Stochastic Strategy Table with Trend (1m–4H) + Toggle📊 Multi-Timeframe Stochastic Strategy Table with Trend Detection
This script is designed for intraday and swing traders who want to monitor Stochastic momentum across multiple timeframes in real-time — all directly on the main chart.
🔎 What This Script Does
This script builds a compact, color-coded table that displays:
✅ %K and %D values of the Stochastic oscillator
✅ Cross direction (K > D or K < D)
✅ Overbought/Oversold zone conditions
✅ Short-term trend detection via %K movement
It covers ten timeframes:
1m, 2m,3m,5m, 15m, 30m, 1H, 2H, 3H, 4H
🟩 How to Use It
Trend colors in header:
🟢 Green = %K is rising (uptrend)
🔴 Red = %K is falling (downtrend)
⚪ Gray = flat or neutral
Cross Row:
Green background = Bullish (%K > %D)
Red background = Bearish (%K < %D)
Zone Row:
Green = Oversold (%K and %D below 20)
Red = Overbought (%K and %D above 80)
Gray = Neutral zone
Use Case:
Look for multiple timeframes aligning in trend
Enter trades on short timeframes (e.g. 5m) when HTFs confirm direction
Especially powerful when used with price action on 5m/15m candles
⚙️ Configurable Inputs
%K Length
%K Smoothing
%D Length
Table location
Table size
💡 Why This Script Is Unique
Shows true higher timeframe Stochastic values (not interpolated from current chart)
Works in real-time with consistent updates
Trend direction is visualized without needing extra space
Built for serious intraday traders who rely on clean data and signal alignment
🙏 Credits & Notes
This tool was created to solve a real problem: getting accurate HTF stochastic data in a clean, real-time, decision-friendly format.
I built it for my own use — and now I'm sharing it for luck, and for anyone else looking to trade more clearly and confidently.
Feel free to fork, customize, or build upon it.
Good luck, and trade safe! 🍀💹
Indicateurs et stratégies
ONE RING 8 MA Bands with RaysCycle analysis tool ...
MAs: Eight moving averages (MA1–MA8) with customizable lengths, types (RMA, WMA, EMA, SMA), and offsets
Bands: Upper/lower bands for each MA, calculated based on final_pctX (Percentage mode) or final_ptsX (Points mode), scaled by multiplier
Rays: Forward-projected lines for bands, with customizable start points, styles (Solid, Dashed, Dotted), and lengths (up to 500 bars)
Band Choices
Manual: Uses individual inputs for band offsets
Uniform: Sets all offsets to base_pct (e.g., 0.1%) or base_pts (e.g., 0.1 points)
Linear: Scales linearly (e.g., base_pct * 1, base_pct * 2, base_pct * 3 ..., base_pct * 8)
Exponential: Scales exponentially (e.g., base_pct * 1, base_pct * 2, base_pct * 4, base_pct * 8 ..., base_pct * 128)
ATR-Based: Offsets are derived from the Average True Range (ATR), scaled by a linear factor. Dynamic bands that adapt to market conditions, useful for breakout or mean-reversion strategies. (final_pct1 = base_pct * atr, final_pct2 = base_pct * atr * 2, ..., final_pct8 = base_pct * atr * 8)
Geometric: Offsets follow a geometric progression (e.g., base_pct * r^0, base_pct * r^1, base_pct * r^2, ..., where r is a ratio like 1.5) This is less aggressive than Exponential (which uses powers of 2) and provides a smoother progression.
Example: If base_pct = 0.1, r = 1.5, then final_pct1 = 0.1%, final_pct2 = 0.15%, final_pct3 = 0.225%, ..., final_pct8 ≈ 1.71%
Harmonic: Offsets are based on harmonic flavored ratios. final_pctX = base_pct * X / (9 - X), final_ptsX = base_pts * X / (9 - X) for X = 1 to 8 This creates a harmonic-like progression where offsets increase non-linearly, ensuring MA8 bands are wider than MA1 bands, and avoids duplicating the Linear choice above.
Ex. offsets for base_pct = 0.1: MA1: ±0.0125% (0.1 * 1/8), MA2: ±0.0286% (0.1 * 2/7), MA3: ±0.05% (0.1 * 3/6), MA4: ±0.08% (0.1 * 4/5), MA5: ±0.125% (0.1 * 5/4), MA6: ±0.2% (0.1 * 6/3), MA7: ±0.35% (0.1 * 7/2), MA8: ±0.8% (0.1 * 8/1)
Square Root: Offsets grow with the square root of the band index (e.g., base_pct * sqrt(1), base_pct * sqrt(2), ..., base_pct * sqrt(8)). This creates a gradual widening, less aggressive than Linear or Exponential. Set final_pct1 = base_pct * sqrt(1), final_pct2 = base_pct * sqrt(2), ..., final_pct8 = base_pct * sqrt(8).
Example: If base_pct = 0.1, then final_pct1 = 0.1%, final_pct2 ≈ 0.141%, final_pct3 ≈ 0.173%, ..., final_pct8 ≈ 0.283%.
Fibonacci: Uses Fibonacci ratios (e.g., base_pct * 1, base_pct * 1.618, base_pct * 2.618
Percentage vs. Points Toggle:
In Percentage mode, bands are calculated as ma * (1 ± (final_pct / 100) * multiplier)
In Points mode, bands are calculated as ma ± final_pts * multiplier, where final_pts is in price units.
Threshold Setting for Slope:
Threshold setting for determining when the slope would be significant enough to call it a change in direction. Can check efficiency by setting MA1 to color on slope temporarily
Arrow table: Shows slope direction of 8 MAs using an Up or Down triangle, or shows Flat condition if no triangle.
Trend Channel SwiftEdgeTrend Channel SwiftEdge
The Trend Channel SwiftEdge is a powerful, visually striking tool designed to help traders identify trends and potential trade setups across multiple timeframes with a futuristic, tech-inspired design. This indicator combines a dynamic trend channel with a multi-timeframe trend dashboard and intelligent signal filtering to provide clear, actionable insights for both novice and experienced traders. Its unique neon-lit, holographic visuals give it a modern, cutting-edge feel, making your chart analysis both functional and visually engaging.
What It Does
This indicator identifies trends on your chart using a dynamic price channel and provides buy and sell signals based on trend alignments across multiple timeframes. It also features a dashboard that displays the trend direction (Up, Down, or Neutral) for six timeframes: 1-minute, 5-minute, 15-minute, 1-hour, 4-hour, and 1-day. The signals are filtered using a user-selected higher timeframe to ensure they align with broader market trends, reducing noise and improving trade reliability.
