Bitcoin Logarithmic Regression OscillatorOverview
The Bitcoin Logarithmic Regression Oscillator (BLR Osc.) is an analytical tool designed to measure Bitcoin's price deviation from its historical logarithmic growth curve. By comparing the current price to a mathematical "fair value," this indicator helps traders and investors identify macroeconomic accumulation zones and potential market cycle peaks.
How it Works
Historically, Bitcoin's price action has followed a non-linear, logarithmic growth trajectory where the rate of growth slows down over time. This script calculates a theoretical "fair value" based on the number of days since the first available price data, using the following logarithmic regression model:
Fair Value = 10^(a * ln(days) + b)
The oscillator at the bottom of the chart represents the natural logarithm of the ratio between the current closing price and this fair value math.log(close / fairValue)
A value of 0 means the price is exactly at its fair value.
Positive values indicate overvaluation and potential market exuberance (cycle tops).
Negative values highlight undervaluation and accumulation phases (bear market bottoms).
How to Use
Monitor the oscillator in the lower pane to gauge the current stage of the market cycle. When the oscillator drops below the user-defined Buy Threshold (default is -0.50), the script highlights these undervalued zones by turning both the oscillator line and the price line green.
💡 Visualization Tip:
If you want to see the regression curve and colored line on your main chart pane more clearly, you can hide the default standard Bitcoin candles using the chart's object tree/settings.
Conversely, if you only want to use the oscillator in the lower pane and keep your main chart clean, simply uncheck the "Plot on the Main Pane" option in the indicator's settings.
Curve Calibration & Customization
The default mathematical coefficients provided in this script are based on an approximation fitted on March 30, 2026 (with an R² = 0.9720).
Because the logarithmic curve requires periodic recalibration as new market data emerges, advanced users can perform their own mathematical approximations. You can easily update the coefficients by entering your new a (slope) , b (intercept) , and offset (days) values directly into the indicator's settings menu under the "Logarithmic Regression" group. There is no need to edit the source code. Indicator
Pi Cycle Top OscillatorOverview
The Pi Cycle Top Oscillator is an advanced, adaptive iteration of the classic Pi Cycle Top indicator, reimagined as a continuous risk metric. While the original indicator famously predicted Bitcoin’s macro peaks by waiting for a binary crossover of the 111-day SMA and the 2x 350-day SMA, this script translates the relationship between these two moving averages into a normalized 0 to 1 oscillator, providing both buy and sell signals.
As an asset matures, its volatility historically compresses. In the 2021 cycle, the classic moving averages barely touched, meaning future cycles might never see a pure crossover due to the law of diminishing returns. This oscillator solves that problem by replacing the rigid crossover requirement with dynamic, regression-based boundaries.
Tip
Hide the Bitcoin price chart to clearly view the metric in the main chart pane:
How it Works
Instead of waiting for a binary signal, this indicator calculates the exact mathematical ratio between the two moving averages:
ratio = ta.sma(close, 111) / (ta.sma(close, 350) * 2)
Using historical extremes of this ratio, the script projects two dynamic boundaries:
Top Boundary: A logarithmic regression curve that accounts for historical volatility decay, descending over time.
Bottom Boundary: A linear regression line representing macro bottoms.
The current ratio is then normalized between these two converging lines, producing a continuous Risk metric.
Key Features
Continuous Risk Scale: Unlike the classic indicator which is either "on" or "off", this oscillator provides a constant reading from 0 (historical bottom) to 1 (probable macro top).
Volatility Adjusted: The logarithmic top line factors in macro volatility decay, ensuring the indicator remains relevant in future cycles even if a classic crossover never occurs.
Visual Chart Feedback: The main chart automatically highlights price bars in Green when Risk falls below your custom Buy Zone Level, and Red when Risk exceeds your Sell Zone Level.
Dual Display Modes: Use the indicator settings to toggle between the normalized 0-1 "Oscillator" view and the raw "Fit Lines" view to see the actual ratio and regression curves.
How to Use
This tool is designed for macro-level portfolio risk management rather than short-term trading.
Accumulation: Readings near or below 0.1 historically correlate with macro bottoms, presenting potential long-term accumulation zones.
Distribution: Readings near or above 0.9 indicate severe market overheating, signaling potential distribution zones.
You can adjust the Buy and Sell zone thresholds in the indicator settings to fit your personal risk tolerance.
Limitations
Bitcoin Exclusive: This indicator is designed strictly for analyzing Bitcoin. Its mathematical model is based entirely on Bitcoin's historical macro cycles and is not applicable to other cryptocurrencies or traditional assets.
No Guaranteed Extremes: There are no guarantees that the oscillator will reach the upper or lower boundaries in future cycles, nor that it will remain strictly within the 0 to 1 range. For example, during the 2025 cycle, the oscillator never reached the theoretical sell zone, demonstrating that market dynamics can and do shift.
Static Curve Fitting: The regression curves for the upper and lower boundaries were fitted using the global tops and bottoms of the 111-day and 2x 350-day SMA ratio prior to 2023. The resulting equation coefficients are hardcoded directly into the script. As new macro extremes form in the future, these boundary models may eventually require a new approximation to maintain their accuracy.
Indicator
Indicator
Contrarian Extremes: VIX + Put/Call (CPC, PCC)What this indicator does (in one line :) ):
It highlights sentiment extremes using only CPC, PCC , and VIX , so you can spot the moments when the market is most likely overreacting.
Most indicators try to “predict” price. This one is simpler, it tracks Fear vs Euphoria and marks the zones where emotions are stretched.
The 3 inputs behind it
INDEX:CPC (TotalPut/Call) --> broad options sentiment
USI:PCC --> equity/retail-style fear proxy
CBOE:VIX --> volatility stress / hedging pressure
What you’ll see on the chart
The script paints the background based on 3 regimes:
🫨 Panic --> extreme stress (capitulation-type conditions) --> 🎶 The background music is (Melancholy Man by The Moody Blues) 😨
😰 Fear / Risk-Off --> elevated fear --> defensive positioning
😌 Complacency / Calm --> low fear --> “everything is fine” mode --> 🎶 The background music is (What a Wonderful World by Louis Armstrong) 😁
All thresholds and colors are fully customizable in the Inputs, so you can also change the criteria to get higher or lower frequency signals on the chart.
How I personally interpret it (as a long-term investor)
In my backtests, this indicator behaves like a contrarian compass:
Fear / Panic zones often show up close to better long-term buy areas (not perfect timing, but good asymmetric entries).
Complacency zones often show up near better long-term reduce / take-profit areas (or at least be careful with fresh risk here).
This is not magic and it’s not a buy/sell button. Markets can stay fearful or complacent longer than you expect. But as a long-term investor , this helps you stop chasing hype and start scaling decisions around emotion extremes.
A simple long-term workflow:
Use Daily or Weekly timeframe.
When Fear/Panic appears: consider scaling in (DCA entries, add on confirmation, respect your risk limits).
When Complacency appears: consider scaling out, tightening risk, or being picky with new buys.
Always combine with basics: trend, levels, market structure, and risk management.
Where it tends to work best
Interestingly, this doesn’t only fit S&P/Nasdaq. It also behaves well on:
OANDA:XAUUSD & OANDA:XAGUSD
Large-cap stocks ( NASDAQ:AAPL NASDAQ:NVDA NASDAQ:MSFT NASDAQ:GOOG NASDAQ:AMZN NASDAQ:TSLA NASDAQ:META )
BINANCE:BTCUSD & BINANCE:ETHUSD
In general, it tends to work better (i.e. helps you more) in markets that move more on fear and greed and less on deep fundamental re-pricing.
