Uptrick: Dynamic Z-Score DeviationOverview
Uptrick: Dynamic Z‑Score Deviation is a trading indicator built in Pine Script that combines statistical filters and adaptive smoothing to highlight potential reversal points in price action. It combines a hybrid moving average, dual Z‑Score analysis on both price and RSI, and visual enhancements like slope‑based coloring, ATR‑based shadow bands, and dynamically scaled reversal signals.
Introduction
Statistical indicators like Z‑Scores measure how far a value deviates from its average relative to the typical variation (standard deviation). Standard deviation quantifies how dispersed a set of values is around its mean. A Z‑Score of +2 indicates a value two standard deviations above the mean, while -2 is two below. Traders use Z‑Scores to spot unusually high or low readings that may signal overbought or oversold conditions.
Moving averages smooth out price data to reveal trends. The Arnaud Legoux Moving Average (ALMA) reduces lag and noise through weighted averaging. A Zero‑Lag EMA (approximated here using a time‑shifted EMA) seeks to further minimize delay in following price. The RSI (Relative Strength Index) is a momentum oscillator that measures recent gains against losses over a set period.
ATR (Average True Range) gauges market volatility by averaging the range between high and low over a lookback period. Shadow bands built using ATR give a visual mood of volatility around a central trend line. Together, these tools inform a dynamic but statistically grounded view of market extremes.
Purpose
The main goal of this indicator is to help traders spot short‑term reversal opportunities on lower timeframes. By requiring both price and momentum (RSI) to exhibit statistically significant deviations from their norms, it filters out weak setups and focuses on higher‑probability mean‑reversion zones. Reversal signals appear when price deviates far enough from its hybrid moving average and RSI deviates similarly in the same direction. This makes it suitable for discretionary traders seeking clean entry cues in volatile environments.
Originality and Uniqueness
Uptrick: Dynamic Z‑Score Deviation distinguishes itself from standard reversal or mean‑reversion tools by combining several elements into a single framework:
A composite moving average (ALMA + Zero‑Lag EMA) for a smooth yet responsive baseline
Dual Z‑Score filters on price and RSI rather than relying on a single measure
Adaptive visual elements, including slope‑aware coloring, multi‑layer ATR shadows, and signal sizing based on combined Z‑Score magnitude
Most indicators focus on one aspect—price envelopes or RSI thresholds—whereas Uptrick: Dynamic Z‑Score Deviation requires both layers to align before signaling. Its visual design aids quick interpretation without overwhelming the chart.
Why these indicators were merged
Every component in Uptrick: Dynamic Z‑Score Deviation has a purpose:
• ALMA: provides a smooth moving average with reduced lag and fewer false crossovers than a simple SMA or EMA.
• Zero‑Lag EMA (ZLMA approximation): further reduces the delay relative to price by applying a time shift to EMA inputs. This keeps the composite MA closer to current price action.
• RSI and its EMA filter: RSI measures momentum. Applying an EMA filter on RSI smooths out false spikes and confirms genuine overbought or oversold momentum.
• Dual Z‑Scores: computing Z‑Scores on both the distance between price and the composite MA, and on smoothed RSI, ensures that signals only fire when both price and momentum are unusually stretched.
• ATR bands: using ATR‑based shadow layers visualizes volatility around the MA, guiding traders on potential support and resistance zones.
At the end, these pieces merge into a single indicator that detects statistically significant mean reversions while staying adaptive to real‑time volatility and momentum.
Calculations
1. Compute ALMA over the chosen MA length, offset, and sigma.
2. Approximate ZLMA by applying EMA to twice the price minus the price shifted by the MA length.
3. Calculate the composite moving average as the average of ALMA and ZLMA.
4. Compute raw RSI and smooth it with ALMA. Apply an EMA filter to raw RSI to reduce noise.
5. For both price and smoothed RSI, calculate the mean and standard deviation over the Z‑Score lookback period.
6. Compute Z‑Scores:
• z_price = (current price − composite MA mean) / standard deviation of price deviations
• z_rsi = (smoothed RSI − mean RSI) / standard deviation of RSI
7. Determine reversal conditions: both Z‑Scores exceed their thresholds in the same direction, RSI EMA is in oversold/overbought zones (below 40 or above 60), and price movement confirms directionality.
8. Compute signal strength as the sum of the absolute Z‑Scores, then classify into weak, medium, or strong.
9. Calculate ATR over the chosen period and multiply by layer multipliers to form shadow widths.
10.Derive slope over the chosen slope length and color the MA line and bars based on direction, optionally smoothing color transitions via EMA on RGB channels.
How this indicator actually works
1. The script begins by smoothing price data with ALMA and approximating a zero‑lag EMA, then averaging them for the main MA.