How It Works
The Trend Channel SwiftEdge operates in three key steps:
Dynamic Trend Channel:
A moving average (MA) is calculated based on your chosen type (SMA, EMA, or WMA) and length (default is 14 periods). This MA forms the backbone of the trend channel.
The channel’s upper and lower bounds are created by calculating the highest and lowest values of the MA over a period (default is 2x the MA length). These bounds help identify the trend: if the price is above the upper channel, the trend is Up; if below the lower channel, the trend is Down; otherwise, it’s Neutral.
The MA and channel lines are plotted with neon colors (green for Up, red for Down, blue for the channel bounds) to create a holographic effect, with a glowing background fill between the channels to highlight the trend direction.
Multi-Timeframe Trend Dashboard:
The indicator analyzes trends across six timeframes (1M, 5M, 15M, 1H, 4H, D1) using the same trend channel logic.
A dashboard in the top-right corner displays each timeframe’s trend direction with a futuristic design: neon green for Up, neon red for Down, and gray for Neutral, all set against a dark background with neon blue accents.
Signal Generation with Higher Timeframe Filter:
Buy and Sell signals are generated when the trend on the chart’s timeframe (e.g., 1M) aligns with a user-selected higher timeframe (e.g., 15M).
A Buy signal ("🚀 SwiftEdge BUY") appears when the price crosses above the upper channel (indicating an Up trend) and the selected higher timeframe’s trend also turns Up. If the higher timeframe is Neutral, the indicator checks even higher timeframes (e.g., 1H and 4H for a 15M filter) to confirm the trend direction.
A Sell signal ("🛑 SwiftEdge SELL") appears when the price crosses below the lower channel (indicating a Down trend) and the selected higher timeframe’s trend turns Down, with the same higher timeframe check for Neutral cases.
Signals are displayed as neon-colored labels with emojis for a futuristic touch, making them easy to spot.
Why This Combination?
The combination of a dynamic trend channel, multi-timeframe analysis, and signal filtering in Trend Channel SwiftEdge is designed to provide a comprehensive view of market trends while reducing false signals. The trend channel identifies the primary trend on your chart, while the multi-timeframe dashboard ensures you’re aware of the broader market context. The signal filter leverages higher timeframes to confirm that your trades align with larger trends, which is particularly useful in volatile markets where smaller timeframes can be noisy. This synergy creates a balanced approach, blending short-term precision with long-term trend confirmation, all wrapped in a visually engaging tech-inspired design.
How to Use It
Add the Indicator: Apply Trend Channel SwiftEdge to your TradingView chart.
Customize Settings:
SwiftEdge Moving Average Type: Choose between SMA, EMA, or WMA (default is EMA) to adjust the trend channel’s sensitivity.
SwiftEdge MA Length: Set the period for the moving average (default is 14).
SwiftEdge Signal Filter Timeframe: Select a higher timeframe (1M, 5M, 15M, 1H, 4H, D1) to filter signals (default is 15M). For example, on a 1M chart, selecting 15M ensures signals align with the 15-minute trend.
Show SwiftEdge Ribbon: Toggle the visibility of the trend channel’s moving average (default is true).
Show SwiftEdge Background Glow: Toggle the glowing background fill between the channel bounds (default is true).
Start/End Year: Set a time range for the indicator’s signals (default is 1900–2100).
Interpret the Dashboard: Check the top-right dashboard to see the trend direction across all timeframes. Use this to understand the broader market context.
Trade with Signals:
Look for "🚀 SwiftEdge BUY" labels (neon green) below candles to enter long positions when the trend aligns across timeframes.
Look for "🛑 SwiftEdge SELL" labels (neon red) above candles to enter short positions or exit longs.
Ensure the signal aligns with your trading strategy and risk management.
What Makes It Original?
Trend Channel SwiftEdge stands out with its futuristic, tech-inspired design and multi-timeframe synergy. Unlike traditional trend indicators, it combines a visually striking neon aesthetic with practical functionality, making trend analysis both intuitive and engaging. The signal filtering mechanism, which checks higher timeframes dynamically, ensures trades are backed by broader market trends, reducing the risk of false signals. The dashboard provides a quick, at-a-glance view of trends across multiple timeframes, empowering traders to make informed decisions without needing to switch charts. This blend of advanced trend analysis, intelligent signal filtering, and a high-tech visual theme makes it a unique tool for modern traders.
Notes
Best used on trending markets; in choppy conditions, consider using higher timeframes for signal filtering to reduce noise.
Adjust the MA length and signal timeframe based on your trading style (shorter for scalping, longer for swing trading).
Why This Description Complies with TradingView House Rules
What It Does:
Clearly explains that the script identifies trends using a dynamic channel, provides buy/sell signals, and displays a multi-timeframe dashboard.
How It Does It:
Breaks down the process into three steps: trend channel calculation, multi-timeframe analysis, and signal generation with higher timeframe filtering.
Explains the logic (e.g., price crossing the channel, trend alignment across timeframes) in simple terms.
How to Use It:
Provides step-by-step instructions on adding the indicator, customizing settings, interpreting the dashboard, and trading with signals.
What Makes It Original:
Highlights the unique tech-inspired design, the combination of trend channel and multi-timeframe filtering, and the dynamic higher timeframe check.
Justifies the Combination:
Explains why the trend channel, multi-timeframe dashboard, and signal filtering are used together: to balance short-term precision with long-term trend confirmation, reducing false signals.
Self-Contained:
All concepts (trend channel, multi-timeframe analysis, signal filtering) are explained within the description without requiring external research.
Avoids technical jargon that would confuse non-Pine readers, focusing on user-friendly language.
This updated description with the new name "Trend Channel SwiftEdge" should fully comply with TradingView’s House Rules. If you need further adjustments, let me know!
Volume Weighted Median Price (VWMP)The volume is indeed crucial for confirming price moves and understanding market conviction. While many traders are familiar with VWAP (Volume Weighted Average Price), this indicator introduces a lesser-known but powerful cousin: the Volume Weighted Median Price (VWMP).
What is VWMP?
Unlike VWAP, which calculates the average price weighted by volume over a period, VWMP identifies the median price level weighted by volume.
Think of it this way: If you line up all the trades within a specific lookback period, sorted by price, and then start accumulating the volume traded at each price level, the VWMP is the price level where 50% of the total volume occurred below it, and 50% occurred above it.
It essentially finds the "middle ground" of trading activity based on where the bulk of the volume actually traded, not just the average price.
Key Difference: VWMP vs. VWAP
VWAP: Volume Weighted Average Price. Sensitive to outliers (single large trades at extreme prices can skew the average).
VWMP: Volume Weighted Median Price. More robust to outliers. It represents the price that splits the period's volume distribution in half.
Because it uses the median, VWMP can sometimes provide a more stable or representative level of the "typical" price where significant volume is changing hands, especially in volatile markets or when large, anomalous trades occur.
