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BTC Mayer Multiple BandsIntroduced by Trace Mayer as a way to gauge the current price of Bitcoin against its long range historical price movements (200 day moving average), the Mayer Multiple highlights when Bitcoin is overbought or oversold in the context of longer time frames. It's worth noting that as the market becomes larger and less volatile, the peaks are becoming less exaggerated. This is because a 200 day moving average baseline is a static yardstick against an ever growing, more stable, Bitcoin market. We should recalibrate what constitutes the overbought/oversold extremes on this chart accordingly. Idea by CryptoKea. Original author:
مؤشر Pine Script®
من ‎jaggedsoft‎
7
BTC Net Volume Delta (Spot)One of my favorite indicators for trend analysis. We sum the volume from all significant BTC Spot exchanges and subtract the sell volume from the buy volume for a cumulative total. A futures version is also available but spot volume is more consistent for analysis. To follow trends you can buy when sell momentum is decreasing, and sell when buy momentum is decreasing. Do you have any ideas for monitoring sentiment or open interest across multiple exchanges? Message me and I will try to make it happen.
مؤشر Pine Script®
من ‎jaggedsoft‎
14
BTC 1D Alerts V1This script contains a variety of key indicator for bitcoin all-in-one and they can be activated individually in the menu. These are meant to be used on the 1D chart for Bitcoin. 1457 Day Moving Average: the bottom of the bitcoin price and arguably the rock bottom price target. Ichimoku Cloud: a common useful indicator for bitcoin support and resistance. 350ma fibs (21 8 5 3 2 and 1.6) : Signify the tops of each logarthmic rise in bitcoin price. They are generally curving higher over the long term. For halvening #3, the predicted market crash would be after hitting the 350ma x3 fib. Also the 350 ma / 111 ma cross signifies bull market top within about 3 days as well. Using the combination of the 350ma fibs and the 350/111 crosses, reasonably identify when market top is about to occur. 50,120,200 ma: Common moving averages that bitcoin retests during bull market runs. Also, the 50/200 golden and death crosses. 1D EMA Superguppy Ribbons: green = bull market, gray is indeterminate, red = bear market. Very high specificity indicator of bull runs, especially for bitcoin. You can change to 3D candle for even more specificity for a bull market start. Use the 1W for even more specificity. 1D Superguppy is recommended for decisionmaking. 1W EMA21: a very good moving average programmed to be shown on both the daily and weekly candle time. Bitcoin commonly corrects to this repeatedly during past bull runs. Acts as support during bull run and resistance during a bear market. Steps to identifying a bull market: 1. 50/200 golden cross 2. 1D EMA superguppy green 3. 3D EMA superguppy green (if you prefer more certainty than step 2). 4. Hitting the 1W EMA21 and bouncing off during the bull run signifies corrections. Once a bull market is identified, Additional recommended buying and selling techniques: Indicators: - Fiblines - to determine retracements from peaks (such as all time high or recent highs) - Stochastic RSI - 1d, 3d, and 1W SRSI are great time to buy, especially the 1W SRSI which comes much less frequently. - volumen consolidado - for multi exchange volumes compiled into a single line. I prefer buying on the lowest volume days which generally coincide with dips. - MACD - somewhat dubious utility but many algorithms are programmed to buy or sell based on this. Check out the Alerts for golden crosses and 350ma Fib crosses which are invaluable for long term buying planning. I left this open source so that all the formulas can be understood and verified. Much of it hacked together from other sources but all indicators that are fundamental to bitcoin. I apologize in advance for not attributing all the articles and references... but then again I am making no money off of this anyway.
مؤشر Pine Script®
من ‎Cephii‎
BTC Weighted Composite IndexThis script was written to complement my custom built equal weighted btc composite indice: type the following text as the symbol: ~~ (BITMEX:XBTUSD*42.74+BINANCE:BTCUSDT*31.41+BITFINEX:BTCUSD*23.47+COINBASE:BTCUSD*8.1+BITSTAMP:BTCUSD*8.2+KRAKEN:XBTUSD*3.9+POLONIEX:BTCUSDT*1.1+GEMINI:BTCUSD*2.8+BITTREX:BTCUSDT*1.1)/122.82 ~~ by applying this script to the above symbol: it shows total volume, in $ amounts across the 9 exchanges.
