Smart % Levels📈 Smart % Levels – Visualize Significant Percentage Moves
What it does:
This indicator plots horizontal levels based on a percentage change from the previous day's close (or open, if selected). It allows traders to visualize price movements relative to meaningful thresholds like ±1%, ±2%, etc.
What makes it different:
Unlike other level indicators, Smart % Levels only displays the relevant levels based on current price action. This avoids clutter by showing only the levels that are being approached or crossed by the current price. It's a clean and dynamic way to visualize key price zones for intraday analysis.
How it works:
- Select between using the previous day's Close or Open as the reference
- Choose the percentage spacing between levels (e.g., 1%, 0.5%, etc.)
- Enable optional labels to see the exact percentage of each level
- Automatically filters levels to only show those between yesterday's price and today's current price
- Includes customization for colors, line styles, widths, and opacity
Best for:
Day traders and scalpers who want a quick, clean view of how far the current price has moved from yesterday’s reference, without being overwhelmed by unnecessary lines.
Extra notes:
- The levels are recalculated each day at the market open
- All graphics reset at the start of each session to maintain clarity
- This script avoids repainting by only plotting levels relative to available historical data (no lookahead)
This tool is for informational purposes only and should not be considered as financial advice. Always do your own research before making trading decisions.
Forecasting
Daily ProtractorDaily Protractor Indicator
Overview
The Daily Protractor is a visually intuitive tool designed for traders who want to analyze price action through angular measurements on a 5-minute chart. By overlaying a protractor on the chart, this indicator helps identify potential support, resistance, and trend directions based on angular relationships from the first 5-minute candle of each day. It’s particularly useful for intraday traders looking to incorporate geometric analysis into their strategies for spot or strike charts.
Key Features
Dynamic Protractor Overlay: Draws a protractor centered on the low of the first 5-minute candle of each day, with customizable radius in both bars (horizontal) and price units (vertical).
Angular Measurements: Displays angles in 5-degree increments, covering a full 360° circle or a 105° to -105° (91° to 269°) half-circle, depending on user preference.
Customizable Display:
Adjust the number of days to display protractors (up to 5 days).
Customize line colors for different angle ranges (0° to 180°, 180° to 360°, and 0° specifically).
Modify line thickness, label size, and label colors for better visibility.
Center Point Highlight: Marks the center of each protractor with a labeled point for easy reference.
Efficient Design:
Optimized with max_lines_count, max_labels_count, and max_bars_back to ensure smooth performance on TradingView.
How It Works
The indicator identifies the first 5-minute candle of each day and uses its low price as the center point for a protractor. It then draws lines at 5-degree intervals, radiating from the center, with each line representing an angle from 0° to 360°. Labels at the end of each line display the angle in degrees, with negative values shown for angles between 195° and 345° (e.g., 270° is displayed as -90°). The protractor’s radius can be adjusted in both time (bars) and price units, allowing traders to scale the tool to their chart’s characteristics.
Usage Instructions
Add to Chart:
Apply the indicator to a 5-minute chart of your chosen instrument (e.g., spot or strike charts).
Interpret the Protractor:
Use the angular lines to identify potential price levels or trend directions.
The 0° line (horizontal) can act as a reference for horizontal support/resistance.
Angles between 0° and 180° (upper half) and 180° and 360° (lower half) are color-coded for quick identification.
Customize Settings:
Toggle the Show 105° to -105° option to display a half-circle (91° to 269°) instead of a full 360° protractor.
Adjust the Radius in Bars and Radius in Price Units to scale the protractor to your chart.
Set the Maximum Days to Display to control how many daily protractors are shown.
Modify line thickness, colors, and label settings to suit your visual preferences.
Customization Options
Protractor Settings:
Show 105° to -105° (91° to 269°): Toggle between a full circle or a half-circle protractor.
Radius in Bars: Set the horizontal span of the protractor (default: 75 bars).
Radius in Price Units: Set the vertical span in price units (default: 1000.0).
Maximum Days to Display: Limit the number of protractors shown (default: 5 days).
Line Settings:
Line Thickness: Adjust the thickness of the protractor lines (1 or 2).
Line Color (0° to 180°): Color for the upper half (default: light blue).
Line Color (180° to 360°): Color for the lower half (default: light red).
Line Color (0°): Color for the 0° line (default: black).
Label Settings:
Label Size: Choose between small, normal, or large labels.
Label Color (0° to 180°): Color for labels in the upper half (default: red).
Label Color (180° to 360°): Color for labels in the lower half (default: green).
Notes
The indicator was designed with the help of Grok3 for use on 5-minute charts only, as it relies on the first 5-minute candle of the day to set the protractor’s center.
For best results, adjust the radius settings to match the volatility and price scale of your instrument. However, where the price is in single digits it is advised to switch off the labels or I would suggest not to use the same.
The protractor can be used alongside other technical tools to confirm trends, reversals, or key price levels.
Limitations: This cannot be used on instruments that trade for more than 75 candles with a timeframe of 5 minutes as the angles would not cover the entire trading window. I am working coming up with a script to address this limitation.
Feedback
I’d love to hear your thoughts! If you find the Daily Protractor helpful or have suggestions for improvements, please leave a comment or reach out. Happy trading!
SuperTrader Trend Analysis and Trade Study DashboardSuperTrader Trend Analysis and Trade Study Dashboard
Overview
This script offers a multi-faceted look at market behavior. It combines signals from different momentum indicators, daily cross checks, and a specialized dashboard to reveal trend strength, potential divergences, and how far price has traveled from its recent averages.