How to Interpret and Use VWMP in trading
The VWMP plots as a line on your chart, similar to a moving average or VWAP. Here are a few ways traders might use it:
Dynamic Support and Resistance:
Like VWAP, the VWMP line can act as a dynamic level of interest.
Watch how price interacts with the VWMP. Consistent acceptance above VWMP might suggest bullish control and potential support.
Consistent rejection or acceptance below VWMP might indicate bearish control and potential resistance.
Trend Filter / Confirmation:
Uptrend: Look for price consistently staying above the VWMP line. Pullbacks to the VWMP that hold could offer entry opportunities.
Downtrend: Look for price consistently staying below the VWMP line. Rallies to the VWMP that fail could present shorting opportunities.
Use it to filter trades: Only take long trades if price is above VWMP, and short trades if below.
Mean Reversion Potential (Use with Caution):
When price extends significantly far away from the VWMP, some traders might look for potential reversion back towards this volume-based median level.
Important: This should not be used in isolation. Always look for confirmation from other indicators (like RSI, Stochastics, or candlestick patterns) before trading counter-trend reversions.
Confluence with Other Indicators:
VWMP works best when combined with other analysis tools.
Look for confluence: Does the VWMP align with a key Fibonacci level, a standard moving average, or a prior support/resistance zone? This confluence strengthens the level's potential significance.
Considerations
Lookback Period: The length input is crucial. A shorter period makes VWMP more responsive to recent action; a longer period makes it smoother and reflects longer-term volume distribution. Experiment to find what suits your timeframe and trading style.
Lagging Nature: Like all indicators based on past data, VWMP is inherently lagging. It reflects past volume distribution, not the future.
Market Context: Its effectiveness can vary depending on the market conditions (trending vs. ranging) and the asset being traded.
Momentum + Keltner Stochastic Combo)The Momentum-Keltner-Stochastic Combination Strategy: A Technical Analysis and Empirical Validation
This study presents an advanced algorithmic trading strategy that implements a hybrid approach between momentum-based price dynamics and relative positioning within a volatility-adjusted Keltner Channel framework. The strategy utilizes an innovative "Keltner Stochastic" concept as its primary decision-making factor for market entries and exits, while implementing a dynamic capital allocation model with risk-based stop-loss mechanisms. Empirical testing demonstrates the strategy's potential for generating alpha in various market conditions through the combination of trend-following momentum principles and mean-reversion elements within defined volatility thresholds.
1. Introduction
Financial market trading increasingly relies on the integration of various technical indicators for identifying optimal trading opportunities (Lo et al., 2000). While individual indicators are often compromised by market noise, combinations of complementary approaches have shown superior performance in detecting significant market movements (Murphy, 1999; Kaufman, 2013). This research introduces a novel algorithmic strategy that synthesizes momentum principles with volatility-adjusted envelope analysis through Keltner Channels.
2. Theoretical Foundation
2.1 Momentum Component
The momentum component of the strategy builds upon the seminal work of Jegadeesh and Titman (1993), who demonstrated that stocks which performed well (poorly) over a 3 to 12-month period continue to perform well (poorly) over subsequent months. As Moskowitz et al. (2012) further established, this time-series momentum effect persists across various asset classes and time frames. The present strategy implements a short-term momentum lookback period (7 bars) to identify the prevailing price direction, consistent with findings by Chan et al. (2000) that shorter-term momentum signals can be effective in algorithmic trading systems.
2.2 Keltner Channels
Keltner Channels, as formalized by Chester Keltner (1960) and later modified by Linda Bradford Raschke, represent a volatility-based envelope system that plots bands at a specified distance from a central exponential moving average (Keltner, 1960; Raschke & Connors, 1996). Unlike traditional Bollinger Bands that use standard deviation, Keltner Channels typically employ Average True Range (ATR) to establish the bands' distance from the central line, providing a smoother volatility measure as established by Wilder (1978).
2.3 Stochastic Oscillator Principles
The strategy incorporates a modified stochastic oscillator approach, conceptually similar to Lane's Stochastic (Lane, 1984), but applied to a price's position within Keltner Channels rather than standard price ranges. This creates what we term "Keltner Stochastic," measuring the relative position of price within the volatility-adjusted channel as a percentage value.
3. Strategy Methodology
3.1 Entry and Exit Conditions
The strategy employs a contrarian approach within the channel framework:
Long Entry Condition:
Close price > Close price periods ago (momentum filter)
KeltnerStochastic < threshold (oversold within channel)
Short Entry Condition:
Close price < Close price periods ago (momentum filter)
KeltnerStochastic > threshold (overbought within channel)
Exit Conditions:
Exit long positions when KeltnerStochastic > threshold
Exit short positions when KeltnerStochastic < threshold
This methodology aligns with research by Brock et al. (1992) on the effectiveness of trading range breakouts with confirmation filters.
3.2 Risk Management
Stop-loss mechanisms are implemented using fixed price movements (1185 index points), providing definitive risk boundaries per trade. This approach is consistent with findings by Sweeney (1988) that fixed stop-loss systems can enhance risk-adjusted returns when properly calibrated.
3.3 Dynamic Position Sizing
The strategy implements an equity-based position sizing algorithm that increases or decreases contract size based on cumulative performance:
$ContractSize = \min(baseContracts + \lfloor\frac{\max(profitLoss, 0)}{equityStep}\rfloor - \lfloor\frac{|\min(profitLoss, 0)|}{equityStep}\rfloor, maxContracts)$
This adaptive approach follows modern portfolio theory principles (Markowitz, 1952) and Kelly criterion concepts (Kelly, 1956), scaling exposure proportionally to account equity.
4. Empirical Performance Analysis
Using historical data across multiple market regimes, the strategy demonstrates several key performance characteristics:
Enhanced performance during trending markets with moderate volatility
Reduced drawdowns during choppy market conditions through the dual-filter approach
Optimal performance when the threshold parameter is calibrated to market-specific characteristics (Pardo, 2008)
5. Strategy Limitations and Future Research
While effective in many market conditions, this strategy faces challenges during:
Rapid volatility expansion events where stop-loss mechanisms may be inadequate
Prolonged sideways markets with insufficient momentum
Markets with structural changes in volatility profiles
Future research should explore:
Adaptive threshold parameters based on regime detection
Integration with additional confirmatory indicators
Machine learning approaches to optimize parameter selection across different market environments (Cavalcante et al., 2016)
References
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Cavalcante, R. C., Brasileiro, R. C., Souza, V. L., Nobrega, J. P., & Oliveira, A. L. (2016). Computational intelligence and financial markets: A survey and future directions. Expert Systems with Applications, 55, 194-211.
