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.
التقلب
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.
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.
📊 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.
Scalping strategy [EMA 9/21/200 + VWAP]This strategy works best during high-volume periods on the 1-minute and 5-minute charts.
🟢 Buy Setup:
EMA 9 crosses above EMA 21 (bullish momentum)
Price is above VWAP (bullish bias)
Look for bullish candlestick patterns (engulfing, pin bar, etc.)
Optional: Entry on a pullback to EMA 9 or 21
🔴 Sell Setup:
EMA 9 crosses below EMA 21 (bearish momentum)
Price is below VWAP (bearish bias)
Look for bearish candlestick patterns
Optional: Entry on pullback to EMA 9 or 21
📈 Exit Strategy:
Take profit at predefined risk-reward
Or use EMA 9 crossing back over 21 in the opposite direction
Stop loss just below/above recent swing
Like this indicator? Boost it ♡
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.
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.
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.
Price Variation Percent (PVP) с таймфреймомA standard PVP indicator that has a multi-timeframe function added to it
Heikin Ashi Reversal AlertHeikin ashi reverseal bullish after three or more bearish heikin ashi candles
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.
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) .
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.
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.
30-Day Rolling Beta30 Day rolling beta for portfolio modelling purpose.
This is meant for high-octane L/S portfolio.
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
30D Annualized Volatility30D Annualized Volatility for portfolio modelling.
This is for managing high-octane L/S portfolio.
Impulse Volume Oscillator [Alpha Extract]Impulse Volume Oscillator
A sophisticated indicator designed to identify market impulse moves and volume-based momentum shifts, helping traders capture significant price movements with precision.
Combining price deviations with volume analysis, this oscillator dynamically measures market strength and weakness, providing clear signals for potential trend continuations and reversals.
🔶 Volume-Adjusted Normalization
Utilizes a unique normalization technique that incorporates volume impact to enhance signal quality. This approach ensures the indicator responds more strongly to high-volume price movements while filtering out low-volume noise.
vol_ratio = ta.rsi(volume, 14) / 50
vol_factor = vol_impact > 0 ? 1 + (vol_ratio - 1) * vol_impact : 1
raw_normalized = dev / (ta.stdev(source, bars) * mult)
vol_adjusted = raw_normalized * vol_factor
normalized = ta.sma(vol_adjusted, smooth)
🔶 Adaptive Regime Detection
Incorporates threshold-based regime identification that clearly distinguishes between trending and mean-reverting market conditions. The customizable threshold system allows traders to adapt to different market volatilities and timeframes.
🔶 Customizable Parameters
Fine-tune detection sensitivity with adjustable inputs for lookback period, standard deviation multiplier, volume impact, and signal smoothing. These parameters enable traders to optimize the indicator for various trading styles and market conditions.
❓How It Works
🔶 Impulse Calculation
The oscillator measures price deviation from a moving average baseline, normalized by standard deviation, and then adjusts the signal based on relative volume strength. This creates a responsive yet stable indicator that accurately reflects market momentum.
// Calculate the basis using the selected MA
basis = get_ma(source, bars)
// Calculate the normalized value with volume impact
dev = source - basis
🔶 Dynamic Visualization
The histogram changes color based on signal strength, providing instant visual cues about market conditions. Green bars indicate positive momentum while red bars represent negative momentum, with color intensity reflecting signal strength.
🔶 Trend Confirmation
Built-in trend direction analysis provides confluence with the primary signal, helping traders distinguish between counter-trend bounces and genuine trend reversals. This dual-confirmation approach significantly reduces false signals.
🔶 Visual Alerts & Boundary Tracking
Monitors signal extremes and dynamically adjusts visualization transparency based on signal strength. The indicator highlights particularly strong impulse moves with background shading, making potential trading opportunities immediately apparent.
🔶 Custom Candle Coloring
Optional candle coloring applies the same color logic as the histogram directly to price candles, providing a unified visual framework that helps traders correlate indicator signals with price action.
