avoid trend strategies, and be cautious even with mean-reversion or scalping.
Settings and Inputs
The script is fully open-source; here are key inputs the user can adjust:
Entropy Window (len_entropy) : Number of bars used for entropy and tradeability (default 50). Larger = smoother, more lag; smaller = more sensitivity.
Rhythm Window (len_rhythm ): Bars used for cycle detection (default 30). This limits the longest cycle we detect.
Dashboard Position : Choose any corner (Top Right default) so it doesn’t cover chart action.
Show Heatmap : Toggles the entropy background coloring on/off.
Heatmap Style : “Neon Rainbow” (colorful) or “Classic” (green→red).
Show Mode Bar : Turn the bottom mode bar on/off.
Show Dashboard : Turn the fixed table panel on/off.
Each setting has a tooltip explaining its effect. In the description we will mention typical settings (e.g. default window sizes) and that the user can move the dashboard corner as desired.
Oscillator Interpretation (Recap)
Lines : Blue/Pink = Entropy (low=trend, high=chop); Green/Yellow = Tradeability (low=quiet, high=volatile).
Fill : Orange tinted area between them (for visual emphasis).
Bars : Green=Trending, Magenta=Choppy, Cyan=Neutral (at bottom).
Star Line : White star = ideal conditions, Gold = good but not ideal.
Horizontal Guides : 0.2 and 0.8 lines mark low/high thresholds for each metric.
Using the chart, a coder or trader can see exactly what each output represents and make decisions accordingly.
Disclaimer
This indicator is provided as-is for educational and analytical purposes only. It does not guarantee any particular trading outcome. Past market patterns may not repeat in the future. Users should apply their own judgment and risk management; do not rely solely on this tool for trading decisions. Remember, TradingView scripts are tools for market analysis, not personalized financial advice. We encourage users to test and combine MERV with other analysis and to trade responsibly.
-BullByte
Chandelier Exit Oscillator [LuxAlgo]The Chandelier Exit Oscillator is a technical analysis tool that provides insights into potential trend reversals, momentum shifts, and trend continuation patterns, helping traders pinpoint optimal exit points for both long and short positions.
By calculating trailing stop levels based on a multiple of the Average True Range (ATR), the oscillator visually indicates when prices move above or below these critical stop levels.
This script uniquely combines the Chandelier Exit indicator with an oscillator format, equipping traders with a versatile tool that leverages ATR-based levels for enhanced trend analysis.
🔶 USAGE
Displaying the Chandelier Exit as an oscillator allows traders to gauge trend momentum and strength, recognize potential reversals, and refine their market insights.
The Timeframe option specifies the timeframe used for calculations, enabling multi-timeframe analysis and allowing traders to align the indicator’s signals with broader or narrower market trends.
The Chandelier Exit Oscillator allows users to select between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
The Chandelier Exit Overlay allows users to enable or disable the display of Chandelier Exit levels directly on the price chart. When enabled, this overlay plots trailing stop levels for both long and short positions, helping traders visually monitor potential exit points and trend boundaries alongside the price action.
The Trend-based Bar Color feature allows users to color the bars on the price chart according to the current trend direction. This visual differentiation aids in quicker decision-making and provides a clearer understanding of market dynamics.
🔶 SETTINGS
🔹 Chandelier Exit Settings
Timeframe: Sets the timeframe for calculations, allowing multi-timeframe analysis.
ATR Length: Defines the number of bars used for calculating the Average True Range (ATR), which helps in setting Chandelier Exit levels.
ATR Multiplier: Adjusts the sensitivity of the Chandelier Exit lines based on the ATR. Higher values make the indicator more conservative, while lower values make it more responsive.
🔹 Chandelier Exit Oscillator
Chandelier Exit Oscillator: Allows users to choose between a Regular or Normalized oscillator type. The Regular option displays raw oscillator values, while the Normalized version smooths values and scales them from 0 to 100.
Oscillator Smoothing: Controls the level of smoothing applied to the oscillator. Higher smoothing values filter out minor fluctuations.
🔹 Chandelier Exit Overlay
Chandelier Exit Overlay: Enables or disables the display of Chandelier Exit levels directly on the price chart.