Chan, L. K. C., Jegadeesh, N., & Lakonishok, J. (2000). Momentum strategies. The Journal of Finance, 51(5), 1681-1713.
Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. The Journal of Finance, 48(1), 65-91.
Kaufman, P. J. (2013). Trading systems and methods (5th ed.). John Wiley & Sons.
Kelly, J. L. (1956). A new interpretation of information rate. The Bell System Technical Journal, 35(4), 917-926.
Keltner, C. W. (1960). How to make money in commodities. The Keltner Statistical Service.
Lane, G. C. (1984). Lane's stochastics. Technical Analysis of Stocks & Commodities, 2(3), 87-90.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. The Journal of Finance, 55(4), 1705-1765.
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77-91.
Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time series momentum. Journal of Financial Economics, 104(2), 228-250.
Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. New York Institute of Finance.
Pardo, R. (2008). The evaluation and optimization of trading strategies (2nd ed.). John Wiley & Sons.
Raschke, L. B., & Connors, L. A. (1996). Street smarts: High probability short-term trading strategies. M. Gordon Publishing Group.
Sweeney, R. J. (1988). Some new filter rule tests: Methods and results. Journal of Financial and Quantitative Analysis, 23(3), 285-300.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
SMT SwiftEdge PowerhouseSMT SwiftEdge Powerhouse: Precision Trading with Divergence, Liquidity Grabs, and OTE Zones
The SMT SwiftEdge Powerhouse is a powerful trading tool designed to help traders identify high-probability entry points during the most active market sessions—London and New York. By combining Smart Money Technique (SMT) Divergence, Liquidity Grabs, and Optimal Trade Entry (OTE) Zones, this script provides a unique and cohesive strategy for capturing market reversals with precision. Whether you're a scalper or a swing trader, this indicator offers clear visual signals to enhance your trading decisions on any timeframe.
What Does This Script Do?
This script integrates three key concepts to identify potential trading opportunities:
SMT Divergence:
SMT Divergence compares the price action of two correlated assets (e.g., Nasdaq and S&P 500 futures) to detect hidden market reversals. When one asset makes a higher high while the other makes a lower high (bearish divergence), or one makes a lower low while the other makes a higher low (bullish divergence), it signals a potential reversal. This technique leverages institutional "smart money" behavior to anticipate market shifts.
Liquidity Grabs:
Liquidity Grabs occur when price breaks above recent highs or below recent lows on higher timeframes (5m and 15m), often triggering stop-loss orders from retail traders. These breakouts are identified using pivot points and confirm institutional activity, setting the stage for a reversal. The script focuses on liquidity grabs during the London and New York sessions for maximum market activity.
Optimal Trade Entry (OTE) Zones:
OTE Zones are Fibonacci-based retracement areas (e.g., 61.8%) calculated after a liquidity grab. These zones highlight where price is likely to retrace before continuing in the direction of the reversal, offering a high-probability entry point. The script adjusts the width of these zones using the Average True Range (ATR) to adapt to market volatility.
By combining these components, the script identifies when institutional activity (liquidity grabs) aligns with market reversals (SMT divergence) and pinpoints precise entry points (OTE zones) during high-liquidity sessions.
Why Combine These Components?
The integration of SMT Divergence, Liquidity Grabs, and OTE Zones creates a robust trading system for several reasons:
Synergy of Institutional Signals: SMT Divergence and Liquidity Grabs both reflect "smart money" behavior—divergence shows hidden reversals, while liquidity grabs confirm institutional intent to trap retail traders. Together, they provide a strong foundation for identifying high-probability setups.
Session-Based Precision: Focusing on the London and New York sessions ensures signals occur during periods of high volatility and liquidity, increasing their reliability.
Precision Entries with OTE: After confirming a setup with divergence and liquidity grabs, OTE zones provide a clear entry area, reducing guesswork and improving trade accuracy.
Adaptability: The script works on any timeframe, with adjustable settings for signal sensitivity, session times, and Fibonacci levels, making it versatile for different trading styles.
This combination makes the script unique by aligning institutional insights with actionable entry points, tailored to the most active market hours.
How to Use the Script
Setup:
Add the script to your chart (works on any timeframe, e.g., 1m, 5m, 15m).
Configure the settings in the indicator's inputs:
Session Settings: Adjust the start/end times for London and New York sessions (default: London 8-11 UTC, New York 13-16 UTC). You can disable session restrictions if desired.
Asset Settings: Set the primary and secondary assets for SMT Divergence (default: NQ1! and ES1!). Ensure the assets are correlated.
Signal Settings: Adjust the lookback period, ATR period, and signal sensitivity (Low/Medium/High) to control the frequency of signals.
OTE Settings: Choose the Fibonacci level for OTE zones (default: 61.8%).
Visual Settings: Enable/disable OTE zones, SMT labels, and debug labels for troubleshooting.
Interpreting Signals:
Blue Circles: Indicate a liquidity grab (price breaking a 5m or 15m pivot high/low), marking the start of a potential setup.
Blue OTE Zones: Appear after a liquidity grab, showing the retracement area (e.g., 61.8% Fibonacci level) where price is likely to enter for a reversal trade. The label "OTE Trigger 5m/15m" confirms the direction (Short/Long) and session.
Green/Red Entry Boxes: Mark precise entry points when price enters the OTE zone and confirms the SMT Divergence. Green boxes indicate a long entry, red boxes a short entry.
Trading Example:
On a 1m chart, a blue circle appears when price breaks a 5m pivot high during the London session.
A blue OTE zone forms, showing a retracement area (e.g., 61.8% Fibonacci level) with the label "OTE Trigger 5m/15m (Short, London)".
Price retraces into the OTE zone, and a red "Short Entry" box appears, confirming a bearish SMT Divergence.
Enter a short trade at the red box, with a stop-loss above the OTE zone and a take-profit at the next support level.
Originality and Utility
The SMT SwiftEdge Powerhouse stands out by merging SMT Divergence, Liquidity Grabs, and OTE Zones into a single, session-focused indicator. Unlike traditional indicators that focus on one aspect of price action, this script combines institutional reversal signals with precise entry zones, tailored to the most active market hours. Its adaptability across timeframes, customizable settings, and clear visual cues make it a versatile tool for traders seeking to capitalize on smart money movements with confidence.
Tips for Best Results
Use on correlated assets like NQ1! (Nasdaq futures) and ES1! (S&P 500 futures) for accurate SMT Divergence.
Test on lower timeframes (1m, 5m) for scalping or higher timeframes (15m, 1H) for swing trading.
Adjust the "Signal Sensitivity" to "High" for more signals or "Low" for fewer, high-quality setups.
Enable "Show Debug Labels" if signals are not appearing as expected, to troubleshoot pivot points and liquidity grabs.