⚠️ Disclaimer: educational tool only. No indicator is a guarantee. Use proper position sizing and understand the product you trade. Indicator
MVRV Z-Score (DEMA Smoothed) | CipherDecodedMVRV Z-Score (DEMA Smoothed) | CipherDecoded
Overview
The MVRV Z-Score (DEMA Smoothed) is a structural trend-following oscillator derived from Bitcoin’s on-chain capital positioning.
Rather than interpreting MVRV purely as a valuation metric, this implementation treats the relationship between market value and realized value as a proxy for capital regime expansion and contraction. By statistically normalizing MVRV and applying Double Exponential Moving Average (DEMA) smoothing, the indicator converts on-chain profitability dynamics into a tradable trend signal.
The result is a regime-sensitive momentum framework anchored to underlying cost basis structure.
Structural Rationale
Market cycles are driven by shifts in aggregate positioning:
When market value persistently exceeds realized value, capital is in profit and reflexive expansion tends to dominate.
When market value compresses toward or below realized value, distribution and contraction phases emerge.
By standardizing MVRV into a rolling Z-score, the indicator measures the velocity and persistence of profitability expansion, not just its magnitude.
The subsequent DEMA smoothing filters short-term volatility while preserving structural inflection points, making the signal more suitable for systematic trend models.
Inputs
BTC Market Capitalization
BTC Realized Market Capitalization
Daily confirmed data to prevent repainting
Z-Score Normalization
Rolling lookback mean and standard deviation
Converts raw ratio into standardized regime measure
DEMA Smoothing
Applied to the Z-score output
Reduces noise while maintaining responsiveness to regime shifts
Trend Threshold
User-defined bias level (default: 0.0)
Above threshold = expansion regime
Below threshold = contraction regime
Interpretation
This indicator is designed to identify structural trend bias, not overbought/oversold extremes.
Sustained positive readings indicate persistent capital expansion.
Sustained negative readings indicate structural compression.
Threshold crossovers signal potential regime transitions.
Slope and persistence are often more informative than absolute level.
Design Principles
Statistical normalization separates signal from secular growth effects.
Smoothing is applied post-normalization to preserve structural information.
Inputs are modular, allowing independent control of regime sensitivity and signal responsiveness.
Data is requested on confirmed daily closes to ensure signal stability.
Strategic Context
Unlike traditional price-only oscillators, this framework derives trend information from underlying capital positioning. It therefore reacts to structural shifts in profitability rather than short-term price volatility.
This makes it particularly suited for:
Medium- to long-horizon trend strategies
Macro regime allocation models
Risk scaling frameworks
Summary
The MVRV Z-Score (DEMA Smoothed) reframes on-chain valuation data into a structural trend engine. By combining statistical normalization with adaptive smoothing, it provides a capital-anchored momentum signal designed for regime-based trading and systematic bias control. Indicator
Bitcoin Miners Max Pain (BMMP)Bitcoin Miner Max Pain (BMMP)
Core idea : Bitcoin always gravitates back toward its production cost. When price gets way too far above or below what it costs to mine a coin — and miners start showing stress signals — that's historically been where the real turning points happen.
I built the MEI to capture exactly that. It's a composite oscillator that blends four on-chain mining metrics into a single score.
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How it works:
PPC Ratio (Price-to-Production Cost) — The backbone of the indicator. Estimates what it actually costs to produce 1 BTC using either a difficulty regression model (based on Hayes 2018), a bottom-up electricity model, or an external data feed. When price trades below production cost, miners bleed. When it's multiples above, euphoria is probably peaking.
Difficulty Momentum — Compares fast vs slow rate of change in mining difficulty. Rapidly rising difficulty = miners are expanding aggressively (often late-cycle). Collapsing difficulty = capitulation (often near bottoms).
Puell Multiple — Daily miner revenue relative to the 365-day average. Low values mean miners are earning far less than usual (stress). High values mean revenue is running hot.
Hashrate Z-Score — How far current hashrate deviates from its smoothed trend. Captures whether the network is overextended or contracting.
Each component gets normalized via rolling z-scores so they're on a comparable scale, then weighted into one number.
Reading the signals
- Below -1.5 → Strong Buy — historically these have been generational bottoms
- -1.5 to -0.5 → Accumulation zone
- -0.5 to 0.5 → Fair value / neutral
- 0.5 to 1.5 → Distribution zone
- Above 1.5 → Strong Sell — historically cycle tops
Customization
Pretty much everything is adjustable — the cost model, component weights, lookback periods, signal thresholds. You can toggle individual component lines on/off to see what's driving the composite score at any given time.
Three production cost models to choose from depending on what data you have access to. The difficulty regression works out of the box with free data. The electricity model lets you plug in your own assumptions about fleet efficiency and power costs. Or just feed in an external cost estimate if you have one.
Setup
Apply to BTCUSD daily. You'll need data feeds for difficulty, hashrate, and miner revenue — default tickers point to Quandl/Blockchain.com but alternatives from IntoTheBlock or Glassnode work too. Adjust the ticker inputs to whatever your PulseWire plan supports.
Alerts included for all signal transitions — strong buy, buy, sell, strong sell, and zero-line crosses.
This isn't financial advice. It's a tool I built for my own analysis and decided to share. Do your own research, manage your risk, and don't blindly follow any indicator. Indicator
SMC Pro BTC - ICT Order Blocks & FVG [DOE]SMC Pro BTC - ICT Order Blocks & FVG
A multi-timeframe Smart Money Concepts engine built exclusively for Bitcoin. This indicator combines order blocks, fair value gaps, liquidity sweeps, break of structure, and premium/discount zone analysis into one backtest-verified, non-repainting strategy.
Every signal you see in history is exactly what you would have seen live. No repainting. No lookahead. No curve-fitting.
Built by a former quantitative analyst from a US-based systematic fund. The structural logic behind this indicator is the same order flow mechanics that institutional algorithms use to identify and exploit liquidity imbalances — adapted for retail traders on PulseWire.
TWO STRATEGY MODES
The indicator offers two execution modes on the same structural foundation. Both include commissions (0.075% per trade) and slippage (3 ticks) in all backtested results.
AGGRESSIVE MODE — More trades, more exposure
Entries fire on any valid BOS or CHoCH confirmed by an order block and fair value gap on the confirmation timeframe. Accepts a lower win rate in exchange for capturing a larger portion of trending moves.
Metric Value
Period Jan 2021 — Feb 2026 (5 years)
Total Trades 90
Win Rate 45.56%
Net P&L +14.36%
Profit Factor 1.95
Max Drawdown 1.36%
90 trades across 5 full years — including the 2022 bear market. A profit factor of 1.95 means that for every dollar lost, the system recovered nearly two. The 45% win rate works because winning trades are structurally larger than losers. This is positive expectancy executed over a statistically meaningful sample.
SELECTIVE MODE — Fewer trades, higher precision
Adds a premium/discount zone filter. Longs only in the discount zone of the HTF dealing range. Shorts only in the premium zone. This single structural filter cuts the trade count significantly while improving signal quality.
Metric Value
Period Jan 2021 — Feb 2026 (5 years)
Total Trades 29
Win Rate 51.72%
Net P&L +1.10%
Profit Factor 1.324
Max Drawdown 1.23%
The Selective mode sacrifices P&L for risk control — the maximum drawdown over 5 years was just 1.23%. The lower trade count (29) reflects the strict filtering: every signal requires structural confluence plus optimal price positioning. This mode is designed for traders who prioritize capital preservation over returns.
Both modes are provided so you can evaluate the tradeoff between frequency and precision. There is no objectively "better" mode — only the one that matches your risk tolerance.
Note on sample size: The Aggressive mode produces 90 trades over the 5-year test period, approaching the 100-trade benchmark for statistical significance. The Selective mode produces 29 trades due to the strict confluence requirements — each trade requires alignment across 6 independent conditions (BOS, OB, FVG, liquidity sweep, premium/discount zone). We recommend supplementing the backtest with forward-testing on live data for additional confidence. The Strategy Tester is fully available for you to verify all results with your own settings.