2. RSI is calculated, then smoothed and filtered.
3. Using a rolling window, the script computes statistical measures for both price deviations and RSI.
4. Z‑Scores tell how far current values lie from their recent norms.
5. When both Z‑Scores cross configured thresholds and momentum conditions align, reversal signals are flagged.
6. Signals are drawn with size and color reflecting strength.
7. The MA is plotted with dynamic coloring; ATR shadows are layered beneath to show volatility envelopes.
8. Bars can be colored to match MA slope, reinforcing trend context.
9. Alert conditions allow automated notifications when signals occur.
Inputs
Main Length: Main MA Length. Sets the period for ALMA and ZLMA.
RSI Length: RSI Length. Determines the lookback for momentum calculations.
Z-Score Lookback: Z‑Score Lookback. Window for mean and standard deviation computations.
Price Z-Score Threshold: Price Z‑Score Threshold. Minimum deviation required for price.
RSI Z-Score threshold: RSI Z‑Score Threshold. Minimum deviation required for momentum.
RSI EMA Filter Length: RSI EMA Filter Length. Smooths raw RSI readings.
ALMA Offset: Controls ALMA’s focal point in the window.
ALMA Sigma: Adjusts ALMA’s smoothing strength.
Show Reversal Signals : Toggle to display reversal signal markers.
Slope Sensitivity: Length for slope calculation. Higher values smooth slope changes.
Use Bar Coloring: Enables coloring of price bars based on MA slope.
Show MA Shadow: Toggle for ATR‑based shadow bands.
Shadow Layer Count: Number of shadow layers (1–4).
Base Shadow ATR Multiplier: Multiplier for ATR when sizing the first band.
Smooth Color Transitions (boolean): Smooths RGB transitions for line and shadows, if enabled.
ATR Length for Shadow: ATR Period for computing volatility bands.
Use Dynamic Signal Size: Toggles dynamic scaling of reversal symbols.
Features
Moving average smoothing: a hybrid of ALMA and Zero‑Lag EMA that balances responsiveness and noise reduction.
Slope coloring: MA line and optionally price bars change color based on trend direction; color transitions can be smoothed for visual continuity.
ATR shadow layers: translucent bands around the MA show volatility envelopes; up to four concentric layers help gauge distance from normal price swings.
Dual Z‑Score filters: price and momentum must both deviate beyond thresholds to trigger signals, reducing false positives.
Dynamic signal sizing: reversal markers scale in size based on the combined Z‑Score magnitude, making stronger signals more prominent.
Adaptive visuals: optional smoothing of color channels creates gradient effects on lines and fills for a polished look.
Alert conditions: built‑in buy and sell alerts notify traders when reversal setups emerge.
Conclusion
Uptrick: Dynamic Z‑Score Deviation delivers a structured way to identify short‑term reversal opportunities by fusing statistical rigor with adaptive smoothing and clear visual cues. It guides traders through multiple confirmation layers—hybrid moving average, dual Z‑Score analysis, momentum filtering, and volatility envelopes—while keeping the chart clean and informative.
Disclaimer
This indicator is provided for informational and educational purposes only and does not constitute financial advice. Trading carries risk and may not be suitable for all participants. Past performance is not indicative of future results. Always do your own analysis and risk management before making trading decisions.
Volatilidade
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.
Enhanced Bollinger Bands📈 *Enhanced Bollinger Bands – Custom Indicator*
This custom indicator is a more flexible and informative version of the traditional *Bollinger Bands*, designed to help traders better visualize price volatility, trend direction, and breakout signals.
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🔍 Key Features:
✅ *Multiple Moving Average Options*
Choose between:
- *SMA (Simple Moving Average)*
- *EMA (Exponential Moving Average)*
- *WMA (Weighted Moving Average)*
This allows you to tailor the indicator to your trading strategy.
✅ *Dynamic Bands Based on Volatility*
The upper and lower bands are calculated using a user-defined standard deviation multiplier, showing volatility around the selected moving average.
✅ *Color-Coded Trend Visualization*
The bands change color based on the slope of the moving average:
- 🟢 *Green* when the trend is up
- 🔴 *Red* when the trend is down
- ⚪ *Gray* when the trend is flat
This helps traders visually confirm trend direction.
✅ *Optional Band Fill*
You can enable a shaded area between the upper and lower bands, making it easier to identify *volatility squeezes* and *expansions*.
✅ *Breakout Signal Arrows*
Automatic signal arrows appear when:
- 📈 Price *crosses above* the upper band (potential breakout)
- 📉 Price *crosses below* the lower band (potential breakdown)
These signals can help spot strong momentum entries.
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⚙️ Inputs:
- *MA Type:* SMA / EMA / WMA
- *Length:* Period for the moving average and standard deviation
- *Multiplier:* Standard deviation multiplier for band width
- *Source:*Price source (default: close)
- *Toggle Fill:* Turn band fill on/off
- *Toggle Signals:* Show or hide breakout arrows
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🧠 How to Use:
- Use band *tightening* as a sign of low volatility (possible breakout setup).
- Use band *expansion* to confirm high momentum moves.
- Use signal arrows for early entries on momentum plays.
- Combine with RSI, MACD, or volume indicators for confluence.
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Let me know if you want to write a version tailored for publishing on TradingView, including tags and disclaimers.
