Total Returns indicator by PtahXPtahX Total Returns – True Total-Return View for Any Symbol
Most charts only show price. This script shows what your position actually did once you include dividends and, optionally, inflation.
What this indicator does
1. Builds a Total Return series
You choose how dividends are treated:
* Reinvest (default): All gross dividends are automatically reinvested into more shares on the ex-dividend bar.
* Cash: Dividends are kept as cash added on top of your initial position.
* Ignore: Price only, like a regular chart.
This answers: “If I bought once at the start and held, how much would that position be worth now, given this dividend policy?”
2. Optional inflation-adjusted (real) returns
You can also plot a real total-return line, which adjusts for inflation using a CPI series.
This answers: “How did my purchasing power change after inflation?”
3. Stats window and exponential trendline
You can pick the time window:
* Since inception (full available history)
* YTD
* Last 1 Year
* Last 5 Years
* Custom start date
For that window, the script:
* Normalizes Total Return to 1.0 at the window start.
* Fits an exponential trendline (pink) to the normalized series.
* Displays a stats table in the bottom-right showing:
• Overall Return (%) over the selected range
• CAGR (compound annual growth rate, % per year)
• Trendline growth (% per year)
• R² of the trendline (fit quality)
• A separate “Since inception” block (overall return and CAGR from the first bar on the chart)
How to use it
1. Add the indicator to your chart.
2. Open the settings:
Total Return & Dividends
* Dividend mode
• Reinvest: closest to a true total-return curve (default).
• Cash: price plus cash dividends.
• Ignore: price only.
* Plot inflation-adjusted TR line
• Turn this on if you want to see a real (CPI-adjusted) total-return line.
Inflation / Real Returns
* Inflation country code and field code
• Leave defaults if you just want a standard CPI series.
* Use real TR for stats & trendline
• On: stats and trendline use the inflation-adjusted curve.
• Off: stats use the nominal (non-adjusted) total return.
Stats Range & Trendline
* Stats range: Since inception, YTD, 1 Year, 5 Years, or Custom date.
* Custom date: set year, month, and day if you choose “Custom date”.
* Plot TR exponential trendline: show or hide the pink curve.
* Show stats table / Show Overall Return / Show Trendline stats: toggle what appears in the table.
3. Zoom and change timeframe as usual. The stats range is based on calendar time (YTD, 1Y, 5Y, etc.), not bar count, so the numbers stay meaningful as you change resolutions.
How to read the outputs
* Teal line: Nominal Total Return (using your chosen dividend mode).
* Orange line (if enabled): Real (inflation-adjusted) Total Return.
* Pink line (if enabled): Exponential trendline for the selected stats window.
On the right edge, small labels show the latest value of each active line.
In the bottom-right stats table:
* Overall Return: total percentage gain or loss over the chosen stats range.
* CAGR: the smoothed annual rate that would turn 1.0 into the current value over that range.
* Exponential Trendline: the average trendline growth per year and the R².
• R² near 1 means prices follow a clean exponential path.
• Lower R² means more noise or sideways movement around the trend.
* Range: which window those stats apply to (YTD, 1Y, 5Y, etc.).
* Since inception: overall return and CAGR from the first bar on the chart up to the latest bar, independent of the current stats range.
Use this when you want to compare true performance, not just price – especially for dividend-heavy ETFs, funds, and income strategies.
Göstergeler ve stratejiler
8FigRenko – Precision FVG Zones8FigRenko – Pure FVG Zones is a clean, reliable Fair Value Gap tool designed for traders who want accurate FVG zones only from the chart timeframe — without repainting, without higher-timeframe complications, and without messy borders.
This script is built for traders who want simple, precise, and visually clean imbalance zones that work the way FVGs should work:
🔥 Features
✔ Chart-timeframe FVGs only
No request.security, no multi-TF artifacts, no lagging or repainting.
The script reads exactly what your chart shows and never mixes timeframes.
✔ Wick-based or Body-based detection
Use classic ICT wick gaps, or switch to body-only gaps with one click.
✔ Minimum FVG size (points)
Filters out noise by requiring a minimum point distance (default: 5 points).
Great for futures and fast intraday charts.
✔ Clean, seamless boxes (no borders)
The FVG zones are rendered with borderless boxes, matching the modern style shown in institutional imbalance tools.
✔ Proper “end-to-end” FVG drawing
Each gap box starts from the origin of the imbalance and extends forward automatically.
✔ Auto-disrespect removal
FVGs are automatically deleted when price invalidates the zone:
Bullish FVG removed if close < FVG low
Bearish FVG removed if close > FVG high
No clutter. No manual cleanup.
✔ Extend zones forever or to the current bar
Choose if your FVGs run across the full future chart or just up to the latest candle.
✔ Optional: show only most recent FVG
Great for scalping or IFV (Immediate Fair Value) strategies.
Advanced Market Profile & S/R Zones (Pro)Advanced Market Profile & S/R Zones
This indicator brings professional Auction Market Theory to your chart using a custom rolling Volume Profile algorithm. Unlike standard profiles that remain fixed, this tool dynamically calculates the "Fair Value" of the asset based on your specific lookback period (e.g., the last 100 bars).
It automatically highlights the Point of Control (POC), Value Area (VA), and suggests statistical Discount (Buy) and Premium (Sell) zones.
Key Features
Volume Splitting Algorithm:
Most basic scripts dump the entire volume of a candle into a single price point (the average). This script splits the volume across the candle's entire High-Low range. This results in a much smoother, higher-resolution bell curve that accurately reflects price action, especially on higher timeframes like Monthly charts.
Auto-generated Zones:
Green Zone (Discount): Prices below the Value Area Low (VAL). Statistically "cheap."
Red Zone (Premium): Prices above the Value Area High (VAH). Statistically "expensive."
Real-Time Dashboard:
A built-in panel displays the exact price levels for the POC, VAH, and VAL for precise limit order placement, along with the current Market Trend.
How to Use
For Intraday (Day Trading):
Settings: Set Lookback to 100 - 300.
Strategy: Watch for price to open outside the Value Area. If price breaks back inside the Value Area, target the POC (Red Line).