Trend-based Bar Colors: Allows users to color bars based on trend direction, enhancing the visual analysis of market direction.
🔶 RELATED SCRIPTS
Market-Structure-Oscillator
Rolling 250-Day Sharpe RatioThis Pine Script indicator, “Rolling 250-Day Sharpe Ratio”, computes the trailing Sharpe Ratio for any traded asset over a 250-session window, equivalent to approximately one trading year. The script first derives daily log returns and adjusts them by subtracting the daily equivalent of the 3-month US Treasury yield to obtain the excess return. It then calculates the rolling mean and standard deviation of these excess returns to produce the annualized Sharpe Ratio, which is displayed as a continuous time series on the chart. This allows traders and analysts to assess how the asset’s risk-adjusted performance evolves over time relative to a risk-free benchmark.
A persistently high Sharpe Ratio can indicate strong risk-adjusted returns, but it is essential to approach extreme values with caution. Elevated Sharpe readings can sometimes reflect unsustainable trends, excessive leverage, or periods of unusually low volatility that may revert abruptly. Conversely, a low or negative Sharpe Ratio does not automatically imply an asset should be avoided; it might signal an opportunity if the risk environment normalizes.
AZRO Systems XRP Top/Bottom Indicator — Invite-OnlyAZRO Systems – XRP Top/Bottom Indicator — Invite-Only
VERSION v1.0.4 — Early tops & bottoms flagged; label auto-flips to MAJOR at weekly close
──────────────────────────────────────────────────────
WHAT IT DOES
• EARLY TOP / EARLY BOTTOM prints intra-bar the moment any multi-factor recipe triggers.
• When the weekly bar closes, the label flips to MAJOR TOP / MAJOR BOTTOM and the confirmed alert fires.
• (If Soft-Confirm is ON, a TOP must first pull back ≈ 30 % of ATR-90 before confirmation.)
• Adds large green/red labels and a light bar-tint once major status is confirmed.
• Historical tests indicate materially lower drawdowns versus passive holding while still capturing each macro upswing.
HOW IT WORKS (concept level — exact thresholds are locked)
• Macro-Rotation Gauge – BTC dominance
Weekly BTC.D enters a historic extreme, then reverses for ≥ 2 weekly closes to flag potential rotation; never fires solo.
• Asset-Share Pivot – XRP market-cap share filters out false RSI spikes.
• Momentum-Stress Check – Weekly RSI + ATR pull-back captures exhaustion without waiting for close.
A label prints only when a recipe combining these lenses is met, greatly reducing false signals versus single-factor scripts.
HOW TO USE
Chart : XRP-USD · 1-WEEK (lower timeframes unsupported)
Watch : EARLY label → flips to MAJOR at weekly confirmation (bar tint appears)
Alerts : • EARLY Bottom / EARLY Top → ONCE PER BAR
• MAJOR Bottom / MAJOR Top → ONCE PER BAR CLOSE
USER-VISIBLE INPUTS
• Label distance (% ATR-90) – vertical offset for labels (Default 50)
• Light-mode palette – swap colors for bright themes (Default OFF)
• Soft-Confirm filter – ON waits for ≈ 30 % ATR pull-back on tops; OFF prints faster tops (Default ON)
• Warning checkbox – visual reminder only; no impact on signals (Default OFF)
ROADMAP
An intraday scalp mode for this XRP script is under development.
LIMITATIONS & DISCLAIMER
• Designed exclusively for the weekly timeframe; extreme market events can override any model—always manage risk.
• Educational tool — not financial advice. Past performance ≠ future returns.
Adaptive Cycle Oscillator with EMADescription of the Adaptive Cycle Oscillator with EMA Pine Script
This Pine Script, titled "Adaptive Cycle Oscillator with EMA", is a custom technical indicator designed for TradingView to help traders analyze market cycles and identify potential buy or sell opportunities. It combines an Adaptive Cycle Oscillator (ACO) with multiple Exponential Moving Averages (EMAs), displayed as colorful, wavy lines, and includes features like buy/sell signals and divergence detection. Below is a beginner-friendly explanation of how the script works, adhering to TradingView's Script Publishing Rules.