ENTRY LOGIC — STEP BY STEP
Every signal requires alignment across structure, zone, imbalance, and liquidity. No single condition is sufficient.
LONG ENTRY SEQUENCE
Step 1 — HTF Directional Bias
The Direction Timeframe (default: 4H) detects a bullish break of structure or change of character. This establishes the higher-timeframe directional bias. Without bullish structure on the HTF, no long signal fires.
Step 2 — MTF Confirmation
The Confirmation Timeframe (default: 1H) must confirm with its own bullish BOS or CHoCH, aligning both timeframes in the same direction.
Step 3 — Order Block Identification
The script finds the last bearish candle before the impulsive bullish move — the order block where smart money accumulated positions.
Step 4 — Fair Value Gap Validation
A bullish FVG must overlap the identified order block zone. An OB alone is a level. An OB combined with an FVG is confluence.
Step 5 — Liquidity Sweep Confirmation
A recent liquidity sweep must have occurred — price dipped below a prior swing low, triggering stop-losses, before reversing.
Step 6 — Premium/Discount Zone Filter (Selective Mode Only)
Entry must occur in the discount zone of the HTF dealing range.
Step 7 — Execution
All conditions met. Signal fires. Stop-loss below the order block. Take-profit at the configured R:R distance.
SHORT ENTRY SEQUENCE
Mirrors the long with inverted conditions:
HTF bearish BOS/CHoCH
MTF bearish BOS/CHoCH confirms
Bearish order block identified
Bearish FVG overlaps the OB zone
Liquidity sweep above a prior swing high
Price in premium zone (Selective only)
SL above OB high + buffer; TP at R:R below entry
Every step is objective. No discretionary component.
FEATURES
Non-repainting, non-lookahead signals — barstate.isconfirmed enforced on all calculations
Multi-timeframe structure analysis — HTF for direction, MTF for confirmation, entry TF for execution
Order block detection with configurable lookback and automatic invalidation
Fair value gap multi-zone display — configurable by count and max distance from price
Liquidity sweep recognition with adjustable memory window
BOS and CHoCH detection on multiple timeframes
Premium/discount zone mapping with configurable threshold
Automatic SL/TP with visual trade boxes
Two strategy modes — Aggressive and Selective
Fully configurable parameters with sensible BTC 4H defaults
Built-in strategy engine — backtest directly in Strategy Tester
DEFAULT STRATEGY PROPERTIES
These are the exact settings used for the published backtest. You can verify all results by loading the indicator with default settings and opening the Strategy Tester:
Symbol: BTCUSDT (Binance)
Timeframe: 4H
Period: January 2021 — February 2026 (5+ years)
Initial Capital: $10,000
Order Size: 10% of equity per trade
Commission: 0.075% per trade (Binance taker fee)
Slippage: 3 ticks per order
Pyramiding: 0 (one position at a time)
Non-repainting: barstate.isconfirmed enforced
No lookahead bias: lookahead = barmerge.lookahead_off on all request.security() calls
No future leakage: entries execute on the bar after all conditions are confirmed
The 10% equity sizing means each trade risks a sustainable portion of the account. This is consistent with professional risk management standards where no single trade should expose more than 5-10% of capital.
SETTINGS DOCUMENTATION
Strategy Mode — Aggressive / Selective
Aggressive: BOS/CHoCH + Order Block + FVG + Liquidity Sweep. Selective adds premium/discount zone filter. New to SMC? Start with Selective.
Direction TF (HTF) — Default: 240 (4H)
Higher timeframe for directional bias. Increase to Daily for fewer, higher-conviction signals.
Confirmation TF (MTF) — Default: 60 (1H)
Mid timeframe that confirms HTF bias. Default 240/60 provides a 4:1 ratio.
Swing Length — Default: 10 | Range: 3-50
Bars used to identify swing highs/lows. Lower = more sensitive, higher = major shifts only.
OB Lookback Bars — Default: 15 | Range: 3-30
How far back to search for valid order blocks after a structural break.
Sweep Memory — Default: 20 bars | Range: 5-50
Lookback window for detecting liquidity sweeps before entries.
Risk:Reward Ratio — Default: 2.0 | Range: 1.0-5.0
TP placement relative to SL distance. Re-run backtest after changing.
SL Buffer % — Default: 0.3 | Range: 0.0-2.0
Buffer beyond OB boundary to prevent wick stop-outs.
P/D Zone Threshold — Default: 0.80 | Range: 0.50-0.85 | Selective Only
How deep into premium/discount zone for entry qualification.
Max FVGs per Side — Default: 5 | Range: 1-10
Active FVGs displayed per direction.
FVG Max Distance % — Default: 8.0 | Range: 1.0-25.0
Hides FVGs beyond this % from current price.
Show Trade Boxes — On / Off
Visual boxes showing entry, SL, and TP for each signal.
CONCEPTS EXPLAINED
Order Blocks (OB) — The last opposing candle before a significant impulsive move. Where institutional participants positioned themselves. The foundation of SMC entry models.
Fair Value Gap (FVG) — A three-candle price imbalance where the market moved too fast for orders to fill. Markets tend to return to these inefficiencies. When an FVG overlaps an OB, that is high-probability confluence.
Break of Structure (BOS) — Price moves beyond a prior swing high/low in the trend direction. Signals continuation.
Change of Character (CHoCH) — A structural break against the prevailing trend. The first objective signal of a potential reversal.
Liquidity Sweep — Price pushes beyond a key level to trigger stop-losses, then reverses. Institutional participants hunting clustered orders for liquidity.
Premium and Discount Zones — The HTF range divided by the 50% equilibrium. Premium = expensive (favor shorts). Discount = cheap (favor longs).
HOW TO USE
Add to any BTCUSDT chart (optimized for 4H Binance)
Select Aggressive or Selective mode in Settings
Green arrows = long entries, red arrows = short entries, with SL/TP lines
Enable Show Trade Boxes for visual risk/reward on every signal
Open Strategy Tester to verify all backtest results with your own settings
Adjust one setting at a time and re-run the backtest after each change
Combine with your own analysis — this is a structural tool, not a prediction engine
Manage risk — no indicator guarantees profits
CREDITS
This script builds upon concepts and structural approaches from the following open-source projects:
LuxAlgo — SMC structural detection framework
ICT Master Suite — ICT concepts implementation reference
PineScript-SMC-Strategy — SMC strategy architecture reference
Significant modifications and original work include: dual-mode strategy engine (Aggressive/Selective), multi-timeframe confluence model requiring 5-6 simultaneous conditions, FVG multi-zone display with distance filtering, integrated backtest engine with realistic position sizing, and complete strategy automation with configurable risk management.
DISCLAIMER
This indicator is published for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any asset. Trading Bitcoin involves substantial risk of loss. Never trade capital you cannot afford to lose. Past performance does not guarantee future results. You are solely responsible for your own trading decisions. Use at your own risk. Strategy
BTC Cycle RSI + LinReg Bands DCA Strategy v2Overview
BTC Cycle RSI DCA Strategy v2 backtests a phase-based dollar-cost averaging system with sequential sell rotations to a simulated yield basket (STRC) and hybrid yield-funded DCA during deep bear markets. Built on smoothed RSI with self-adjusting linear regression bands (adapted from Zeiierman's open-source work).
