Stochastic Overlay [NLR]If you've ever traded with the Stochastic oscillator, you probably love its ability to gauge momentum and overbought/oversold conditions. However, one common frustration is interpreting its movements alongside the actual price chart. The oscillator, plotted separately, can feel disconnected from price action, forcing traders to constantly glance back and forth. That’s exactly the problem I wanted to solve with this indicator.
The Solution: Stochastic Overlay
This indicator takes the familiar Stochastic oscillator and integrates it directly onto the price chart. Instead of struggling to correlate Stochastic signals with price movements, you now see the levels overlaid on the main chart, bringing momentum analysis into a more intuitive space.
What is the Stochastic Oscillator? (For the Newbies)
The Stochastic oscillator is a momentum-based indicator that measures the closing price relative to the high-low range over a specified period. It fluctuates between 0 and 100, helping traders identify potential reversals when the market is overbought (above 80) or oversold (below 20). The two key components are:
%K (fast-moving line)
%D (a smoothed moving average of %K)
Technical Details of the Overlay
The indicator adjusts the traditional Stochastic calculation by multiplying the timeframe (HTF multiplier), allowing traders to view higher-timeframe Stochastics. Set HTF Multiplier to 1 to see current timeframe Stochastics
It plots horizontal reference lines representing 0%, 20%, 40%, 50%, 60%, 80%, and 100% levels, giving a visual framework of price movement.
Color-coded fills help differentiate bullish and bearish zones—making it easy to spot potential turning points.
Why Do the %K & %D Lines Look “Crooked”?
Normally, the %K and %D lines range between 0 and 100, but in this overlay, they are scaled to fit the current price gap (the difference between the highest and lowest price in the selected period). This means their movement aligns more closely with price action, but it may appear distorted compared to a standard Stochastic oscillator.
For clarity, you can enable the visibility of %K and %D (Show %K %D option), allowing the scaled Stochastic values to be plotted within the price range.
Why Use This Overlay?
Better price interpretation: Instead of staring at a separate oscillator panel, you see momentum levels right where the price action unfolds.
Higher-timeframe integration: Adjusting the multiplier allows you to track the Stochastic behavior of larger timeframes without switching charts.
Clear visual cues: The colored fills and midpoint signals enhance readability for momentum shifts.
This tool transforms the way traders engage with Stochastic indicators, making momentum analysis more intuitive and efficient. Try it out, and see how your interpretation of price and momentum improves!
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RSI Trigger Count (30 Days) - Both SidesRSI Dual Trigger Counter (30 Days)
This indicator tracks both oversold ( crossunder ) and overbought ( crossover ) RSI events on a 30-minute chart, featuring:
Dual-Mode Selector:
Counts either RSI < 30 (oversold) or RSI > 70 (overbought) crossings
Toggle between modes via input menu
30-Day Rolling Count:
Displays total triggers in the last 30 days (e.g., "Times triggered (Oversold) ① 19")
Visual Alerts:
Red triangles ↓ for oversold crossunders
Green triangles ↑ for overbought crossovers
Customizable:
Adjustable RSI length (2-100) and thresholds (1-100)
Works on any timeframe (auto-scales calculations)
Purpose: Identifies frequent reversal signals for both buying dips (oversold) and selling rallies (overbought).
Z-Score Normalized Volatility IndicesVolatility is one of the most important measures in financial markets, reflecting the extent of variation in asset prices over time. It is commonly viewed as a risk indicator, with higher volatility signifying greater uncertainty and potential for price swings, which can affect investment decisions. Understanding volatility and its dynamics is crucial for risk management and forecasting in both traditional and alternative asset classes.
Z-Score Normalization in Volatility Analysis
The Z-score is a statistical tool that quantifies how many standard deviations a given data point is from the mean of the dataset. It is calculated as:
Z = \frac{X - \mu}{\sigma}
Where X is the value of the data point, \mu is the mean of the dataset, and \sigma is the standard deviation of the dataset. In the context of volatility indices, the Z-score allows for the normalization of these values, enabling their comparison regardless of the original scale. This is particularly useful when analyzing volatility across multiple assets or asset classes.
This script utilizes the Z-score to normalize various volatility indices:
1. VIX (CBOE Volatility Index): A widely used indicator that measures the implied volatility of S&P 500 options. It is considered a barometer of market fear and uncertainty (Whaley, 2000).
2. VIX3M: Represents the 3-month implied volatility of the S&P 500 options, providing insight into medium-term volatility expectations.
3. VIX9D: The implied volatility for a 9-day S&P 500 options contract, which reflects short-term volatility expectations.
4. VVIX: The volatility of the VIX itself, which measures the uncertainty in the expectations of future volatility.
5. VXN: The Nasdaq-100 volatility index, representing implied volatility in the Nasdaq-100 options.
6. RVX: The Russell 2000 volatility index, tracking the implied volatility of options on the Russell 2000 Index.
7. VXD: Volatility for the Dow Jones Industrial Average.
8. MOVE: The implied volatility index for U.S. Treasury bonds, offering insight into expectations for interest rate volatility.
9. BVIX: Volatility of Bitcoin options, a useful indicator for understanding the risk in the cryptocurrency market.
10. GVZ: Volatility index for gold futures, reflecting the risk perception of gold prices.
11. OVX: Measures implied volatility for crude oil futures.
Volatility Clustering and Z-Score
The concept of volatility clustering—where high volatility tends to be followed by more high volatility—is well documented in financial literature. This phenomenon is fundamental in volatility modeling and highlights the persistence of periods of heightened market uncertainty (Bollerslev, 1986).
Moreover, studies by Andersen et al. (2012) explore how implied volatility indices, like the VIX, serve as predictors for future realized volatility, underlining the relationship between expected volatility and actual market behavior. The Z-score normalization process helps in making volatility data comparable across different asset classes, enabling more effective decision-making in volatility-based strategies.
Applications in Trading and Risk Management
By using Z-score normalization, traders can more easily assess deviations from the mean in volatility, helping to identify periods when volatility is unusually high or low. This can be used to adjust risk exposure or to implement volatility-based trading strategies, such as mean reversion strategies. Research suggests that volatility mean-reversion is a reliable pattern that can be exploited for profit (Christensen & Prabhala, 1998).