What This Indicator Does
The Adaptive Cycle Oscillator with EMA helps you:
Visualize market cycles using an oscillator that adapts to price movements.
Track trends with seven EMAs of different lengths, plotted as a rainbow of wavy lines.
Identify potential buy or sell signals when the oscillator crosses predefined thresholds.
Spot divergences between the oscillator and price to anticipate reversals.
Use customizable settings to adjust the indicator to your trading style.
Note: This is a technical analysis tool and does not guarantee profits. Always combine it with other analysis methods and practice risk management.
Step-by-Step Explanation for New Users
1. Understanding the Indicator
Adaptive Cycle Oscillator (ACO): The ACO analyzes price data (based on high, low, and close prices, or HLC3) to detect market cycles. It smooths price movements to create an oscillator that swings between overbought and oversold levels.
EMAs: Seven EMAs of different lengths are applied to the ACO and scaled based on the market's dominant cycle. These EMAs are plotted as colorful, wavy lines to show trend direction.
Buy/Sell Signals: The script generates signals when the ACO crosses above or below user-defined thresholds, indicating potential entry or exit points.
Divergence Detection: The script identifies bullish or bearish divergences between the ACO and the fastest EMA, which may signal potential reversals.
Visual Style: The indicator uses a rainbow of seven colors (red, orange, yellow, green, blue, indigo, violet) for the EMAs, with wavy lines for a unique visual effect. Static levels (zero, overbought, oversold) are also wavy for consistency.
2. How to Add the Indicator to Your Chart
Open TradingView and load the chart of any asset (e.g., stock, forex, crypto).
Click on the Indicators button at the top of the chart.
Search for "Adaptive Cycle Oscillator with EMA" (or paste the script into TradingView’s Pine Editor if you have access to it).
Click to add the indicator to your chart. It will appear in a separate panel below the price chart.
3. Customizing the Indicator
The script offers several input options to tailor it to your needs:
Base Cycle Length (Default: 20): Sets the initial period for calculating the dominant cycle. Higher values make the indicator slower; lower values make it more sensitive.
Alpha Smoothing (Default: 0.07): Controls how much the ACO smooths price data. Smaller values produce smoother results.
Show Buy/Sell Signals (Default: True): Toggle to display green triangles (buy) and red triangles (sell) on the chart.
Threshold (Default: 0.0): Defines overbought (above threshold) and oversold (below threshold) levels. Adjust to widen or narrow signal zones.
EMA Base Length (Default: 10): Sets the starting length for the fastest EMA. Other EMAs are incrementally longer (12, 14, 16, etc.).
Divergence Lookback (Default: 14): Determines how far back the script looks to detect divergences.
To adjust these:
Right-click the indicator on your chart and select Settings.
Modify the inputs in the pop-up window.
Click OK to apply changes.
4. Reading the Indicator
Oscillator and EMAs: The ACO and seven EMAs are plotted in a separate panel. The EMAs (colored lines) move in a wavy pattern:
Red (fastest) to Violet (slowest) represent different response speeds.
When the faster EMAs (e.g., red, orange) are above slower ones (e.g., blue, violet), it suggests bullish momentum, and vice versa.
Zero Line: A gray wavy line at zero acts as a neutral level. The ACO above zero indicates bullish conditions; below zero indicates bearish conditions.
Overbought/Oversold Lines: Red (overbought) and green (oversold) wavy lines mark threshold levels. Extreme ACO values near these lines may suggest reversals.
Buy/Sell Signals:
Green Triangle (Bottom): Appears when the ACO crosses above the oversold threshold, suggesting a potential buy.
Red Triangle (Top): Appears when the ACO crosses below the overbought threshold, suggesting a potential sell.
Divergences:
Green Triangle (Bottom): Indicates a bullish divergence (price makes a lower low, but the EMA makes a higher low), hinting at a potential upward reversal.
Red Triangle (Top): Indicates a bearish divergence (price makes a higher high, but the EMA makes a lower high), hinting at a potential downward reversal.
5. Using Alerts
You can set alerts for key events:
Right-click the indicator and select Add Alert.