How It Works
Eight cycle phases drive DCA multipliers from 5x (Deep Bear) down to 0x (Mature Bull), with post-peak taper at 0.5x (Distribution) and 0.25x (Weakening)
Two sequential sells (20% then 40%) rotate BTC holdings into a simulated yield basket when RSI breaks below the midline after an overbought cycle
Plunge guard locks out the second sell if RSI collapses to the lower band after the first sell
Yield basket compounds at a configurable APR and deploys capital back into BTC during deep bear phases via a hybrid model (time ramp + drawdown scaling + pool cap)
Start date filter lets you isolate specific cycles for backtesting
Starting yield basket balance input lets you seed the simulation with an existing position
Default Properties
Initial capital: $100,000 | Commission: 0.05% per side | Slippage: 5 ticks | Base DCA: $100/week | Yield APR: 11% | Hybrid deploy: 25% of pool/week, 4% cap, 25-week ramp, cubic drawdown scaling
Realistic Backtesting Notes
Commission and slippage are enabled by default. The strategy uses fixed USD-denominated DCA orders rather than percentage-of-equity sizing, reflecting real-world DCA behavior. The yield basket is simulated off-chain and is NOT included in Strategy Tester equity — check the Total Wealth plot for the combined view.
Attribution
RSI + self-adjusting linear regression band structure adapted from Zeiierman's open-source indicator. Post-peak phase logic, DCA taper, plunge guard, sell sequencing, yield simulation, and hybrid deployment model are original additions.
Disclaimer
Backtesting results are hypothetical and do not guarantee future performance. This strategy is for educational and informational purposes only. Always do your own research.
Strategy
BTC Cycle Navigator v2 - Phase DCA + Yield Deploy GuidanceOverview
BTC Cycle Navigator v2 is a phase-based guidance indicator built on smoothed RSI with self-adjusting linear regression bands (adapted from Zeiierman's open-source work). It identifies eight distinct cycle phases and provides real-time DCA sizing, sell rotation signals, and yield deployment suggestions — all displayed in an on-chart table.
What It Does
Detects cycle phases: Deep Bear → Bear Recovery → Early Bull → Bull Building → Bull Confirmed → Mature Bull → Distribution → Weakening
Post-peak awareness: after RSI crosses the overbought level, Bull Confirmed becomes Distribution and Bull Building becomes Weakening — with tapered DCA (0.5x and 0.25x)
Two-stage sell rotation: FIRST_SELL (20%) and SECOND_SELL (40%) triggered by confirmed RSI midline breakdowns after an overbought cycle
Plunge guard: if RSI collapses to the lower band after FIRST_SELL, the second sell is locked out to prevent selling into a crash
Hybrid yield deployment model: suggests weekly capital deployment from a yield basket during deep bear phases using time-ramped, drawdown-scaled, pool-capped logic
How To Use
Apply to BTCUSD on the 1W (weekly) timeframe
Set your Start Date to the beginning of the cycle you want to track
Enter your Base DCA amount (the 1x weekly amount in USD)
Enter your Yield Basket size and target keep % for deployment guidance
Read the on-chart table for current phase, DCA amount, sell status, and yield deploy suggestion
Set alerts for phase changes and sell signals
Phase → DCA Multiplier
Deep Bear: 5x | Bear Recovery: 3x | Early Bull: 2x | Bull Building: 1x | Bull Confirmed: 1x | Mature Bull: 0x (paused) | Distribution: 0.5x | Weakening: 0.25x
Attribution
RSI + self-adjusting linear regression band structure adapted from Zeiierman's open-source indicator. Post-peak phase logic, DCA taper model, plunge guard, sell sequencing, and hybrid yield deployment are original additions.
Disclaimer
This indicator provides informational guidance only. It does not constitute financial advice. Past RSI patterns do not guarantee future performance. Always do your own research.
Indicator
ScalpFlow: Dynamic Range & Structure Engine"Intraday S/R + Fractal Liquidity Mapper"
Navigate the Noise with Precision Structure Mapping
In the world of 5-minute scalping, the biggest challenge is identifying true trend shifts versus minor noise. ScalpFlow transforms your chart into a structural map, grouping price action into time-based "Blocks" that automatically label market highs and lows.
Stop guessing where the next support level is—ScalpFlow draws it for you based on realized market volatility.
Key Features
Automated Block Structure: Groups price action into clear visual boxes. Each box is color-coded (Bullish/Bearish) and automatically identifies HH (Higher Highs), LH (Lower Highs), LL (Lower Lows), and HL (Higher Lows).
Instant S/R Projection: The script identifies the High and Low of the previous completed block and projects them forward as dashed Support & Resistance lines. This gives you immediate targets for breakouts or mean-reversion trades.
Fractal HH/LL Labels: High-speed "Mini-Pivots" (Fractals) are labeled on the candles themselves, allowing you to spot micro-reversals before the larger block even closes.
Dynamic Trend-Line Midpoints: A blue trend line connects the midpoints of every block, providing a smoothed visual representation of the overall price trajectory.
Scalper’s HUD: A clean dashboard in the bottom-right corner that tells you exactly where price is relative to the range: "BREAKOUT UP," "INSIDE RANGE," or "BREAKDOWN DOWN."
Integrated VWAP: Standardized institutional volume weighting to ensure you are trading with the "Value" of the day.
The Scalper's Edge
This tool is designed for "Structure Traders." By seeing the market as a series of boxes rather than just lines, you can easily identify "Equality Highs" (EQH) or "Equality Lows" (EQL)—common areas where liquidity sits and where big moves often begin.
Best Used For:
Asset: Crypto (BTC/ETH), Forex (Major pairs), and Equities.
Timeframe: 1-Minute to 15-Minute (Optimized for 5m).
Style: Trend Following, Breakout Trading, and Range Scalping. Indicator
Indicator
BTC Liquidation Heatmap | Multi-ExchangeBTC Liquidation Heatmap | Multi-Exchange
🔍 This heatmap pulls volume data from Binance, Coinbase, and Bitstamp simultaneously to show you where the real liquidation clusters are sitting. Instead of guessing where stops might get hit, you get actual volume-weighted zones with a strength score that tells you which levels matter.
The zones change color based on how much volume is stacked at each level. Bright colors mean heavy liquidation potential, faded colors mean weak spots. Each label shows the volume size, a strength rating out of 10, and how far away it is from current price in percentage terms.
Works best on 4H/D1 timeframes for Bitcoin. The default settings are tuned for day trading but you can dial them up or down depending on your style.
⚙️Drop it on your BTCUSD chart and you'll see colored boxes above and below price. Purple zones are short liquidations (above price), teal zones are long liquidations (below price). The thermometer on the right shows you the intensity scale.
Labels show three things: volume amount, strength ranking, and distance from current price. A level showing "1.45B ||| Strength 8/10 ||| 2.34%" means there's 1.45 billion in volume weight, it's an 8 out of 10 in terms of strength, and it's 2.34% away from where you are now.
The strength ranking is calculated using a proprietary algorithm that weighs multiple factors. Higher numbers mean more likely to cause a reaction when price gets there.
Settings You Actually Need to Know
📊 Lookback Bars: How far back to scan for levels. Default is 1000 bars which gives you plenty of context without cluttering the chart.
Pivot Width: Higher numbers = fewer but stronger levels. Start with 5, bump it to 8-10 if you're getting too much noise.
Min Level Weight: Filter out weak levels by raising this number. If your chart looks messy, start increasing it by 100M increments until it cleans up.
Label Size: Set to Normal by default. Switch to Large if you're on a big monitor or Small if you want a cleaner look.
How to Use It
🎯 Look for clusters of high-strength levels (8-10 rating) near current price. Those are your magnets. Price tends to get pulled toward them because that's where the liquidity is sitting. When you see a 10/10 level a few percent away, that's your target or your invalidation point depending on which side you're trading.
If price breaks through a strong level with momentum, it usually means the liquidations got triggered and you're looking at a real move. Weak levels (1-4 rating) are more likely to get ignored.