🔶 Momentum Shift Detection
Automatically identifies important zero-line crossovers that often signify the beginning of new impulse moves. These transition points frequently offer favorable risk/reward entry opportunities.
🔶 Snapshot samples
1 Week
1 Day
15 Min
🔶 Why Choose AE - Impulse Volume Oscillator?
This indicator provides a comprehensive approach to identifying significant market moves by combining volume analysis with price momentum. By offering clear visual signals for both trend continuation and reversal scenarios, it empowers traders to make more informed decisions across various market conditions and timeframes.
Chandelier Exit with ZLSMA SwiftEdgeChandelier Exit with ZLSMA
Overview
The "Chandelier Exit with ZLSMA" indicator is a powerful trading tool designed to identify trend reversals and high-probability entry points in financial markets. By combining the volatility-based Chandelier Exit with the low-lag Zero Lag Least Squares Moving Average (ZLSMA), this indicator provides clear Buy and Sell signals, enhanced with a unique signal strength score to help traders prioritize high-quality opportunities. Visual enhancements, including dynamic color coding, background highlights, and trend arrows, make it intuitive and visually appealing for both novice and experienced traders.
What It Does
This indicator generates Buy and Sell signals when a trend reversal is detected by the Chandelier Exit, but only if the price crosses the ZLSMA for the first time in the direction of the trend. Each signal is accompanied by a percentage score (0-100%) that measures its strength based on price movement and momentum. The indicator overlays directly on the price chart, displaying:
Buy/Sell labels with signal strength (e.g., "Buy (85%)").
A ZLSMA line that changes color (green for bullish, red for bearish) to indicate trend direction.
Background highlights to mark signal candles.
Trend arrows to visually confirm signal points.
How It Works
The indicator combines two complementary components:
Chandelier Exit:
Uses the Average True Range (ATR) to create dynamic trailing stop levels (long_stop and short_stop) that adapt to market volatility.
Signals a Buy when the price crosses above the short stop (indicating a potential uptrend) and a Sell when it crosses below the long stop (indicating a potential downtrend).
Default settings use an ATR period of 1 and a multiplier of 2.0 for high sensitivity to short-term price movements.
Zero Lag LSMA (ZLSMA):
A low-lag moving average based on linear regression, designed to reduce delay compared to traditional moving averages.
Acts as a trend filter: Buy signals are only generated when the price closes above ZLSMA for the first time, and Sell signals when it closes below for the first time.
Default length of 50 balances smoothness with responsiveness.
Signal Strength Score:
Each signal is assigned a score (0-100%) based on:
Distance to ZLSMA (60% weight): How far the price is from ZLSMA, normalized by ATR. Larger distances indicate stronger breakouts.
Candlestick size (40% weight): The size of the signal candle, normalized by ATR. Larger candles suggest stronger momentum.
A high score (e.g., >80%) indicates a robust signal, while a low score (e.g., <50%) suggests caution.
Visual Features:
The ZLSMA line changes color (green for bullish, red for bearish) to reflect the trend.
Signal candles are highlighted with a subtle green (Buy) or red (Sell) background.
Tiny triangular arrows appear below Buy signals and above Sell signals for clear visual confirmation.
Why Combine Chandelier Exit and ZLSMA?
The Chandelier Exit excels at identifying trend reversals through volatility-based stops, but it can generate false signals in choppy markets due to its sensitivity (especially with a short ATR period of 1). The ZLSMA addresses this by acting as a trend filter, ensuring signals are only triggered when the price confirms a trend by crossing the ZLSMA for the first time. This combination reduces noise and focuses on high-probability setups. The signal strength score further enhances decision-making by quantifying the conviction behind each signal, making the indicator feel intuitive and "smart."
How to Use
Setup:
Add the indicator to your chart in TradingView.
Adjust inputs in the settings panel:
ATR Period (default: 1): Controls the sensitivity of Chandelier Exit. Increase for smoother signals.
ATR Multiplier (default: 2.0): Sets the distance of stop levels from price extremes.
