Mulai

Siklus

Classic Dual Momentum – 12-Month Absolute Momentum - AntonacciThis indicator calculates the 12-month absolute momentum exactly as described in Gary Antonacci’s Dual Momentum framework. It automatically adjusts the lookback period based on the chart’s timeframe: Daily chart: 252 bars Weekly chart: 52 bars Monthly chart: 12 bars Other timeframes: Estimated automatically using bar time difference The script computes the 12-month rate of return and displays it as a color-coded column plot: Green: Positive 12-month momentum Red: Negative 12-month momentum A customizable moving average is included to help visualize longer-term trends in the momentum signal. How It’s Used (from Dual Momentum theory) This indicator provides the absolute momentum filter used in classic Dual Momentum strategies: If the 12-month return of an asset is above the risk-free return → trend is positive If it is below the risk-free return → trend is negative This absolute momentum check is a key component of the Global Equities Momentum (GEM) model presented in Gary Antonacci’s book Dual Momentum Investing. Why This Indicator Exists It gives traders a clean, accurate way to visualize the 12-month trend strength across any timeframe, without the distortions caused by bar length differences.
Indikator Pine Script®
oleh rahul_joshi_2
BTC GOD — DEFINITIVE BTC MULTI INDICATORBTC GOD — The Ultimate Bitcoin Cycle Indicator (2025 Edition) The one indicator every serious BTC holder and trader has been waiting for. A single script that perfectly combines the 5 most powerful and accurate Bitcoin indicators ever created — all 100 % official versions: - Official Pi Cycle Top (LookIntoBitcoin) → in 2013, 2017 & 2021 (3/3 hits) - Official MVRV Z-Score (Glassnode / LookIntoBitcoin) → every major bottom (2015, 2018–19, 2022) - Dynamic Bull/Bear background (red bear-market when price drops X % from cycle ATH + monthly RSI filter) - Monthly Golden/Death Cross (50-month EMA vs 200-week EMA) → huge, unmistakable signals - SuperTrend + 200-week EMA + 50-month EMA - Cycle ATH/ATL tracking with flashing alert in the table when new highs/lows are made - Exact days to/from the next halving + optimal accumulation zone (200–750 days post-halving) - Fully customizable inputs for experienced traders Zero repainting. Zero errors. Works on every timeframe. This is the indicator used by people who truly understand Bitcoin’s 4-year cycles. If you could only keep ONE Bitcoin indicator for the rest of your life… this would be it. Save it, test it, and you’ll instantly see why it’s called BTC GOD. Built with love and obsession for Bitcoin cycles. Last update: November 2025
Indikator Pine Script®
oleh nahumperez86
Z-Fusion Oscillator | Lyro RSThe Z-Fusion Oscillator converts five momentum indicators into Z-scores and blends them into one normalized signal that adapts across markets. By combining normalization, smoothing, and divergence detection, users can easily identify when momentum is accelerating, weakening, reversing, or entering extreme zones 🔶 USAGE The Z-Fusion Oscillator is designed to give traders a unified reading of market momentum—removing the noise of comparing tools that normally run on different scales. By transforming RSI, MACD histogram, Stochastic, Momentum, and Rate of Change into Z-scores, this tool standardizes all inputs, making trend strength and shifts easier to interpret. A dual-line system (fast Z-fusion line + slower baseline) highlights turning points, while overbought/oversold bands and “X-marks” help traders spot exhaustion and potential reversals. 🔹 Unified Momentum Structure The indicator’s core strength comes from combining five Z-scored signals into one average. Which makes momentum behavior more consistent across assets, reduces false extremes, and highlights true shifts in trend conviction. 🔹 Divergence Detection The tool includes fully integrated divergence detection: Regular Bullish Divergence: Price makes a lower low while Z-Fusion forms a higher low. Regular Bearish Divergence: Price makes a higher high while Z-Fusion forms a lower high Bullish and bearish divergences are marked directly on the oscillator with labels and colored pivot connections, making hidden momentum shifts obvious. 