The distance percentage helps you figure out if a level is even worth watching. A 10/10 level that's 15% away might not matter for your intraday trade, but a 6/10 level that's only 0.5% away definitely does.
Exchange Toggles
🔄 You can turn off any of the three exchanges if you want. All three are on by default because more data = better picture. But if you only care about Binance and Coinbase, just uncheck Bitstamp in the settings. The volume recalculates automatically.
What to Ignore
Don't trade every level you see. Focus on the ones with 6/10 strength or higher that are within 5% of current price. Everything else is just context. And if a level gets hit (price crosses through it), it'll fade out so you know it's done.
The thermometer on the right is just a reference. You don't need to stare at it, but it helps when you're trying to figure out if a level is relatively strong or weak compared to everything else on screen.
Indicator
Strategy
Smart Money Structure FilterEnglish Description
Overview
Smart Money Structure Analyzer is a professional trading tool that implements Smart Money Concepts (SMC) to identify key market structure shifts, Break of Structure (BOS), and Change of Character (CHoCH) patterns. This indicator helps traders follow the "smart money" flow by detecting institutional order flow patterns on any timeframe.
Key Features
Swing Point Detection - Identifies significant highs and lows using fractal-based logic
Market Structure Analysis - Classifies market conditions as Uptrend, Downtrend, or Consolidation
Break of Structure (BOS) - Detects when price breaks key structural levels
Change of Character (CHoCH) - Identifies potential trend reversals
Mitigation Levels - Shows potential retracement targets after structure breaks
How It Works
The indicator analyzes price action through several layers:
Swing Detection Algorithm
Uses a configurable swing period (3-21 bars)
Identifies valid swing highs and lows that are confirmed by surrounding price action
Stores the last 20 swings for structure analysis
Structure Determination
Uptrend: Higher Highs (HH) + Higher Lows (HL)
Downtrend: Lower Lows (LL) + Lower Highs (LH)
Consolidation: Mixed structure or ranging market
Break of Structure (BOS) Logic
Bearish BOS: Price closes below the last confirmed Higher Low (HL)
Bullish BOS: Price closes above the last confirmed Lower High (LH)
Change of Character (CHoCH) Logic
Bearish CHoCH: After a bearish BOS, price forms a Lower Low (confirms trend reversal)
Bullish CHoCH: After a bullish BOS, price forms a Higher High (confirms trend reversal)
Mitigation Levels
Calculates potential retracement levels after BOS (typically ±0.2% from broken structure)
Visual Elements
Fractals: Swing points (optional display)
Structure Lines: Last Higher Low (blue) and Last Lower High (purple)
BOS Signals: Triangles marking structure breaks
CHoCH Signals: Circles confirming trend changes
Mitigation Levels: Dotted orange lines for potential retracements
Info Label: Real-time structure status and key levels
Alerts
The indicator provides alerts for:
Break of Structure (BOS) events
Change of Character (CHoCH) confirmations
Settings
Swing Period: Sensitivity of swing detection (default: 3)
Show Fractals: Toggle swing point markers
Show Structure Lines: Display key structure levels
Show Break of Structure: Display BOS signals
Show Change of Character: Display CHoCH signals
Show Mitigation Levels: Display retracement levels
Best Practices
Use on higher timeframes (1H+) for more reliable signals
Combine with volume analysis for confirmation
Wait for CHoCH confirmation before entering trades
Use mitigation levels as potential entry zones
Русское описание
Обзор
Smart Money Structure Analyzer - профессиональный торговый инструмент, реализующий концепции Smart Money (SMC) для определения ключевых сдвигов рыночной структуры, Break of Structure (BOS) и Change of Character (CHoCH). Индикатор помогает отслеживать поток "умных денег", выявляя паттерны институционального ордерного потока на любом таймфрейме.
Ключевые возможности
Определение свингов - Выявляет значимые максимумы и минимумы с помощью фрактальной логики
Анализ структуры рынка - Классифицирует состояние рынка: Восходящий тренд, Нисходящий тренд или Консолидация
Break of Structure (BOS) - Обнаружение пробития ключевых уровней структуры
Change of Character (CHoCH) - Определение потенциальных разворотов тренда
Уровни митигации - Показывает потенциальные цели отката после пробоя структуры
Принцип работы
Индикатор анализирует ценовое действие через несколько уровней:
Алгоритм определения свингов
Использует настраиваемый период свинга (3-21 свечи)
Определяет валидные максимумы и минимумы, подтвержденные окружающим движением цены
Сохраняет последние 20 свингов для анализа структуры
Определение структуры
Восходящий тренд: Higher Highs (HH) + Higher Lows (HL)
Нисходящий тренд: Lower Lows (LL) + Lower Highs (LH)
Консолидация: Смешанная структура или флет
Логика Break of Structure (BOS)
Медвежий BOS: Цена закрывается ниже последнего Higher Low (HL)
Бычий BOS: Цена закрывается выше последнего Lower High (LH)
Логика Change of Character (CHoCH)
Медвежий CHoCH: После медвежьего BOS формируется Lower Low (подтверждает разворот)
Бычий CHoCH: После бычьего BOS формируется Higher High (подтверждает разворот)
Уровни митигации
Расчет потенциальных уровней отката после BOS (обычно ±0.2% от сломанной структуры)
Визуальные элементы
Фракталы: Точки свингов (опционально)
Линии структуры: Последний Higher Low (синий) и последний Lower High (фиолетовый)
Сигналы BOS: Треугольники, отмечающие пробой структуры
Сигналы CHoCH: Круги, подтверждающие изменение тренда
Уровни митигации: Пунктирные оранжевые линии для потенциальных откатов
Инфо-метка: Статус структуры и ключевые уровни в реальном времени
Оповещения
Индикатор предоставляет алерты для:
Событий Break of Structure (BOS)
Подтверждений Change of Character (CHoCH)
Настройки
Период свинга: Чувствительность определения свингов (по умолчанию: 3)
Показывать фракталы: Включение/выключение маркеров свингов
Показывать линии структуры: Отображение ключевых уровней структуры
Показывать Break of Structure: Отображение сигналов BOS
Показывать Change of Character: Отображение сигналов CHoCH
Показывать уровни митигации: Отображение уровней отката
Рекомендации по использованию
Используйте на старших таймфреймах (1H+) для более надежных сигналов
Комбинируйте с анализом объема для подтверждения
Ждите подтверждения CHoCH перед входом в сделку
Используйте уровни митигации как потенциальные зоны входа
Технические особенности
Максимальное количество меток: 500
Работает на любых таймфреймах
Не перерисовывает прошлые сигналы
Эффективно использует ресурсы благодаря ограничению хранения свингов
Индикатор предназначен для трейдеров, работающих с Price Action и концепциями Smart Money, и помогает систематизировать анализ рыночной структуры в соответствии с подходами институциональных трейдеров. Indicator
Bitcoin Halving Cycles [DotGain]Halving Cycles
A lightweight, time-anchored Bitcoin halving cycle visualizer built for clean charting, repeatable process planning, and simple profit/DCA timing references.
This Code was heavily inspired by KevinSvenson_ who created Bitcoin Halving Cycle Profit .
What this indicator does
This script plots the key “cycle landmarks” relative to each halving date:
Halving (⛏) – the cycle anchor
Profit START – marks the beginning of the post-halving profit window (default: 40 weeks )
Profit END / Last Call – marks the final phase of the profit window (default: 77 weeks )
DCA START – marks the point where long-term accumulation becomes the focus again (default: 135 weeks )
How to read it
Vertical lines = the exact cycle milestones
Bottom labels = description of each milestone aligned to its line (keeps the chart clean)
Green background (optional) = active Profit Zone on existing bars
Red background (optional) = optional warning zone after Profit END
HUD Panel (top-right)
The HUD gives you a fast “where are we in the cycle?” view with two modes:
Current Cycle
Shows: Halving date, Weeks since, and time remaining to Profit START / Last Call / DCA START within the current cycle.