VolVolVolVol: Volatility & Volume
The indicator consists of 3 oscillating components that are all represented on a positive/negative percentage scale.
Direction : Green/Red shaded area
Smoothened distance between Close and EMA of Close relative to StDev of Close
Intensity : Turquoise line
If direction = bullish: Smoothened distance between Low and EMA of Low relative to StDev of Low
If direction = bearish: Smoothened distance between High and EMA of High relative to StDev of High
Momentum : Fuchsia line
Double exponential average of bullish closing volume - bearish closing volume
The indicator provides the following signals on the candlestick charts based on the above components' movements.
Bullish position signals: Below candles
Bearish position signals: Above candles
Entry signal : Increase in all 3 factors or sharp increase in Intensity + Momentum
Add signal : Trend slowdown because of volume drop or retracement following a temporary consolidation
Exit signal : Increase in Intensity and Momentum against the prevailing trend direction
There may be simultaneous Bullish and Bearish signals. These should be treated as hedges for existing positions.
Trend Matrix Multi-Timeframe Dashboard(TechnoBlooms)Trend Matrix Multi-Timeframe Dashboard is a Minimalist Multi-Timeframe Trend Analyzer with Smart Indicator Integration. Trend Matrix MTF Dashboard is a clean, efficient, and visually intuitive trend analyzer built for traders who value simplicity without compromising on technical depth.
This dashboard empowers you to track trend direction across multiple timeframes using a curated set of powerful technical indicators—all from one compact visual panel. The design philosophy is simple: eliminate clutter, highlight trend clarity, and accelerate your decision-making process.
Key Features
✅ Minimalist Design with Maximum Insight
A compact dashboard view designed for clean charts and focused trading
Optimized layout shows everything you need—nothing you don’t
✅ Multi-Timeframe Access at a Glance
Instantly read the trend direction of selected indicators on multiple timeframes (e.g., 15m, 1h, 4h, 1D)
Customize the timeframe stack to fit scalping, intraday, swing, or positional strategies
✅ Robust Technical Indicators Built In
Each one is hand-picked for trend reliability:
MACD – Momentum and crossover confirmation
RSI – Overbought/oversold and directional shift
EMA – Dynamic support/resistance and trend bias
Bollinger Bands – Volatility structure and trend containment
PVT – Volume-Weighted Trend Confirmation
Supertrend – Price-following trend tracker
✅ Live Updates & Lightweight Performance
Built to update efficiently on every bar close
Minimal performance impact even with multiple timeframes active
By offering multi-timeframe (MTF) access to proven trend-following indicators, Trend Matrix helps you confidently align with the market’s dominant direction—without jumping between charts or analyzing indicators one by one.
This indicator offers customizable settings. The trader can choose the input parameters timeframes as per the choice.
Trend Matrix Multi-Timeframe Dashboard helps traders to identify trend based on technical indications. Trader can refer this while taking trading decisions.
🧠 Ideal For
Scalpers who need higher timeframe confirmation
Swing traders identifying clean entries aligned with the macro trend
Trend followers seeking clarity before committing capital
Price action & SMC traders validating market structure setups
Beginners who want a high-level trend guide without messy indicators
Log-Normal Price ForecastLog-Normal Price Forecast
This Pine Script creates a log-normal forecast model of future price movements on a TradingView chart, based on historical log returns. It plots expected price trajectories and bands representing different levels of statistical deviation.
Parameters
Model Length – Number of bars used to calculate average and standard deviation of log returns (default: 100).
Forecast Length – Number of bars into the future for which the forecast is projected (default: 100, max: 500).
Volatility SMA Length – The smoothing length for the standard deviation (default: 20).
Confidence Intervals – Confidence intervals for price bands (default: 95%, 99%, 99.9%).
Daily Levels & Stats Pro - [Aspect] v4.0# Description of the "Daily Levels & Stats Pro - v4.0" Indicator
This indicator is a powerful tool for market analysis through the lens of key daily levels and statistical price movement indicators. It allows you to display important trading session opening levels, daily statistical movements, and high volatility zones on the price chart.
## Main Indicator Functions:
### Key Time Levels:
- **Daily Open (DO)** - daily trading session opening level at 02:00
- **NY Midnight (NYM)** - New York session opening level at 06:00
- **Trade Open (TO)** - active trading opening level at 10:00
### Analysis Zones:
- **Previous Close Zone (PCZ)** - previous day's closing zone (displayed on M5 timeframe)
- **Open Day Zone (ODZ)** - current day's opening zone (displayed on M5 timeframe)
### Statistical Price Movement Levels:
- **Min** - minimum statistical movement from DO
- **Max** - maximum statistical movement from DO
- **Aver** - average statistical movement from DO
- **Dev-** - lower deviation of movement from DO
- **Dev+** - upper deviation of movement from DO
### TO Impulse Movement Statistical Levels:
- **Aver TO** - average statistical movement from TO
- **Dev+ TO** - upper deviation of movement from TO
- **Max TO** - maximum statistical movement from TO
## Indicator Features:
- Complete customization of colors, styles, and line widths for all levels
- Ability to select time for each main level
- Adjustment of the number of bars for level display
- Automatic calculation of level values relative to DO and TO
- Visual display of TO-levels starts 3 bars before the actual TO point, providing better visual perception
- Ability to enable/disable individual levels and zones
- Automatic updates and resets when the day changes
- Adaptive text labels to mark levels
This indicator is excellent for traders who use statistical data and daily support/resistance levels in their trading strategy. It is particularly useful for DAX40 and other highly liquid instruments where daily trading statistics are important for making trading decisions.
Market Sessions & Viewer Panel [By MUQWISHI]▋ INTRODUCTION :
The “Market Sessions & Viewer Panel” is a clean and intuitive visual indicator tool that highlights up to four trading sessions directly on the chart. Each session is fully customizable with its name, session time, and color. It also generates a panel that provides a quick-glance summary of each session’s candle/bar shape, helping traders gain insight into the volatility across all trading sessions.
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▋ OVERVIEW:
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▋ CREDIT:
This indicator utilizes the “ Timezone — Library ”. A huge thanks to @n00btraders for effort and well-organized work.
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▋ SESSION PANEL:
The Session Panel allows traders to visually compare session volatility using a candlestick/bar pattern.
Each bar represents the price action during a session and includes the session status, session name, closing price, change(%) from open, and a tooltip that reveals detailed OHLC and volume when hovered over.
Chart Type:
It offers two styles Bar or Candle to display based on traders’ preference
Sorting:
Allowing to arrange session candles/bars based on…
—Left to Right: The most recently opened on the left, moving backward in time to the right.
—Right to Left: The most recently opened on the right, moving backward in time to the left.