ZLSMA Length (default: 50): Adjusts the smoothness of the ZLSMA line. Shorter lengths (e.g., 20-30) are more responsive; longer lengths (e.g., 50-100) are smoother.
Use Close Price for Extremums (default: true): Determines whether Chandelier Exit uses closing prices or high/low prices for calculations.
Interpreting Signals:
Buy Signal: A green "Buy (X%)" label appears below a candle when the price crosses above the Chandelier Exit short stop and closes above ZLSMA for the first time. The percentage indicates signal strength (higher = stronger).
Sell Signal: A red "Sell (X%)" label appears above a candle when the price crosses below the Chandelier Exit long stop and closes below ZLSMA for the first time.
Use the ZLSMA line’s color (green for bullish, red for bearish) to confirm the overall trend.
Prioritize signals with high strength scores (e.g., >70%) for better reliability.
Trading Considerations:
Combine signals with other analysis (e.g., support/resistance, volume) for confirmation.
Test the indicator on a demo account or use TradingView’s Strategy Tester to evaluate performance.
Be cautious with the default ATR period of 1, as it is highly sensitive and may generate frequent signals in volatile markets.
What Makes It Unique
This indicator stands out due to its thoughtful integration of Chandelier Exit and ZLSMA, creating a synergy that balances sensitivity with reliability. The first-cross filter ensures signals are triggered only at the start of potential trends, reducing false positives. The signal strength score adds a layer of intelligence, helping traders assess the quality of each signal without needing external tools. Visual enhancements, such as dynamic ZLSMA coloring, background highlights, and trend arrows, make the indicator user-friendly and visually engaging, appealing to traders seeking a modern, intuitive tool.
Limitations and Notes
The short ATR period (1) makes the indicator highly sensitive, which suits short-term traders but may produce noise in sideways markets. Increase the ATR period for smoother signals.
The signal strength score is a heuristic based on price movement and momentum, not a predictive model. Use it as a guide, not a definitive predictor.
Always backtest the indicator on your preferred market and timeframe to ensure it aligns with your trading strategy.
SwiftEdge NW EnvelopeSwiftEdge NW Envelope
Overview
The SwiftEdge NW Envelope is a visually striking technical indicator designed for traders seeking to identify high-probability buy and sell opportunities in volatile markets. By combining the Relative Strength Index (RSI), Average True Range (ATR), and Nadaraya-Watson Envelope, this indicator provides a unique blend of momentum, volatility, and non-linear trend analysis. Its futuristic, AI-inspired aesthetic—featuring neon gradients and dynamic colors—enhances chart readability while delivering actionable trading signals.
What It Does
The SwiftEdge NW Envelope generates buy and sell signals based on price interactions with dynamically calculated support and resistance bands, confirmed by RSI conditions. The indicator:
Plots a Nadaraya-Watson Envelope to identify smooth, non-linear price trends and dynamic support/resistance zones.
Uses ATR to scale the envelope’s bands, adapting to market volatility.
Employs RSI to confirm overbought/oversold conditions, ensuring signals align with momentum.
Visualizes signals with neon-colored markers, background zones, and labels for intuitive decision-making.
How It Works
The indicator integrates three key components:
Nadaraya-Watson Envelope:
A kernel-based regression technique that smooths price data to create a central trend line (mean) and dynamic upper/lower bands.
Unlike traditional moving averages, it provides a non-linear, adaptive view of price trends, making it ideal for capturing complex market movements.
The band width is determined by ATR, ensuring responsiveness to volatility.
Average True Range (ATR):
Measures market volatility to scale the envelope’s bands.
A multiplier (default: 0.5) adjusts the sensitivity of the bands, allowing traders to fine-tune the indicator for different assets or market conditions.
Relative Strength Index (RSI):
A momentum oscillator with a shortened period (default: 5) for increased sensitivity.
Confirms buy signals when RSI is oversold (default: <30) and sell signals when RSI is overbought (default: >70).