Next Halving (Projection)
Shows: Countdown to the next enabled future halving, plus the projected weeks from today to Profit START / Last Call / DCA START after that future halving.
Future Halvings (manual)
You can manually add up to 3 future halving dates (Halving #1–#3).
This is useful for forward planning and cycle projection even before the event happens.
Enable Halving #1 / #2 / #3
Set Year / Month / Day for each
Optional: show/hide future markers & projections
Note: background zones only shade existing bars . Future projections are shown via lines/labels.
Settings overview
Show all cycles – plots every enabled cycle (historical + optional future). If disabled, only the current cycle is drawn.
Show Profit Zone background – green shading during the active profit window (current cycle only).
Show vertical markers + labels – toggles all milestone lines + labels.
Show HUD – toggles the HUD panel.
HUD Mode – switch between Current Cycle and Next Halving (Projection).
Cycle Logic – edit offsets in weeks (Profit START / Profit END / DCA START).
Optional Warning Zone – show a post-profit warning shading for a chosen number of weeks.
Have fun :)
Disclaimer
This Halving Cycles indicator is provided for informational and educational purposes only. It does not, and should not be construed as, financial, investment, or trading advice.
This indicator is an independent implementation of a time-based Bitcoin halving cycle visualization tool and is not affiliated with, or endorsed by, any third-party trading systems, strategies, protocols, or trademarked methodologies. The cycle zones, milestone markers, and countdown values displayed by this indicator are generated by a predefined set of algorithmic rules based on historical halving dates and user-defined time offsets. They do not constitute a direct recommendation to buy, sell, or hold any financial instrument or digital asset.
All trading and investing in financial markets involves a substantial risk of loss. You may lose part or all of your invested capital. Past performance does not guarantee future results. This indicator highlights historical and projected time-based market cycles and may produce false, lagging, incomplete, or misleading signals. Market behavior is influenced by many external factors and can deviate significantly from historical patterns or expectations.
The creator DotGain assumes no responsibility or liability for any financial losses, damages, or decisions made based on the use of this indicator or the information it provides. You are solely responsible for your own trading and investment decisions. Always conduct your own research (DYOR), use proper risk management, validate insights with additional tools or analysis, and consider your personal financial situation and risk tolerance before making any financial decision. Indicator
Mission Control Dashboard (AI, Crypto, Liquidity) FASTCONCEPT Price is a lagging indicator. Liquidity is a leading indicator. "Mission Control Dashboard (AI, Crypto, Liquidity) FAST" is a sophisticated macroeconomic dashboard designed to audit the "plumbing" of the financial system in real-time. Unlike standard indicators that rely solely on price action, this tool pulls data from the Federal Reserve (FRED), Treasury Statements, Corporate Financials (10-K/10-Q), and On-Chain Stablecoin metrics to visualize the structural flows driving the market.
THE "UNIFIED FIELD" SOLVER One of the hardest challenges in cross-asset scripting is "Time Dilation"—synchronizing 24/7 Crypto markets (Bitcoin) with Mon-Fri Traditional markets (Stocks/Bonds).
Standard scripts fail on weekends, showing mismatched data.
This engine uses a Weekly Anchor system. It calculates all momentum and liquidity metrics based on "Week-to-Date" or "Month-Ago" anchors. This ensures that a "Liquidity Drain" looks identical whether you are viewing a Bitcoin chart on Saturday or an Apple chart on Monday.
THE CHRONOS LOGIC The dashboard is sorted by Time Sensitivity (Speed of impact), from fast-twitch tactical signals to slow-moving structural fundamentals.
1. TACTICAL (Reacts in 24–48h)
Stablecoin Flight: Measures the immediate flow of capital from Volatile Assets to Stablecoins (USDT/USDC). A spike (>0.5%) indicates fear/sidelining.
Liquidity Alpha: Calculates the efficiency of capital. It subtracts "Friction" (Dollar Strength + Yields) from "Flow" (Liquidity Beta). High Alpha means money is flowing easily into risk assets.
Alt Euphoria: Tracks the overheating of the Altcoin market (TOTAL3). Green indicates sustainable growth; Red (>45%) warns of a "blow-off top."
Retail FOMO: A sentiment gauge comparing Coinbase Stock ( NASDAQ:COIN ) performance vs. Bitcoin ( CRYPTOCAP:BTC ). When Retail outperforms the Asset, local tops often follow.
2. LIQUIDITY & MACRO (Reacts in 1–4 Weeks)
Debt Wall (10Y): The Rate-of-Change of the US 10-Year Treasury Yield. Spiking yields act as gravity on risk assets.
Liquidity Beta: The raw "Quantity of Money." Tracks the 4-week change in Net Liquidity (Fed Balance Sheet - TGA + Stablecoins).
TGA Balance: The Critical Monitor. Tracks the Treasury General Account. When the TGA rises (Red), the government is draining liquidity from the banking system. When it falls (Green), it releases cash.
Note: This script includes an auto-scaler to handle TGA data in both Billions and Millions.
3. STRUCTURAL (Reacts in 3–12 Months)
AI Capex (YoY & QoQ): The "Floor" of the 2025/2026 cycle. Tracks the Capital Expenditure of the Hyperscalers (MSFT, GOOGL, AMZN, META). As long as this remains high (>30%), the infrastructure boom supports the tech narrative.
PMI Manufacturing: Tracks the ISM Manufacturing cycle. Contraction (<50) often forces Fed intervention.
Micron Inventory: A lead indicator for the hardware cycle.
HOW TO USE
Status Colors: The traffic light system helps you assess risk at a glance.
🟢 GREEN (Healthy): Flow is positive, friction is low, fundamentals are strong.
🔴 RED (Danger): Liquidity is draining (TGA spike), yields are shock-rising, or FOMO is excessive.
Zero Configuration: The script auto-detects asset classes and scales units (Billions/Trillions) automatically.
DATA SOURCES
Federal Reserve Economic Data (FRED)
Daily Treasury Statement (DTS)
CryptoCap (PulseWire)
Nasdaq/Corporate Financials
Disclaimer: This tool is for informational purposes only and does not constitute financial advice. Macro data feeds are subject to reporting delays. Indicator
Indicator
Indicator
BTC ETF Average Inflow Cost BasisConcept
Since the historic launch of Bitcoin Spot ETFs on January 11, 2024, institutional flows have become a major driver of price action. This indicator aims to visualize the aggregate Cost Basis (average entry price) of the major Bitcoin ETFs relative to the underlying asset.
It serves as an on-chain proxy for institutional positioning, helping traders identify critical support levels where ETF inflows have historically concentrated.
How it Works
The script aggregates daily volume data from the top Bitcoin ETFs (IBIT, FBTC, ARKB, GBTC, BITB) and compares it against the Bitcoin price (BTCUSDT).
ETF Cost Basis (Pink Line):
This is calculated as a Cumulative Volume-Weighted Average Price (VWAP), anchored specifically to the ETF launch date (Jan 11, 2024).
Formula: It accumulates (BTC Price * Total ETF Volume) and divides it by the Cumulative Total ETF Volume.
This creates a dynamic level representing the "breakeven" price for the aggregate volume traded through these funds.
True Market Mean (Gray Line):
This represents the simple cumulative average of the Bitcoin price since the ETF launch date. It acts as a neutral baseline for the post-ETF market era.
How to Use
Institutional Support: The Cost Basis line often acts as a strong dynamic support level during corrections. When price revisits this level, it suggests the market is returning to the average institutional entry price.