—Default: Arrange sessions in the user-defined input order.
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▋ CHART VISUALIZATION:
The chart visualization highlights each trading session using color-coded backgrounds in two selectable drawing styles that span their respective active timeframes. Each session block provides session’s name, close price, and change from open.
Chart Type: Candle
Chart Type: Box
Extra Drawing Feature:
This feature may not exist in other indicators within the same category, it extends the session block drawing to the projected end of the session. This's done through estimation based on historical data; however, it doesn’t function fully on seconds-based timeframes due to drawing limitations.
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▋ INDICATOR SETTINGS:
Section(1): Sessions
(1) Universal Timezone.
(2) Each Session: Enable/Disable, Name, Color, and Time.
Section(2): Session Panel
(1) Show/Hide Session Panel.
(2) Chart Type: Candle/Bar.
(3) Bar’s Up/Down color.
(4) Width and Height of the bar.
(5) Location of Session Panel on chat.
(6) Sort: Left to Right (most recent session is placed on the left), Right to Left (most recent session is placed on the right), and Default (as input arrangement).
Section(3): Chart Visualization
(1) Show/Hide Chart Block Visualization.
(2) Draw Shape: Box/Candle.
(3) Border Style and Size.
(4) Label Styling includes location, size, and some essential selectable infos.
Please let me know if you have any questions
for your comparison: Global M2 Money Supply // Days Offset =📈 Global M2 Money Supply Overlay – Offset Adjustable
This script plots an aggregated, FX-adjusted global M2 money supply index directly on your TradingView chart. It pulls M2 data from multiple global regions—including North America, Europe, Asia, Latin America, and more—and normalizes it for comparison in USD terms.
You can apply a custom time offset to the M2 line using the settings, allowing you to test potential leading or lagging correlations between global liquidity and market price action (e.g., Bitcoin, equities, commodities).
💡 Ideal for macro traders, long-term investors, and anyone interested in liquidity-driven market behavior.
Features:
Combines M2 data from 20+ countries and currency zones
FX-adjusted for consistency in USD terms
Offset slider to shift M2 data forward or backward in time
Scaled to trillions for readability
Plots directly on the main chart for visual comparison
Akkerman IMB + Targets IndicatorAkkerman IMB + Targets Indicator
The Akkerman IMB + Targets Indicator is a powerful tool for traders who use the Smart Money Concept (SMC) methodology for intraday trading. This indicator combines several key elements of technical analysis, such as IMB (Imbalance) zones, liquidity zones, and intraday targets, to help traders identify significant levels on the chart for potential entry and exit points.
Main Features of the Indicator:
IMB (Imbalance) Zones:
The indicator detects IMB zones (imbalances) on the chart, which are often significant for the market because these zones can signal unsupported price moves where the market may either retrace or continue the move.
Green box — indicates a bullish IMB, where the price moves downward but does not reach the previous "low" level.
Red box — indicates a bearish IMB, where the price moves upward but does not reach the previous "high" level.
Liquidity Zones:
The indicator automatically identifies liquidity zones, which are critical levels for potential retracements or breakouts. These zones are determined by equal highs and lows on the chart (where the price has made similar highs or lows).
Triangles or lines highlight levels where significant buy or sell orders might be gathered.
Intraday Target Lines:
The indicator generates targets for intraday trading based on support and resistance levels over the last 10 periods.
These target lines on the chart indicate potential entry or exit points based on the lowest and highest prices over the past 10 bars, which represent key points for trading within the current session.
Indicator Settings:
Show IMB: Toggle to show or hide IMB zones on the chart.
Show Liquidity Zones: Toggle to show or hide liquidity zones on the chart.
Show Targets (Intraday): Toggle to show or hide intraday target lines.
Max Targets (maxTargets): Set the maximum number of targets to display on the chart.
How to Use:
IMB Zones help identify potential retracement or breakout zones on the market. These zones are a critical part of Smart Money analysis, as markets often retrace to these areas after significant price moves.
Liquidity Zones provide clues about where large orders may be gathered, which could lead to a retracement or breakout.
Intraday Targets assist in identifying important levels for entering or exiting trades within the current session to take advantage of short-term price movements.
Important Notes:
This indicator works best on the 1-hour timeframe (H1) for more accurate and stable signals.
For maximum effectiveness, it is recommended to combine this indicator with other technical indicators and analysis methods.
HL2 Moving Average with BandsThis indicator is designed to assist traders in identifying potential trade entries and exits for S&P 500 (ES) and Nasdaq-100 (NQ) futures. It calculates a Simple Moving Average (SMA) based on the HL2 value (average of high and low prices) of the current candle over a user-defined lookback period (default: 200 periods). The indicator plots this SMA as a blue line, providing a smoothed reference for price trends.
Additionally, it includes upper and lower bands calculated as a percentage (default: 0.5%) above and below the SMA, plotted as green and red lines, respectively. These bands act as dynamic thresholds to identify overbought or oversold conditions. The indicator generates trade signals based on price action relative to these bands:
Long Entry: A green upward triangle is plotted below the candle when the close crosses above the upper band, signaling a potential buy.
Close Long: A red square is plotted above the candle when the close crosses back below the upper band, indicating an exit for the long position.
Short Entry: A red downward triangle is plotted above the candle when the close crosses below the lower band, signaling a potential sell.
Close Short: A green square is plotted below the candle when the close crosses back above the lower band, indicating an exit for the short position.
The script is customizable, allowing users to adjust the SMA length and band percentage to suit their trading style or market conditions. It is plotted as an overlay on the price chart for easy integration with other technical analysis tools.
Recommended Time Frame and Settings for Trading S&P 500 and Nasdaq-100 Futures
Based on research and market dynamics for S&P 500 (ES) and Nasdaq-100 (NQ) futures, the 5-minute chart is recommended as the optimal time frame for day trading with this indicator. This time frame strikes a balance between capturing intraday trends and filtering out excessive noise, which is critical for futures trading due to their high volatility and leverage. The 5-minute chart aligns well with periods of high liquidity and volatility, such as the U.S. market open (9:30 AM–11:00 AM EST) and the afternoon session (2:00 PM–4:00 PM EST), when institutional traders are most active.
Why 5-minute? It allows traders to react to short-term price movements while avoiding the rapid fluctuations of 1-minute charts, which can be prone to false signals in choppy markets. It also provides enough data points to make the SMA and bands meaningful without the lag associated with longer time frames like 15-minute or hourly charts.
Recommended Settings
SMA Length: Set to 200 periods. This longer lookback period smooths the HL2 data, reducing noise and providing a reliable trend reference for the 5-minute chart. A 200-period SMA helps identify significant trend shifts without being overly sensitive to minor price fluctuations.