For Macro (Monthly/Weekly Charts):
Settings: Set Lookback to 12 (1 Year) or 60 (5 Years).
Strategy: Identify multi-year structural support. When a monthly candle enters the Green Discount Zone of a 5-year profile, it is often a high-probability institutional entry point.
Trend Logic
The Dashboard indicates trend based on price location relative to value:
Strong Bullish: Price is accepted ABOVE the Value Area.
Strong Bearish: Price is accepted BELOW the Value Area.
Neutral / In VA: Price is chopping inside the Value Area.
Disclaimer
This is a "Rolling Profile." It calculates the profile based on the current lookback window relative to the latest bar. As new bars form, the lookback window shifts, and the profile updates to reflect the new dataset.
Multi Timeframe Bollinger Bands Spectrum [Ata]Multi-Timeframe Bollinger Bands Spectrum
Technical Overview
This script integrates multi-timeframe volatility analysis with volume-derived order flow estimation. By combining Bollinger Bands (statistical deviation) with internal candle volume logic, the indicator qualifies price movements to differentiate between sustained trends, reversals, and exhaustion events.
The system is designed to provide a structural context for price action, visualizing market regimes through a dual-zone spectrum and filtering signals based on the interaction between price location and specific volume thresholds.
Core Logic & Calculation
1. Volume Decomposition Algorithm
Instead of using total volume, the script estimates Buying Pressure vs. Selling Pressure based on the close position relative to the candle's High/Low range:
- Buying Volume (vb): Increases as the close approaches the High.
- Selling Volume (vs): Increases as the close approaches the Low.
This logic allows the detection of directional flow even within standard volume bars.
2. Statistical Spectrum
The indicator renders deviations from the Basis (SMA) as two distinct zones:
- Bullish Zone (Blue): Price positioning between the Basis and Upper Band.
- Bearish Zone (Red): Price positioning between the Basis and Lower Band.
This structure is applied across multiple timeframes (overlay) to visualize the macro trend context without noise.
3. Non-Repainting Execution
To ensure historical accuracy and reliability for backtesting, all higher-timeframe data is requested using "lookahead_off". Signals are confirmed only upon the closure of the respective timeframe's candle.
Signal Definitions
Signals are generated only when specific Volatility and Volume conditions intersect:
Reversal Setups (Reaction to Liquidity)
- WALL: Triggered when price rejects the Upper Band accompanied by Extreme Selling Volume (vs > Limit). This suggests active limit sell orders absorbing the rally.
- FLOOR: Triggered when price rejects the Lower Band accompanied by Extreme Buying Volume (vb > Limit). This suggests active limit buy orders absorbing the drop.
- ABSORP: Identifies absorption near the lower bands where selling pressure is met with passive buying (indicated by lower wicks and relative buy volume).
Momentum Setups (Trend Continuation)
- POWER: Validates a breakout above the Upper Band only if supported by Dominant Buying Volume and a strong candle body.
- PANIC: Validates a breakdown below the Lower Band only if supported by Dominant Selling Volume.
- TRAP: Marks failed breakouts where price exits the bands but volume analysis contradicts the move (e.g., low directional volume).
Exhaustion Setups (Statistical Extremes)
- CLIMAX/CRASH: Identifies anomalies where price deviates significantly from the mean (Extreme Deviation) or when volume reaches unsustainable levels relative to the average, often preceding a mean reversion.
Input Parameters
- Bollinger Logic: Configuration for Length and Standard Deviation Multiplier.
- Volume Thresholds: Adjustable factors for Minimum Volume (Trend) and Extreme Volume (Reversal/Climax).
- Timeframe Layers: Toggle visibility for up to 5 higher timeframes.
- Theme: Adjusts label contrast for Dark/Light backgrounds.
Disclaimer
This indicator is strictly for analytical purposes. It provides a visualization of past market data based on statistical and volumetric formulas. Users should apply their own risk management protocols.
200SMA Distance OscillatorThe oscillator measures the percentage deviation of closing price x from SMA200.
The idea behind the oscillator was preceded by an analysis of how often MAs in the index hold/bounce or are broken through.
Basically, the idea was about index analysis, i.e., the macro picture of a market.
Who wants to buy individual stocks when the overall market is plummeting ;-)
Or in other words: How long are you long in a market? When is it time to take profits?
After the analysis of the stability of SMAs in the index was rather modest (ratio of just under 6:4 for bounce to breakout – overall in 20, 50, 100, and 200 frames from 2020 to 2025), it was noticeable that the percentage over- or underperformance was scalable, especially in indices.
And since indices generally move upwards, there were fixed limits for over- and underestimations – especially in the longer term (SMA200) – unlike with individual stocks.
It is therefore more a question of macro trends and less of short-term movements, e.g., in day trading.
It was now interesting to see at what percentage range counter-movements were likely – particularly in the positive range for profit-taking, but of course also in the negative range for entry into sold-off markets.
If, for example, closing prices around +25% above SMA200 were reached in the NDX, the probability is very high that the market has overreacted and an interim correction will follow – so the theory goes.
On the other hand, continuous levels of +5 to +10% are a product of healthy positive development in a bull market and do not necessarily require action.
The oscillator was specifically designed for the NDX, but can also be used for the SPX and others.
The style was based on the RSI, so that the color level rises from 10% to 20% (overbought/oversold principle).
Based on manually examined movements, the criteria were set as follows:
+/-10% = flow / no color background
> +/-10% = border areas / color background
The center line represents the 252 average of the percentage deviations and could also be used as a trigger, provided it has been historically examined and is valid.
The oscillator is very interesting because it behaves completely differently from one financial instrument to another and, as a result, also in the timeframes (4h, D, W).
It would probably make sense to change the flow and border levels in the code when using it outside of indices.
The fact is that the oscillator must be “adjusted” to each instrument in order to achieve its goal of providing the best possible prediction. “Adjusting” refers to the analysis of the levels at which an instrument/asset usually reacts.
As with all indicators and oscillators, it is advisable to take other indicators and, in particular, macro news into account when analyzing this development.
If I find any substantial correlations with other indicators, I will be happy to provide an update.