Three Musketeers Method
This script uses a special set of three indicators (the “Three Musketeers”) to determine bullish or bearish pressure on the current chart.
Trend Condition – Compares fast vs. slow EMAs (50 and 200) and checks which side of the line price is favoring.
Mean Reversion Condition – Watches RSI crossing typical oversold or overbought thresholds (e.g., crossing above 30 or below 70).
Bollinger Condition – Checks whether price pushes above/below the Bollinger Bands (based on a 20 SMA + standard deviations).
When at least two out of these three conditions align in a bullish way, the script issues a Buy Signal . Conversely, if at least two align in a bearish way, a Sell Signal is triggered. This “Three Musketeers” synergy ensures multiple confirmations before calling a potential market turn.
Mag 8 Daily Performance
The script tracks eight highly influential stocks (AAPL, AMZN, GOOG, NFLX, NVDA, TSLA, META, MSFT) to see which are green (higher) or red (lower) compared to yesterday’s close. It then prints a quick tally – helpful in gauging overall market mood via these major players.
Golden / Death Cross Signals
On a daily time frame, the script notes when the 50-day SMA crosses above or below the 200-day SMA. A “Golden Cross” often signals rising momentum, while a “Death Cross” can hint at oncoming weakness.
RSI & Divergence Checks
RSI helps identify hidden turning points. Whenever a bullish or bearish divergence is spotted, the script updates you via a concise readout.
Hardcoded Settings
EMA lengths for trend checks, Bollinger parameters, etc., are locked in, letting you focus on adjusting only the pivotal study inputs (e.g., RSI length, VIDYA momentum).
VIDYA Trend Line & Fill
Built on an adaptive Variable Index Dynamic Average, it plots a line that quickly reacts to changing momentum. Users can set a “Trend Band Distance” to mark ATR-based thresholds around that line, identifying possible breakouts or breakdowns.
YoYo Distance
This concept measures how far price strays from SMA(10). If it’s too far, the script colors your display to indicate potential snapbacks.
Gap Up/Down Probability
By weighing volume, MACD signals, and whether price sits above/below its midrange, the script estimates probabilities of a gap up or down on the next daily candle.
Table Output & Trend Label
Turning on Show Table Widget reveals a quick dashboard on the chart detailing RSI, CCI, divergences, bull/bear scores, and more. A label on the last bar further summarizes overall trend, gap distance, and the Mag 8 snapshot – perfect for a fast read of current market posture.
Use this script to unify multiple signals in one place, see how far price has ventured from typical patterns, and get daily cross signals plus real-time bullish/bearish calls – all at a glance.
IU Smart Flow SystemDESCRIPTION
The IU Smart Flow System is a powerful and dynamic order flow-based strategy designed to capture high-probability trades by analyzing bullish and bearish imbalances, trend direction, and RSI strength. It identifies trading opportunities by aligning order flow conditions with the prevailing trend and momentum, making it suitable for trend-following and momentum-based trading.
This system utilizes a unique combination of:
- Order flow score to gauge market imbalance
- Trend filter using SMA and ATR to confirm market direction
- RSI to ensure entry only during strong momentum
USER INPUTS:
- Imbalance Length: Defines the lookback period for calculating bullish and bearish imbalances. (Default: 10)
- Trend Length: Determines the length of the SMA to evaluate the trend direction. (Default: 50)
- RSI Length: Specifies the RSI period to assess momentum strength. (Default: 14)
LONG CONDITIONS:
Long entries are triggered when:
- Order flow score is positive, indicating bullish imbalance
- Price is above the bullish trend level (SMA + ATR), confirming an uptrend
- RSI is above 50, indicating bullish momentum
- No active short position is currently open
SHORT CONDITIONS:
Short entries are triggered when:
- Order flow score is negative, indicating bearish imbalance
- Price is below the bearish trend level (SMA - ATR), confirming a downtrend
- RSI is below 50, indicating bearish momentum
- No active long position is currently open
WHY IT IS UNIQUE:
- Imbalance-Based Approach: Unlike traditional strategies that rely solely on price action, this system evaluates bullish and bearish imbalances to anticipate order flow direction.
- Adaptive Trend Filter: The combination of SMA and ATR dynamically adjusts to market volatility, providing a reliable trend confirmation mechanism.
- Momentum Validation with RSI: Ensures that entries are taken only in the direction of strong momentum, reducing false signals.
HOW USERS CAN BENEFIT FROM IT:
- Enhanced Trade Accuracy: Aligning order flow, trend, and momentum reduces false signals and improves trade success rates.
- Versatile Application: Suitable for various markets and timeframes, making it adaptable to different trading styles.
- Clear Trade Signals: Provides clear entry labels and alerts, ensuring traders never miss a potential opportunity.
- Visual Clarity: The filled region between bullish and bearish trends highlights trend direction, enhancing decision-making.
M2 Global Liquidity Index - X Days LeadThis custom indicator overlays the Bitcoin price chart with the Global Liquidity M2 chart, providing a unique perspective on how monetary supply might influence Bitcoin's price movements. The indicator distinguishes between past and future segments of the liquidity data using two distinct colors.
- Past Segment: The portion of the Global Liquidity M2 chart that has already passed is displayed in one color, allowing users to assess historical correlations with Bitcoin's price.