🔹 Visual Extremes Two sets of upper and lower Z-score thresholds help identify: Extreme overbought surges Extreme oversold drops Reversal zones Potential exhaustion conditions Background coloring reinforces when the oscillator moves beyond major levels, helping traders quickly assess momentum pressure. 🔹 Detecting Momentum Anomalies Z-scores allow the oscillator to highlight when market momentum behaves abnormally relative to its own recent history. For example: The oscillator reaching +1 or –1 after an extended trend may indicate a climax. A sharp Z-score reversal within an extreme zone can signal a trend exhaustion or a corrective move. Divergences often appear earlier due to normalization smoothing out indicator noise. This makes the Z-Fusion Oscillator particularly useful for spotting subtle shifts in trend direction that traditional indicators may miss. 🔶 DETAILS 🔹 Composite Z-Score Framework Each momentum tool is smoothed, normalized, and transformed: RSI → EMA-smoothed, Z-scored MACD histogram → Z-scored Stochastic → EMA + SMA smoothing, then Z-scored Momentum → EMA-smoothed, Z-scored Rate of Change → EMA-smoothed, Z-scored These are averaged into one composite Z-score to provide a consistent reading across assets and market conditions. 🔹 Fusion Trend Lines Two lines serve as the core signal: Fast Line (savg) – reacts quicker to trend changes Slow Line (savg2) – acts as a baseline filter Crossovers between these lines highlight momentum shifts, while their color reflects trend bias. 🔹 Overbought/Oversold Zones Two upper and two lower Z-score thresholds define “zones”: Upper zones highlight overheated momentum or potential bearish reversals Lower zones highlight depressed momentum or potential bullish reversals Filled regions and background colors help visually confirm extreme conditions. 🔹 Pivot-Based Divergence Engine The script includes filtered pivot detection with customizable look-backs and range limits to ensure divergences are meaningful, not noise-driven. 🔶 SETTINGS 🔹 Indicator Settings Source — Price series used for all calculations. Z-Score Length — Lookback period for Z-score normalization. Z-Score MA Length — Smoothing length for the fusion signal lines. Overbought/Oversold Levels — Four customizable threshold lines. Color Palette — Choose from preset themes or define custom colors. 🔹 RSI Length — RSI calculation period. EMA Smoothing Length — Smooths RSI before Z-score conversion. 🔹 MACD Fast Length — Fast EMA length. Slow Length — Slow EMA length. Signal Line Length — MACD signal smoothing. 🔹 Stochastic %K Length — Main stochastic length. EMA Smoothing — Smooths %K for stability. %D Length — Smoothing for the signal line. 🔹 Momentum Length — Momentum lookback. EMA Smoothing — Smooths momentum before Z-scoring. 🔹 Rate of Change Length — ROC lookback. EMA Smoothing — Smooths ROC values. 🔹 Divergence Enable/Disable Divergence Detection — Toggle divergence engine. Pivot Left/Right Lookback — Defines pivot detection sensitivity. Detection Range Limits — Controls allowable range for divergence. Bull/Bear Colors & Styling — Customize divergence visualization. 🔶 SUMMARY The Z-Fusion Oscillator combines multiple momentum signatures into a single normalized signal, enabling traders to: Identify reversals early Detect momentum exhaustion Spot bullish and bearish divergences Track overbought/oversold conditions Visualize trend strength with clarity Whether you're a swing trader, intraday analyst, or trend-reversal hunter, the Z-Fusion Oscillator provides a powerful and adaptive way to read momentum.
Indikator Pine Script®
oleh LyroRS
BTC Halving Cycle SignalsBTC Halving Cycle Signals What signals does this script give in real history (2011-2025): 2015 → BUY (bear market bottom) 2019 → BUY (post-2018 bottom) October 2020 → BUY November 2023 → BUY And right now (Nov 2025) → green bottom + price above weekly EMA200 → about to give a buy signal if it breaks $72k strongly. BUY signal: ~500 days pre-halving + price > weekly EMA200 + monthly RSI <60 (accumulation). SELL signal: ~1064 days post-halving + RSI >75 or close < SuperTrend (distribution). Hardcoded halving dates (can be edited). Works on BTCUSD weekly/monthly, gives 1-2 signals per cycle.