Choose a condition (e.g., "ACO Buy Signal", "Bullish Divergence").
Configure the alert settings (e.g., notify via email, app, or pop-up).
Click Create to activate the alert.
Available alert conditions:
ACO Buy Signal: When the ACO crosses above the oversold threshold.
ACO Sell Signal: When the ACO crosses below the overbought threshold.
Bullish Divergence: When a potential upward reversal is detected.
Bearish Divergence: When a potential downward reversal is detected.
6. Tips for Using the Indicator
Combine with Other Tools: Use the indicator alongside support/resistance levels, candlestick patterns, or other indicators (e.g., RSI, MACD) for confirmation.
Test on Different Timeframes: The indicator works on any timeframe (e.g., 1-minute, daily). Shorter timeframes may produce more signals but with more noise.
Practice Risk Management: Never rely solely on this indicator. Set stop-losses and position sizes to manage risk.
Backtest First: Use TradingView’s Strategy Tester (if you convert the script to a strategy) to evaluate performance on historical data.
Compliance with TradingView’s Script Publishing Rules
This description adheres to TradingView’s Script Publishing Rules (as outlined in the provided link):
No Performance Claims: The description avoids promising profits or specific results, emphasizing that the indicator is a tool for analysis.
Clear Instructions: It provides step-by-step guidance for adding, customizing, and using the indicator.
Risk Disclaimer: It notes that trading involves risks and the indicator should be used with other analysis methods.
No Misleading Terms: Terms like “buy” and “sell” are used to describe signals, not guaranteed actions.
Transparency: The description explains the indicator’s components (ACO, EMAs, signals, divergences) without exaggerating its capabilities.
No External Links: The description avoids linking to external resources or soliciting users.
Educational Tone: It focuses on educating users about the indicator’s functionality.
Limitations
Not a Standalone System: The indicator is not a complete trading strategy. It provides insights but requires additional analysis.
Lagging Nature: As with most oscillators and EMAs, signals may lag behind price movements, especially in fast markets.
False Signals: Signals and divergences may not always lead to successful trades, particularly in choppy markets.
Market Dependency: Performance varies across assets and market conditions (e.g., trending vs. ranging markets).
True Seasonal Pattern [tradeviZion]True Seasonal Pattern: Uncover Hidden Market Cycles
Markets have rhythms and patterns that repeat with surprising regularity. The True Seasonal Pattern indicator reveals these hidden cycles across different timeframes, helping you anticipate potential market movements based on historical seasonal tendencies.
What This Indicator Does
The True Seasonal Pattern analyzes years of historical price data to identify recurring seasonal trends. It then plots these patterns on your chart, showing you both the historical pattern and future projection based on past seasonal behavior.
Automatic Timeframe Detection: Works with Monthly, Weekly, and Daily charts
Historical Pattern Analysis: Analyzes up to 100 years of data (customizable)
Future Projection: Projects the seasonal pattern ahead on your chart
Smart Smoothing: Applies appropriate smoothing based on your timeframe
How to Use This Indicator
Add the indicator to a Daily, Weekly, or Monthly chart (not designed for intraday timeframes)
The indicator automatically detects your chart's timeframe
The blue line shows the historical seasonal pattern
Watch for potential turning points in the pattern that align with other technical signals
Seasonal patterns work best as a supporting factor in your analysis, not as standalone trading signals. They are particularly effective in markets with well-established seasonal influences.
Best Applications
Futures Markets: Commodities and futures often show strong seasonal tendencies due to production cycles, weather patterns, and economic factors
Stock Indices: Many stock markets demonstrate regular seasonal patterns (like the "Sell in May" phenomenon)
Individual Stocks: Companies with seasonal business cycles often show predictable price patterns
Practical Applications
Identify potential turning points based on historical seasonal patterns
Plan entries and exits around seasonal tendencies
Add seasonal context to your existing technical analysis
Understand why certain months or periods might show consistent behavior
Pro Tip: For best results, use this tool on instruments with at least 5+ years of historical data. Longer timeframes often reveal more reliable seasonal patterns.