References:
• Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2012). Realized volatility and correlation dynamics: A long-run approach. Journal of Financial Economics, 104(3), 385-406.
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
• Christensen, B. J., & Prabhala, N. R. (1998). The relation between implied and realized volatility. Journal of Financial Economics, 50(2), 125-150.
• Whaley, R. E. (2000). Derivatives on market volatility and the VIX index. Journal of Derivatives, 8(1), 71-84.
RiskCalc FX & GoldRiskCalc FX & Gold is a multi-market position sizing tool designed to help you manage risk quickly and accurately. With this script, simply enter your account capital, the percentage of risk you wish to take, and your stop in ticks. Depending on the selected market—Forex or XAUUSD—the script automatically adjusts its calculations:
Forex: Assumes 1 lot equals 100,000 units.
XAUUSD: Assumes 1 lot equals 100 ounces.
The script calculates your risk in dollars and, using a fixed value of 1 USD per tick per lot, determines the ideal position size in both lots and total contracts. Results are displayed in a clear, centralized table at the top of the chart for real-time decision-making.
Perfect for traders operating across multiple markets who need an automated and consistent approach to risk management.
Oracle Prediction Futur
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Indicator Description: Oracle Prediction Futur
The Oracle Prediction Futur is a sophisticated technical indicator designed for traders and analysts looking to gain insights into market trends through the analysis of price movements. This Pine Script™ code integrates innovative elements to enhance the trading experience and is governed by the Mozilla Public License 2.0.
Key Features:
Normalization of Closing Prices:
The indicator normalizes closing prices over a defined lookback period (100 periods) to provide a percentage-based representation of the current price relative to its historical range. This helps in identifying potential price extremes.
Peak and Trough Detection:
It identifies and plots peak tops and bottom troughs based on normalized closing values. Peak tops are marked with vibrant magenta circles, while peak bottoms are indicated by soothing cyan circles, helping traders visually spot significant turning points in the price action.
Dynamic Background Gradient:
The indicator features a visually appealing gradient background that represents market sentiment. The background color transitions between bear and bull colors based on the position of the normalized close within the 0-100 range. This provides an immediate visual cue about the strength or weakness of the market.
Horizontal Reference Lines:
The indicator includes horizontal lines at key levels (9.51 and 92.5) for quick reference, which can help to gauge areas of potential support or resistance.
User-Friendly Visuals:
The combination of background colors, dynamic plots, and clear labeling offers a user-friendly visual representation, making it easier to interpret market conditions at a glance.
Overlay Options:
As an overlay-free indicator, it maintains clarity on the price chart while providing insightful trends and forecasts.
Practical Application:
Traders can utilize the Oracle Prediction Futur indicator to identify potential entry and exit points in their trading strategies. By observing the peaks, troughs, and background color shifts, users can better understand market momentum and price action.
How to Use:
Deploy this indicator on your trading platform, and analyze the peaks and troughs along with the normalized close line and background gradient to inform your trading decisions. Look for alignment between price action and the signaling provided by the indicator for optimized trading results.
Multi-TF Support LevelsThe Multi-TF Support Levels indicator identifies and displays key support levels based on swing lows across three user-selected timeframes.
How it works:
Input Parameters:
Lookback Period (100) — historical depth to search for swing lows.
Timeframe 1-3 (15, 45, 240) — three timeframes (e.g., 15min, 45min, 4hr).
Logic:
For each timeframe, a swing low is detected: the lowest price within the lookback period that is also lower than the two preceding candles.
Support levels update dynamically when new swing lows are formed.
The most recent levels are plotted as horizontal cross marks (blue, red, green for each timeframe).
Purpose: Visualize significant support zones from multiple timeframes to identify confluent areas for trading decisions.
Индикатор Multi-TF Support Levels (Мультитаймфреймовые уровни поддержки) определяет и отображает ключевые уровни поддержки на основе минимумов свингов (swing lows) на трёх выбранных таймфреймах.
Как работает:
Входные параметры:
Lookback Period (100) — глубина анализа для поиска минимумов.
Timeframe 1-3 (15, 45, 240) — три таймфрейма (например, 15 минут, 45 минут, 4 часа).
Логика:
Для каждого таймфрейма определяется свинг-минимум: цена, которая является самой низкой за период lookback и ниже двух предыдущих свечей.
Уровни поддержки обновляются при появлении новых свинг-минимумов.
Последние актуальные уровни отображаются на графике в виде горизонтальных линий-крестиков (синий, красный, зелёный для каждого таймфрейма).
Цель: Визуализировать значимые уровни поддержки с разных таймфреймов для поиска зон "конфлюэнса".
Multi-Fibonacci Trend Average[FibonacciFlux]Multi-Fibonacci Trend Average (MFTA): An Institutional-Grade Trend Confluence Indicator for Discerning Market Participants
My original indicator/Strategy:
Engineered for the sophisticated demands of institutional and advanced traders, the Multi-Fibonacci Trend Average (MFTA) indicator represents a paradigm shift in technical analysis. This meticulously crafted tool is designed to furnish high-definition trend signals within the complexities of modern financial markets. Anchored in the rigorous principles of Fibonacci ratios and augmented by advanced averaging methodologies, MFTA delivers a granular perspective on trend dynamics. Its integration of Multi-Timeframe (MTF) filters provides unparalleled signal robustness, empowering strategic decision-making with a heightened degree of confidence.
MFTA indicator on BTCUSDT 15min chart with 1min RSI and MACD filters enabled. Note the refined signal generation with reduced noise.
MFTA indicator on BTCUSDT 15min chart without MTF filters. While capturing more potential trading opportunities, it also generates a higher frequency of signals, including potential false positives.
Core Innovation: Proprietary Fibonacci-Enhanced Supertrend Averaging Engine
The MFTA indicator’s core innovation lies in its proprietary implementation of Supertrend analysis, strategically fortified by Fibonacci ratios to construct a truly dynamic volatility envelope. Departing from conventional Supertrend methodologies, MFTA autonomously computes not one, but three distinct Supertrend lines. Each of these lines is uniquely parameterized by a specific Fibonacci factor: 0.618 (Weak), 1.618 (Medium/Golden Ratio), and 2.618 (Strong/Extended Fibonacci).