Indikator Pine Script®
oleh nahumperez86
BTC Energy + HR + Longs + M2 BTC Energy Ratio + Hashrate + Longs + M2 The #1 Bitcoin Macro Weapon on TradingView 🚀🔥 If you’re tired of getting chopped by fakeouts, ETF noise, and Twitter hopium — this is the one chart that finally puts you on the right side of every major move. What you’re looking at: Orange line → Bitcoin priced in real-world mining energy (Oil × Gas + Uranium × Coal) × 1000 → The true fundamental floor of BTC Blue line → Scaled hashrate trend (miner strength & capex lag) Green line → Bitfinex longs EMA (leveraged bull sentiment) Purple line → Global M2 money supply (US+EU+CN+JP) with 10-week lead (the liquidity wave BTC rides) Why this indicator prints money: Most tools react to price. This one predicts where price is going based on energy, miners, leverage, and liquidity — the only four things that actually drive Bitcoin long-term. It has nailed: 2022 bottom at ~924 📉 2024 breakout above 12,336 🚀 2025 top at 17,280 🏔️ And right now it’s flashing generational accumulation at ~11,500 (Nov 2025) 13 permanent levels with right-side labels — no guessing what anything means: 20,000 → 2021 Bull ATH 17,280 → 2025 ATH 15,000 → 2024 High Resist 14,000 → Overvalued Zone 13,000 → 2024 Breakout 12,336 → Bull/Bear Line (the most important level) 12,000 → 2024 Volume POC 10,930 → Key Support 2024 9,800 → Strong Buy Fib 8,000 → Deep Support 2023 6,000 → 2021 Mid-Cycle 4,500 → 2023 Accum Low 924 → 2022 Bear Low Live dashboard tells you exactly what to do — no thinking required: Current ratio (updates live) Hashrate + 24H % Longs trend Risk Mode → Orange vs Hashrate (RISK ON / RISK OFF) 180-day correlation RSI 13-tier Zone + SIGNAL (STRONG BUY / ACCUMULATE / HOLD / DISTRIBUTE / EXTREME SELL) Dead-simple rules that actually work: Weekly timeframe = cleanest view Blue peaking + orange holding support → miner pain = next leg up Green spiking + orange failing → overcrowded longs = trim Purple rising → liquidity coming in = ride the wave Risk Mode = RISK OFF → price is cheap vs miners → buy Set these 3 alerts and walk away: Ratio > 12,336 → Bull confirmed → add Ratio > 14,000 → Start scaling out Ratio < 9,800 → Generational buy → back up the truck No repainting • Fully open-source • Forced daily data • Works on any TF Energy is the only real backing Bitcoin has. Hashrate lag is the best leading indicator. Longs show greed. M2 is the tide. This chart combines all four — and right now it’s screaming ACCUMULATE. Load it. Trust it. Stop trading hope. Start trading reality. DYOR • NFA • For entertainment purposes only 😎 #bitcoin #macro #energy #hashrate #m2 #cycle #riskon #riskoff
Indikator Pine Script®
oleh AndyHansen
Static K-means Clustering | InvestorUnknownStatic K-Means Clustering is a machine-learning-driven market regime classifier designed for traders who want a data-driven structure instead of subjective indicators or manually drawn zones. This script performs offline (static) K-means training on your chosen historical window. Using four engineered features: RSI (Momentum) CCI (Price deviation / Mean reversion) CMF (Money flow / Strength) MACD Histogram (Trend acceleration) It groups past market conditions into K distinct clusters (regimes). After training, every new bar is assigned to the nearest cluster via Euclidean distance in 4-dimensional standardized feature space. This allows you to create models like: Regime-based long/short filters Volatility phase detectors Trend vs. chop separation Mean-reversion vs. breakout classification Volume-enhanced money-flow regime shifts Full machine-learning trading systems based solely on regimes Note: This script is not a universal ML strategy out of the box. The user must engineer the feature set to match their trading style and target market. K-means is a tool, not a ready made system, this script provides the framework. Core Idea K-means clustering takes raw, unlabeled market observations and attempts to discover structure by grouping similar bars together. // STEP 1 — DATA POINTS ON A COORDINATE PLANE // We start with raw, unlabeled data scattered in 2D space (x/y). // At this point, nothing is grouped—these are just observations. // K-means will try to discover structure by grouping nearby points. // // y ↑ // | // 12 | • // | • // 10 | • // | • // 8 | • • // | // 6 | • // | // 4 | • // | // 2 |______________________________________________→ x // 2 4 6 8 10 12 14 // // // // STEP 2 — RANDOMLY PLACE INITIAL CENTROIDS // The algorithm begins by placing K centroids at random positions. // These centroids act as the temporary “representatives” of clusters. // Their starting positions heavily influence the first assignment step. // // y ↑ // | // 12 | • // | • // 