Signal Logic
Buy Signal: Triggered when the price crosses above the lower band of the Nadaraya-Watson Envelope and RSI is below the oversold threshold. Marked by a green circle and a "BUY" label below the candle.
Sell Signal: Triggered when the price crosses below the upper band and RSI is above the overbought threshold. Marked by a magenta circle and a "SELL" label above the candle.
Background Zones: Green (buy) or red (sell) translucent zones highlight signal areas for quick recognition.
Visual Features
Dynamic Colors: The central trend line shifts between cyan (uptrend), purple (downtrend), or gray (neutral) based on price position relative to the mean.
Neon Gradient Fill: A translucent blue fill between the upper (green) and lower (red) bands creates a glowing, futuristic effect.
Modern Signal Markers: Small, vibrant circles (green for buy, magenta for sell) and clear labels enhance visual clarity.
Why This Combination?
The SwiftEdge NW Envelope combines RSI, ATR, and Nadaraya-Watson Envelope to create a robust trading tool:
RSI provides momentum confirmation, filtering out false signals in choppy markets.
ATR ensures the envelope adapts to changing volatility, making it suitable for both trending and ranging markets.
Nadaraya-Watson Envelope offers a sophisticated, non-linear alternative to traditional bands (e.g., Bollinger Bands), capturing subtle price dynamics. Together, these components deliver a balanced approach to trend-following and mean-reversion strategies, with RSI acting as a gatekeeper to improve signal reliability.
Customize Settings:
RSI Period (5): Adjust for more/less sensitivity to momentum.
RSI Overbought/Oversold (70/30): Modify thresholds to tighten or loosen signal conditions.
ATR Period (14) and Multiplier (0.5): Tune volatility sensitivity.
NW Length (25), Bandwidth (8.0), Multiplier (3.0): Adjust the smoothness and width of the envelope.
Interpret Signals:
Buy: Look for green circles and "BUY" labels when price crosses above the lower band, confirmed by low RSI.
Sell: Look for magenta circles and "SELL" labels when price crosses below the upper band, confirmed by high RSI.
Use background zones to quickly spot active signal areas.
Combine with Other Tools:
Pair with support/resistance levels or volume analysis for additional confirmation.
Test signals on a demo account before live trading.
Originality
The SwiftEdge NW Envelope stands out due to:
Its innovative use of Nadaraya-Watson regression, a less common but powerful tool for non-linear trend analysis.
A unique visual design with neon gradients and dynamic colors, inspired by AI and futuristic interfaces, making it both functional and visually engaging.
A streamlined signal system that balances momentum (RSI), volatility (ATR), and trend (Nadaraya-Watson), reducing noise and enhancing trade precision.
Notes
Best suited for volatile markets (e.g., forex, crypto, stocks) where price swings create clear envelope breakouts.
Adjust input parameters to match your trading style (e.g., shorter RSI period for scalping, wider bands for swing trading).
Always backtest and validate signals in your specific market and timeframe before trading.
Multi Timeframe ATR, CCI & RSIMulti Timeframe ATR, CCI & RSI (MTF IND)
This indicator displays ATR, CCI, and RSI values from a custom selected timeframe in a clean table overlay.
It helps monitor volatility and momentum from higher/lower timeframes directly on your current chart.
Features:
• Select custom timeframe for all indicators (e.g., 1D, 1W, 65m, etc.)
• ATR with selectable smoothing type (RMA, SMA, EMA, WMA)
• CCI & RSI with trend arrows (▲ rising, ▼ falling, ▬ neutral)
• Compact summary table
Trend-Following VWAP + Keltner scalping This indicator is designed for lower timeframes like 1m or 5m.