The idea came from me, the code from Grok.
The code is not 100% perfect, but the data (percentage deviation, color background) is correct according to initial analysis.
In the settings, you can make the lines of the plots invisible. This makes the oscillator clearer. You can also adjust the settings for the average line.
DeltaATR + VWAP DIF + MA'sI attempted to create an indicator using a different approach to analyzing potential trend reversals, and although it is still a work in progress, it is already fully functional. The indicator combines the price relative to VWAP with ATR normalization, providing a way to measure deviations in terms of market volatility.
How the indicator works:
Delta Calculation:
The core of the indicator calculates the difference between the current price and the VWAP (Volume Weighted Average Price), then normalizes this difference by the ATR (Average True Range). This provides a volatility-adjusted measure of how far the price has moved relative to its typical range.
Histogram Visualization:
The deltaATR is displayed as a histogram, where positive values indicate the price is above VWAP and negative values indicate it is below. The histogram is color-coded for easy interpretation: typically red for above VWAP and green for below, with configurable transparency.
Dual Moving Averages:
Two moving averages (fast and slow) are applied to the deltaATR. This creates a crossover system:
When the fast average crosses above the slow average, it may indicate an upcoming bullish reversal.
When the fast average crosses below the slow average, it may indicate a potential bearish reversal.
Zero Line Reference:
A reference line at zero corresponds to VWAP, helping traders see whether price is generally above or below the average volume-weighted level.
Alert Lines (Optional Panel):
A second panel provides four configurable alert lines, allowing users to set key thresholds to monitor extreme deltaATR values. These lines are thin, dashed, and fully customizable in terms of color and thickness.
Panel for Values and Signals:
The indicator includes a side panel showing:
Current deltaATR
Fast and slow averages
Current trend signal (Bullish, Bearish, or Neutral)
How it can be used:
Identify potential trend reversals by monitoring the crossover between the fast and slow averages of deltaATR.
Use the histogram to observe when the price is deviating significantly from VWAP in terms of ATR.
Set alert lines for specific thresholds to highlight overextended conditions or significant volatility moves.
Combine with other technical indicators for confirmation before entering or exiting trades.
This indicator is particularly useful for traders looking to anticipate reversals in volatile markets, as it adapts the delta measure to the current market conditions using ATR normalization, making it more responsive and robust than raw price deviations alone.
Flux-Tensor Singularity [FTS]Flux-Tensor Singularity - Multi-Factor Market Pressure Indicator
The Flux-Tensor Singularity (FTS) is an advanced multi-factor oscillator that combines volume analysis, momentum tracking, and volatility-weighted normalization to identify critical market inflection points. Unlike traditional single-factor indicators, FTS synthesizes price velocity, volume mass, and volatility context into a unified framework that adapts to changing market regimes.
This indicator identifies extreme market conditions (termed "singularities") where multiple confirming factors converge, then uses a sophisticated scoring system to determine directional bias. It is designed for traders seeking high-probability setups with built-in confluence requirements.
THEORETICAL FOUNDATION
The indicator is built on the premise that market time is not constant - different market conditions contain varying levels of information density. A 1-minute bar during a major news event contains far more actionable information than a 1-minute bar during overnight low-volume trading. Traditional indicators treat all bars equally; FTS does not.
The theoretical framework draws conceptual parallels to physics (purely as a mental model, not literal physics):
Volume as Mass: Large volume represents significant market participation and "weight" behind price moves. Just as massive objects have stronger gravitational effects, high-volume moves carry more significance.
Price Change as Velocity: The rate of price movement through price space represents momentum and directional force.
Volatility as Time Dilation: When volatility is high relative to its historical norm, the "information density" of each bar increases. The indicator weights these periods more heavily, similar to how time dilates near massive objects in physics.
This is a pedagogical metaphor to create a coherent mental model - the underlying mathematics are standard financial calculations combined in a novel way.
MATHEMATICAL FRAMEWORK
The indicator calculates a composite singularity value through four distinct steps:
Step 1: Raw Singularity Calculation
S_raw = (ΔP × V) × γ²
Where:
ΔP = Price Velocity = close - close
V = Volume Mass = log(volume + 1)
γ² = Time Dilation Factor = (ATR_local / ATR_global)²
Volume Transformation: Volume is log-transformed because raw volume can have extreme outliers (10x-100x normal). The logarithm compresses these spikes while preserving their significance. This is standard practice in volume analysis.
Volatility Weighting: The ratio of short-term ATR (5 periods) to long-term ATR (user-defined lookback) is squared to create a volatility amplification factor. When local volatility exceeds global volatility, this ratio increases, amplifying the raw singularity value. This makes the indicator regime-aware.
Step 2: Normalization
The raw singularity values are normalized to a 0-100 scale using a stochastic-style calculation:
S_normalized = ((S_raw - S_min) / (S_max - S_min)) × 100
Where S_min and S_max are the lowest and highest raw singularity values over the lookback period.
Step 3: Epsilon Compression
S_compressed = 50 + ((S_normalized - 50) / ε)
This is the critical innovation that makes the sensitivity control functional. By applying compression AFTER normalization, the epsilon parameter actually affects the final output:
ε < 1.0: Expands range (more signals)
ε = 1.0: No change (default)
ε > 1.0: Compresses toward 50 (fewer, higher-quality signals)
For example, with ε = 2.0, a normalized value of 90 becomes 70, making threshold breaches rarer and more significant.
Step 4: Smoothing
S_final = EMA(S_compressed, smoothing_period)
An exponential moving average removes high-frequency noise while preserving trend.
SIGNAL GENERATION LOGIC
When the tensor crosses above the upper threshold (default 90) or below the lower threshold (default 10), an extreme event is detected. However, the indicator does NOT immediately generate a buy or sell signal. Instead, it analyzes market context through a multi-factor scoring system:
Scoring Components:
Price Structure (+1 point): Current bar bullish/bearish
Momentum (+1 point): Price higher/lower than N bars ago
Trend Context (+2 points): Fast EMA above/below slow EMA (weighted heavier)
Acceleration (+1 point): Rate of change increasing/decreasing
Volume Multiplier (×1.5): If volume > average, multiply score
The highest score (bullish vs bearish) determines signal direction. This prevents the common indicator failure mode of "overbought can stay overbought" by requiring directional confirmation.