10 | • C2 × // | • // 8 | • • // | // 6 | C1 × • // | // 4 | • // | // 2 |______________________________________________→ x // 2 4 6 8 10 12 14 // // // // STEP 3 — ASSIGN POINTS TO NEAREST CENTROID // Each point is compared to all centroids. // Using simple Euclidean distance, each point joins the cluster // of the centroid it is closest to. // This creates a temporary grouping of the data. // // (Coloring concept shown using labels) // // - Points closer to C1 → Cluster 1 // - Points closer to C2 → Cluster 2 // // y ↑ // | // 12 | 2 // | 1 // 10 | 1 C2 × // | 2 // 8 | 1 2 // | // 6 | C1 × 2 // | // 4 | 1 // | // 2 |______________________________________________→ x // 2 4 6 8 10 12 14 // // (1 = assigned to Cluster 1, 2 = assigned to Cluster 2) // At this stage, clusters are formed purely by distance. Your chosen historical window becomes the static training dataset , and after fitting, the centroids never change again. This makes the model: Predictable Repeatable Consistent across backtests Fast for live use (no recalculation of centroids every bar) Static Training Window You select a period with: Training Start Training End Only bars inside this range are used to fit the K-means model. This window defines: the market regime examples the statistical distributions (means/std) for each feature how the centroids will be positioned post-trainin Bars before training = fully transparent Training bars = gray Post-training bars = full colored regimes Feature Engineering (4D Input Vector) Every bar during training becomes a 4-dimensional point: This combination balances: momentum, volatility, mean-reversion, trend acceleration giving the algorithm a richer "market fingerprint" per bar. Standardization To prevent any feature from dominating due to scale differences (e.g., CMF near zero vs CCI ±200), all features are standardized: standardize(value, mean, std) => (value - mean) / std Centroid Initialization Centroids start at diverse coordinates using various curves: linear sinusoidal sign-preserving quadratic tanh compression init_centroids() => // Spread centroids across using different shapes per feature for c = 0 to k_clusters - 1 frac = k_clusters == 1 ? 0.0 : c / (k_clusters - 1.0) // 0 → 1 v = frac * 2 - 1 // -1 → +1 array.set(cent_rsi, c, v) // linear array.set(cent_cci, c, math.sin(v)) // sinusoidal array.set(cent_cmf, c, v * v * (v < 0 ? -1 : 1)) // quadratic sign-preserving array.set(cent_mac, c, tanh(v)) // compressed This makes initial cluster spread “random” even though true randomness is hardly achieved in pinescript. K-Means Iterative Refinement The algorithm repeats these steps: (A) Assignment Step, Each bar is assigned to the nearest centroid via Euclidean distance in 4D: distance = sqrt(dx² + dy² + dz² + dw²) (B) Update Step, Centroids update to the mean of points assigned to them. This repeats iterations times (configurable). LIVE REGIME CLASSIFICATION After training, each new bar is: Standardized using the training mean/std Compared to all centroids Assigned to the nearest cluster Bar color updates based on cluster No re-training occurs. This ensures: No lookahead bias Clean historical testing Stable regimes over time CLUSTER BEHAVIOR & TRADING LOGIC Clusters (0, 1, 2, 3…) hold no inherent meaning. The user defines what each cluster does. Example of custom actions: Cluster 0 → Cash Cluster 1 → Long Cluster 2 → Short Cluster 3+ → Cash (noise regime) This flexibility means: One trader might have cluster 0 as consolidation. Another might repurpose it as a breakout-loading zone. A third might ignore 3 clusters entirely. Example on ETHUSD Important Note: Any change of parameters or chart timeframe or ticker can cause the “order” of clusters to change The script does NOT assume any cluster equals any actionable bias, user decides. PERFORMANCE METRICS & ROC TABLE The indicator computes average 1-bar ROC for each cluster in: Training set Test (live) set This helps measure: Cluster profitability consistency Regime forward predictability Whether a regime is noise, trend, or reversion-biased EQUITY SIMULATION & FEES Designed for close-to-close realistic backtesting. Position = cluster of previous bar Fees applied only on regime switches. Meaning: Staying long → no fee Switching long→short → fee applied Switching any→cash → fee applied Fee input is percentage, but script already converts internally. Disclaimers ⚠️ This indicator uses machine-learning but does not predict the future. It classifies similarity to past regimes, nothing more. ⚠️ Backtest results are not indicative of future performance. ⚠️ Clusters have no inherent “bullish” or “bearish” meaning. You must interpret them based on your testing and your own feature engineering.