VWAP (Volume Weighted Average Price):
Green when price is above → bullish bias
Red when price is below → bearish bias
Keltner Channels:
Upper band = potential resistance or breakout zone
Lower band = potential support or breakdown zone
Middle line (basis) = dynamic trend support/resistance (EMA-based)
🟢 Bullish Setup (Buy Scalps):
Price is above VWAP (VWAP is green) → Market is bullish
Price pulls back to Keltner basis or lower band
Look for bullish price action (e.g., engulfing candle, pin bar)
Enter long near the lower band or midline
Target: Upper band or previous high
Stop Loss: Just below the lower band or recent swing low
🔴 Bearish Setup (Sell Scalps):
Price is below VWAP (VWAP is red) → Market is bearish
Price pulls back to Keltner basis or upper band
Look for bearish price action (e.g., bearish engulfing)
Enter short near upper band or midline
Target: Lower band or previous low
Stop Loss: Just above the upper band or recent swing high
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RSI - 5UP Overview
The "RSI - 5UP" indicator is a versatile tool that enhances the traditional Relative Strength Index (RSI) by adding smoothing options, Bollinger Bands, and divergence detection. It provides a clear visual representation of RSI levels with customizable bands and optional moving averages, helping traders identify overbought/oversold conditions and potential trend reversals through divergence signals.
Features
Customizable RSI: Adjust the RSI length and source to fit your trading style.
Overbought/Oversold Bands: Visualizes RSI levels with intuitive color-coded bands (red for overbought at 70, white for neutral at 50, green for oversold at 30).
Smoothing Options: Apply various types of moving averages (SMA, EMA, SMMA, WMA, VWMA) to the RSI, with optional Bollinger Bands for volatility analysis.
Divergence Detection: Identifies regular bullish and bearish divergences, with visual labels ("Bull" for bullish, "Bear" for bearish) and alerts.
G radient Fills: Highlights overbought and oversold zones with gradient fills (green for overbought, red for oversold).
How to Use
1. Add to Chart: Apply the "RSI - 5UP" indicator to any chart. It works well on timeframes from 5 minutes to daily.
2. Configure Settings:
RSI Settings:
RSI Length: Adjust the period for RSI calculation (default: 14).
Source: Choose the price source for RSI (default: close).
Calculate Divergence: Enable to detect bullish/bearish divergences (default: disabled).
Smoothing:
Type: Select the type of moving average to smooth the RSI ("None", "SMA", "SMA + Bollinger Bands", "EMA", "SMMA (RMA)", "WMA", "VWMA"; default: "SMA").
Length: Set the period for the moving average (default: 14).
BB StdDev: If "SMA + Bollinger Bands" is selected, adjust the standard deviation multiplier for the bands (default: 2.0).
3.Interpret the Indicator:
RSI Levels: The RSI line (purple) oscillates between 0 and 100. Levels above 70 (red band) indicate overbought conditions, while levels below 30 (green band) indicate oversold conditions. The 50 level (white band) is neutral.
Gradient Fills: The background gradients (green above 70, red below 30) highlight overbought and oversold zones for quick reference.
Moving Average (MA): If enabled, a yellow MA line smooths the RSI. If "SMA + Bollinger Bands" is selected, green bands appear around the MA to show volatility.
Divergences: If "Calculate Divergence" is enabled, look for "Bull" (green label) and "Bear" (red label) signals:
Bullish Divergence: Indicates a potential upward reversal when the price makes a lower low, but the RSI makes a higher low.
Bearish Divergence: Indicates a potential downward reversal when the price makes a higher high, but the RSI makes a lower high.
4. Set Alerts:
Use the "Regular Bullish Divergence" and "Regular Bearish Divergence" alert conditions to be notified when a divergence is detected.
Notes
The indicator does not provide direct buy/sell signals. Use the RSI levels, moving averages, and divergence signals as part of a broader trading strategy.
Divergence detection requires the "Calculate Divergence" option to be enabled and may not work on all timeframes or assets due to market noise.
The Bollinger Bands are only visible when "SMA + Bollinger Bands" is selected as the smoothing type.
Credits
Developed by Marrulk. Enjoy trading with RSI - 5UP! 🚀
volatilityThis indicator indicates whether volatility is sufficient for trading. It works on time frames from 1 minute to 2 hours. The redder the indicator, the less volatility there is, and the greener the indicator, the more volatility there is.