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval=0.01, step=0.01, tooltip='Factor 1 (Weak/Fibonacci)', group="Fibonacci Supertrend")
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval=0.01, step=0.01, tooltip='Factor 2 (Medium/Golden Ratio)', group="Fibonacci Supertrend")
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval=0.01, step=0.01, tooltip='Factor 3 (Strong/Extended Fib)', group="Fibonacci Supertrend")
This multi-faceted architecture adeptly captures a spectrum of market volatility sensitivities, ensuring a comprehensive assessment of prevailing conditions. Subsequently, the indicator algorithmically synthesizes these disparate Supertrend lines through arithmetic averaging. To achieve optimal signal fidelity and mitigate inherent market noise, this composite average is further refined utilizing an Exponential Moving Average (EMA).
// Calculate average of the three supertends and a smoothed version
superlength = input.int(21, 'Smoothing Length', tooltip='Smoothing Length for Average Supertrend', group="Fibonacci Supertrend")
average_trend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_trend = ta.ema(average_trend, superlength)
The resultant ‘Smoothed Trend’ line emerges as a remarkably responsive yet stable trend demarcation, offering demonstrably superior clarity and precision compared to singular Supertrend implementations, particularly within the turbulent dynamics of high-volatility markets.
Elevated Signal Confluence: Integrated Multi-Timeframe (MTF) Validation Suite
MFTA transcends the limitations of conventional trend indicators by incorporating an advanced suite of three independent MTF filters: RSI, MACD, and Volume. These filters function as sophisticated validation protocols, rigorously ensuring that only signals exhibiting a confluence of high-probability factors are brought to the forefront.
1. Granular Lower Timeframe RSI Momentum Filter
The Relative Strength Index (RSI) filter, computed from a user-defined lower timeframe, furnishes critical momentum-based signal validation. By meticulously monitoring RSI dynamics on an accelerated timeframe, traders gain the capacity to evaluate underlying momentum strength with precision, prior to committing to signal execution on the primary chart timeframe.
// --- Lower Timeframe RSI Filter ---
ltf_rsi_filter_enable = input.bool(false, title="Enable RSI Filter", group="MTF Filters", tooltip="Use RSI from lower timeframe as a filter")
ltf_rsi_timeframe = input.timeframe("1", title="RSI Timeframe", group="MTF Filters", tooltip="Timeframe for RSI calculation")
ltf_rsi_length = input.int(14, title="RSI Length", minval=1, group="MTF Filters", tooltip="Length for RSI calculation")
ltf_rsi_threshold = input.int(30, title="RSI Threshold", minval=0, maxval=100, group="MTF Filters", tooltip="RSI value threshold for filtering signals")
2. Convergent Lower Timeframe MACD Trend-Momentum Filter
The Moving Average Convergence Divergence (MACD) filter, also calculated on a lower timeframe basis, introduces a critical layer of trend-momentum convergence confirmation. The bullish signal configuration rigorously mandates that the MACD line be definitively positioned above the Signal line on the designated lower timeframe. This stringent condition ensures a robust indication of converging momentum that aligns synergistically with the prevailing trend identified on the primary timeframe.
// --- Lower Timeframe MACD Filter ---
ltf_macd_filter_enable = input.bool(false, title="Enable MACD Filter", group="MTF Filters", tooltip="Use MACD from lower timeframe as a filter")
ltf_macd_timeframe = input.timeframe("1", title="MACD Timeframe", group="MTF Filters", tooltip="Timeframe for MACD calculation")
ltf_macd_fast_length = input.int(12, title="MACD Fast Length", minval=1, group="MTF Filters", tooltip="Fast EMA length for MACD")
ltf_macd_slow_length = input.int(26, title="MACD Slow Length", minval=1, group="MTF Filters", tooltip="Slow EMA length for MACD")
ltf_macd_signal_length = input.int(9, title="MACD Signal Length", minval=1, group="MTF Filters", tooltip="Signal SMA length for MACD")
3. Definitive Volume Confirmation Filter
The Volume Filter functions as an indispensable arbiter of trade conviction. By establishing a dynamic volume threshold, defined as a percentage relative to the average volume over a user-specified lookback period, traders can effectively ensure that all generated signals are rigorously validated by demonstrably increased trading activity. This pivotal validation step signifies robust market participation, substantially diminishing the potential for spurious or false breakout signals.
// --- Volume Filter ---
volume_filter_enable = input.bool(false, title="Enable Volume Filter", group="MTF Filters", tooltip="Use volume level as a filter")
volume_threshold_percent = input.int(title="Volume Threshold (%)", defval=150, minval=100, group="MTF Filters", tooltip="Minimum volume percentage compared to average volume to allow signal (100% = average)")
These meticulously engineered filters operate in synergistic confluence, requiring all enabled filters to definitively satisfy their pre-defined conditions before a Buy or Sell signal is generated. This stringent multi-layered validation process drastically minimizes the incidence of false positive signals, thereby significantly enhancing entry precision and overall signal reliability.
Intuitive Visual Architecture & Actionable Intelligence
MFTA provides a demonstrably intuitive and visually rich charting environment, meticulously delineating trend direction and momentum through precisely color-coded plots:
Average Supertrend: Thin line, green/red for uptrend/downtrend, immediate directional bias.
Smoothed Supertrend: Bold line, teal/purple for uptrend/downtrend, cleaner, institutionally robust trend.
Dynamic Trend Fill: Green/red fill between Supertrends quantifies trend strength and momentum.
Adaptive Background Coloring: Light green/red background mirrors Smoothed Supertrend direction, holistic trend perspective.
Precision Buy/Sell Signals: ‘BUY’/‘SELL’ labels appear on chart when trend touch and MTF filter confluence are satisfied, facilitating high-conviction trade action.
MFTA indicator applied to BTCUSDT 4-hour chart, showcasing its effectiveness on higher timeframes. The Smoothed Length parameter is increased to 200 for enhanced smoothness on this timeframe, coupled with 1min RSI and Volume filters for signal refinement. This illustrates the indicator's adaptability across different timeframes and market conditions.
Strategic Applications for Institutional Mandates
MFTA’s sophisticated design provides distinct advantages for advanced trading operations and institutional investment mandates. Key strategic applications include:
High-Probability Trend Identification: Fibonacci-averaged Supertrend with MTF filters robustly identifies high-probability trend continuations and reversals, enhancing alpha generation.