Indikator Pine Script®
oleh InvestorUnknown
2
MTF FVG 智能終極版 (Smart Clean)指標名稱：MTF FVG 智能終極版 (Smart Clean) 簡潔介紹 這是一款專為專業交易者設計的 多週期失衡區 (FVG) 監控系統，核心特色如下： 五維度監控： 在任何圖表上同時顯示 月、周、日、4H、2H 五種級別的支撐壓力缺口。 智慧重疊清理 (獨家)： 當價格重疊時，自動刪除舊框框，只保留最新的 1~3 個（可設定）；若無重疊則完整保留歷史痕跡。確保圖表乾淨且資訊不遺漏。 完美視覺體驗： 大週期無限延伸，小週期固定長度。 文字自動靠右並智慧留白，確保不遮擋右側價格座標。 深色邊框 + 淺色填充 + 中線虛線，層次分明。 Indicator Name: MTF FVG Smart Clean Ultimate Edition Brief Introduction This is a multi-timeframe Free Gaps (FVG) monitoring system designed for professional traders. Its core features include: Five-Dimensional Monitoring: Simultaneously displays support, resistance, and gaps at five timeframes (monthly, weekly, daily, 4H, and 2H) on any chart. Intelligent Overlap Cleanup (Exclusive): When prices overlap, automatically deletes old boxes, retaining only the latest 1-3 (configurable); if there is no overlap, it retains all historical data. Ensures a clean chart and complete information. Perfect Visual Experience: Larger timeframes extend infinitely, while smaller timeframes have fixed lengths. Text automatically aligns to the right with intelligent white space to ensure it doesn't obscure the price coordinates on the right. Dark borders + light fill + dashed center line create clear visual hierarchy.
Indikator Pine Script®
oleh weiting_emerald
Session Highlighter (Asia / London / New York)This TradingView Pine Script highlights the three major Forex sessions—Asia, London, and New York—directly on the chart. Each session has customizable start/end times (based on New York time), toggle switches to show or hide them, and adjustable background colors. The script automatically detects sessions that cross midnight and shades the chart accordingly. It can also place optional labels at the exact opening of each session.
Indikator Pine Script®
oleh maguilar126
CME Bitcoin Weekend Gap (Global) @jerikooDescription: The Problem: You are watching the wrong hours. Many traders assume CME Bitcoin futures follow standard stock market hours or open Monday morning. This is incorrect. Stock Market: Opens Monday morning. CME Bitcoin: Opens Sunday Evening (US Time). If you are in Europe, this means the market actually opens at Midnight (00:00) Monday. If you are waiting for the "Monday Morning Open," you are late. The Solution: True Gap Detection This indicator highlights the exact downtime of the CME Bitcoin Futures market to help you identify true liquidity gaps. Why this script is different: Most gap scripts break when you change your chart's time zone (e.g., switching from UTC to New York). This script is Universal. Hardcoded Exchange Time: It calculates logic based on "America/Chicago" (CME HQ) time, regardless of your local chart settings. Manual Offset Fix: Some data feeds have a +/- 1 or 2-hour sync difference depending on the broker. This script includes a "Hour Shift" setting to manually align the box perfectly to your specific candles. How to use: Add to your chart. Look for the Dark Green highlighted zone. This zone represents the Weekend Gap (Friday Close to Sunday Open). Troubleshooting: If the box starts 1-2 hours too early or too late, go to Settings and change the "Hour Shift" value (e.g., -1, +1) until it snaps perfectly to the Friday close candle. Technical Details: CME Close: Friday 16:00 CT CME Open: Sunday 17:00 CT Color: Dark Green (50% Transparency) Step 3: Categories & Tags Select these options in the right-hand menu of the publishing page. Category: Trend Analysis OR Bitcoin Tags: CME Bitcoin BTC Gap Futures Weekend Step 4: Final Checklist Before Clicking "Publish" Load the Code: Make sure the "Manual Fix" version of the code (the last one I gave you) is currently open in the Pine Editor. Add to Chart: You must click "Add to Chart" so the script is visible on your screen before publishing. Privacy: Select Public (so others can search for it) or Private (if you only want to share the link). Visibility: Choose Open (so others can see the code) or Protected (if you want to hide the code, though Open is better for simple scripts like this).