Signal Conditions:
A BUY signal requires:
Extreme event detection (tensor crosses threshold)
Bullish score > Bearish score
Price confirmation: Bullish candle (optional, user-controlled)
Volume confirmation: Volume > average (optional, user-controlled)
Momentum confirmation: Positive momentum (optional, user-controlled)
A SELL signal requires the inverse conditions.
INPUTS EXPLAINED - Core Parameters:
Global Horizon (Context): Default 20. Lookback period for normalization and volatility comparison. Higher values = smoother but less responsive. Lower values = more signals but potentially more noise.
Tensor Smoothing: Default 3. EMA period applied to final output. Removes "quantum foam" (high-frequency noise). Range 1-20.
Singularity Threshold: Default 90. Values above this (or below 100-threshold) trigger extreme event detection. Higher = rarer, stronger signals.
Signal Sensitivity (Epsilon): Default 1.0. Post-normalization compression factor. This is the key innovation - it actually works because it's applied AFTER normalization. Range 0.1-5.0.
Signal Interpreter Toggles:
Require Price Confirmation: Default ON. Only generates buy signals on bullish candles, sell signals on bearish candles. Reduces false signals but may delay entry.
Require Volume Confirmation: Default ON. Only signals when volume > average. Critical for stocks/crypto, less important for forex (unreliable volume data).
Use Momentum Filter: Default ON. Requires momentum agreement with signal direction. Prevents counter-trend signals.
Momentum Lookback: Default 5. Number of bars for momentum calculation. Shorter = more responsive, longer = trend-following bias.
Visual Controls:
Colors: Customizable colors for bullish flux, bearish flux, background, and event horizon.
Visual Transparency: Default 85. Master control for all visual elements (accretion disk, field lines, particles, etc.). Range 50-99. Signals and dashboard have separate controls.
Visibility Toggles: Individual on/off switches for:
Gravitational field lines (trend EMAs)
Field reversals (trend crossovers)
Accretion disk (background gradient)
Singularity diamonds (neutral extreme events)
Energy particles (volume bursts)
Event horizon flash (extreme event background)
Signal background flash
Signal Size: Tiny/Small/Normal triangle size
Signal Offsets: Separate controls for buy and sell signal vertical positioning (percentage of price)
Dashboard Settings:
Show Dashboard: Toggle on/off
Position: 9 placement options (all corners, centers, middles)
Text Size: Tiny/Small/Normal/Large
Background Transparency: 0-50, separate from visual transparency
VISUAL ELEMENTS EXPLAINED
1. Accretion Disk (Background Gradient):
A three-layer gradient background that intensifies as the tensor approaches extremes. The outer disk appears at any non-neutral reading, the inner disk activates above 70 or below 30, and the core layer appears above 85 or below 15. Color indicates direction (cyan = bullish, red = bearish). This provides instant visual feedback on market pressure intensity.
2. Gravitational Field Lines (EMAs):
Two trend-following EMAs (10 and 30 period) visualized as colored lines. These represent the "curvature" of market trend - when they diverge, trend is strong; when they converge, trend is weakening. Crossovers mark potential trend reversals.
3. Field Reversals (Circles):
Small circles appear when the fast EMA crosses the slow EMA, indicating a potential trend change. These are distinct from extreme events and appear at normal market structure shifts.
4. Singularity Diamonds:
Small diamond shapes appear when the tensor reaches extreme levels (>90 or <10) but doesn't meet the full signal criteria. These are "watch" events - extreme pressure exists but directional confirmation is lacking.
5. Energy Particles (Dots):
Tiny dots appear when volume exceeds 2× average, indicating significant participation. Color matches bar direction. These highlight genuine high-conviction moves versus low-volume drifts.
6. Event Horizon Flash:
A golden background flash appears the instant any extreme threshold is breached, before directional analysis. This alerts you to pay attention.
7. Signal Background Flash:
When a full buy/sell signal is confirmed, the background flashes cyan (buy) or red (sell). This is your primary alert that all conditions are met.
8. Signal Triangles:
The actual buy (▲) and sell (▼) markers. These only appear when ALL selected confirmation criteria are satisfied. Position is offset from bars to avoid overlap with other indicators.
DASHBOARD METRICS EXPLAINED
The dashboard displays real-time calculated values:
Event Density: Current tensor value (0-100). Above 90 or below 10 = critical. Icon changes: 🔥 (extreme high), ❄️ (extreme low), ○ (neutral).
Time Dilation (γ): Current volatility ratio squared. Values >2.0 indicate extreme volatility environments. >1.5 = elevated, >1.0 = above average. Icon: ⚡ (extreme), ⚠ (elevated), ○ (normal).
Mass (Vol): Log-transformed volume value. Compared to volume ratio (current/average). Icon: ● (>2× avg), ◐ (>1× avg), ○ (below avg).
Velocity (ΔP): Raw price change. Direction arrow indicates momentum direction. Shows the actual price delta value.
Bullish Flux: Current bullish context score. Displayed as both a bar chart (visual) and numeric value. Brighter when bullish score dominates.
Bearish Flux: Current bearish context score. Same visualization as bullish flux. These scores compete - the winner determines signal direction.
Field: Trend direction based on EMA relationship. "Repulsive" (uptrend), "Attractive" (downtrend), "Neutral" (ranging). Icon: ⬆⬇↔
State: Current market condition:
🚀 EJECTION: Buy signal active
💥 COLLAPSE: Sell signal active
⚠ CRITICAL: Extreme event, no directional confirmation
● STABLE: Normal market conditions
HOW TO USE THE INDICATOR
1. Wait for Extreme Events:
The indicator is designed to be selective. Don't trade every fluctuation - wait for tensor to reach >90 or <10. This alone is not a signal.
2. Check Context Scores:
Look at the Bullish Flux vs Bearish Flux in the dashboard. If scores are close (within 1-2 points), the market is indecisive - skip the trade.
3. Confirm with Signals:
Only act when a full triangle signal appears (▲ or ▼). This means ALL your selected confirmation criteria have been met.