Precision Entry/Exit Signals: Volume and momentum-filtered signals enable institutional-grade precision for optimized risk-adjusted returns.
Algorithmic Trading Integration: Clear signal logic facilitates seamless integration into automated trading systems for scalable strategy deployment.
Multi-Asset/Timeframe Versatility: Adaptable parameters ensure applicability across diverse asset classes and timeframes, catering to varied trading mandates.
Enhanced Risk Management: Superior signal fidelity from MTF filters inherently reduces false signals, supporting robust risk management protocols.
Granular Customization and Parameterized Control
MFTA offers unparalleled customization, empowering users to fine-tune parameters for precise alignment with specific trading styles and market conditions. Key adjustable parameters include:
Fibonacci Factors: Adjust Supertrend sensitivity to volatility regimes.
ATR Length: Control volatility responsiveness in Supertrend calculations.
Smoothing Length: Refine Smoothed Trend line responsiveness and noise reduction.
MTF Filter Parameters: Independently configure timeframes, lookback periods, and thresholds for RSI, MACD, and Volume filters for optimal signal filtering.
Disclaimer
MFTA is meticulously engineered for high-quality trend signals; however, no indicator guarantees profit. Market conditions are unpredictable, and trading involves substantial risk. Rigorous backtesting and forward testing across diverse datasets, alongside a comprehensive understanding of the indicator's logic, are essential before live deployment. Past performance is not indicative of future results. MFTA is for informational and analytical purposes only and is not financial or investment advice.
Optimized WPR Strategy with Filters (Debug)Identifying Market Trends:
The 200-period EMA is used to determine the short-term trend of the market.
When the price is above the 200-period EMA, it suggests a potential bullish market and an uptrend, and the strategy will only look for buying opportunities.
When the price is below the 200-period EMA, it suggests a potential bearish market and a downtrend, and the strategy will only look for selling opportunities.
When the 200-period EMA intersects with the price, it indicates that the market may be in a directionless consolidation phase.
Identifying Potential Reversal Points:
The strategy employs two Williams %R (WPR) indicators: one with a 9-period (fast WPR) and another with a 28-period (slow WPR).
WPR is a momentum indicator used to identify overbought and oversold conditions in the market. Its value oscillates between -100 and 0, with values near -100 indicating oversold conditions and values near 0 indicating overbought conditions.
In an uptrend (when the price is above the 200 EMA), the strategy seeks buying opportunities when both WPR indicators cross above -80 (the oversold zone) from below. This is considered a bullish signal, suggesting the market may be about to rebound. Sell signals are ignored at this time.
In a downtrend (when the price is below the 200 EMA), the strategy seeks selling opportunities when both WPR indicators cross below -20 (the overbought zone) from above. This is considered a bearish signal, suggesting the market may be about to reverse downward. Buy signals are ignored at this time.
Summary:
In summary, this strategy first uses the 200-period EMA to determine the overall trend direction of the market. Then, within the confirmed trend direction, it utilizes the simultaneous crossing of the overbought or oversold zones by the dual WPR indicators to identify potential reversal points as entry signals for trading. The strategy emphasizes that trading signals are only valid when both WPR indicators meet the conditions.
TR FVG & Swing High Low FinderTR FVG & Swing Level Finder
Overview:
The TR FVG & Swing Level Finder is a powerful Pine Script indicator designed for traders who want to identify Fair Value Gaps (FVGs) and Swing Highs/Lows on their charts. This indicator combines two essential technical analysis tools into one, helping traders spot potential areas of support, resistance, and trend reversals. FVGs are price gaps that often act as areas of interest for price to return to, while swing highs and lows help identify key turning points in the market. The indicator is highly customizable, allowing users to adjust colors, limits, and display options to suit their trading style.
Key Features:
1: Fair Value Gap (FVG) Detection:
- Identifies Bullish FVGs: Occur when the high of two candles ago is lower than the low of the current candle, indicating a potential upward price movement.
- Identifies Bearish FVGs: Occur when the low of two candles ago is higher than the high of the current candle, indicating a potential downward price movement.
- Displays FVGs as colored boxes on the chart, with customizable border and fill colors based on the timeframe.
- Labels each FVG box with the corresponding timeframe (e.g., "1m FVG", "1h FVG", "Daily FVG").
2: Swing High and Swing Low Detection:
- Detects Swing Highs: A 3-candle pattern where the middle candle's high is higher than the highs of the candles on either side.
- Detects Swing Lows: A 3-candle pattern where the middle candle's low is lower than the lows of the candles on either side.
- Draws a solid black line with 50% opacity at each swing high and low, extending 5 bars to the right for better visibility.
- Adds a small Swing High or Swing Low label at the right end of each line, colored according to user-defined settings.
3: Timeframe-Specific FVG Visualization:
- FVGs are color-coded based on the chart's timeframe, making it easy to distinguish between FVGs on different timeframes.
- Each timeframe has its own fill color for bullish and bearish FVGs, with adjustable transparency for better chart clarity.
- A dashed black line is drawn in the middle of each FVG box to highlight the midpoint of the gap.
4: Customizable Display Options:
- FVG Limit: Control the maximum number of FVGs displayed on the chart (from 1 to 20).
- Extend Options for FVG Boxes:
- "None": FVG boxes extend only 2 bars to the right.
- "Limited": FVG boxes extend a user-defined number of candles to the right (1 to 100 candles).
- "Default": FVG boxes extend 3 bars to the right of the current bar.
- Color Customization:
- Set border colors for bullish and bearish FVGs.
- Adjust fill colors for FVGs on different timeframes (1m, 5m, 15m, 30m, 1h, 4h, Daily, Weekly, Monthly).
- Customize the colors of swing high and swing low labels.
5: Performance Optimization:
- The indicator only plots FVGs and swings on the last confirmed bar (barstate.islastconfirmedhistory), ensuring efficient performance and reducing chart clutter.
- Limits the number of displayed FVGs and swings to the user-defined fvgLimit, keeping the chart clean and focused on the most recent price action.
6: Inputs and Customization:
- Number of FVGs to Show (fvgLimit): Set the maximum number of FVGs and swings to display (default: 3, range: 1 to 20).