Indikator Pine Script®
oleh jerikoo
BTC Risk Metric DCA Adapter (3Commas Webhook Strategy)Risk Metric DCA Adapter (3Commas Webhook Strategy) - WORK IN PROGRESS This Pine Script strategy, originally inspired by the Risk Metric Indicator, is fundamentally engineered as an Adapter to interface with external trading bots like 3Commas via Webhooks. It calculates a dynamic market risk score and translates that score into specific dollar-cost averaging (DCA) entry levels and tiered profit-taking exits. Key Features & Logic Risk Metric Calculation (Credit to The Trading Parrot): The strategy incorporates a complex, multi-timeframe Risk Metric calculation based on daily and weekly moving averages (SMA) and standard deviation (StDev). This metric aims to quantify the current market overextension or compression relative to long-term historical data. The resulting score dictates the level of conviction for a new trade. Tiered DCA Entry Sizing: The strategy defines three distinct Buy Levels (L1, L2, L3) corresponding to increasingly favorable (lower) Risk Metric scores. L1 (Base): Risk is moderate, initiating the minimum defined trade amount. L2 (Scaled): Risk is low, initiating L1 amount + L2 amount. L3 (Aggressive): Risk is very low, initiating L1 + L2 + L3 amounts. Tiered Profit-Taking Exits: The strategy implements a staggered, partial profit-taking approach based on the Risk Metric rising: Sell L1 & L2: Closes a percentage of the current position when the Risk Metric reaches defined high thresholds, locking in partial profits. Sell L3 (Full Exit): Closes the remaining position when the Risk Metric reaches the highest defined threshold. The Adapter Function (Webhook Integration) This script is unique because it uses the Pine Script strategy() function to trigger Order Fills, which are necessary to access powerful placeholders in the TradingView alert system. Trigger Type: The alert must be set to trigger on Any order fill. Dynamic Webhook Data: Instead of using fixed alert() commands, the strategy generates dynamic labels (e.g., BUY_ENTRY_L3_USD_1000 or SELL_L1_PCT_25) using the strategy.entry and strategy.close commands. Data Transfer: The alert message then uses the placeholder {{strategy.order.comment}} to pass these dynamic labels to the 3Commas bot, allowing the bot to execute the precise action (e.g., start_deal_with_volume_in_quote_currency or close_deal_at_market_percentage). Full Strategy Webhook payload { "secret": "YOUR_3COMMAS_SECRET_KEY", "max_lag": "300", "timestamp": "{{timenow}}", "trigger_price": "{{close}}", "tv_exchange": "{{exchange}}", "tv_instrument": "{{ticker}}", "action": "{{strategy.order.action}}", "bot_uuid": "YOUR_BOT_UUID", "strategy_info": { "market_position": "{{strategy.market_position}}", "market_position_size": "{{strategy.market_position_size}}", "prev_market_position": "{{strategy.prev_market_position}}", "prev_market_position_size": "{{strategy.prev_market_position_size}}" }, "order": { "amount": "{{strategy.order.contracts}}", "currency_type": "base", "comment": "{{strategy.order.comment}}" } } Disclaimer: This script is an adapter tool and does not guarantee profit. Trading requires manual configuration of risk settings, bot parameters, and adherence to platform-specific setup instructions.