- Future Segment: The upcoming part of the liquidity chart is shown in a different color, offering insights into potential future impacts on Bitcoin's price trajectory.
by walkin
SPY MACD Histogram Reversals and RejectionsStrategy Overview: Intraday SPY Options Day Trading with MACD Histogram Reversals and Rejections
This is an intraday trading strategy designed specifically for trading SPY (or SPX) using 1DTE options. It focuses on price action during the morning session and leverages MACD histogram crossovers, volatility analysis, and short-term price rejections to enter directional trades (calls or puts). The goal is to capitalize on early momentum shifts and retracement failures after initial market moves.
Key Trading Hours and Constraints
Trading Window: Only trades between 9:50 AM and 1:00 PM EST are considered.
Trade Cutoff Buffer: New trades are blocked in the final 5 minutes before the 1:00 PM end time to avoid auto-close conflicts.
First Hour Focus: Special logic applies during the first hour of the session (9:30 AM to 10:30 AM), where reversal-based setups are tracked more aggressively.
MACD Histogram Setup
The strategy calculates both 5-minute and 10-minute MACD values.
Signals are generated when the 5-minute MACD histogram crosses the zero line, indicating a momentum shift.
The magnitude of the histogram (absolute value) must exceed a threshold (0.10) to validate strong enough momentum.
The 10-minute histogram is used as a confirmation filter: if it’s under 0.17 in magnitude, it favors a call entry (bullish breakout); otherwise, it defaults to put entry (bearish momentum).
Reversal & Protection Logic (Early Morning Retests)
Call Rejection Protection (To avoid entering long after a strong upward move and sharp retrace):
Monitors price from 9:30–10:00 AM for the lowest point.
Then from 10:00–10:35 AM, it tracks the highest price.
If price retraces more than 90% of that move up, it avoids new call entries.
Put Rejection Protection (To avoid entering short after a downward move and retrace):
Tracks the highest point from 9:30–10:00 AM, then the lowest price from 10:00–10:35 AM.
If price retraces more than 90% of that downward move, put entries are skipped.
This avoids buying into failed breakouts or deep retracements, protecting against reversal traps.
Entry Conditions Summary
A trade is considered only if:
It's within the allowed time window.
MACD histogram crosses zero with sufficient strength.
No retracement rejection conditions are triggered.
The 10-minute MACD filter confirms momentum direction.
Risk Management – Dynamic ATR-Based Stop Loss & Profit Target
Uses a 6-period ATR to size both the stop loss and profit target.
ATR multipliers are adjusted dynamically based on RSI(14) values to account for current volatility and overbought/oversold conditions:
Profit Targets: Scaled using an aggressive ATR multiplier tied to RSI position.
Stop Losses: Slightly wider to prevent premature exits from minor retracements.
This adaptive approach helps ensure realistic targets while keeping risk within bounds.
Options Profit Estimation
Estimated option move is calculated using:
The difference between entry price and the profit target (in underlying asset).
Assumes 0.48 delta to approximate the expected option gain/loss.
These values are displayed directly on the chart as part of the trade label.
Trade Execution and Labeling
Each trade is assigned a unique ID and visually labeled on the chart with:
Direction (Call or Put)
Profit target level
Estimated underlying move
Estimated option gain in dollars
Alerts are also triggered to notify on entry signals, showing the estimated option profit.
Performance Tracking and Statistics
Tracks total trades, wins, losses, and current win streak using strategy.closedtrades.
Displays these values in a live stats table on the chart for real-time feedback.
Additional Visual Aids
Table showing:
MACD profit targets and histograms
Estimated option moves
Intraday range (high – low)
Draws a horizontal line at the nearest rounded price level for quick visual context.
Marks key morning times (9:55, 10:00, and 10:30) with small labeled markers.
Overall Objective
This strategy aims to:
Catch early directional momentum in SPY within a controlled risk framework.
Avoid trading into retracements or false breakouts.
Provide visually clear, data-supported trade entries for real-time manual execution.
Estimate profitability in terms of options pricing for quick decision-making.
It's ideal for traders looking to day trade 0DTE or 1DTE SPY options using technical triggers, real-time filtering, and protective logic to reduce false signals and improve timing.
Futuristic Trend PredictorAI-based trend predictor. converting it to a strategy for backtesting. thanks.
Composite Reversal IndicatorOverview
The "Composite Reversal Indicator" aggregates five technical signals to produce a composite score that ranges from -5 (strongly bearish) to +5 (strongly bullish). These signals come from:
Relative Strength Index (RSI)
Moving Average Convergence Divergence (MACD)
Accumulation/Distribution (A/D)
Volume relative to its moving average
Price proximity to support and resistance levels
Each signal contributes a value of +1 (bullish), -1 (bearish), or 0 (neutral) to the total score. The raw score is plotted as a histogram, and a smoothed version is plotted as a colored line to highlight trends.
Step-by-Step Explanation
1. Customizable Inputs
The indicator starts with user-defined inputs that allow traders to tweak its settings. These inputs include:
RSI: Length (e.g., 14), oversold level (e.g., 30), and overbought level (e.g., 70).
MACD: Fast length (e.g., 12), slow length (e.g., 26), and signal length (e.g., 9).
Volume: Moving average length (e.g., 20) and multipliers for high (e.g., 1.5) and low (e.g., 0.5) volume thresholds.
Price Levels: Period for support and resistance (e.g., 50) and proximity percentage (e.g., 2%).