4. Use with Price Structure:
Combine with support/resistance levels. A buy signal AT support is higher probability than a buy signal in the middle of nowhere.
5. Respect the Dashboard State:
When State shows "CRITICAL" (⚠), it means extreme pressure exists but direction is unclear. These are the most dangerous moments - wait for resolution.
6. Volume Matters:
Energy particles (dots) and the Mass metric tell you if institutions are participating. Signals without volume confirmation are lower probability.
MARKET AND TIMEFRAME RECOMMENDATIONS
Scalping (1m-5m):
Lookback: 10-14
Smoothing: 5-7
Threshold: 85
Epsilon: 0.5-0.7
Note: Expect more noise. Confirm with Level 2 data. Best on highly liquid instruments.
Intraday (15m-1h):
Lookback: 20-30 (default settings work well)
Smoothing: 3-5
Threshold: 90
Epsilon: 1.0
Note: Sweet spot for the indicator. High win rate on liquid stocks, forex majors, and crypto.
Swing Trading (4h-1D):
Lookback: 30-50
Smoothing: 3
Threshold: 90-95
Epsilon: 1.5-2.0
Note: Signals are rare but high conviction. Combine with higher timeframe trend analysis.
Position Trading (1D-1W):
Lookback: 50-100
Smoothing: 5-7
Threshold: 95
Epsilon: 2.0-3.0
Note: Extremely rare signals. Only trade the most extreme events. Expect massive moves.
Market-Specific Settings:
Forex (EUR/USD, GBP/USD, etc.):
Volume data is unreliable (spot forex has no centralized volume)
Disable "Require Volume Confirmation"
Focus on momentum and trend filters
News events create extreme singularities
Best on 15m-1h timeframes
Stocks (High-Volume Equities):
Volume confirmation is CRITICAL - keep it ON
Works excellently on AAPL, TSLA, SPY, etc.
Morning session (9:30-11:00 ET) shows highest event density
Earnings announcements create guaranteed extreme events
Best on 5m-1h for day trading, 1D for swing trading
Crypto (BTC, ETH, major alts):
Reduce threshold to 85 (crypto has constant high volatility)
Volume spikes are THE primary signal - keep volume confirmation ON
Works exceptionally well due to 24/7 trading and high volatility
Epsilon can be reduced to 0.7-0.8 for more signals
Best on 15m-4h timeframes
Commodities (Gold, Oil, etc.):
Gold responds to macro events (Fed announcements, geopolitical events)
Oil responds to supply shocks
Use daily timeframe minimum
Increase lookback to 50+
These are slow-moving markets - be patient
Indices (SPX, NDX, etc.):
Institutional volume matters - keep volume confirmation ON
Opening hour (9:30-10:30 ET) = highest singularity probability
Strong correlation with VIX - high VIX = more extreme events
Best on 15m-1h for day trading
WHAT MAKES THIS INDICATOR UNIQUE
1. Post-Normalization Sensitivity Control:
Unlike most oscillators where sensitivity controls don't actually work (they're applied before normalization, which then rescales everything), FTS applies epsilon compression AFTER normalization. This means the sensitivity parameter genuinely affects signal frequency. This is a novel implementation not found in standard oscillators.
2. Multi-Factor Confluence Requirement:
The indicator doesn't just detect "overbought" or "oversold" - it detects extreme conditions AND THEN analyzes context through five separate factors (price structure, momentum, trend, acceleration, volume). Most indicators are single-factor; FTS requires confluence.
3. Volatility-Weighted Normalization:
By squaring the ATR ratio (local/global), the indicator adapts to changing market regimes. A 1% move in a low-volatility environment is treated differently than a 1% move in a high-volatility environment. Traditional indicators treat all moves equally regardless of context.
4. Volume Integration at the Core:
Volume isn't an afterthought or optional filter - it's baked into the fundamental equation as "mass." The log transformation handles outliers elegantly while preserving significance. Most price-based indicators completely ignore volume.
5. Adaptive Scoring System:
Rather than fixed buy/sell rules ("RSI >70 = sell"), FTS uses competitive scoring where bullish and bearish evidence compete. The winner determines direction. This solves the classic problem of "overbought markets can stay overbought during strong uptrends."
6. Comprehensive Visual Feedback:
The multi-layer visualization system (accretion disk, field lines, particles, flashes) provides instant intuitive feedback on market state without requiring dashboard reading. You can see pressure building before extreme thresholds are hit.
7. Separate Extreme Detection and Signal Generation:
"Singularity diamonds" show extreme events that don't meet full criteria, while "signal triangles" only appear when ALL conditions are met. This distinction helps traders understand when pressure exists versus when it's actionable.
COMPARISON TO EXISTING INDICATORS
vs. RSI/Stochastic:
These normalize price relative to recent range. FTS normalizes (price change × log volume × volatility ratio) - a composite metric, not just price position.
vs. Chaikin Money Flow:
CMF combines price and volume but lacks volatility context and doesn't use adaptive normalization or post-normalization compression.
vs. Bollinger Bands + Volume:
Bollinger Bands show volatility but don't integrate volume or create a unified oscillator. They're separate components, not synthesized.
vs. MACD:
MACD is pure momentum. FTS combines momentum with volume weighting and volatility context, plus provides a normalized 0-100 scale.
The specific combination of log-volume weighting, squared volatility amplification, post-normalization epsilon compression, and multi-factor directional scoring is unique to this indicator.
LIMITATIONS AND PROPER DISCLOSURE
Not a Holy Grail:
No indicator is perfect. This tool identifies high-probability setups but cannot predict the future. Losses will occur. Use proper risk management.
Requires Confirmation:
Best used in conjunction with price action analysis, support/resistance levels, and higher timeframe trend. Don't trade signals blindly.
Volume Data Dependency:
On forex (spot) and some low-volume instruments, volume data is unreliable or tick-volume only. Disable volume confirmation in these cases.
Lagging Components:
The EMA smoothing and trend filters are inherently lagging. In extremely fast moves, signals may appear after the initial thrust.