Important Notes
This indicator works best on Daily, Weekly, and Monthly timeframes - not intraday charts
Seasonal patterns are tendencies, not guarantees
Always combine seasonal analysis with other technical tools
Past patterns may not repeat exactly in the future
// Sample of the seasonal calculation approach
float yearHigh = array.max(currentYearHighs)
float yearLow = array.min(currentYearLows)
// Calculate seasonality for each period
for i = 0 to array.size(currentYearCloses) - 1
float periodClose = array.get(currentYearCloses, i)
if not na(periodClose) and yearHigh != yearLow
float seasonality = (periodClose - yearLow) / (yearHigh - yearLow) * 100
I developed this indicator to help traders incorporate seasonal analysis into their trading approach without the complexity of traditional seasonal tools. Whether you're analyzing agricultural commodities, energy futures, or stock indices, understanding the seasonal context can provide valuable insights for your trading decisions.
Remember: Markets don't always follow seasonal patterns, but when they do, being aware of these tendencies can give you a meaningful edge in your analysis.
Leonid's Bitcoin Macro & Liquidity Regime Tracker🧠 Macro Overlay Score (Bitcoin Liquidity Regime Tracker)
This indicator combines the most important macroeconomic and on-chain inputs into a single unified score to help investors identify Bitcoin’s long-term cycle phases. Each input is normalized into a 0–100 score and blended using configurable weights to generate a dynamic, forward-looking macro regime tracker.
✅ Best used on the **Bitcoin All Time History Index with Weekly resolution** (`INDEX:BTCUSD`) for maximum historical context and signal clarity.
---
📈 Why Macro?
Macro liquidity conditions — interest rates, monetary expansion, dollar strength, credit risk — drive Bitcoin cycles . Risk assets like BTC thrive during periods of:
Monetary easing
Liquidity injections
Expansionary central bank policy
This overlay surfaces those periods *before* price follows. It captures cycle shifts in the business cycle, monetary policy, and investor sentiment — making it ideal for long-term allocators, macro-aligned investors, and cycle-focused BTC holders.
🔔 This is **not** designed for short-term or swing trading. It is optimized for **macro trend confirmation and regime awareness** — not fast entry/exit signals.
---
🔍 What It Tracks
Macro Inputs:
- 🏭 ISM 3M Trend (Business Cycle)
- 💹 CPI YoY (Inverted Inflation)
- 💵 M2 YoY + M2 Acceleration
- 🇨🇳 China M2 (Global Liquidity)
- 💱 DXY 3M Trend (USD Strength)
- 🏦 TGA & RRP YoY (Treasury / MMF Flows)
- 🏛 Fed Balance Sheet (WALCL)
- 💳 High Yield Spread (Credit Conditions)
- 💧 Net Liquidity Composite = WALCL – TGA – RRP
On-Chain Inputs:
- ⚠️ MVRV Ratio (Valuation Cycles)
- 🚀 Mayer Multiple Acceleration (200DMA Momentum)
---
🧩 How It Works
Each input is:
Normalized to a 0–100 score
Weighted by importance (fully configurable)
Combined into a **composite Macro Score**, then normalized across history
The chart will display:
🔷 A 0–100 **Macro Score Line**
🧭 **Cycle Phase classification**: Accumulation, Expansion, Distribution, Capitulation
📊 Optional **debug table** with all sub-scores
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🧠 Interpreting the Signal
| Signal Type | Meaning |
|-------------------|---------------------------------------------|
| Macro Score ↑ | Liquidity improving → Bullish regime forming |
| Macro Score ↓ | Liquidity deteriorating → Caution warranted |
| Score < 40 & Rising | 🔵 Accumulation cycle likely beginning |
| Score > 70 & Falling | 🟡 Distribution / Macro exhaustion |
| Net Liquidity ↑ | Strong driver of BTC upside historically |
---
❓ FAQ
Q: Why did the Macro Score peak in March 2021, but Bitcoin topped in November?
> The indicator reflects **macro liquidity**, not price momentum. M2 growth slowed, DXY bottomed, and the Fed stopped expanding WALCL by Q1 2021 — all signs of macro exhaustion. BTC continued on **residual momentum**, but the smart money began exiting months earlier.