- Bullish FVG Border Color (bullishColor): Choose the border color for bullish FVGs (default: green).
- Bearish FVG Border Color (bearishColor): Choose the border color for bearish FVGs (default: red).
- Swing High Color (swingHighColor): Set the color for swing high labels (default: blue).
- Swing Low Color (swingLowColor): Set the color for swing low labels (default: purple).
- Extend Options:
- Extend Option (extendOption): Choose how far FVG boxes extend to the right ("None", "Limited", or "Default"; default: "Default").
- Extend Candles (extendCandles): If "Limited" is selected, specify the number of candles to extend FVG boxes (default: 8, range: 1 to 100).
- Timeframe-Specific Fill Colors:
- Customize fill colors for bullish and bearish FVGs on various timeframes (1m, 5m, 15m, 30m, 1h, 4h, Daily, Weekly, Monthly).
- Each fill color has a default transparency (e.g., 93% for most timeframes, 90% for 30m), which can be adjusted as needed.
How to Use:
1: Add the Indicator to Your Chart:
- Open TradingView, go to the Pine Editor, and paste the script.
- Click "Add to Chart" to apply the indicator to your current chart.
2: Adjust Settings:
- Open the indicator settings by clicking the gear icon next to the indicator name on your chart.
- Modify the inputs to suit your preferences:
- Set the number of FVGs and swings to display.
- Choose your preferred colors for FVGs and swings.
- Adjust the extend options for FVG boxes.
3: Interpret the Indicator:
- FVG Boxes: Look for colored boxes on the chart, which represent Fair Value Gaps. Bullish FVGs (green borders by default) suggest potential buying opportunities, while bearish FVGs (red borders by default) suggest potential selling opportunities. The label inside each box indicates the timeframe of the FVG.
- Swing Highs and Lows: Identify key turning points with solid black lines (50% opacity) at swing highs and lows. Each line extends 5 bars to the right, with an "SH" (Swing High) or "SL" (Swing Low) label at the end. Swing highs can act as resistance levels, while swing lows can act as support levels.
4: Combine with Your Strategy:
- Use FVGs to identify areas where price might return to fill the gap, often acting as support or resistance.
- Use swing highs and lows to spot potential trend reversals or to set stop-loss and take-profit levels.
- Combine the indicator with other tools (e.g., trendlines, moving averages) for a more comprehensive trading strategy.
Notes:
- The indicator works on all timeframes, but the appearance of FVGs and swings will vary depending on the chart's timeframe.
- For best results, use the indicator on a clean chart to avoid visual clutter, especially if you increase the fvgLimit.
- The swing high/low lines are drawn with 50% opacity to ensure they don’t overpower other chart elements, but they are still clearly visible.
Author’s Note:
This script was developed to help traders identify key price levels with ease. I hope it adds value to your trading! If you have any feedback or suggestions for improvement, feel free to leave a comment. Happy trading!
[blackcat] L2 Risk Assessment for Trend StrengthOVERVIEW
This script provides an advanced technical analysis tool combining real-time **Risk Assessment** and **Trend Strength Indicators**, displayed independently from price charts. It calculates multi-layered metrics using weighted algorithms and visualizes risk thresholds via dynamically-colored zones.
FEATURES
- Dual ** RISKA ** calculations ( RSVA1 / RSVA2 ) across 9-period cycles
- Smoothed outputs via proprietary **boldWeighted Moving Averages (WMAs)**
- Dynamic **Current Safety Level Plot** (fuchsia area-style visualization)
- Color-coded **Trend Strength Line** reacting to real-time shifts across four danger/optimism tiers
- Automated threshold validation mechanism using last-valid-value logic
- Visually distinct risk zones (blue/green/yellow/red/fuchsia) filling background areas
HOW TO USE
1. Add to your chart to observe two core elements:
- Area plot showing current risk tolerance buffer
- Thick line indicating momentum strength direction
2. Interpret values relative to vertical thresholds:
• Above 100 = Ultra-safe zone (light blue)
• 80–100 = Safe zone (green)
• 20–80 = Moderate/high-risk zones (yellow)
• Below 20 = Extreme risk (red)
3. Monitor trend confidence shifts using the colored line:
> **Blue**: Strong bullish momentum (>80%)
> **Green/Yellow**: Neutral/moderate trends (50%-80%)
> **Red**: Bearish extremes (<20%)
LIMITATIONS
• Relies heavily on prior 33-period low and 21-period high volatility patterns
• WMA smoothing introduces minor backward-looking bias
• Not optimized for intraday timeframe sub-hourly usage
• Excessive weighting parameters may amplify noise during sideways markets
Dynamic CAGR LineIndicator: Dynamic CAGR Line
Overview
This Pine Script (version 6) creates a custom indicator called "Dynamic CAGR Moving Line," designed to calculate and display the Compound Annual Growth Rate (CAGR) in percentage terms for a financial instrument, such as a stock or cryptocurrency, based on a user-defined lookback period (default: 5 years). Unlike traditional overlays that plot directly on the price chart, this indicator appears in a separate pane below the chart, providing a clear visual of how the CAGR evolves over time with each new candle.
Purpose
The indicator helps traders and investors analyze the annualized growth rate of an asset’s price over a specified historical period. By plotting the CAGR as a percentage in a separate pane, users can easily track how the growth rate changes as new price data is added, offering insights into long-term performance trends without cluttering the price chart.
How It Works
User Input:
The script begins with an input parameter, lookback_years, allowing users to define the number of years (e.g., 5) to look back for the CAGR calculation. This is a floating-point value with a minimum of 1 and a step of 0.5, adjustable via the indicator’s settings in TradingView.
Timeframe Conversion:
Assuming a daily chart, the script converts the lookback years into a number of bars using bars_per_year = 252 (the average number of trading days in a year). The total lookback period in bars is calculated as lookback_bars = math.round(lookback_years * bars_per_year). For example, 5 years equals approximately 1260 bars.
Price Data:
For each candle, the start_price is fetched from the closing price lookback_bars ago (e.g., the close price from 5 years prior), using close .
The end_price is the current candle’s closing price, accessed via close.
CAGR Calculation:
The total return is computed as (end_price - start_price) / start_price, measuring the percentage change from the start price to the current price.