Adaptive ATR LimitsThis script plots adaptive ATR limits for intraday trading. It is intended for equities. It is not tested for other securities like futures, crypto, etc, though it may work for these too. It works for both regular trading hours and extended trading hours.
The limit lines (top and bottom) are always exactly 1 ATR/ADR apart. This is a key feature of the indicator.
The main mode is ATR, which includes overnight gaps and pre- and post-market movements. This also means the previous day close is considered to part of the current days range (which aligns with the definition of ATR). There is also an ADR mode, which uses the average range the price moves within regular hours only and is not affected by prices outside of these. Other than that, they work the same (including ATR/ADR length option and smoothing).
When in ADR mode, it treats premarket as a separate session from the regular/post-market and resets the session range at the regular market open. This is so it can plot the limits in the regular/post-market hours without being affected by the pre-market range. This is necessary since the daily ADR includes only regular market moves and due to the way the limits adapt.
It tries to plot the most sensible ATR limits based on the current daily ATR, in order to provide a visual target for how far a price could/should move intraday. In order to do this, it uses two methods to calculate limits, i) based on the mid-point of the current session range, and ii) based on the currently established range and current relative price position within that range.
The session starts using the first method. As more of the ATR is covered in the session, it transitions over of the second method. Once (if) the full ATR is covered within the session, it will have completely transitioned to the second method and will only use that for the rest of the session. In between these states, a weighted average of the two methods is used depending on the amount of the ATR the session has covered.
To explain the effect, as an example, imagine that the price is approaching the full ATR range on the high side. The indicator will have almost fully transitioned to the second (relative) method. The lower ATR limit will now be anchored to the daily low as the price hits the upper ATR limit. If the price goes beyond the upper ATR, the lower ATR limit will stay anchored to the daily low, and the upper limit will stay anchored to 1 ATR above the lower limit. This allows you to see how far the price is going beyond the upper ATR limit. If the price then returns and backs off the upper ATR limit, the lower ATR limit will un-anchor from the daily low (it will actually rise since the daily ATR range has been exceeded so the lower ATR limit needs to come up since the actual daily range can't fit into the ATR range anymore). The overall effect is to give you the best visual indication where the price is in relation to a possible upper ATR-based target. Reverse this example for when price low approaches the ATR range on the low side.
There is also a "basic mode" which simply plots 1 ATR/ADR above/below the session low/high. When using ADR, the session resets at the end of the pre-market.
The ATR length (averaging period) can be set (number of days), as well as a visual smoothing of the ATR limits using EMA.
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.
Freedom LR Price Action PublicThis is a script using multiple types of linear regression with channels, LSMAs, signal lines based on LSMAs, and ATR based on linear regression.
Highest/Lowest Range in TimeframeThis script helps traders visually identify the highest high and lowest low within a customizable range of recent bars.
🔍 Key Features
Scans the last 100 to 1000 bars (user-defined)
Automatically detects:
The highest wick (high) and lowest wick (low)
Draws dotted green horizontal lines at both levels
Shows a label indicating the percentage range between high and low
Displays real-time high and low price labels directly on the chart
⚙️ Use Cases
Quickly spot price extremes over your desired time window
Visually measure market range and volatility
Identify breakout potential or reversal zones
✅ How to Use
Add the script to your chart.
Set the “Bars to Scan” input to your desired lookback period (between 100–1000).
Use the displayed lines and labels to identify key high/low price levels and range metrics.
Heikin Ashi Reversal AlertHeikin ashi reverseal bullish after three or more bearish heikin ashi candles
Polygot Moving AveragesDescription
This is essentially a source merger of Bollinger Bands by Trading View and Simple Moving Averages by stoxxinbox. My additions and subtractions are minimal. There is the BB MA, which I default at 5d, and the other 4 averages are the standard 21, 50, 100, 200, day moving averages. I default the averaging method to WMA (Weighted Moving Average). The method of averaging can be changed as also can the lengths of the inputs to match user preferences. This is what I wanted for an indicator and didn't find.
Usage
The same as you would use any other BB or MA indicator. The benefit of this one is that it has 4 MAs, one MA with the Bollinger Bands attached, and the colours adjusted to be easy on the eyes when using high contrast themes, to be discernible yet sit quietly in the background with lines and candle sticks everywhere shouting for attention. I use it as a base first indicator which I can hide easily (imagine hiding five MA indicators individually constantly) when the more serious indicators come into play.
💥 Early Breakout Detector (Penny Stocks)Early Breakout Detector – Penny Stocks Edition"
This script is designed to detect early breakout signals in low-priced stocks (penny stocks) before the actual breakout happens. It combines multiple technical indicators to spot high-probability setups where a price explosion may be imminent.
🔍 Included logic:
– Unusual relative volume (volume > 2x 20-period average)
– RSI momentum turning bullish (RSI > 50)
– Price trading above the 20-period moving average
– Price approaching recent resistance (within 3%) but not yet breaking it
📈 When all conditions align, a "PRE" label appears on the chart, and an alert can be triggered to catch the move before it happens.