Extreme Event Rarity:
With conservative settings (high threshold, high epsilon), signals can be rare. This is by design - quality over quantity. If you need more frequent signals, reduce threshold to 85 and epsilon to 0.7.
Not Financial Advice:
This indicator is an analytical tool. All trading decisions and their consequences are solely your responsibility. Past performance does not guarantee future results.
BEST PRACTICES
Don't trade every singularity - wait for context confirmation
Higher timeframes = higher reliability
Combine with support/resistance for entry refinement
Volume confirmation is CRITICAL for stocks/crypto (toggle off only for forex)
During major news events, singularities are inevitable but direction may be uncertain - use wider stops
When bullish and bearish flux scores are close, skip the trade
Test settings on your specific instrument/timeframe before live trading
Use the dashboard actively - it contains critical diagnostic information
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
COT Net Positions OTCCOT Net Positions Indicator Description
This is a TradingView Pine Script indicator that displays Commitment of Traders (COT) data for any trading instrument.
What it does:
Fetches COT Data - Uses the TradingView COT library to retrieve official CFTC (Commodity Futures Trading Commission) data for the current symbol
Calculates Net Positions for three trader categories:
Commercial (Blue) - Large hedging institutions; represents institutional long/short positioning
Non-Commercial (Yellow) - Large speculators and hedge funds; often considered "smart money"
Retail (Red) - Small individual traders; often considered contrarian indicators
Net Position Calculation - For each category:
Takes Long Positions minus Short Positions
Plots the result on a separate panel below the price chart
Special Symbol Handling - Includes custom mappings for specific commodities:
Copper (HG) → CFTC code 085692
Brazilian Real (LBR) → CFTC code 058644
Use Cases:
Market Bias Detection - See if institutions are mostly long or short
Contrarian Trading - When retail traders are extremely positioned one way, often the market reverses
Trend Confirmation - Non-commercial positioning often aligns with established trends
Support/Resistance - Extreme COT positions can signal market turning points
MoneyLine FusionMoneyLine Fusion is a clean, no-nonsense confluence indicator that combines a linear-regression “Money Line” with adaptive ATR bands, Fisher Transform triggers, correct Aroon trend strength, and an instant-read Score (-4 to +4) built from MACD, ADX, MFI and RSI. It only flashes a BUY or SELL label when all the pieces line up — giving you high-probability entries without the noise. The bright lime/red Money Line never blends with candles, the bands stay perfectly anchored no matter how you pan or zoom, and the tiny info panel tells you at a glance exactly how strong the current setup is. In short, it turns five proven tools into one simple, visual decision engine so you spend less time second-guessing and more time catching clean moves.
Mirpapa_Lib_4waveLibrary "Mirpapa_Lib_4wave"
Library for MACD 4Wave Trading System - Type definitions and calculation functions
_macd_calc(_src, _fast, _slow, _signal)
Parameters:
_src (float)
_fast (simple int)
_slow (simple int)
_signal (simple int)
_normalize(_value, _current_max, _current_norm)
Parameters:
_value (float)
_current_max (float)
_current_norm (float)
calc_visual(_current, _prev_val, _color_up, _color_down, _transparency_up, _transparency_down)
Parameters:
_current (float)
_prev_val (float)
_color_up (color)
_color_down (color)
_transparency_up (int)
_transparency_down (int)
_detect_line_position(_line1, _line2)
Parameters:
_line1 (float)
_line2 (float)
_get_divergence_score(_div)
Parameters:
_div (_DivergenceCounter)
calculate_score_1_HighTrend(_htfHigh_macd_norm, _htfHigh_macd_norm_prev, _max_score)
Parameters:
_htfHigh_macd_norm (float)
_htfHigh_macd_norm_prev (float)
_max_score (int)
calculate_score_1_TRIX_Align(_trix_norm, _trix_norm_prev, _max_score)
Parameters:
_trix_norm (float)
_trix_norm_prev (float)
_max_score (int)
calculate_score_2_MidAlign(_htfMid_macd_norm, _htfMid_macd_norm_prev, _htfHigh_macd_norm, _htfHigh_macd_norm_prev, _max_score)
Parameters:
_htfMid_macd_norm (float)
_htfMid_macd_norm_prev (float)
_htfHigh_macd_norm (float)
_htfHigh_macd_norm_prev (float)
_max_score (int)
calculate_score_3_LowAlign(_htfLow_macd_norm, _htfLow_macd_norm_prev, _htfMid_macd_norm, _htfMid_macd_norm_prev, _htfHigh_macd_norm, _htfHigh_macd_norm_prev, _max_score)
Parameters:
_htfLow_macd_norm (float)
_htfLow_macd_norm_prev (float)
_htfMid_macd_norm (float)
_htfMid_macd_norm_prev (float)
_htfHigh_macd_norm (float)
_htfHigh_macd_norm_prev (float)
_max_score (int)
calculate_score_4_CurrentAlign(_current_macd_norm, _htfMid_macd_norm, _htfHigh_macd_norm, _max_score)
Parameters:
_current_macd_norm (float)
_htfMid_macd_norm (float)
_htfHigh_macd_norm (float)
_max_score (int)
calculate_score_4_CurrentHistogram(_hist, _hist_prev, _max_score)
Parameters:
_hist (float)
_hist_prev (float)
_max_score (int)
calculate_score_4_MACD_Cross(_current_norm, _htfLow_norm, _htfMid_norm, _htfHigh_norm, _max_score)
Parameters:
_current_norm (float)
_htfLow_norm (float)
_htfMid_norm (float)