To avoid division-by-zero errors, a conditional check ensures start_price != 0; if it is, the return defaults to 0.
The CAGR is then calculated using the formula: math.pow(1 + total_return, 1 / lookback_years) - 1, which annualizes the total return over the lookback period.
The result is converted to a percentage by multiplying by 100 (cagr_percent = cagr * 100).
Plotting:
The CAGR percentage is plotted as a blue line in a separate pane using plot(). The line only appears after enough data exists (bar_index >= lookback_bars), otherwise it plots na (not available).
A label is added for each candle, displaying the current CAGR percentage (e.g., "CAGR: 5.23%") near the plotted value, styled with a blue background and white text.
Usage
Chart Setup: Apply the indicator to a daily chart with sufficient historical data (e.g., more than 5 years for the default setting). It’s designed for daily timeframes but can be adapted for others by adjusting bars_per_year (e.g., 52 for weekly).
Interpretation: A positive CAGR (e.g., 5%) indicates annualized growth, while a negative value (e.g., -2%) shows an annualized decline. A flat line at 0% suggests no net change over the lookback period.
Customization: Adjust lookback_years in the settings to analyze different periods (e.g., 3 or 10 years).
Notes
Ensure your chart has enough data to cover the lookback period, or the line won’t appear until sufficient bars are available.
For debugging, you can temporarily plot start_price and end_price on the main chart to verify the calculation inputs.
Schaff Trend Cycle (STC)The STC (Schaff Trend Cycle) indicator is a momentum oscillator that combines elements of MACD and stochastic indicators to identify market cycles and potential trend reversals.
Key features of the STC indicator:
Oscillates between 0 and 100, similar to a stochastic oscillator
Values above 75 generally indicate overbought conditions
Values below 25 generally indicate oversold conditions
Signal line crossovers (above 75 or below 25) can suggest potential entry/exit points
Faster and more responsive than traditional MACD
Designed to filter out market noise and identify cyclical trends
Traders typically use the STC indicator to:
Identify potential trend reversals
Confirm existing trends
Generate buy/sell signals when combined with other technical indicators
Filter out false signals in choppy market conditions
This STC implementation includes multiple smoothing options that act as filters:
None: Raw STC values without additional smoothing, which provides the most responsive but potentially noisier signals.
EMA Smoothing: Applies a 3-period Exponential Moving Average to reduce noise while maintaining reasonable responsiveness (default).
Sigmoid Smoothing: Transforms the STC values using a sigmoid (S-curve) function, creating more gradual transitions between signals and potentially reducing whipsaw trades.
Digital (Schmitt Trigger) Smoothing: Creates a binary output (0 or 100) with built-in hysteresis to prevent rapid switching.
The STC indicator uses dynamic color coding to visually represent momentum:
Green: When the STC value is above its 5-period EMA, indicating positive momentum
Red: When the STC value is below its 5-period EMA, indicating negative momentum
The neutral zone (25-75) is highlighted with a light gray fill to clearly distinguish between normal and extreme readings.
Alerts:
Bullish Signal Alert:
The STC has been falling
It bottoms below the 25 level
It begins to rise again
This pattern helps confirm potential uptrend starts with higher reliability.
Bearish Signal Alert:
The STC has been rising
It peaks above the 75 level
It begins to decline
This pattern helps identify potential downtrend starts.
Nebula Volatility and Compression Radar (TechnoBlooms)This dynamic indicator spots volatility compression and expansion zones, highlighting breakout opportunities with precision. Featuring vibrant Bollinger Bands, trend-colored candles and real-time signals, Nebula Volatility and Compression Radar (NVCR) is your radar for navigating price moves.
Key Features:-
1. Gradient Bollinger Bands - Visually stunning bands with gradient fills for clear price boundaries.
The gradient filling is coded simply so that even beginners can easily understand the concept. Trader can change the gradient color according to their preference.
fill(pupBB, pbaseBB,upBB,baseBB,top_color=color.rgb(238, 236, 94), bottom_color=color.new(chart.bg_color,100),title = "fill color", display =display.all,fillgaps = true,editable = false)
fill(pbaseBB, plowBB,baseBB,lowBB,top_color=color.new(chart.bg_color,100),bottom_color=color.rgb(230, 20, 30),title = "fill color", display =display.all,fillgaps = true,editable = false)
These two lines are used for giving gradient shades. You can change the colors as per your wish to give preferred color combination.
For Example:
Another Example:
2. Customizable Settings - Adjust Bollinger Bands, ATR and trend lengths to fit your trading styles.
3. Trend Insights - Candles turn green for uptrends, red for downtrends, and gray for neutral zones.
Nebula Volatility and Compression Radar create dynamic cloud like zones that illuminate trends with clarity.
Jurik Moving Average (JMA)Overview
Jurik Moving Average (JMA) is an adaptive moving average developed by Mark Jurik, widely regarded as one of the most powerful moving averages available to traders. This implementation provides a direct Pine Script translation of the reverse-engineered JMA algorithm
What Makes JMA Special
Unlike traditional moving averages, JMA adapts to market volatility in real-time. This "triple adaptive" approach allows JMA to:
Reduce lag significantly while maintaining exceptional smoothness
React quickly during trending markets
Filter out noise during consolidation phases
Provide clearer trend signals with fewer whipsaws
The Triple Adaptive Edge
JMA employs a three-stage smoothing process:
Preliminary smoothing via an adaptive EMA
Secondary smoothing using a Kalman filter with phase adjustment
Final smoothing through a unique Jurik adaptive filter
This approach combines with a dynamic volatility-based factor (alpha) that adapts to market conditions, making JMA superior to traditional moving averages in most situations.
Key Parameters
Period : Controls the lookback period (default: 14)
Phase : Adjusts the heaviness of the indicator (-100 to 100, default: 0)
Positive values reduce lag but may cause overshoot
Negative values increase smoothness but reduce responsiveness
Power : Smoothing factor (0.1-0.9, default 0.45)
Higher values create smoother curves
Lower values create more responsive but choppy curves
Normalized VolumeOVERVIEW
The Normalized Volume (NV) is an attempt at visualizing volume in a format that is more understandable by placing the values on a scale of 0 to 100. 0 in this case is the lowest volume candle available on the chart, and 100 being the highest. Calling a candle “high volume” can be misleading without having something to compare to. For example, in scaling the volume this way we can clearly see that a given candle had 80% of the peak volume or 20%, and gauge the validity of price moves more accurately.