💡 Ideal for traders looking to enter positions before breakouts occur, especially in momentum-driven penny stocks.
🚨 Alerts included. Works on any timeframe. Best results observed on 5min–1H for intraday setups.
🛠 You can modify volume thresholds, RSI period, or resistance distance to suit your strategy.
— Built by AI
Bullish and Bearish Breakout Alert for Gold Futures PullbackBelow is a Pine Script (version 6) for TradingView that includes both bullish and bearish breakout conditions for my intraday trading strategy on micro gold futures (MGC). The strategy focuses on scalping two-legged pullbacks to the 20 EMA or key levels with breakout confirmation, tailored for the Apex Trader Funding $300K challenge. The script accounts for the Daily Sentiment Index (DSI) at 87 (overbought, favoring pullbacks). It generates alerts for placing stop-limit orders for 175 MGC contracts, ensuring compliance with Apex’s rules ($7,500 trailing threshold, $20,000 profit target, 4:59 PM ET close).
Script Requirements
Version: Pine Script v6 (latest for TradingView, April 2025).
Purpose:
Bullish: Alert when price breaks above a rejection candle’s high after a two-legged pullback to the 20 EMA in a bullish trend (price above 20 EMA, VWAP, higher highs/lows).
Bearish: Alert when price breaks below a rejection candle’s low after a two-legged pullback to the 20 EMA in a bearish trend (price below 20 EMA, VWAP, lower highs/lows).
Context: 5-minute MGC chart, U.S. session (8:30 AM–12:00 PM ET), avoiding overbought breakouts above $3,450 (DSI 87).
Output: Alerts for stop-limit orders (e.g., “Buy: Stop=$3,377, Limit=$3,377.10” or “Sell: Stop=$3,447, Limit=$3,446.90”), quantity 175 MGC.
Apex Compliance: 175-contract limit, stop-losses, one-directional news trading, close by 4:59 PM ET.
How to Use the Script in TradingView
1. Add Script:
Open TradingView (tradingview.com).
Go to “Pine Editor” (bottom panel).
Copy the script from the content.
Click “Add to Chart” to apply to your MGC 5-minute chart .
2. Configure Chart:
Symbol: MGC (Micro Gold Futures, CME, via Tradovate/Apex data feed).
Timeframe: 5-minute (entries), 15-minute (trend confirmation, manually check).
Indicators: Script plots 20 EMA and VWAP; add RSI (14) and volume manually if needed .
3. Set Alerts:
Click the “Alert” icon (bell).
Add two alerts:
Bullish Breakout: Condition = “Bullish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Bearish Breakout: Condition = “Bearish Breakout Alert for Gold Futures Pullback,” trigger = “Once Per Bar Close.”
Customize messages (default provided) and set notifications (e.g., TradingView app, SMS).
Example: Bullish alert at $3,377 prompts “Stop=$3,377, Limit=$3,377.10, Quantity=175 MGC” .
4. Execute Orders:
Bullish:
Alert triggers (e.g., stop $3,377, limit $3,377.10).
In TradingView’s “Order Panel,” select “Stop-Limit,” set:
Stop Price: $3,377.
Limit Price: $3,377.10.
Quantity: 175 MGC.
Direction: Buy.
Confirm via Tradovate.
Add bracket order (OCO):
Stop-loss: Sell 175 at $3,376.20 (8 ticks, $1,400 risk).
Take-profit: Sell 87 at $3,378 (1:1), 88 at $3,379 (2:1) .
Bearish:
Alert triggers (e.g., stop $3,447, limit $3,446.90).
Select “Stop-Limit,” set:
Stop Price: $3,447.
Limit Price: $3,446.90.
Quantity: 175 MGC.
Direction: Sell.
Confirm via Tradovate.
Add bracket order:
Stop-loss: Buy 175 at $3,447.80 (8 ticks, $1,400 risk).
Take-profit: Buy 87 at $3,446 (1:1), 88 at $3,445 (2:1) .
5. Monitor:
Green triangles (bullish) or red triangles (bearish) confirm signals.
Avoid bullish entries above $3,450 (DSI 87, overbought) or bearish entries below $3,296 (support) .
Close trades by 4:59 PM ET (set 4:50 PM alert) .
RSI Divergence Strategy - AliferCryptoStrategy Overview
The RSI Divergence Strategy is designed to identify potential reversals by detecting regular bullish and bearish divergences between price action and the Relative Strength Index (RSI). It automatically enters positions when a divergence is confirmed and manages risk with configurable stop-loss and take-profit levels.
Key Features
Automatic Divergence Detection: Scans for RSI pivot lows/highs vs. price pivots using user-defined lookback windows and bar ranges.
Dual SL/TP Methods:
- Swing-based: Stops placed a configurable percentage beyond the most recent swing high/low.
- ATR-based: Stops placed at a multiple of Average True Range, with a separate risk/reward multiplier.