Q: What does the score range mean?
- 0–25 : Tight liquidity, unfavorable conditions
- 50 : Neutral environment
- 75–100 : Strong easing, liquidity surge
Q: Is this good for short-term signals?
> No. This is a **macro-level overlay**, best used for 3–12 month context shifts, not day trades.
Q: Can I adjust the weights?
> Yes. You can tune the influence of each input to match your thesis (e.g., overweight on-chain, or global liquidity).
Q: Do I need special data access?
> No. All symbols are public TradingView datasets (FRED, CryptoCap, etc.). Just use this on a BTC chart like `BTCUSD`.
---
✅ How to Use
- Load on **`INDEX:BTCUSD`**, set to **Weekly timeframe**
- Confirm long-term bottoms when score is low and rising (Accumulation → Expansion)
- Watch for tops when score is high and falling (Distribution → Capitulation)
- Combine with price structure, realized profit/loss, and market sentiment
---
🚀 If you're serious about understanding Bitcoin's macro regime, this is your alpha map. Share it, clone it, and build on it.
NY Time Cycles# New York Time Cycles Indicator
## Overview
The Time Cycles indicator is a specialized technical analysis tool designed to divide the trading day into distinct time blocks based on New York trading hours. Developed for TradingView, this indicator helps traders identify and analyze market behavior during specific time periods throughout the trading session. The indicator displays six consecutive time blocks, each representing 90-minute segments of the trading day, while tracking price ranges within each block.
## Core Concept
The Time Cycles indicator is built on the premise that different periods during the trading day often exhibit unique market characteristics and behaviors. By segmenting the trading day into standardized 90-minute blocks, traders can:
1. Identify recurring patterns at specific times of day
2. Compare price action across different time blocks
3. Recognize potential support and resistance levels based on the high and low of previous time blocks
4. Develop time-based trading strategies specific to certain market hours
## Time Block Structure
The indicator divides the trading day into six sequential 90-minute blocks based on New York time:
1. **Box 1**: 07:00 - 08:30 ET
2. **Box 2**: 08:30 - 10:00 ET
3. **Box 3**: 10:00 - 11:30 ET
4. **Box 4**: 11:30 - 13:00 ET
5. **Box 5**: 13:00 - 14:30 ET
6. **Box 6**: 14:30 - 16:00 ET
These time blocks cover the core US trading session from pre-market into regular market hours.
## Visual Representation
Each time block is represented on the chart as a visual box that:
- Spans the exact time period of the block (horizontally)
- Extends from the highest high to the lowest low recorded during that time period (vertically)
- Is displayed with customizable colors and transparency levels
- Automatically builds in real-time as price action develops
Additionally, the indicator draws dashed projection lines that:
- Display the high and low of the most recently completed time block
- Extend forward in time (for up to 24 hours)
- Help traders identify potential support and resistance levels
## Technical Implementation
The indicator employs several key technical features:
1. **Time Detection**: Accurately identifies the current New York time to place each box in the correct time period
2. **Dynamic Box Creation**: Initializes and updates boxes in real-time as price action develops
3. **Range Tracking**: Continuously monitors and adjusts the high and low of each active time block
4. **Projection Lines**: Creates horizontal dashed lines projecting the high and low of the most recently completed time block
5. **Daily Reset**: Automatically resets all boxes and lines at the start of each new trading day
6. **Customization**: Allows users to set custom colors and transparency levels for each time block
This Time Cycles indicator provides traders with a structured framework for analyzing intraday market movements based on specific time periods. By understanding how the market typically behaves during each 90-minute block, traders can develop more targeted strategies and potentially identify higher-probability trading opportunities throughout the trading day.
HALC SYHALC SY @CK
Heikin Ashi Last Candle shows color of the last closed 30m heikin ashi candle for every new candle on your graph indicating local trend for scalp & short term trading in rder to help u choose right direction in your 1-5m tf trading. Non-repainting & designed for use on any graph type incl HA, Renko and other problematic syntetic as well as any of your own.
Dont recommend as entry signal but strong support to confirm/deny your trade system entry signal. Enjoy!