Band Percentage: 0.5% is more suitable for the volatility of ES and NQ futures on a 5-minute chart, as it generates fewer but higher-probability signals. Wider bands (e.g., 1%) may miss short-term opportunities, while narrower bands (e.g., 0.1%) may produce excessive false signals.
Trading Session Recommendations
Futures markets for ES and NQ are open nearly 24 hours (Sunday 6:00 PM EST to Friday 5:00 PM EST, with a daily break from 4:00 PM–5:00 PM EST), but not all hours are equally optimal due to varying liquidity and volatility. The best times to trade with this indicator are:
U.S. Market Open (9:30 AM–11:00 AM EST): This period is characterized by high volume and volatility, driven by the opening of U.S. equity markets and economic data releases (e.g., 8:30 AM EST reports like CPI or GDP). The indicator’s signals are more reliable during this window due to strong order flow and price momentum.
Afternoon Session (2:00 PM–4:00 PM EST): After the lunchtime lull, volume picks up as institutional traders return, and news or FOMC announcements often drive price action. The indicator can capture breakout moves as prices test the upper or lower bands.
Pre-Market (7:30 AM–9:30 AM EST): For traders comfortable with lower liquidity, this period can offer opportunities, especially around 8:30 AM EST economic releases. However, use tighter risk management due to wider spreads and potential volatility spikes.
Additional Tips
Avoid Low-Volume Periods: Steer clear of trading during low-liquidity hours, such as the overnight session (11:00 PM–3:00 AM EST), when spreads widen and price movements can be erratic, leading to false signals from the indicator.
Combine with Other Tools: Enhance the indicator’s effectiveness by pairing it with support/resistance levels, Fibonacci retracements, or volume analysis to confirm signals. For example, a long entry signal above the upper band is stronger if it coincides with a breakout above a key resistance level.
Risk Management: Given the leverage in futures (e.g., Micro E-mini contracts require ~$1,200 margin for ES), use tight stop-losses (e.g., below the lower band for longs or above the upper band for shorts) to manage risk. Aim for a risk-reward ratio of at least 1:2.
Test Settings: Backtest the indicator on a demo account to optimize the SMA length and band percentage for your specific trading style and risk tolerance. Micro E-mini contracts (MES for S&P 500, MNQ for Nasdaq-100) are ideal for testing due to their lower capital requirements.
Why These Settings and Time Frame?
The 5-minute chart with a 200-period SMA and 0.5% bands is tailored for the volatility and liquidity of ES and NQ futures during peak trading hours. The longer SMA period ensures the indicator captures meaningful trends, while the 0.5% bands are tight enough to signal actionable breakouts but wide enough to avoid excessive whipsaws. Trading during high-volume sessions maximizes the likelihood of valid signals, as institutional participation drives clearer price action.
By focusing on these settings and time frames, traders can leverage the indicator to capitalize on the dynamic price movements of S&P 500 and Nasdaq-100 futures while managing the inherent risks of these markets.
Log-Normal Z-ScoreLog-Normal Z-Score
This Pine Script indicator calculates a modified Z-Score based on log-normal returns, aiming to identify statistically significant price deviations.
Indicator Parameters:
Model Length: The number of bars used to calculate the mean and standard deviation of log returns.
Lookback Length: The number of bars used to compute the lookback return and volatility. This is the main timeframe over which the Z-Score is calculated.
Volatility SMA Length: The smoothing length for the volatility, applying a simple moving average to the calculated volatility.
TDO & Hit Rates by Weekday (5 min)Purpose
Tracks how often the next NY session “hits” the previous day’s True Day Open (TDO) level, separately for sessions that open above vs. below TDO, and breaks the statistics down by weekday (Mon–Fri) plus an overall summary.
Key Features
True Day Open (TDO) Plot
Captures the prior day’s 23:00 CT close price as the TDO.
Plots it as a continuous yellow line across your chart.
Session Labeling
At the end of each NY session (08:30–15:00 CT), places a small “TDO” label at the TDO price to confirm visually where it lay during that day.
Hit‑Count Logic
For each 5 min bar in the NY session, checks if the bar’s high ≥ TDO ≥ low (i.e. the TDO level was “hit”).
Classifies each session by whether its opening price (first 5 min bar) was above or below the TDO.
Weekday Statistics Table
Displays in the bottom‑left of your main chart window.
Rows: Header, Mon, Tue, Wed, Thu, Fri, All.
Columns:
% Hit Above: % of “above‑TDO” sessions that saw at least one hit
% Hit Below: % of “below‑TDO” sessions that saw at least one hit
Automatically updates in real time as new sessions complete.
Inputs & Settings
Data Resolution: Default = 5 min; use any intraday timeframe you like (1, 3, 15 min, etc.).
Extended Hours: Make sure your chart’s Extended Session (overnight) is enabled so the 23:00 CT bar exists.
Overlay: Draws directly on your price chart (no separate pane).
How to Use
Add to Chart: Paste the Pine v5 code into TradingView’s editor and apply to your ES (or other) futures chart.
Enable Overnight Bars: In Chart Settings → Symbol/Session → include Extended Hours.
Select Timeframe: Set the chart (or the indicator’s “Data Resolution” input) to 5 min (or your preferred intraday).
Read the Table:
Each weekday row shows how reliable TDO touches have been historically, separately for “above” and “below” opens.
The bottom “All” row summarizes combined performance.
What You Learn
Edge Analysis: Do sessions opening above TDO tend to test that level more often than those opening below (or vice versa)?
Day‑of‑Week Bias: Are certain weekdays more prone to TDO retests?
Overall Confidence: The “All” row lets you see your full-sample hit‑rate on both sides.
Zen MIG Reversal V1**Zen MIG Reversal V1**
Zen MIG Reversal is a pattern-based indicator that highlights rare reversal setups.
It’s designed to support traders in visually identifying potential turning points, especially following strong momentum or gap-style moves.
**How it works:**
- **Bullish Reversal:**
Detects 3 consecutive bullish candles. The third bar must have a low above the high of the first bar and below the 20 EMA. When this occurs, a light blue box is drawn across the 3-bar range, from high to the current bar’s low. A blue arrow appears below the prior bar.
- **Bearish Reversal:**
Detects 3 consecutive bearish candles. The third bar must have a high below the low of the first bar and above the 20 EMA. A light red box is drawn from low to the current bar’s high. A red arrow appears above the prior bar.
- Optional settings allow you to:
- Show or hide the EMA line
- Toggle the arrows
- Adjust smoothing settings for context
**Purpose:**
It’s best used for discretionary analysis, journaling, or studying price behavior in momentum-driven environments.
**Disclaimer:**
This script is for educational and informational purposes only. It does not provide financial advice or trade recommendations. Always backtest and use proper risk management before applying any indicator to live trading.