Score Smoothing: Length for smoothing the score (e.g., 5).
These inputs make the indicator adaptable to different trading styles, assets, or timeframes.
2. Indicator Calculations
The script calculates five key indicators using the input parameters:
RSI: Measures momentum and identifies overbought or oversold conditions.
Formula: rsi = ta.rsi(close, rsi_length)
Example: With a length of 14, it analyzes the past 14 bars of closing prices.
MACD: Tracks trend and momentum using two exponential moving averages (EMAs).
Formula: = ta.macd(close, macd_fast, macd_slow, macd_signal)
Components: MACD line (fast EMA - slow EMA), signal line (EMA of MACD line).
Accumulation/Distribution (A/D): A volume-based indicator showing buying or selling pressure.
Formula: ad = ta.accdist
Reflects cumulative flow based on price and volume.
Volume Moving Average: A simple moving average (SMA) of trading volume.
Formula: vol_ma = ta.sma(volume, vol_ma_length)
Example: A 20-bar SMA smooths volume data.
Support and Resistance Levels: Key price levels based on historical lows and highs.
Formulas:
support = ta.lowest(low, price_level_period)
resistance = ta.highest(high, price_level_period)
Example: Over 50 bars, it finds the lowest low and highest high.
These calculations provide the raw data for generating signals.
3. Signal Generation
Each indicator produces a signal based on specific conditions:
RSI Signal:
+1: RSI < oversold level (e.g., < 30) → potential bullish reversal.
-1: RSI > overbought level (e.g., > 70) → potential bearish reversal.
0: Otherwise.
Logic: Extreme RSI values suggest price may reverse.
MACD Signal:
+1: MACD line > signal line → bullish momentum.
-1: MACD line < signal line → bearish momentum.
0: Equal.
Logic: Crossovers indicate trend shifts.
A/D Signal:
+1: Current A/D > previous A/D → accumulation (bullish).
-1: Current A/D < previous A/D → distribution (bearish).
0: Unchanged.
Logic: Rising A/D shows buying pressure.
Volume Signal:
+1: Volume > high threshold (e.g., 1.5 × volume MA) → strong activity (bullish).
-1: Volume < low threshold (e.g., 0.5 × volume MA) → weak activity (bearish).
0: Otherwise.
Logic: Volume spikes often confirm reversals.
Price Signal:
+1: Close near support (within proximity %, e.g., 2%) → potential bounce.
-1: Close near resistance (within proximity %) → potential rejection.
0: Otherwise.
Logic: Price near key levels signals reversal zones.
4. Composite Score
The raw composite score is the sum of the five signals:
Formula: score = rsi_signal + macd_signal + ad_signal + vol_signal + price_signal
Range: -5 (all signals bearish) to +5 (all signals bullish).
Purpose: Combines multiple perspectives into one number.
5. Smoothed Score
A smoothed version of the score reduces noise:
Formula: score_ma = ta.sma(score, score_ma_length)
Example: With a length of 5, it averages the score over 5 bars.
Purpose: Highlights the trend rather than short-term fluctuations.
6. Visualization
The indicator plots two elements:
Raw Score: A gray histogram showing the composite score per bar.
Style: plot.style_histogram
Color: Gray.
Smoothed Score: A line that changes color:
Green: Score > 0 (bullish).
Red: Score < 0 (bearish).
Gray: Score = 0 (neutral).
Style: plot.style_line, thicker line (e.g., linewidth=2).
These visuals make it easy to spot potential reversals.
How It Works Together
The indicator combines signals from:
RSI: Momentum extremes.
MACD: Trend shifts.
A/D: Buying/selling pressure.
Volume: Confirmation of moves.
Price Levels: Key reversal zones.
By summing these into a composite score, it filters out noise and provides a unified signal. A high positive score (e.g., +3 to +5) suggests a bullish reversal, while a low negative score (e.g., -3 to -5) suggests a bearish reversal. The smoothed score helps traders focus on the trend.
Practical Use
Bullish Reversal: Smoothed score is green and rising → look for buying opportunities.
Bearish Reversal: Smoothed score is red and falling → consider selling or shorting.
Neutral: Score near 0 → wait for clearer signals.
Traders can adjust inputs to suit their strategy, making it versatile for stocks, forex, or crypto.
Pivot S/R with Volatility Filter## *📌 Indicator Purpose*
This indicator identifies *key support/resistance levels* using pivot points while also:
✅ Detecting *high-volume liquidity traps* (stop hunts)
✅ Filtering insignificant pivots via *ATR (Average True Range) volatility*
✅ Tracking *test counts and breakouts* to measure level strength
---
## *⚙ SETTINGS – Detailed Breakdown*
### *1️⃣ ◆ General Settings*
#### *🔹 Pivot Length*
- *Purpose:* Determines how many bars to analyze when identifying pivots.
- *Usage:*
- *Low values (5-20):* More pivots, better for scalping.
- *High values (50-200):* Fewer but stronger levels for swing trading.
- *Example:*
- Pivot Length = 50 → Only the most significant highs/lows over 50 bars are marked.
#### *🔹 Test Threshold (Max Test Count)*
- *Purpose:* Sets how many times a level can be tested before being invalidated.
- *Example:*
- Test Threshold = 3 → After 3 tests, the level is ignored (likely to break).
#### *🔹 Zone Range*
- *Purpose:* Creates a price buffer around pivots (±0.001 by default).