_htfHigh_norm (float)
_max_score (int)
calculate_score_4_MACD_Extreme(_htfMid_norm, _htfMid_norm_prev, _htfLow_norm, _htfLow_norm_prev, _htfHigh_norm, _oversold_line, _overbought_line, _max_score)
Parameters:
_htfMid_norm (float)
_htfMid_norm_prev (float)
_htfLow_norm (float)
_htfLow_norm_prev (float)
_htfHigh_norm (float)
_oversold_line (float)
_overbought_line (float)
_max_score (int)
calculate_score_4_MACD_Convergence(_htfLow_norm, _htfMid_norm, _htfHigh_norm, _max_score)
Parameters:
_htfLow_norm (float)
_htfMid_norm (float)
_htfHigh_norm (float)
_max_score (int)
calculate_score_5_RSI_Divergence(_rsiDivBull, _rsiDivBear, _max_score)
Parameters:
_rsiDivBull (_DivergenceCounter)
_rsiDivBear (_DivergenceCounter)
_max_score (int)
calculate_score_5_MACD_Divergence(_macdDivBull, _macdDivBear, _max_score)
Parameters:
_macdDivBull (_DivergenceCounter)
_macdDivBear (_DivergenceCounter)
_max_score (int)
calculate_score_5_Bonus_Divergence(_rsiDivBull, _rsiDivBear, _macdDivBull, _macdDivBear, _trixDivBull, _trixDivBear, _max_score)
Parameters:
_rsiDivBull (_DivergenceCounter)
_rsiDivBear (_DivergenceCounter)
_macdDivBull (_DivergenceCounter)
_macdDivBear (_DivergenceCounter)
_trixDivBull (_DivergenceCounter)
_trixDivBear (_DivergenceCounter)
_max_score (int)
_calculate_total_score(_score_data)
Parameters:
_score_data (_Score)
_FilterSettings
Fields:
_need_macd (series bool)
_need_rsi (series bool)
_need_trix (series bool)
_show_indicator_visual (series bool)
_show_trade_visual (series bool)
_Macd
Fields:
_macd (series float)
_signal (series float)
_hist (series float)
_hist_prev (series float)
_max (series float)
_norm (series float)
_normPrev (series float)
_Rsi
Fields:
_value (series float)
_norm (series float)
_normPrev (series float)
_Trix
Fields:
_value (series float)
_max (series float)
_norm (series float)
_normPrev (series float)
_Divergence
Fields:
_bull (series bool)
_bear (series bool)
_DivergenceCounter
Fields:
_div1 (series int)
_div2 (series int)
_div3 (series int)
_Score
Fields:
_1_MACD_HighTrend (series float)
_1_TRIX_Align (series float)
_2_MACD_MidAlign (series float)
_3_MACD_LowAlign (series float)
_4_MACD_CurrentAlign (series float)
_4_MACD_CurrentHistogram (series float)
_4_MACD_Cross (series float)
_4_MACD_Extreme (series float)
_4_MACD_Convergence (series float)
_5_RSI_Divergence (series float)
_5_MACD_Divergence (series float)
_5_Bonus_Divergence (series float)
_total (series float)
_canContinue (series bool)
_directionAligned (series bool)
_IsNewBar
Fields:
_high (series bool)
_mid (series bool)
_low (series bool)
_Visual
Fields:
_prev (series float)
_increasing (series bool)
_color (series color)
_ScoreThresholds
Fields:
_1_MACD_HighTrend_MAX (series int)
_1_TRIX_Align_MAX (series int)
_2_MACD_MidAlign_MAX (series int)
_3_MACD_LowAlign_MAX (series int)
_4_MACD_CurrentAlign_MAX (series int)
_4_MACD_CurrentHistogram_MAX (series int)
_4_MACD_Cross_MAX (series int)
_4_MACD_Extreme_MAX (series int)
_4_MACD_Convergence_MAX (series int)
_5_RSI_Divergence_MAX (series int)
_5_MACD_Divergence_MAX (series int)
_5_Bonus_Divergence_MAX (series int)
_EntryThresholds
Fields:
_LONG (series int)
_SHORT (series int)
_StopLossThresholds
Fields:
_PCT (series float)
_SCORE_DROP (series int)
_MDDThresholds
Fields:
_DAILY_LIMIT (series float)
_PositionSizeMultipliers
Fields:
_SIZE_120_PLUS (series float)
_SIZE_100_119 (series float)
_SIZE_90_99 (series float)
_SIZE_75_89 (series float)
_SIZE_60_74 (series float)
_MDDMultipliers
Fields:
_MULT_0_1 (series float)
_MULT_1_2 (series float)
_MULT_2_25 (series float)
_MULT_25_3 (series float)
_MULT_3_PLUS (series float)
_TrixThresholds
Fields:
_STRONG_BULL (series float)
_WEAK_BULL (series float)
_STRONG_BEAR (series float)
_WEAK_BEAR (series float)
_RsiThresholds
Fields:
_OVERSOLD_STRONG (series int)
_OVERSOLD_WEAK (series int)
_OVERBOUGHT_WEAK (series int)
_OVERBOUGHT_STRONG (series int)
_MacdThresholds
Fields:
_OVERSOLD_STRONG (series int)
_OVERSOLD_WEAK (series int)
_OVERBOUGHT_WEAK (series int)
_OVERBOUGHT_STRONG (series int)
_LineThresholds
Fields:
_TOP (series int)
_MIDDLE (series int)
_BOTTOM (series int)
_HIST_BASE (series int)
_Transparency
Fields:
_MAX (series int)
_STRONG (series int)
_MEDIUM (series int)
_WEAK (series int)
_MIN (series int)
_FILL (series int)
_TimeframeNames
Fields:
_CURRENT (series string)
_HTF1 (series string)
_HTF2 (series string)
_HTF3 (series string)
_IndicatorColors
Fields:
_RSI (series color)
_TRIX (series color)
_MACD_CURRENT (series color)
_MACD_HTF1 (series color)
_MACD_HTF2 (series color)
_MACD_HTF3 (series color)
_EntryState
Fields:
_WAITING (series string)
_ENTERED (series string)
_CLOSED (series string)
_TradeState
Fields:
_state (series string)
_is_long (series bool)
_signal_bar (series int)
_signal_score (series float)
_signal_high (series float)
_signal_low (series float)
_entry_bar (series int)
_entry_price (series float)
_entry_score (series float)
_entry_reason (series string)
_exit_bar (series int)
_exit_price (series float)
_exit_reason (series string)
_h_line (series line)
_v_line (series line)
_signal_label (series label)
_entry_label (series label)
_exit_label (series label)
9/21 EMA Trend TOP rIGHT CORNER INDICATORCrossover indicator for the 9 & 21 EMA. Buy Sell for cross up or down respectively. Daily, weekly and Monthly trend.