Long and Short Entries: Buys on bullish divergences; sells short on bearish divergences.
Fully Customizable: Input groups for RSI, divergence, swing, ATR, and general SL/TP settings.
Visual Plotting: Marks divergences on chart and plots stop-loss (red) and take-profit (green) lines for active trades.
Alerts: Built-in alert conditions for both bullish and bearish RSI divergences.
Detailed Logic
RSI Calculation: Computes RSI of chosen source over a specified period.
Pivot Detection:
- Identifies RSI pivot lows/highs by scanning a lookback window to the left and right.
- Uses ta.barssince to ensure pivots are separated by a minimum/maximum number of bars.
Divergence Confirmation:
- Bullish: Price makes a lower low while RSI makes a higher low.
- Bearish: Price makes a higher high while RSI makes a lower high.
Entry:
- Opens a Long position when bullish divergence is true.
- Opens a Short position when bearish divergence is true.
Stop-Loss & Take-Profit:
- Swing Method: Computes the recent swing high/low then adjusts by a percentage margin.
- ATR Method: Uses the current ATR × multiplier applied to the entry price.
- Take-Profit: Calculated as entry price ± (risk × R/R ratio).
Exit Orders: Uses strategy.exit to place bracket orders (stop + limit) for both long and short positions.
Inputs and Configuration
RSI Settings: Length & price source for the RSI.
Divergence Settings: Pivot lookback parameters and valid bar ranges.
SL/TP Settings: Choice between Swing or ATR method.
Swing Settings: Swing lookback length, margin (%), and risk/reward ratio.
ATR Settings: ATR length, stop multiplier, and risk/reward ratio.
Usage Notes
Adjust the Pivot Lookback and Range values to suit the volatility and timeframe of your market.
Use higher ATR multipliers for wider stops in choppy conditions, or tighten swing margins in trending markets.
Backtest different R/R ratios to find the balance between win rate and reward.
Disclaimer
This script is for educational purposes only and does not constitute financial advice. Trading carries significant risk and you may lose more than your initial investment. Always conduct your own research and consider consulting a professional before making any trading decisions.
Fair Value Area at Swing ZonesIts as the name says. It combines volume profile important areas (70% of trading taking place in whats called a Fair value zone) and area between a swing high and a swing low which is also considered a fair value zone.
You can use it to trade breakout trades as well as range trades.
📊 Volume Split Buy/Sell | Copytrade TungdubaiThis Pine Script calculates the estimated buy and sell volume based on price action (relative position of the close within the price range of the candle) and plots the values on the chart. Additionally, it detects significant volume spikes by comparing the current volume to a 20-period moving average of volume.
Here’s a breakdown of what each section of the script does:
1. **Inputs and Variables:**
- `vol`: This variable holds the volume of the current candle.
- `body`: This calculates the absolute difference between the close and open prices (i.e., the body size of the candle).
- `price_range`: This is the range between the high and low of the candle.
- `buy_ratio`: This is the ratio of the candle's body above the close relative to the total range, representing buying pressure.
- `sell_ratio`: This is the inverse of `buy_ratio`, representing selling pressure.
2. **Volume Calculation:**
- `buy_volume`: The estimated buying volume is calculated as the total volume multiplied by the buying ratio.
- `sell_volume`: The estimated selling volume is calculated as the total volume multiplied by the selling ratio.
3. **Volume Plots:**
- The script plots the estimated selling volume in red below the baseline (`sell_volume`).
- The estimated buying volume is plotted in lime above the baseline (`buy_volume`).
4. **Volume Spike Detection:**
- `vol_ma`: This is the 20-period simple moving average of volume.
- `vol_spike`: This condition checks if the current volume is greater than 2.5 times the 20-period moving average of volume.
- If a volume spike is detected, a tiny purple circle is plotted at the bottom of the volume bar.
This script can be useful for visualizing the relative strength of buy and sell volumes, as well as detecting unusual volume spikes that might signal significant market activity.
30D Annualized Volatility30D Annualized Volatility for portfolio modelling.
This is for managing high-octane L/S portfolio.
30-Day Rolling Beta30 Day rolling beta for portfolio modelling purpose.
This is meant for high-octane L/S portfolio.
Price Variation Percent (PVP) с таймфреймомA standard PVP indicator that has a multi-timeframe function added to it
Heikin Ashi Smoothed con Gradienti e MA Dinamico
📊 Advanced Heikin-Ashi + 3 Bollinger Bands Indicator
This indicator combines Smoothed Heikin-Ashi candles with three customizable sets of Bollinger Bands, providing a complete visual analysis of trend and market volatility.