- *Why?* Markets often respect "zones" rather than exact prices.
---
### *2️⃣ ◆ Volatility Filter (ATR)*
#### *🔹 ATR Period*
- *Purpose:* Smoothing period for Average True Range calculation.
- *Default:* 14 (standard for volatility measurement).
#### *🔹 ATR Multiplier (Min Move)*
- *Purpose:* Requires pivots to show *meaningful price movement*.
- *Formula:* Min Move = ATR × Multiplier
- *Example:*
- ATR = 10 pips, Multiplier = 1.5 → Only pivots with *15+ pip swings* are valid.
#### *🔹 Show ATR Filter Info*
- Displays current ATR and minimum move requirements on the chart.
---
### *3️⃣ ◆ Volume Analysis*
#### *🔹 Volume Change Threshold (%)*
- *Purpose:* Filters for *unusual volume spikes* (institutional activity).
- *Example:*
- Threshold = 1.2 → Requires *120% of average volume* to confirm signals.
#### *🔹 Volume MA Period*
- *Purpose:* Lookback period for "normal" volume calculation.
---
### *4️⃣ ◆ Wick Analysis*
#### *🔹 Wick Length Threshold (Ratio)*
- *Purpose:* Ensures rejection candles have *long wicks* (strong reversals).
- *Formula:* Wick Ratio = (Upper Wick + Lower Wick) / Candle Range
- *Example:*
- Threshold = 0.6 → 60% of the candle must be wicks.
#### *🔹 Min Wick Size (ATR %)*
- *Purpose:* Filters out small wicks in volatile markets.
- *Example:*
- ATR = 20 pips, MinWickSize = 1% → Wicks under *0.2 pips* are ignored.
---
### *5️⃣ ◆ Display Settings*
- *Show Zones:* Toggles support/resistance shaded areas.
- *Show Traps:* Highlights liquidity traps (▲/▼ symbols).
- *Show Tests:* Displays how many times levels were tested.
- *Zone Transparency:* Adjusts opacity of zones.
---
## *🎯 Practical Use Cases*
### *1️⃣ Liquidity Trap Detection*
- *Scenario:* Price spikes *above resistance* then reverses sharply.
- *Requirements:*
- Long wick (Wick Ratio > 0.6)
- High volume (Volume > Threshold)
- *Outcome:* *Short Trap* signal (▼) appears.
### *2️⃣ Strong Support Level*
- *Scenario:* Price bounces *3 times* from the same level.
- *Indicator Action:*
- Labels the level with test count (3/5 = 3 tests out of max 5).
- Turns *red* if broken (Break Count > 0).
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
Deep Dive: How This Indicator Works*
This indicator combines *four professional trading concepts* into one powerful tool:
1. *Classic Pivot Point Theory*
- Identifies swing highs/lows where price previously reversed
- Unlike basic pivot indicators, ours uses *confirmed pivots only* (filtered by ATR)
2. *Volume-Weighted Validation*
- Requires unusual trading volume to confirm levels
- Filters out "phantom" levels with low participation
3. *ATR Volatility Filtering*
- Eliminates insignificant price swings in choppy markets
- Ensures only meaningful levels are plotted
4. *Liquidity Trap Detection*
- Spots institutional stop hunts where markets fake out traders
- Uses wick analysis + volume spikes for high-probability signals
---
## *📊 Parameter Encyclopedia (Expanded)*
### *1️⃣ Pivot Engine Settings*
#### *Pivot Length (50)*
- *What It Does:*
Determines how many bars to analyze when searching for swing highs/lows.
- *Professional Adjustment Guide:*
| Trading Style | Recommended Value | Why? |
|--------------|------------------|------|
| Scalping | 10-20 | Captures short-term levels |
| Day Trading | 30-50 | Balanced approach |
| Swing Trading| 50-200 | Focuses on major levels |
- *Real Market Example:*
On NASDAQ 5-minute chart:
- Length=20: Identifies levels holding for ~2 hours
- Length=50: Finds levels respected for entire trading day
#### *Test Threshold (5)*
- *Advanced Insight:*
Institutions often test levels 3-5 times before breaking them. This setting mimics the "probe and push" strategy used by smart money.
- *Psychology Behind It:*
Retail traders typically give up after 2-3 tests, while institutions keep testing until stops are run.