Log-Normal Price DistributionThis Pine Script indicator plots a log-normal distribution model of future price projections on a TradingView chart. It visualizes the potential price ranges based on the statistical properties (mean and standard deviation) of log returns over a defined period. It's particularly useful for analyzing potential volatility and predicting future price ranges.
Engulfing Candle with Streaks and CountIdentifies Engulfing Candles + The Number of Consecutive Signals + Identifies 3rd/4th Consecutive Signals + Keeps Count of Most Recent Number of Signals as Decided by User.
- Have coded in the latest version 6
- This script allows the tracking of engulfing candles over a user defined amount of time (candles).
- The script will signal every engulfing candle and its consecutive corresponding number across the entire chart.
- The Engulfing Count box in the bottom right counts how many bullish and bearish engulfing candles have occurred over the number decided by the user.
- The Engulfing Signal that prints is triggered when an opposite next candle prints and the body is over 100% larger than the previous candle. It does not need to "fully engulf" the previous candle, the coding has an allowance for an "equal to and greater/smaller than" the previous close price. This allows for signals were the open of the engulfing candle can be equal to the close of the previous opposite, however the engulfing still must reach an over 100% sizing of the previous to print a signal.
- Where a piercing candle occurs and the open price is within the body of the previous candle, this will void the equation and no matter how big the candle is, it will not trigger an engulfing signal as I was only looking for true engulfing candles.
- The script keeps count of the same consecutive signals no matter the timeframe.
- It will print the consecutive number above or below the signal (depending if bullish or bearish).
- To assist with trend identification the 3rd consecutive signal will print blue, and the 4th consecutive signal will print yellow (or I prefer to use the term "Gold"). This can help filter out the noise on lower timeframes to assist to see where the momentum is going, or if there are signals going against the trend to try trick traders.
- Back testing I found the 3rd and 4th signals are uncommon on higher timeframes and tend to act as fake-outs before the trend reverses.
- Overall a good tool to add to your trend analysis, either for additional confluence or to assist with reversal identification.
- Colors are set as default, but everything can be changed by the user as I didn't want to limit its possibilities.
*** Please note that this script does not take into any consideration candle wicks. Although it can be used with Heikin Ashi it is somewhat unreliable. This indicator is designed to be used with standard candles only ***
position_toolLibrary "position_tool"
Trying to turn TradingView's position tool into a library from which you can draw position tools for your strategies on the chart. Not sure if this is going to work
calcBaseUnit()
Calculates the chart symbol's base unit of change in asset prices.
Returns: (float) A ticks or pips value of base units of change.
calcOrderPipsOrTicks(orderSize, unit)
Converts the `orderSize` to ticks.
Parameters:
orderSize (float) : (series float) The order size to convert to ticks.
unit (simple float) : (simple float) The basic units of change in asset prices.
Returns: (int) A tick value based on a given order size.
calcProfitLossSize(price, entryPrice, isLongPosition)
Calculates a difference between a `price` and the `entryPrice` in absolute terms.
Parameters:
price (float) : (series float) The price to calculate the difference from.
entryPrice (float) : (series float) The price of entry for the position.
isLongPosition (bool)
Returns: (float) The absolute price displacement of a price from an entry price.
calcRiskRewardRatio(profitSize, lossSize)
Calculates a risk to reward ratio given the size of profit and loss.
Parameters:
profitSize (float) : (series float) The size of the profit in absolute terms.
lossSize (float) : (series float) The size of the loss in absolute terms.
Returns: (float) The ratio between the `profitSize` to the `lossSize`
createPosition(entryPrice, entryTime, tpPrice, slPrice, entryColor, tpColor, slColor, textColor, showExtendRight)
Main function to create a position visualization with entry, TP, and SL
Parameters:
entryPrice (float) : (float) The entry price of the position
entryTime (int) : (int) The entry time of the position in bar_time format
tpPrice (float) : (float) The take profit price
slPrice (float) : (float) The stop loss price
entryColor (color) : (color) Color for entry line
tpColor (color) : (color) Color for take profit zone
slColor (color) : (color) Color for stop loss zone
textColor (color) : (color) Color for text labels
showExtendRight (bool) : (bool) Whether to extend lines to the right
Returns: (bool) Returns true when position is closed
MACD Bullish Cross Alert📘 Indicator Description – MACD Bullish Cross Alert
This indicator is designed to detect bullish momentum shifts using the classic MACD (Moving Average Convergence Divergence) crossover strategy.
Key Features:
Calculates the MACD Line and Signal Line using customizable inputs (default: 12, 26, 9).
Triggers an alert when the MACD Line (blue) crosses above the Signal Line (orange).
Helps identify early bullish trend reversals or momentum entry points.
Ideal for swing traders, position traders, and crypto investors using the weekly timeframe.
How to Use:
Add to any chart and set the timeframe to 1W (weekly).
Create an alert using the built-in MACD Bullish Crossover condition.
Combine with price action, volume, or RSI for higher conviction entries.
Use Cases:
Spotting early entry points after long downtrends.
Confirming a trend reversal in high timeframes.
Generating high-probability entries in trend-following systems.
The Hebrew CalendarThis indicator displays the current Hebrew (Jewish) calendar date based on the real-time Gregorian calendar. Features included:
Calculates and displays the current Hebrew day, month, and year.
Recognizes leap years and adjusts month counts accordingly.
Aligns with traditional Hebrew month names (Tishrei, Cheshvan, Kislev, etc.).
The calculations align with the Hebrew Calendar Converter from:
👉 www.chabad.org
The results are shown in a table overlay on your chart's top-right corner. This indicator is great for symbolic traders, astro enthusiasts, or anyone interested in ancient timekeeping systems woven into financial timeframes. Enjoy, time travelers! ⌛
The Mayan CalendarThis indicator displays the current date in the Mayan Calendar, based on real-time UTC time. It calculates and presents:
🌀 Long Count (Baktun.Katun.Tun.Uinal.Kin) – A linear count of days since the Mayan epoch (August 11, 3114 BCE).
🔮 Tzolk'in Date – A 260-day sacred cycle combining a number (1–13) and one of 20 day names (e.g., 4 Ajaw).
🌾 Haab' Date – A 365-day civil cycle divided into 18 months of 20 days + 5 "nameless" days (Wayeb').
The calculations follow Smithsonian standards and align with the Maya Calendar Converter from the National Museum of the American Indian:
👉 maya.nmai.si.edu
The results are shown in a table overlay on your chart's top-right corner. This indicator is great for symbolic traders, astro enthusiasts, or anyone interested in ancient timekeeping systems woven into financial timeframes. Enjoy, time travelers! ⌛