Trend Filter:
Price > Cost Basis: The market is in a net profit state relative to ETF flows (Bullish/Trend continuation).
Price < Cost Basis: The market is in a net loss state (Bearish/Capitulation risk).
Confluence: The intersection of the Cost Basis and the True Market Mean can signal pivotal moments of trend reset.
Features
Data Aggregation: Pulls data from 5 major ETFs via request.security without repainting (using closed bars).
Dashboard: Includes a table in the top-right corner displaying real-time values for Price, Cost Basis, and Market Mean.
Customization: You can toggle individual ETF Moving Averages in the settings (disabled by default due to price scale differences between BTC and ETF shares).
Disclaimer
This tool is for educational purposes only and attempts to estimate institutional cost basis using volume proxies. It does not represent financial advice.
Indicator
BTC DCA Risk Metric StrategyBTC DCA Risk Strategy - Automated Dollar Cost Averaging with 3Commas Integration
Overview
This strategy combines the proven Oakley Wood Risk Metric with an intelligent tiered Dollar Cost Averaging (DCA) system, designed to help traders systematically accumulate Bitcoin during periods of low risk and take profits during high-risk conditions.
Key Features
📊 Multi-Component Risk Assessment
4-Year SMA Deviation: Measures Bitcoin's distance from its long-term mean
20-Week MA Analysis: Tracks medium-term momentum shifts
50-Day/50-Week MA Ratio: Captures short-to-medium term trend strength
All metrics are normalized by time to account for Bitcoin's maturing market dynamics
💰 3-Tier DCA Buy System
Level 1 (Low Risk): Conservative entry with base allocation
Level 2 (Lower Risk): Increased allocation as opportunity improves
Level 3 (Extreme Low Risk): Maximum allocation during rare buying opportunities
Buys execute every bar while risk remains below thresholds, enabling true DCA accumulation
📈 Progressive Profit Taking
Sell Level 1: Take initial profits as risk increases
Sell Level 2: Scale out further positions during elevated risk
Sell Level 3: Final exit during extreme market conditions
Sell levels automatically reset when new buy signals occur, allowing flexible re-entry
🤖 3Commas Integration
Fully automated webhook alerts for Custom Signal Bots
JSON payloads formatted per 3Commas API specifications
Supports multiple exchanges (Binance, Coinbase, Kraken, Gemini, Bybit)
Configurable quote currency (USD, USDT, BUSD)
How It Works
The strategy calculates a composite risk metric (0-1 scale):
0.0-0.2: Extreme buying opportunity (green zone)
0.2-0.5: Favorable accumulation range (yellow zone)
0.5-0.8: Neutral to cautious territory (orange zone)
0.8-1.0+: High risk, profit-taking zone (red zone)
Buy Logic: As risk decreases, position sizes increase automatically. If risk drops from L1 to L3 threshold, the strategy combines all three tier allocations for maximum exposure.
Sell Logic: Sequential profit-taking ensures you capture gains progressively. The system won't advance to Sell L2 until L1 completes, preventing premature full exits.
Configuration
Risk Metric Parameters:
All calculations use Bitcoin price data (any BTC chart works)
Time-normalized formulas adapt to market maturity
No manual parameter tuning required
Buy Settings:
Set risk thresholds for each tier (default: 0.20, 0.10, 0.00)
Define dollar amounts per tier (default: $10, $15, $20)
Fully customizable to your risk tolerance and capital
Sell Settings:
Configure risk thresholds for profit-taking (default: 1.00, 1.50, 2.00)
Set percentage of position to sell at each level (default: 25%, 35%, 40%)
3Commas Setup:
Create a Custom Signal Bot in 3Commas
Copy Bot UUID and Secret Token into strategy inputs
Enable 3Commas Alerts checkbox
Create PulseWire alert: Condition → "alert() function calls only", Webhook → api.3commas.io
Backtesting Results
Strengths:
Systematically buys dips without emotion
Averages down during extended bear markets
Captures explosive bull run profits through tiered exits
Pyramiding (1000 max orders) allows true DCA behavior
Considerations:
Requires sufficient capital for multiple buys during prolonged downtrends
Backtest on Daily timeframe for most reliable signals
Past performance does not guarantee future results
Visual Design
The indicator pane displays:
Color-coded risk metric line: Changes from white→red→orange→yellow→green as risk decreases
Background zones: Green (buy), yellow (hold), red (sell) areas
Dashed threshold lines: Clear visual markers for each buy/sell level
Entry/Exit labels: Green buy labels and orange/red sell labels mark all trades
Credits
Original Risk Metric: Oakley Wood
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Modifications: pommesUNDwurst
Disclaimer
This strategy is for educational and informational purposes only. Cryptocurrency trading carries substantial risk of loss. Always conduct your own research and never invest more than you can afford to lose. The authors are not financial advisors and assume no responsibility for trading decisions made using this tool. Strategy
Bitcoin Multibook v1.0 [Apollo Algo]Bitcoin Multibook v1.0 by Apollo Algo is an advanced market depth and order flow visualization tool that brings professional-grade multi-exchange order book analysis to PulseWire. Inspired by Bookmap's multibook functionality and built upon LucF's original single "Tape" indicator concept, this tool aggregates real-time trading data from multiple Bitcoin exchanges into a unified tape display.
Credits & Attribution
This indicator is an evolution of the original "Tape" indicator created by LucF (PulseWire: @LucF). The multibook enhancement and Bitcoin-specific optimizations were developed by Apollo Algo to provide traders with institutional-grade market microstructure visibility across major Bitcoin trading venues.
Purpose & Philosophy
Bitcoin leads the entire cryptocurrency market. By monitoring order flow across the primary Bitcoin exchanges simultaneously, traders gain crucial insights into:
Cross-exchange arbitrage opportunities
Institutional order flow patterns
Market maker positioning
True market sentiment beyond single-exchange data
Key Features
📊 Multi-Exchange Data Aggregation
Real-time tape from 3 major exchanges:
Binance (BTCUSDT)
Coinbase (BTCUSD)
Kraken (BTCUSD)
Customizable source inputs for any trading pair
Synchronized price and volume tracking
Exchange name identification in tape display
📈 Advanced Tape Display
Dynamic tape visualization with configurable line quantity (0-50 lines)
Directional flow indicators (＋/－ symbols for price changes)
Exchange identification for each trade
Volume precision control (0-16 decimal places)
Flexible positioning (9 screen positions available)
Real-time only operation for accurate order flow
🎯 Volume Delta Analysis
Real-time cumulative volume delta calculation
Divergence detection (price vs. volume direction)
Colored visual feedback for market sentiment
Total session delta displayed in footer
Cross-exchange delta aggregation
🚨 Smart Alert System
Marker 1: Volume Delta Bumps (⬆⬇)
Triggers on consecutive volume delta increases
Identifies momentum acceleration points
Filters out divergent movements
Marker 2: Volume Delta Thresholds (⇑⇓)
Fires when delta exceeds user-defined thresholds
Catches significant order imbalances
Excludes divergence conditions
Marker 3: Large Volume Detection (⤊⤋)
Highlights unusually large individual trades
Spots potential institutional activity
Direction-specific triggers
Configure Data Sources
Adjust exchange pairs if needed (e.g., for altcoin analysis)
Leave blank to disable specific exchanges
Use format: EXCHANGE:SYMBOL
Customize Display
Set tape line quantity based on screen size
Position the table for optimal visibility
Choose color scheme (text or background)
Adjust text size for readability
Configure Alerts
Enable desired markers (1, 2, or 3)
Set volume thresholds appropriate for your timeframe
Choose direction (Longs, Shorts, or Both)
Create PulseWire alerts on marker signals
Trading Applications
Scalping (1-5 min)
Monitor tape speed for momentum shifts
Watch for cross-exchange divergences
Track large volume clusters
Use Marker 1 for quick momentum trades
Day Trading (5-60 min)
Identify accumulation/distribution phases
Spot institutional positioning
Confirm breakout validity with volume delta
Use Marker 2 for significant imbalances
Swing Trading (1H+)
Analyze volume delta trends
Detect smart money rotation
Time entries with order flow confirmation
Use Marker 3 for institutional footprints
Advanced Techniques
Cross-Exchange Arbitrage Detection
When price disparities appear between exchanges:
Immediate Opportunity: Price differences > 0.1%
Bot Activity: Rapid convergence patterns
Liquidity Vacuum: One exchange leading others
Divergence Trading Strategies
Volume delta diverging from price direction:
Absorption: Strong hands entering (price down, delta up)
Distribution: Smart money exiting (price up, delta down)
Reversal Setup: Sustained divergence over multiple bars
Institutional Footprint Recognition
Large volume characteristics:
Simultaneous Spikes: Same timestamp across exchanges
TWAP Patterns: Consistent volume over time
Iceberg Orders: Repeated same-size trades
Pine Script v6 Enhancements
Type Safety Improvements
Strict boolean type handling
Explicit type declarations
Enhanced error checking
Performance Optimizations
Improved request.security() function
Better memory management with arrays
Optimized table rendering
Modern Syntax Updates
indicator() instead of study()
Namespaced math functions (math.round())
Typed input functions (input.int(), input.float())
Performance Considerations
System Requirements
Real-time Data: Essential for tape operation
Multiple Security Calls: May impact performance
Array Operations: Memory intensive with high line counts
Table Rendering: CPU usage increases with tape size
Optimization Tips
Reduce tape lines for better performance
Increase volume filter to reduce noise
Disable unused markers
Use text-only coloring for faster rendering Indicator
Indicator
MACD Forecast Colorful [DiFlip]MACD Forecast Colorful
The Future of Predictive MACD — is one of the most advanced and customizable MACD indicators ever published on PulseWire. Built on the classic MACD foundation, this upgraded version integrates statistical forecasting through linear regression to anticipate future movements — not just react to the past.