FEATURES
NV by session
Allows user to filter the volume values across 4 different sessions. This can add context to the volume output, because what it high volume during London session may not be high volume relative to New York session.
Overlay plotting
When volume boxes are turned on, this will allow you to toggle how they are plotted.
Color theme
A standard color theme will color the NV based on if the respective candle closed green or red. Selecting variables will color the NV plot based on which range the value falls within.
Session inputs
Activated with the “By session?” Input. Allows user to break the day up into 4 sessions to more accurately gauge volume relative to time of day.
Show Box (X)
Toggles on chart boxes on and off.
Show historical boxes
Will plot prior occurrences of selected volume boxes, deleting them when price fully moves through them in the opposite direction of the initial candle.
Color inputs
Allows for intensive customization in how this tool appears visually.
INTERPRETATION
There are 6 pre-defined ranges that NV can fall within.
NV <= 10
Volume is insignificant
In this range, volume should not be a confirmation in your trading strategy.
NV > 10 and <= 20
Volume is low
In this range, volume should not be a confirmation in your trading strategy.
NV > 20 and <= 40
Volume is fair
In this range, volume should not be the primary confirmation in your trading strategy.
NV > 40 and <= 60
Volume is high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 60 and <= 80
Volume is very high
In this range, volume can be the primary confirmation in your trading strategy.
NV > 80
Volume is extreme
In this range, volume is likely news driven and caution should be taken. High price volatility possible.
To utilize this tool in conjunction with your current strategy, follow the range explanations above section in this section. The higher the NV value, the stronger you can feel about your directional confirmation.
If NV = 100, this means that the highest volume candle occurred up to that point on your selected timeframe. All future data points will be weighed off of this value.
LIMITATIONS
This tool will not load on tickers that do not have volume data, such as VIX.
STRATEGY
The Normalized Volume plot can be used in exactly the same way as you would normally utilize volume in your trading strategy. All we are doing is weighing the volume relative to itself.
Volume boxes can be used as targets to be filled in a similar way to commonly used “fair value gap” strategies. To utilize this strategy, I recommend selecting “Plot to Wicks” in Overlay Plotting and toggling on Show Historical Boxes.
Volume boxes can be used as areas for entry in a similar way to commonly used “order block” strategies. To utilize this strategy, I recommend selecting “Open To Close” in Overlay Plotting.
NOTES
You are able to plot an info label on right side of NV plot using the "Toggle box label" input. When a box is toggled on this label will tell you when the most recent box of that intensity occurred.
This tool is deeply visually customizable, with the ability to adjust line width for plotted boxes, all colors on both box overlays, and all colors on NV panel. Customize it to your liking!
I have a handful of additional features that I plan on adding to this tool in future updates. If there is anything you would like to see added, any bugs you identify, or any strategies you encounter with this tool, I would love to hear from you!
Huge shoutout to @joebaus for assisting in bringing this tool to life, please check out his work here on TradingView!
OrangeCandle 4EMA 55 + Fib Bands + SignalsThe script is a TradingView indicator that combines three popular technical analysis tools: Exponential Moving Averages (EMAs), Fibonacci bands, and buy/sell signals based on these indicators. Here’s a breakdown of its features:
1. EMA Settings and Calculation:
The script calculates and plots several Exponential Moving Averages (EMAs) on the chart with different lengths:
Short-term EMAs: EMA 9, EMA 13, EMA 21, and EMA 55 (used for tracking short-term price trends).
Long-term EMAs: EMA 100 and EMA 200 (used to analyze longer-term trends).
These EMAs are plotted with different colors to visually distinguish between the short-term and long-term trends.
2. Fibonacci Bands:
The script calculates Fibonacci Bands based on the Average True Range (ATR) and a Simple Moving Average (SMA).
Fibonacci factors (1.618, 2.618, 4.236, 6.854, and 11.090) are used to determine the upper and lower bounds of five Fibonacci bands.
Upper Fibonacci Bands (e.g., fib1u, fib2u) represent resistance levels.
Lower Fibonacci Bands (e.g., fib1l, fib2l) represent support levels.
These bands are plotted with different colors for each level, helping traders identify potential price reversal zones.
3. Buy and Sell Signals:
Long Condition: A buy signal occurs when the price crosses above the EMA 55 (long-term trend indicator) and is above the lower Fibonacci band (support zone).
Short Condition: A sell signal occurs when the price crosses below the EMA 55 and is below the upper Fibonacci band (resistance zone).
These conditions trigger visual signals on the chart (green arrow for long, red arrow for short).
4. Alerts:
The script includes alert conditions to notify the trader when a long or short signal is triggered based on the crossover of price and EMA 55 near the Fibonacci support or resistance levels.
Long Entry Alert: Triggers when the price crosses above the EMA 55 and is near a Fibonacci support level.
Short Entry Alert: Triggers when the price crosses below the EMA 55 and is near a Fibonacci resistance level.
5. Visualization:
EMAs are plotted with distinct colors:
EMA 9 is aqua,
EMA 13 is purple,
EMA 21 is orange,
EMA 55 is blue (with thicker line width for emphasis),
EMA 100 is gray,
EMA 200 is black.
Fibonacci bands are plotted with different colors for each level:
Fib Band 1 (upper and lower) in white,
Fib Band 2 in green (upper) and red (lower),
Fib Band 3 in green (upper) and red (lower),
Fib Band 4 in blue (upper) and orange (lower),
Fib Band 5 in purple (upper) and yellow (lower).
Summary:
This script provides a comprehensive strategy for analyzing the market with multiple EMAs for trend detection, Fibonacci bands for support/resistance, and signals based on price action in relation to these indicators. The combination of these tools can assist traders in making more informed decisions by providing potential entry and exit points on the chart.