---
### *2️⃣ Volatility Filter System*
#### *ATR Multiplier (1.0)*
- *Professional Formula:*
Minimum Valid Swing = ATR(14) × Multiplier
- *Market-Specific Recommendations:*
| Market Type | Optimal Multiplier |
|------------------|--------------------|
| Forex Majors | 0.8-1.2 |
| Crypto (BTC/ETH) | 1.5-2.5 |
| SP500 Stocks | 1.0-1.5 |
- *Why It Matters:*
In EUR/USD (ATR=10 pips):
- Multiplier=1.0 → Requires 10 pip swings
- Multiplier=1.5 → Requires 15 pip swings (fewer but higher quality levels)
---
### *3️⃣ Volume Confirmation System*
#### *Volume Threshold (1.2)*
- *Institutional Benchmark:*
- 1.2x = Moderate institutional interest
- 1.5x+ = Strong smart money activity
- *Volume Spike Case Study:*
*Before Apple Earnings:*
- Normal volume: 2M shares
- Spike threshold (1.2): 2.4M shares
- Actual volume: 3.1M shares → STRONG confirmation
---
### *4️⃣ Liquidity Trap Detection*
#### *Wick Analysis System*
- *Two-Filter Verification:*
1. *Wick Ratio (0.6):*
- Ensures majority of candle shows rejection
- Formula: (UpperWick + LowerWick) / Total Range > 0.6
2. *Min Wick Size (1% ATR):*
- Prevents false signals in flat markets
- Example: ATR=20 pips → Min wick=0.2 pips
- *Trap Identification Flowchart:*
Price Enters Zone →
Spikes Beyond Level →
Shows Long Wick →
Volume > Threshold →
TRAP CONFIRMED
---
## *💡 Master-Level Usage Techniques*
### *Institutional Order Flow Analysis*
1. *Step 1:* Identify pivot levels with ≥3 tests
2. *Step 2:* Watch for volume contraction near levels
3. *Step 3:* Enter when trap signal appears with:
- Wick > 2×ATR
- Volume > 1.5× average
### *Multi-Timeframe Confirmation*
1. *Higher TF:* Find weekly/monthly pivots
2. *Lower TF:* Use this indicator for precise entries
3. *Example:*
- Weekly pivot at $180
- 4H shows liquidity trap → High-probability reversal
---
## *⚠ Critical Mistakes to Avoid*
1. *Using Default Settings Everywhere*
- Crude oil needs higher ATR multiplier than bonds
2. *Ignoring Trap Context*
- Traps work best at:
- All-time highs/lows
- Major psychological numbers (00/50 levels)
3. *Overlooking Cumulative Volume*
- Check if volume is building over multiple tests
MenthorQ Scanner HKThanks to DaveTrade55 for the source code. Just made a few changes for our Discord Groups popular names. The Degen Den
OPR First 15Stupidely simple indicator, It creates a box all around the first 15 minutes of the OPR of London and NY. I'st just boring to do it everyday ... It can be used only in 1 minute timeframe.
Hossa SignalsHow It Works
The "Hossa Signals" indicator generates trading signals based on four distinct strategy modes:
Mode 1 & 2 (Counter Trade Strategies):
These modes trigger buy signals when the price falls below a moving average (SMA50 for Mode 1, SMA200 for Mode 2) combined with a low RSI (having been below 26), and sell signals when the price rises above these SMAs combined with a high RSI (previously above 74).
Mode 3 & 4 (Trend Respect Strategies):
These modes generate buy signals when the price crosses above the respective moving average (SMA50 for Mode 3, SMA200 for Mode 4) and the RSI is strong (above 55 after touching 50), and sell signals when the price crosses below these levels with the RSI dropping below 45.
Additional conditions for taking profit are built into each mode, and the indicator tracks position status to help reset the conditions after a trade is closed.
Signals are plotted directly on the chart with labels (displaying "KUP" for buy and "SPRZEDAJ" for sell) and shapes for visual clarity. The current RSI value is also shown in the top-right corner.
How to Use It
Trade Entry:
For example, in Mode 1, if the price dips below SMA50, the RSI has been low (below 26) and is now rising above 30, a buy signal is generated. This may signal a counter-trend opportunity when the price has oversold.
Trade Exit:
Conversely, if the price rises above SMA50 while the RSI is falling (having been high above 74 and now dropping below 70), a sell signal is generated to exit the trade.
Risk Management:
Take profit (TP) conditions are set based on price action or RSI levels. These conditions help you exit a trade once the market moves in your favor, ensuring you lock in profits.
Example Strategy
Counter-Trend Setup (Mode 1):
Buy: Enter a long position when the price drops below the 50-period SMA and the RSI has been oversold (below 26) but starts to recover (rises above 30).
Sell/TP: Exit when the price moves above the SMA or the RSI reaches a high level (above 70).
Trend Respect Setup (Mode 3):
Buy: Enter when the price crosses above the 50-period SMA and the RSI, after touching around 50, moves up above 55.
Sell/TP: Exit when the price reverses (crosses below the SMA) or the RSI drops below 45.
Combine this indicator with other analysis tools (like volume or support/resistance levels) to refine your entry and exit points.
Please Share
If you find the "Hossa Signals" indicator useful for your trading strategy, please share it with your fellow traders. Sharing helps grow our community and encourages the development of more innovative trading tools.
Enjoy your trading!
Hossa OTF 4-candles"Hossa OTF 4-candles," overlays mini-representations of the higher timeframe candle on your current chart and displays a countdown timer showing how much time remains until that higher timeframe candle closes. Here’s how it works and how you might use it:
How It Works
Multi-Timeframe Display:
The indicator fetches the open, high, low, and close of a higher timeframe candle based on the timeframe you select (for example, 1H, 4H, 8H, 1D, or 1W). It then draws four mini-candles that update as new higher timeframe candles are formed.
Simple Stopwatch Countdown:
It retrieves the open time of the current higher timeframe candle and calculates its full duration (using the timeframe’s minutes converted to milliseconds). The indicator then subtracts the elapsed time from the total duration to show a countdown (formatted in hours and minutes) that tells you how long until the current candle closes.
How to Use It
Multi-Timeframe Analysis:
Use this indicator to see at a glance the status of the higher timeframe candle while you trade on a lower timeframe. For instance, if you're trading on a 5-minute chart but want to see what the 4-hour candle is doing, this indicator places a mini-representation of that 4-hour candle right on your chart.