MAIN FEATURES:
2 Smoothed Heikin-Ashi Candles:
- Based on two Heikin-Ashi smoothing layers with independent settings
- Advanced color styling options:
🎨 Gradient colors
🔲 Hollow candles (only borders and wicks)
🔥 Delta coloring based on wick size difference
🔵 Automatic black borders when wicks are hidden (for contrast)
3 Independent Bollinger Bands:
- Named First, Second, and Third Bollinger Bands, each with:
- Customizable period and standard deviation
- Separate color and fill settings
- Individual toggle for showing band and fill
- Layered fills for clear visual separation between bands
Full Customization:
- Toggle for wick visibility, borders, gradient colors, hollow mode
- Works with both classic and smoothed Heikin-Ashi
- Great visual clarity, even with complex settings
"By setting both Smoothing Length 1 and 2 to a value of 1, the indicator effectively replicates the classic Heikin Ashi candles. This configuration disables additional smoothing, allowing the Heikin Ashi to reflect market data more directly, preserving its original form without delay or averaging effects."
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"The indicator also features advanced gradient coloring for Heikin Ashi candles, providing a visually intuitive way to interpret price action. Instead of fixed bullish or bearish colors, the candle body color can dynamically reflect the relative strength of upper and lower wicks, allowing for more nuanced insights. This gradient can be customized and fine-tuned through a palette of seven user-defined colors, enhancing the visual richness and analytical depth of the chart."
Let me know the next part you'd like to describe!
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Users have the option to disable the candle wicks for a cleaner visual appearance. When wicks are turned off, the indicator automatically sets the candle borders to black, ensuring clear separation and strong visual contrast between candles. This feature enhances readability, especially when using transparent or gradient-filled bodies, making the chart more visually coherent and easier to read.
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When gradient coloring is disabled, the indicator offers an optional 'hollow candle' mode. In this mode, only the borders and wicks of the candles are displayed, while the candle bodies remain transparent. This minimalistic style can help traders focus on structural price patterns without the distraction of filled colors, and is especially useful for those who prefer clean, contrast-driven chart visuals.
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When both wick display and gradient coloring are disabled, and the hollow candle mode is enabled, the indicator switches to a simplified display style. In this configuration, only the candle borders are shown, offering a clean outline-only view. Both bullish and bearish candles share the same customizable border color, which can be set directly from the input settings. This mode is ideal for users seeking maximum simplicity and visual clarity."
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"When the delta color option is enabled, the candle coloring is determined by the relative difference between the upper and lower wick sizes. This method adds an additional layer of price action analysis, where the candle's gradient reflects wick dominance. A stronger upper wick suggests bullish pressure and is visualized through one end of the gradient spectrum, while a dominant lower wick indicates selling pressure and is represented on the opposite end. This nuanced visualization helps traders quickly gauge market sentiment shifts."
Notably, this feature continues to function even when wick display is turned off, allowing traders to benefit from the underlying sentiment insights while maintaining a cleaner visual layout.
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**"The indicator also supports a Smoothed Heikin Ashi (HA) mode, which enhances traditional HA by applying additional smoothing using two independently configurable moving averages. This dual-smoothing approach helps filter out market noise, offering a clearer view of trend direction and strength. Each moving average can be set to different configurations, allowing users to fine-tune the smoothing process to their specific needs. The following customizable settings are available:"**
- Smoothing Length 1: Controls the length of the first smoothed HA.
- Smoothing Length 2: Controls the length of the second smoothed HA.
Moving Average Type 1 and Moving Average Type 2 selectable from:
- Heikin Original
- SMA (Simple Moving Average)
- EMA (Exponential Moving Average)
- SMMA (RMA - Running Moving Average)
- WMA (Weighted Moving Average)
- VWMA (Volume Weighted Moving Average)
- HMA (Hull Moving Average)
- DEMA (Double Exponential Moving Average)
- TEMA (Triple Exponential Moving Average)
- KAMA (Kaufman Adaptive Moving Average)
- ALMA (Arnaud Legoux Moving Average)
**"Both moving averages can be set to different lengths and types, allowing traders to experiment with various smoothing combinations to suit their preferred trading strategy. When both smoothing lengths are set to 1 and the MA type is 'Heikin Original,' the indicator behaves like a classic Heikin Ashi chart, offering full backward compatibility for users preferring the standard format."**
Note: If one of the two Heikin Ashi layers is set to "Heikin Original," any changes made to the Moving Average Type for the other layer will not take effect. In this case, the chart will behave as a standard Smoothed Heikin Ashi chart.
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"The color settings and methods previously available, such as Hollow Candles, Show Wick, C and Delta Gradient, work seamlessly with the Smoothed Heikin Ashi (HA) chart. In fact, they perform even better when applied to the Smoothed HA, offering a more refined visual experience and clearer trend identification.
"These features, when applied to the Smoothed Heikin Ashi, allow traders to benefit from both the clarity of the smoother chart and the enhanced visual cues provided by the color settings. The performance of these settings is significantly improved, offering a more intuitive and reliable charting experience."