Labden Swing 1.0Labden Swing Indicator, non real-time. good with semafor, ema 12 & 26 stochastic rsi and macd
MTF Scalper - alemicihanMulti-Timeframe Scalper Strategy: Aligning the Big Picture for Quick Gains
This article presents a robust futures trading strategy designed for high-frequency scalping in the crypto market. It’s built on the principle of minimizing risk by ensuring that short-term entries are always aligned with the dominant, higher-timeframe trend.
The Core Concept: Alignment is Key
A Balanced Trend Follower approach, now refined for rapid scalping, uses a Multi-Timeframe (MTF) confirmation system to filter out market noise and increase the probability of a successful trade.
The strategy operates on a Low Timeframe (LTF) chart (e.g., 3m, 5m, or 15m) but only executes trades if the direction is validated by three Higher Timeframes (HTF).
ComponentPurposeFunctionHTF (D, 4h, 1h) EMA => Trend Confirmation =>Checks if the current price is above/below all three Exponential Moving Averages (EMA 20). This provides a strong directional bias.
LTF (5m) Stochastic RSI => Momentum Entry => Generates the actual buy/sell signal by spotting a swift crossover, indicating fresh momentum in the direction of the confirmed HTF trend.
How The Signal Is Generated
Trend Alignment: The system first confirms the trend. If the price is trading above the Daily, 4-Hour, and 1-Hour EMAs, the market is deemed to be in a Strong LONG Trend. Only LONG signals are permitted.
Momentum Trigger: Once the trend is confirmed, a Long Signal is generated only when the Stochastic K-Line crosses above the D-Line, indicating a momentum shift (a pullback ending) towards the main trend direction.
Short Signal: The inverse logic applies to the Short Trend confirmation and entry signal.
Mandatory Risk Management: ATR-Based Exit
Given the high leverage nature of futures and scalping, static Stop-Loss (SL) and Take-Profit (TP) levels are inefficient. This strategy uses the Average True Range (ATR) indicator to dynamically set profit and loss targets based on current market volatility.
Stop Loss (SL): Set dynamically at 1.5 x ATR below (for long) or above (for short) the entry price. This gives the trade enough room to breathe without risking excessive capital.
Take Profit (TP): Set dynamically at 3.0 x ATR, establishing a robust Risk-to-Reward Ratio of 1:2.
Final Thoughts on Testing
This sophisticated approach combines the reliability of MTF analysis with the speed of momentum indicators. However, data analysis is key. Backtesting these parameters (EMA, ATR Multipliers, RSI/Stochastic lengths) on your chosen asset (like BTC/USDT or ETH/USDT) and timeframe is crucial to achieving optimal performance.
Astro's MG Detector (Ultra Sensitive V2)This indicator helps you find micro gaps on the cash session meaning when there is an imbalance of price found on the 5-minute chart between candles this should detect them. IYKYK
Change in State of Delivery CISD [AlgoAlpha]🟠 OVERVIEW
This script tracks how price “changes delivery” after failed attempts to push in one direction. It builds swing levels from pivots, watches for those levels to be wicked, and then checks if price delivers cleanly in the opposite direction. When the pattern meets the script’s tolerance rules, it marks a Change in State of Delivery (CISD). These CISD levels are drawn as origin lines and are used to spot shifts in intent, failed pushes, and continuation attempts. A CISD becomes stronger when it forms after opposing liquidity is swept within a defined lookback.
🟠 CONCEPTS
The script first defines structure using swing highs/lows. These levels act as potential liquidity points. When price wicks through a swing, the script registers a mitigation event. After this, it looks for a reversal-style candle sequence: a failed push, followed by a counter-move strong enough to pass a tolerance ratio. This ratio compares how far price expanded away from the failed attempt versus the counter-move that followed. If the ratio is high enough, this becomes a CISD. The idea is simple: liquidity interaction sets context , and the tolerance logic identifies actual intent . CISD levels and sweep markers combine these two ideas into a clean map of where delivery flipped.
🟠 FEATURES
Liquidity tracking: marks swing highs/lows and updates them until expiry
Liquidity sweep confirmation when CISD aligns with recent mitigations
Alert conditions for all key events: mitigations, CISDs, and strong CISDs
🟠 USAGE
Setup : Add the script to your chart. Use it on any timeframe where swing behavior matters. Set the Swing Period for how wide a pivot must be. Set Noise Filter to control how strict the CISD detection is. Liquidity Lookback defines how recent a wick must be to confirm a sweep.
Read the chart : Origin lines mark where the CISD began. A green line signals bullish intent; a red line signals bearish intent. ▲ and ▼ shapes show CISDs that form after liquidity is swept, these mark strong signals for potential entry. Swing dots show recent swing highs/lows. Candle colors follow the latest CISD trend.
Settings that matter : Increasing Swing Period produces fewer but stronger swings. Raising Noise Filter requires cleaner counter-moves and reduces false CISDs. Liquidity Lookback controls how strict the sweep confirmation is. Expiry Bars decides how long swing levels remain active.
Turnover (Volume * HLC/3)Let's get the elephant out of the room. Everyone knows volume is the key to validate price movement, but you can't compare two volume candles of the same stock when the price is 3 times different you need to account for that. So here it is, Turnover chart, to replace volume entirely, because why would you look at volume when you can look at turnover instead?
Hull VWMA Crossover StrategyA simple variation on the Hull Moving Average which reacts faster to high volume events, making it more responsive in those cases than even the standard Hull average -- CREDIT GOES TO Saolof - -- Edited into a strategy with some more options that im going to continue to refine. LMK if theres any features or confluence you want me to add -- cheers!
Astros MG DetectorIFKYK this indicator auto detects micro gaps where price has not yet been after an imbalance on said candles has been created.
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.
Labden Buy/Sell V1.0Based on the semafor dot indicator, emas, hull moving average RSI, and more. best for trend following / momentum trading and reversals
Thi Cloud EMA SystemThis is a spinoff of the Ripster's cloud system.
I altered it in order to be more accurate using the 5 min candle instead of the 10
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.