Time-Based Entries/Exits:
The countdown helps you prepare for potential shifts in market sentiment as the higher timeframe candle closes. For example, if you notice a pattern or reversal setup on your lower timeframe near the end of the higher timeframe candle, it could signal an opportunity to enter or exit a trade.
Confluence with Other Indicators:
Combine this tool with other technical indicators (like RSI, MACD, or moving averages) to build a strategy. For instance, you might wait for a divergence on the lower timeframe as the higher timeframe candle nears its close, which can serve as an extra signal for a potential reversal or breakout.
Example Strategy
Trend Confirmation:
Suppose the 4-hour candle is trending upward. Use the mini-candles and countdown timer to monitor when the current 4-hour candle is about to close.
Entry Signal:
If you see a bullish divergence on your lower timeframe (say, on a 15-minute chart) near the end of the 4-hour candle (as the countdown nears zero), this could signal that the uptrend might continue, suggesting a potential buy signal.
Exit Signal:
Conversely, if you see bearish price action or a breakdown of support as the candle closes, you might consider exiting long positions or even taking a short trade.
Please Share
If you find this indicator useful for your multi-timeframe analysis and timing-based strategies, please consider sharing it with your fellow traders. Sharing helps improve our community's tools and fosters collaboration among traders!
MTF EMA 20 Overlay (15m / 30m / 1h)📌 Multi-Timeframe EMA 20 Overlay — Perfect for scalping and trend-following traders.
This script displays the 20 EMA from 15-minute, 30-minute, and 1-hour timeframes directly on your current chart (e.g., 5-minute).
🟢 15m EMA 20 — Short-term confirmation
🟠 30m EMA 20 — Mid-level support/resistance
🔴 1h EMA 20 — Major trend guide
💡 Ideal for:
• Spotting key pullback zones
• Identifying intraday trend strength
• Aligning lower timeframe entries with higher timeframe structure
🎯 Strategy Tip:
Longs are higher probability when price is above the 15m/30m/1h EMAs. Watch for rejections or bounces near these levels.
Created with ❤️ by @little swiss + ChatGPT support.
hammer1822Indicator that helps identify hammer patterns, both bullish and bearish, taking into account previous highs and lows.
TREND and ZL FLOWHow It Helps Traders
Trend Identification with T3 Moving Average
The script calculates a T3 moving average using a smoother version of traditional moving averages, reducing lag and providing a clearer view of trend direction.
A histogram is plotted, where green bars indicate an uptrend and red bars signal a downtrend. This helps traders visually confirm the market trend and avoid false signals.
Zero Lag Moving Average (ZLMA) for Faster Reversals
The ZLMA is designed to react more quickly to price changes while minimizing lag. It helps traders spot trend reversals sooner than traditional moving averages.
The line color changes green for bullish momentum and red for bearish momentum, making it easier to spot shifts in direction.
Overall, this indicator is useful for trend-following traders who want to capture momentum shifts efficiently. It can be particularly helpful for day traders and swing traders looking for early trend confirmation and automated trade signals.
Bitcoin Power LawThis is the main body version of the script. The Oscillator version can be found here .
Firstly, we would like to give credit to @apsk32 and @x_X_77_X_x as part of the code originates from their work. Additionally, @apsk32 is widely credited with applying the Power Law concept to Bitcoin and popularizing this model within the crypto community. Additionally, the visual layout is fully inspired by @apsk32's designs, and we think it looks amazing. So much so that we had to turn it into a TradingView script. Thank you!
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift . This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point C, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Bitcoin Power Law OscillatorThis is the oscillator version of the script. The main body of the script can be found here .
Firstly, we would like to give credit to @apsk32 and @x_X_77_X_x as part of the code originates from their work. Additionally, @apsk32 is widely credited with applying the Power Law concept to Bitcoin and popularizing this model within the crypto community. Additionally, the visual layout is fully inspired by @apsk32's designs, and we think it looks amazing. So much so that we had to turn it into a TradingView script. Thank you!
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift . This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point C, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
Bitcoin Polynomial Regression ModelThis is the main version of the script. Click here for the Oscillator part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines. The Oscillator version can be found here.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
Bitcoin Polynomial Regression OscillatorThis is the oscillator version of the script. Click here for the other part of the script.
💡Why this model was created:
One of the key issues with most existing models, including our own Bitcoin Log Growth Curve Model , is that they often fail to realistically account for diminishing returns. As a result, they may present overly optimistic bull cycle targets (hence, we introduced alternative settings in our previous Bitcoin Log Growth Curve Model).
This new model however, has been built from the ground up with a primary focus on incorporating the principle of diminishing returns. It directly responds to this concept, which has been briefly explored here .
📉The theory of diminishing returns:
This theory suggests that as each four-year market cycle unfolds, volatility gradually decreases, leading to more tempered price movements. It also implies that the price increase from one cycle peak to the next will decrease over time as the asset matures. The same pattern applies to cycle lows and the relationship between tops and bottoms. In essence, these price movements are interconnected and should generally follow a consistent pattern. We believe this model provides a more realistic outlook on bull and bear market cycles.
To better understand this theory, the relationships between cycle tops and bottoms are outlined below:https://www.tradingview.com/x/7Hldzsf2/
🔧Creation of the model:
For those interested in how this model was created, the process is explained here. Otherwise, feel free to skip this section.
This model is based on two separate cubic polynomial regression lines. One for the top price trend and another for the bottom. Both follow the general cubic polynomial function:
ax^3 +bx^2 + cx + d.