Gradient Color:
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Delta Gradient:
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Show Wick OFF - Gradient Color:
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Show Wick OFF - DELTA Color:
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Show Wick OFF - Normal Color:
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Show Wick OFF - Hollow Candles:
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"Three Bollinger Bands for Enhanced Market Analysis"
"This indicator allows you to use not just a single set of Bollinger Bands, but also two additional sets, each with customizable settings. This provides a more detailed view of price volatility and trend strength. The first Bollinger Band is based on a standard period and standard deviation, while the second and third sets use higher standard deviations for broader price channels, offering insights into extended market movements. Here's how the three sets of Bollinger Bands work:"
1. First Bollinger Band (First Bands, Dev 2):
- This is the traditional Bollinger Band, calculated using a Simple Moving Average (SMA) as the base and a specified standard deviation multiplier.
- Customizable Settings:
- First Length: The period used for calculating the SMA
- First Standard Deviation:** The multiplier for the standard deviation (default is 2.0).
The first Bollinger Band helps identify the range of normal price fluctuations and provides clear support/resistance zones based on the moving average.
2. Second Bollinger Band (Second Bands, Dev 4):
- A second set of Bollinger Bands, calculated using the same base SMA but with a higher standard deviation multiplier (default is 4.0).
- Customizable Settings:
- Second Length: The period for the second set of Bollinger Bands
- Second Deviation: The higher multiplier for the second set of bands (default is 4.0).
The second Bollinger Band gives insight into extreme price movements, highlighting periods of high volatility and potential breakout zones.
3) Third Bollinger Band (Third Bands, Dev 6):
- A third set of Bollinger Bands can be added with customizable settings for a broader analysis
of the market's volatility.
- Customizable Settings:
- Third Length: The period for calculating the third set of Bollinger Bands.
- Third Standard Deviation: The multiplier for the third set of bands (default is 6.0).
The third Bollinger Band acts as an even wider channel for understanding extreme market conditions or prolonged trending periods. Traders can use this band to identify long-term support/resistance levels or extended price ranges.
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"The indicator offers complete control over the length and deviation of each set of bands, allowing traders to customize their analysis for different market conditions. The three Bollinger Bands can provide more detailed insights into market volatility, allowing for better risk management and trade decision-making."
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"Each Bollinger Band and its corresponding fill can be individually enabled or disabled. This means you can choose to focus on any single set of bands (First, Second, or Third) or use multiple bands simultaneously, based on your trading strategy and the market conditions. Similarly, you can activate or deactivate the fills for the bands to further customize the chart's visual display."
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"Additionally, each set of Bollinger Bands can be individually toggled for visibility, making it possible to display just one, two, or all three bands depending on the level of detail you wish to analyze. The fills between the bands can also be toggled on/off independently."
Ultimate Scalping DashboardWhat This Dashboard Includes (Visually Compact):
Trend: EMA 9/21/50 alignment
Momentum: MACD + Stochastic RSI direction
Bias: VWAP position (above/below)
Volume: Spike status
Squeeze: Bollinger Band squeeze
SuperTrend: Bullish/Bearish
Divergence: RSI/MACD signal
Buy/Sell Signal Summary
It gives you a clean table-style display at the top or bottom of the screen — super useful for 15m scalping.
Real-time dashboard at the bottom-right of your chart
Color-coded cells for instant visual clarity
Final signal to tell you: BUY, SELL, or WAIT
MG Thrust Indicator🚀 Explanation 🚀
The MG thrust indicator uses thrust momentum in price with some smoothing to detect uptrend and downtrend shifts.
✨ Key Features ✨
🗡smoothing_length (default: 37): length for smoothing price and thrust values (EMA or SMA).
🗡thrust_threshold (default: 1.5): multiples of ATR to identify significant thrusts.
🗡use_ema (default: true): toggle between EMA (faster response) and SMA (smoother) for smoothing.
🗡lookback_atr (default: 14): lookback period for ATR to normalize thrust.
📈 Thrust Calculation 📈
Thrust = (close - smoothed_price) / atr: measures how far the current price deviates from the smoothed price, normalized by ATR to account for volatility.
Background Highlights: colors the background faintly green/red for bullish/bearish thrusts.
❓ Seeing a bug or an issue ❓
Feel free to DM me if you see a component that seems badly calculated.
I will be happy to fix it.
❗❗ Disclaimer ❗❗
This is a single indicator, even though it's aggregating many, do not use it as a standalone.
Past performance is not indicative of future results.
Always backtest, check, and align parameters before live trading.
QQE SHARPE MAX BOT v2 - Reversals + Trailing + VolumenThe **“QQE SHARPE MAX BOT v2”** strategy is based on detecting momentum shifts using the QQE Mod indicator, combined with a trend filter based on EMA and Heikin Ashi, as well as a volume filter that requires volume to be above its moving average to validate entries. It operates in both directions (long and short) with automatic reversals and manages risk through dynamic trailing stops based on ATR, allowing it to maximize profits during strong trends and avoid trading in low-interest market zones.
Daily ATR BandsATR Finder – Volatility Scanner for Smarter Trade Setups
The ATR Finder is a precision tool designed to help traders quickly identify high-volatility assets using the Average True Range (ATR) – a key metric in assessing market momentum and potential breakout zones. By automatically scanning and highlighting tickers or candles with elevated ATR values relative to their recent historical range, this indicator helps you filter for setups that are more likely to experience significant price moves.