With a total of 22 fully configurable long and short entry conditions, visual enhancements, and full automation support, this indicator is designed for serious traders seeking an analytical edge.
⯁ Real-Time MACD Forecasting
For the first time, a public MACD script combines the classic structure of MACD with predictive analytics powered by linear regression. Instead of simply responding to current values, this tool projects the MACD line, signal line, and histogram n bars into the future, allowing you to trade with foresight rather than hindsight.
⯁ Fully Customizable
This indicator is built for flexibility. It includes 22 entry conditions, all of which are fully configurable. Each condition can be turned on/off, chained using AND/OR logic, and adapted to your trading model.
Whether you're building a rules-based quant system, automating alerts, or refining discretionary signals, MACD Forecast Colorful gives you full control over how signals are generated, displayed, and triggered.
⯁ With MACD Forecast Colorful, you can:
• Detect MACD crossovers before they happen.
• Anticipate trend reversals with greater precision.
• React earlier than traditional indicators.
• Gain a powerful edge in both discretionary and automated strategies.
• This isn’t just smarter MACD — it’s predictive momentum intelligence.
⯁ Scientifically Powered by Linear Regression
MACD Forecast Colorful is the first public MACD indicator to apply least-squares predictive modeling to MACD behavior — effectively introducing machine learning logic into a time-tested tool.
It uses statistical regression to analyze historical behavior of the MACD and project future trajectories. The result is a forward-shifted MACD forecast that can detect upcoming crossovers and divergences before they appear on the chart.
⯁ Linear Regression: Technical Foundation
Linear regression is a statistical method that models the relationship between a dependent variable (y) and one or more independent variables (x). The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted variable (e.g., future MACD value)
x = independent variable (e.g., bar index)
β₀ = intercept
β₁ = slope
ε = random error (residual)
The regression model calculates β₀ and β₁ using the least squares method, minimizing the sum of squared prediction errors to produce the best-fit line through historical values. This line is then extended forward, generating a forecast based on recent price momentum.
⯁ Least Squares Estimation
The regression coefficients are computed with the following formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Regression in Machine Learning
Linear regression is a foundational model in supervised learning. Its ability to provide precise, explainable, and fast forecasts makes it critical in AI systems and quantitative analysis.
Applying linear regression to MACD forecasting is the equivalent of injecting artificial intelligence into one of the most widely used momentum tools in trading.
⯁ Visual Interpretation
Picture the MACD values over time like this:
Time →
MACD →
A regression line is fitted to recent MACD values, then projected forward n periods. The result is a predictive trajectory that can cross over the real MACD or signal line — offering an early-warning system for trend shifts and momentum changes.
The indicator plots both current MACD and forecasted MACD, allowing you to visually compare short-term future behavior against historical movement.
⯁ Scientific Concepts Used
Linear Regression: models the relationship between variables using a straight line.
Least Squares Method: minimizes squared prediction errors for best-fit.
Time-Series Forecasting: projects future data based on past patterns.
Supervised Learning: predictive modeling using labeled inputs.
Statistical Smoothing: filters noise to highlight trends.
⯁ Why This Indicator Is Revolutionary
First open-source MACD with real-time predictive modeling.
Scientifically grounded with linear regression logic.
Automatable through PulseWire alerts and bots.
Smart signal generation using forecasted crossovers.
Highly customizable with 22 buy/sell conditions.
Enhanced visuals with background (bgcolor) and area fill (fill) support.
This isn’t just an update — it’s the next evolution of MACD forecasting.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the MACD?
The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram.
⯁ How to use the MACD?
The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line.
Here are the primary signals generated by the MACD:
• Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal.
• Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal.
• Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal.
• Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI.
⯁ How to use MACD forecast?
The MACD Forecast is built on the same foundation as the classic MACD, but with predictive capabilities.
Step 1 — Spot Predicted Crossovers:
Watch for forecasted bullish or bearish crossovers. These signals anticipate when the MACD line will cross the signal line in the future, letting you prepare trades before the move.
Step 2 — Confirm with Histogram Projection:
Use the projected histogram to validate momentum direction. A rising histogram signals strengthening bullish momentum, while a falling projection points to weakening or bearish conditions.
Step 3 — Combine with Multi-Timeframe Analysis:
Use forecasts across multiple timeframes to confirm signal strength (e.g., a 1h forecast aligned with a 4h forecast).
Step 4 — Set Entry Conditions & Automation:
Customize your buy/sell rules with the 20 forecast-based conditions and enable automation for bots or alerts.
Step 5 — Trade Ahead of the Market:
By preparing for future momentum shifts instead of reacting to the past, you’ll always stay one step ahead of lagging traders.
📈 BUY
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
📉 SELL
🍟 Signal Validity: The signal will remain valid for X bars.
🍟 Signal Sequence: Configurable as AND or OR.
🍟 MACD > Signal Smoothing
🍟 MACD < Signal Smoothing
🍟 Histogram > 0
🍟 Histogram < 0
🍟 Histogram Positive
🍟 Histogram Negative
🍟 MACD > 0
🍟 MACD < 0
🍟 Signal > 0
🍟 Signal < 0
🍟 MACD > Histogram
🍟 MACD < Histogram
🍟 Signal > Histogram
🍟 Signal < Histogram
🍟 MACD (Crossover) Signal
🍟 MACD (Crossunder) Signal
🍟 MACD (Crossover) 0
🍟 MACD (Crossunder) 0
🍟 Signal (Crossover) 0
🍟 Signal (Crossunder) 0
🔮 MACD (Crossover) Signal Forecast
🔮 MACD (Crossunder) Signal Forecast
🤖 Automation
All BUY and SELL conditions can be automated using PulseWire alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Indicator