In this equation, x represents the weekly bar index minus an offset, while a, b, c, and d are determined through polynomial regression analysis. The input (x, y) values used for the polynomial regression analysis are as follows:
Top regression line (x, y) values:
113, 18.6
240, 1004
451, 19128
655, 65502
Bottom regression line (x, y) values:
103, 2.5
267, 211
471, 3193
676, 16255
The values above correspond to historical Bitcoin cycle tops and bottoms, where x is the weekly bar index and y is the weekly closing price of Bitcoin. The best fit is determined using metrics such as R-squared values, residual error analysis, and visual inspection. While the exact details of this evaluation are beyond the scope of this post, the following optimal parameters were found:
Top regression line parameter values:
a: 0.000202798
b: 0.0872922
c: -30.88805
d: 1827.14113
Bottom regression line parameter values:
a: 0.000138314
b: -0.0768236
c: 13.90555
d: -765.8892
📊Polynomial Regression Oscillator:
This publication also includes the oscillator version of the this model which is displayed at the bottom of the screen. The oscillator applies a logarithmic transformation to the price and the regression lines using the formula log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed top and bottom regression line with the formula:
normalized price = log(close) - log(bottom regression line) / log(top regression line) - log(bottom regression line)
This transformation results in a price value between 0 and 1 between both the regression lines.
🔍Interpretation of the Model:
In general, the red area represents a caution zone, as historically, the price has often been near its cycle market top within this range. On the other hand, the green area is considered an area of opportunity, as historically, it has corresponded to the market bottom.
The top regression line serves as a signal for the absolute market cycle peak, while the bottom regression line indicates the absolute market cycle bottom.
Additionally, this model provides a predicted range for Bitcoin's future price movements, which can be used to make extrapolated predictions. We will explore this further below.
🔮Future Predictions:
Finally, let's discuss what this model actually predicts for the potential upcoming market cycle top and the corresponding market cycle bottom. In our previous post here , a cycle interval analysis was performed to predict a likely time window for the next cycle top and bottom:
In the image, it is predicted that the next top-to-top cycle interval will be 208 weeks, which translates to November 3rd, 2025. It is also predicted that the bottom-to-top cycle interval will be 152 weeks, which corresponds to October 13th, 2025. On the macro level, these two dates align quite well. For our prediction, we take the average of these two dates: October 24th 2025. This will be our target date for the bull cycle top.
Now, let's do the same for the upcoming cycle bottom. The bottom-to-bottom cycle interval is predicted to be 205 weeks, which translates to October 19th, 2026, and the top-to-bottom cycle interval is predicted to be 259 weeks, which corresponds to October 26th, 2026. We then take the average of these two dates, predicting a bear cycle bottom date target of October 19th, 2026.
Now that we have our predicted top and bottom cycle date targets, we can simply reference these two dates to our model, giving us the Bitcoin top price prediction in the range of 152,000 in Q4 2025 and a subsequent bottom price prediction in the range of 46,500 in Q4 2026.
For those interested in understanding what this specifically means for the predicted diminishing return top and bottom cycle values, the image below displays these predicted values. The new values are highlighted in yellow:
And of course, keep in mind that these targets are just rough estimates. While we've done our best to estimate these targets through a data-driven approach, markets will always remain unpredictable in nature. What are your targets? Feel free to share them in the comment section below.
VIX Implied MovesKey Features:
Three Timeframe Bands:
Daily: Blue bands showing ±1σ expected move
Weekly: Green bands showing ±1σ expected move
30-Day: Red bands showing ±1σ expected move
Calculation Methodology:
Uses VIX's annualized volatility converted to specific timeframes using square root of time rule
Trading day convention (252 days/year)
Band width = Price × (VIX/100) ÷ √(number of periods)
Visual Features:
Colored semi-transparent backgrounds between bands
Progressive line thickness (thinner for shorter timeframes)
Real-time updates as VIX and ES prices change
Example Calculation (VIX=20, ES=5000):
Daily move = 5000 × (20/100)/√252 ≈ ±63 points
Weekly move = 5000 × (20/100)/√50 ≈ ±141 points
Monthly move = 5000 × (20/100)/√21 ≈ ±218 points
This indicator helps visualize expected price ranges based on current volatility conditions, with wider bands indicating higher market uncertainty. The probabilistic ranges represent 68% confidence levels (1 standard deviation) derived from options pricing.
Date-Based Price Projection (Offset)Predict future price movements by analyzing past trends—customizable, visually intuitive, and perfect for traders! 📊🚀
1️⃣ Predict Future Prices: Uses past price movements to project potential future trends.
2️⃣ Custom Date Selection: Analyze price behavior from any historical date of your choice.
3️⃣ Time Offset Feature: Shift data forward or backward to compare past trends with today.
4️⃣ Visual Projections: Displays future price estimates in a stylish table for easy reference.
5️⃣ Color-Coded Movements: Green for uptrends, red for downtrends—customizable to your preference.
6️⃣ Avoids Weekend Bias: Automatically skips non-trading days for accurate projections.
7️⃣ Great for Trend Analysis: Identify repeating price patterns to enhance trading strategies.
8️⃣ Quick Insights: Instantly see percentage changes and projected prices at a glance.
9️⃣ Works on Any Market: Use it for stocks, forex, crypto, or any chart with historical data.
🔟 Boosts Decision-Making: Helps traders anticipate potential price movements with confidence! 🚀