Whether you're a day trader seeking intraday momentum or a swing trader looking for setups with strong follow-through potential, the ATR Finder cuts through the noise and visually signals which assets are "on the move." It can be paired with other indicators or price action tools to create a high-conviction trading strategy focused on volatility expansion.
Key Features:
Dynamic ATR Calculation over a user-defined period
Visual Alerts or Color-Coding for above-threshold volatility spikes
Supports Multiple Timeframes for both short- and long-term volatility analysis
Great for spotting breakout opportunities, gap continuations, or trend reversals
Use the ATR Finder to stay ahead of price action and build a watchlist that moves with purpose. Perfect for scalpers, breakout traders, and anyone who respects the power of volatility.
Fibonacci Levels with MACD ConfirmationHow to Understand and Use the Fibonacci Levels with MACD Confirmation Script
This custom Pine Script is designed to give traders a clear visual framework by combining dynamic Fibonacci retracement levels, MACD histogram confirmation, and volatility-based swing zones. It aims to simplify trend analysis, improve entry timing, and adapt to various market conditions.
How to Interpret the 23.6% & 61.8% Labels
These Fibonacci levels represent key retracement zones where price often reacts during trend pullbacks or reversals.
The 23.6% level indicates a shallow retracement, useful in strong trends where price resumes early.
The 61.8% level is a deeper retracement, often a "last line of defense" before trend invalidation.
The script labels these zones with "CC 23.6" and "CC 61.8" when the price crosses them with MACD histogram confirmation:
Green label (CC) = bullish confirmation
Red label (CC) = bearish confirmation
How to Modify Inputs (Manual Adjustments)
Input Purpose Default How to Use
ATR Period Measures volatility 14 Increase for smoother, slower reactions; reduce for faster swings
Min Lookback Minimum bars for swing zone 20 Avoids short-term noise
Max Lookback Cap for swing zone scan 100 Avoids excessively wide retracement levels
Inverse Candle Chart Flips high/low logic false Enable for inverted analysis or backtesting "opposite logic"
How to Use the Inverse Candle Chart Option
Activating inverse mode flips candle logic:
Highs become negative lows, and vice versa.
Useful for:
Contrarian analysis
Inverse ETFs or short-biased views
Backtesting reverse-pattern behavior
How to Adjust the Style
You can manually personalize the script’s visual appearance:
Change line width in plot(..., linewidth=2) for bolder or thinner Fib levels.
Change colors from color.green, color.red, etc., to suit your theme.
Modify label.size, label.style, and label.color for different labeling visuals.
Customize MACD histogram style from plot.style_columns to other styles like style_histogram.
How the MACD is Set and Displayed
The MACD uses non-standard values:
Fast Length = 24
Slow Length = 52
Signal Smoothing = 18
These values slow down the indicator, reducing noise and aligning better with medium- to long-term trends.
MACD histogram is plotted directly on the main chart for faster, on-screen decision making.
Color-coded histogram:
Green/Lime = Bullish momentum increasing or steady
Red/Maroon = Bearish momentum increasing or steady
How to Use the Indicator in Real-World Trading
This indicator is most effective when used to:
✅ 1. Spot High-Probability Trend Continuation Zones
In a strong trend, price will often retrace to 23.6% or 61.8%, then resume.
Wait for:
Price to cross 23.6 or 61.8
MACD histogram rising (bullish) or falling (bearish)
"CC 23.6" or "CC 61.8" label to appear
🟢 Entry Example: Price retraces to Fib 61.8%, crosses up with green MACD histogram → take long position
✅ 2. Validate Reversal or Breakout Zones
These Fib levels also act as support/resistance.
If price crosses a Fib level but MACD fails to confirm, it may be a fake breakout.
Use confirmation labels only when MACD aligns.
✅ 3. Add Volatility Context (ATR) for Risk Management
The ATR label shows both value and %.
Use ATR to:
Set dynamic stop-losses (e.g., 1.5x ATR below entry)
Decide trade size based on volatility
How to Combine the Indicator With Other Tools
You can combine this script with other technical tools for a powerful trading framework:
🔁 With Moving Averages
Use 50/200 MA for overall trend direction
Take signals only in the direction of MA slope
🔄 With Price Action Patterns
Use the Fib/MACD signals at confluence points:
Support/resistance zones
Breakout retests
Candlestick patterns (pin bars, engulfing)
🔺 With Volume or Order Flow
Combine with volume spikes or order book signals
Confirm that Fib/MACD signals align with strong volume for conviction
✅ Trade Setup Summary
Criteria Long Setup Short Setup
Price at Fib Level At or crossing Fib 23.6 / 61.8 Same
MACD Histogram Rising and above previous bar Falling and below previous bar
Label Appears Green "CC 23.6" or "CC 61.8" Red "CC 23.6" or "CC 61.8"
Optional Filters Trend direction, ATR range, volume, price pattern Same