مؤشر Pine Script®
من ‎PMtrading20‎
1
Ben's BTC Macro Fair Value OscillatorBen's BTC Macro Fair Value Oscillator Overview The **BTC Macro Fair Value Oscillator** is a non-crypto fair value framework that uses macro asset relationships (equities, dollar, gold) to estimate Bitcoin's "macro-driven fair value" and identify mean-reversion opportunities. "Is BTC cheap or expensive right now?" on the 4 Hour Timeframe ONLY ### Key Features ✅ **Macro-driven**: Uses QQQ, DXY, XAUUSD instead of on-chain or crypto metrics ✅ **Dynamic weighting**: Assets weighted by rolling correlation strength ✅ **Mean-reversion signals**: Identifies when BTC is cheap/expensive vs macro ✅ **Validated parameters**: Optimized through 5-year backtest (Sharpe 6.7-9.9) ✅ **Visual transparency**: Live correlation panel, fair value bands, statistics ✅ **Non-repainting**: All calculations use confirmed historical data only ### What This Indicator Does - Builds a **synthetic macro composite** from traditional assets - Runs a **rolling regression** to predict BTC price from macro - Calculates **deviation z-score** (how far BTC is from macro fair value) - Generates **entry signals** when BTC is extremely cheap vs macro (dev < -2) - Generates **exit signals** when BTC returns to fair value (dev > 0) ### What This Indicator Is NOT ❌ Not a high-frequency trading system (sparse signals by design) ❌ Not optimized for absolute returns (optimized for Sharpe ratio) ❌ Not suitable as standalone trading system (best as overlay/confirmation) ❌ Not predictive of short-term price movements (mean-reversion timeframe: days to weeks) --- ## Core Concept ### The Premise Bitcoin doesn't trade in a vacuum. It's influenced by: - **Risk appetite** (equities: QQQ, SPX) - **Dollar strength** (DXY - inverse to risk assets) - **Safe haven flows** (Gold: XAUUSD) When macro conditions are "good for BTC" (risk-on, weak dollar, strong equities), BTC should trade higher. When macro conditions turn against it, BTC should trade lower. ### The Innovation Instead of looking at BTC in isolation, this indicator: 1. **Measures how strongly** BTC currently correlates with each macro asset 2. **Builds a weighted composite** of those macro returns (the "D" driver) 3. **Regresses BTC price on D** to estimate "macro fair value" 4. **Tracks the deviation** between actual price and fair value 5. **Signals mean reversion** when deviation becomes extreme ### The Edge The validated edge comes from: - **Extreme deviations predict future returns** (dev < -2 → +1.67% over 12 bars) - **Monotonic relationship** (more negative dev → higher forward returns) - **Works out-of-sample** (test Sharpe +83-87% better than training) - **Low correlation with buy & hold** (provides diversification value) --- ## Methodology ### Step 1: Macro Composite Driver D(t) The indicator builds a weighted composite of macro asset returns: **Process:** 1. Calculate **log returns** for BTC and each macro reference (QQQ, DXY, XAUUSD) 2. Compute **rolling correlation** between BTC and each reference over `corrLen` bars 3. **Weight each asset** by `|correlation|` if above `minCorrAbs` threshold, else 0 4. **Sign-adjust** weights (+1 for positive corr, -1 for negative) to handle inverse relationships 5. **Z-score normalize** each reference's returns over `fvWindow` 6. **Composite D(t)** = weighted sum of sign-adjusted z-scores **Formula:** ``` For each reference i: corr_i = correlation(BTC_returns, ref_i_returns, corrLen) weight_i = |corr_i| if |corr_i| >= minCorrAbs else 0 sign_i = +1 if corr_i >= 0 else -1 z_i = (ref_i_returns - mean) / std contrib_i = sign_i * z_i * weight_i D(t) = sum(contrib_i) / sum(weight_i) ``` **Key Insight:** D(t) represents "how good macro conditions are for BTC right now" in a normalized, correlation-weighted way. --- ### Step 2: Fair Value Regression Uses rolling linear regression to predict BTC price from D(t): **Model:** ``` BTC_price(t) = α + β * D(t) ``` **Calculation (Pine Script approach):** ``` corr_CD = correlation(BTC_price, D, fvWindow) sd_price = stdev(BTC_price, fvWindow) sd_D = stdev(D, fvWindow) cov = corr_CD * sd_price * sd_D var_D = variance(D, fvWindow) β = cov / var_D α = mean(BTC_price) - β * mean(D) fair_value(t) = α + β * D(t) ``` **Result:** A time-varying "macro fair value" line that adapts as correlations change. --- ### Step 3: Deviation Oscillator Measures how far BTC price has deviated from fair value: **Calculation:** ``` residual(t) = BTC_price(t) - fair_value(t) residual_std = stdev(residual, normWindow) deviation(t) = residual(t) / residual_std ``` **Interpretation:** - `dev = 0` → BTC at fair value - `dev = -2` → BTC is 2 standard deviations **cheap** vs macro - `dev = +2` → BTC is 2 standard deviations **rich** vs macro --- ### Step 4: Signal Generation **Long Entry:** `dev` crosses below `-2.0` (BTC extremely cheap vs macro) **Long Exit:** `dev` crosses above `0.0` (BTC returns to fair value) **No shorting** in default config (risk management choice - crypto volatility) --- ## How It Works ### Visual Components #### 1. Price Chart (Main Panel) **Fair Value Line (Orange):** - The estimated "macro-driven fair value" for BTC - Calculated from rolling regression on macro composite **Fair Value Bands:** - **±1σ** (light): 68% confidence zone - **±2σ** (medium): 95% confidence zone - **±3σ** (dark, dots): 99.7% confidence zone **Entry/Exit Markers:** - **Green "LONG" label** below bar: Entry signal (dev < -2) - **Red "EXIT" label** above bar: Exit signal (dev > 0) #### 2. Deviation Oscillator (Separate Pane) **Line plot:** - Shows current deviation z-score - **Green** when dev < -2 (cheap) - **Red** when dev > +2 (rich) - **Gray** when neutral **Histogram:** - Visual representation of deviation magnitude - Green bars = negative deviation (cheap) - Red bars = positive deviation (rich) **Threshold lines:** - **Green dashed at -2.0**: Entry threshold - **Red dashed at 0.0**: Exit threshold - **Gray solid at 0**: Fair value line #### 3. Correlation Panel (Top-Right) Shows live correlation and weighting for each macro asset: | Asset | Corr | Weight | |-------|------|--------| | QQQ | +0.45 | 0.45 | | DXY | -0.32 | 0.32 | | XAUUSD | +0.15 | 0.00 | | Avg \|Corr\| | 0.31 | 0.77 | **Reading:** - **Corr**: Current rolling correlation with BTC (-1 to +1) - **Weight**: How much this asset contributes to fair value (0 = excluded) - **Avg |Corr|**: Average correlation strength (should be > 0.2 for reliable signals) **Colors:** - Green/Red corr = positive/negative correlation - White weight = asset included, Gray = excluded (below minCorrAbs) #### 4. Statistics Label (Bottom-Right) ``` ━━━ BTC Macro FV ━━━ Dev: -2.34 Price: $103,192 FV: $110,500 Status: CHEAP ⬇ β: 103.52 ``` **Fields:** - **Dev**: Current deviation z-score - **Price**: Current BTC close price - **FV**: Current macro fair value estimate - **Status**: CHEAP (< -2), RICH (> +2), or FAIR - **β**: Current regression beta (sensitivity to macro) --- ## Installation & Setup ### TradingView Setup 1. Open TradingView and navigate to any **BTC chart** (BTCUSD, BTCUSDT, etc.) 2. Open **Pine Editor** (bottom panel) 3. Click **"+ New"** → **"Blank indicator"** 4. **Delete** all default code 5. **Copy** the entire Pine Script from `GHPT_optimized.pine` 6. **Paste** into the editor 7. Click **"Save"** and name it "BTC Macro Fair Value Oscillator" 8. Click **"Add to Chart"** ### Recommended Chart Settings **Timeframe:** 4h (validated timeframe) **Chart Type:** Candlestick or Heikin Ashi **Overlay:** Yes (indicator plots on price chart + separate pane) **Alternative Timeframes:** - Daily: Works but slower signals - 1h-2h: May work but not validated - < 1h: Not recommended (too noisy) ### Symbol Requirements **Primary:** BTC/USD or BTC/USDT on any exchange **Macro References:** Automatically fetched - QQQ (Nasdaq 100 ETF) - DXY (US Dollar Index) - XAUUSD (Gold spot) **Data Requirements:** - At least **90 bars** of history (warmup period) - Premium TradingView recommended for full historical data --- ## Reading the Indicator ### Identifying Signals #### Strong Long Signal (High Conviction) - ✅ Deviation < -2.0 (extreme undervaluation) - ✅ Avg |Corr| > 0.3 (strong macro relationships) - ✅ Price touching or below -2σ band - ✅ "LONG" label appears below bar **Interpretation:** BTC is extremely cheap relative to macro conditions. Historical data shows +1.67% average return over next 12 bars (48 hours at 4h timeframe). #### Moderate Long Signal (Lower Conviction) - ⚠️ Deviation between -1.5 and -2.0 - ⚠️ Avg |Corr| between 0.2-0.3 - ⚠️ Price approaching -2σ band **Interpretation:** BTC is cheap but not extreme. Consider as confirmation for other signals. #### Exit Signal - 🔴 Deviation crosses above 0 (returns to fair value) - 🔴 "EXIT" label appears above bar **Interpretation:** Mean reversion complete. Close long positions. #### Strong Short/Avoid Signal - 🔴 Deviation > +2.0 (extreme overvaluation) - 🔴 Avg |Corr| > 0.3 - 🔴 Price touching or above +2σ band **Interpretation:** BTC is expensive vs macro. Historical data shows -1.79% average return over next 12 bars. Consider exiting longs or reducing exposure. ### Regime Detection **Strong Regime (Reliable Signals):** - Avg |Corr| > 0.3 - Multiple assets weighted > 0 - Fair value line tracking price reasonably well **Weak Regime (Unreliable Signals):** - Avg |Corr| < 0.2 - Most weights = 0 (grayed out) - Fair value line diverging wildly from price - **Action:** Ignore signals until correlations strengthen
مؤشر Pine Script®
من ‎popularGnuofls7‎