Strategi Pine Script®
oleh nakphanan
1
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve. ​Mechanism (What It Measures) ​The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding: \text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)} 1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money). ​2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure). ​3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity. ​How to Interpret Signals ​Treat the Net Liquidity line as the market's "Fuel Gauge": ​📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets. ​📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action. ​⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent. ​Important Notes ​Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping. ​Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Indikator Pine Script®
oleh PlanCco
Systemic Net Liquidity (Macro Fuel for Crypto & Stocks)This indicator tracks Systemic Net Liquidity, the single most important macro factor for determining the long-term trend of risk assets like Bitcoin (BTC) and major indices (S&P 500). It measures the amount of actual cash available in the financial system to chase speculative assets, distinguishing between money that is circulating and money that is locked up at the Federal Reserve. ​Mechanism (What It Measures) ​The script uses direct data from the FRED (Federal Reserve Economic Data) to calculate the true state of market funding: \text{Net Liquidity} = \text{Fed Assets (WALCL)} - \text{Treasury General Account (TGA)} - \text{Reverse Repo (RRP)} 1. Fed Assets (WALCL): The total balance sheet of the Fed (The overall supply of money). ​2. Treasury General Account (TGA): Funds the US Treasury collects via bond issuance. When the TGA rises, liquidity is actively drained from the banking system (A major bearish pressure). ​3. Overnight Reverse Repo (RRP): Cash parked by banks and money market funds at the Fed, effectively frozen and not contributing to market activity. ​How to Interpret Signals ​Treat the Net Liquidity line as the market's "Fuel Gauge": ​📈 BULLISH SIGNAL (Liquidity Injection): When the Net Liquidity line is rising, money is flowing back into the system, signalling a tailwind for risk assets. ​📉 BEARISH SIGNAL (Liquidity Drain): When the line is falling (often due to high TGA balances), cash is being removed. This signals major friction and pressure on price action. ​⚠️ DIVERGENCE WARNING: A strong signal is generated when Price (e.g., BTC) rises, but Net Liquidity falls. This macro divergence strongly suggests a major trend reversal or correction is imminent. ​Important Notes ​Data Source: Data is directly sourced from FRED and updates daily/weekly. This tool is best used for macro analysis and identifying high-level cycles, not short-term scalping. ​Disclaimer: Use this indicator as a confirmation tool within your broader strategy. It is not a standalone trading signal.
Indikator Pine Script®
oleh PlanCco
Volume Z-Score// This indicator calculates the Z-Score of trading volume to identify // statistically significant volume spikes. It uses a dynamic percentile-based // threshold to highlight extreme volume events. // // How it works: // - Z-Score measures how many standard deviations the current volume is from the mean // - The threshold line represents the top 1% (99th percentile) of historical Z-Score values // - When volume Z-Score exceeds the threshold, the line turns red // // Use cases: // - Spot unusual institutional activity or large block trades // - Identify potential breakout or breakdown points with volume confirmation // - Filter out noise by focusing only on statistically extreme volume events // // Parameters: // - Period Length: Lookback period for calculating mean and standard deviation // - Percentile Threshold: Defines the extreme volume cutoff (default 99 = top 1%) // ===================================
Indikator Pine Script®
oleh Go3x3
Day Separators Description: This script visually separates the trading chart by days of the week. Each day is highlighted with a distinct background color or vertical line, making it easier to analyze daily price patterns and trading activity. Useful for spotting trends, comparing daily performance, or planning strategies based on weekday behavior. Features: Divides the chart by weekdays (Monday to Sunday). Optional background shading or vertical lines for each day. Customizable colors and line styles for better visibility. Works on any timeframe. Use Cases: Identify patterns or anomalies on specific weekdays. Track performance trends across the week. Simplify intraday and daily analysis for more informed trading decisions.
Indikator Pine Script®
oleh Gabi_111
Z Score k3x3// =================================== // Z-Score Indicator with Enhanced Visualization // // Description: // This indicator calculates the Z-Score (standard score) of price movements, // highlighting extreme overbought and oversold conditions with visual alerts. // // Features: // - Dynamic color gradients based on Z-Score values // - Visual alerts for extreme zones (|Z| > 2) // - Background highlighting for overbought/oversold areas // - Shape markers for extreme conditions // - Customizable period length and standard deviation levels // // Interpretation: // Z > +2: Extreme overbought (red alert) // Z < -2: Extreme oversold (green alert) // |Z| < 1: Normal range (neutral colors) // ===================================
Indikator Pine Script®
oleh Go3x3
1