Mehul - ADX Zero LagThis script combines two popular technical indicators into a single visualization:
1. **Average Directional Index (ADX)**:
- Measures trend strength on a scale from 0-100 (now normalized to 0-1 by dividing by 100)
- Displayed as a red line
- Adjustable smoothing and length parameters
2. **Zero Lag MACD (Modified Moving Average Convergence Divergence)**:
- An enhanced version of the traditional MACD with reduced lag
- Shows the relationship between fast and slow moving averages
- Main components include:
- MACD line (black)
- Signal line (gray)
- Histogram (green for positive, purple for negative)
- EMA of the MACD line (red)
- Optional crossing dots
Key features of the combined indicator:
- **Scale Adjustment**: Both indicators can be scaled independently (adxScale and macdScale parameters)
- **Visibility Toggles**: Each indicator can be shown or hidden
- **Advanced Customization**: Parameters for both indicators can be fine-tuned
- **Algorithm Selection**: Option to choose between the "Glaz" algorithm or the "real" zero lag algorithm
- **Display Options**: Toggles for visualization elements like crossing dots
The most significant technical aspect is that both indicators are displayed in the same pane with compatible scaling, achieved by normalizing the ADX values and applying user-defined scale factors to both indicators.
This combined indicator is designed to give traders a comprehensive view of both trend strength (from ADX) and momentum/direction (from Zero Lag MACD) in a single, easy-to-read visualization.
CCI with Signals & Divergence [AIBitcoinTrend]👽 CCI with Signals & Divergence (AIBitcoinTrend)
The Hilbert Adaptive CCI with Signals & Divergence takes the traditional Commodity Channel Index (CCI) to the next level by dynamically adjusting its calculation period based on real-time market cycles using Hilbert Transform Cycle Detection. This makes it far superior to standard CCI, as it adapts to fast-moving trends and slow consolidations, filtering noise and improving signal accuracy.
Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, helping traders identify potential reversals and manage risk effectively.
👽 What Makes the Hilbert Adaptive CCI Unique?
Unlike the traditional CCI, which uses a fixed-length lookback period, this version automatically adjusts its lookback period using Hilbert Transform to detect the dominant cycle in the market.
✅ Hilbert Transform Adaptive Lookback – Dynamically detects cycle length to adjust CCI sensitivity.
✅ Real-Time Divergence Detection – Instantly identifies bullish and bearish divergences for early reversal signals.
✅ Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Hilbert Transform Cycle Detection
The Hilbert Transform estimates the dominant market cycle length based on the frequency of price oscillations. It is computed using the in-phase and quadrature components of the price series:
tp = (high + low + close) / 3
smooth = (tp + 2 * tp + 2 * tp + tp ) / 6
detrender = smooth - smooth
quadrature = detrender - detrender
inPhase = detrender + quadrature
outPhase = quadrature - inPhase
instPeriod = 0.0
deltaPhase = math.abs(inPhase - inPhase ) + math.abs(outPhase - outPhase )
instPeriod := nz(3.25 / deltaPhase, instPeriod )
dominantCycle = int(math.min(math.max(instPeriod, cciMinPeriod), 500))
Where:
In-Phase & Out-Phase Components are derived from a detrended version of the price series.
Instantaneous Frequency measures the rate of cycle change, allowing the CCI period to adjust dynamically.
The result is bounded within a user-defined min/max range, ensuring stability.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while CCI forms a higher low.
Buy signal is confirmed when CCI shows upward momentum.
Bearish Divergence Setup:
Price makes a higher high, while CCI forms a lower high.
Sell signal is confirmed when CCI shows downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ CCI crosses above -100 → Buy signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if the price crosses below the stop.
Bearish Setup:
✅ CCI crosses below 100 → Sell signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if the price crosses above the stop.
👽 Why It’s Useful for Traders
Hilbert Adaptive Period Calculation – No more fixed-length periods; the indicator dynamically adapts to market conditions.
Real-Time Divergence Alerts – Helps traders anticipate market reversals before they occur.
ATR-Based Risk Management – Stops automatically adjust based on volatility.
Works Across Multiple Markets & Timeframes – Ideal for stocks, forex, crypto, and futures.
👽 Indicator Settings
Min & Max CCI Period – Defines the adaptive range for Hilbert-based lookback.
Smoothing Factor – Controls the degree of smoothing applied to CCI.
Enable Divergence Analysis – Toggles real-time divergence detection.
Lookback Period – Defines the number of bars for detecting pivot points.
Enable Crosses Signals – Turns on CCI crossover-based trade signals.
ATR Multiplier – Adjusts trailing stop sensitivity.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Shavarie's MCV IndicatorShavarie's MCV Indicator (MACD + CCI + Volume Delta) is a custom-built trend-following and volume-based indicator that helps traders confirm market direction with high accuracy. It combines the MACD (Moving Average Convergence Divergence), CCI (Commodity Channel Index), and Volume Delta, ensuring that all three indicators align before making a trading decision. The goal is to filter out false signals and provide high-probability trade setups.
History & Development
Shavarie's MCV Indicator was developed by Shavarie Gordon, an experienced swing trader, to improve trend confirmation on Gold (XAUUSD) and other markets. After testing various indicators, Shavarie discovered that MACD, CCI, and Volume Delta together provide the best combination of trend strength, momentum, and real-time volume flow. This indicator was designed to eliminate lagging signals, improve win rates, and enhance market timing for both swing and scalping strategies.
How It Works & Calculations
MACD (Moving Average Convergence Divergence)
Measures momentum and trend strength using the difference between a 12-period EMA and a 26-period EMA.
The MACD line and Signal line crossover confirms buy/sell signals.
A rising MACD histogram confirms bullish strength, while a falling histogram confirms bearish strength.
CCI (Commodity Channel Index)
Measures how far the price is from its statistical average.
Above +100 → Overbought (strong trend continuation or reversal).
Below -100 → Oversold (strong trend continuation or reversal).
When CCI aligns with MACD, it confirms momentum strength.
Volume Delta
Measures the difference between buying and selling volume in real time.
A positive delta means more aggressive buying (bullish).
A negative delta means more aggressive selling (bearish).
Helps confirm MACD and CCI trends by showing real volume strength.
Key Takeaways & Features
✅ No false signals: All three indicators must align before entering a trade.
✅ Trend confirmation: Ensures momentum and volume agree before trading.
✅ Works on multiple timeframes: Designed for swing trading on the daily and scalping on 45 min + 5 min.
✅ Great for Gold & Metals: Optimized for XAUUSD, XAUJPY, XAU/AUD, and possibly Palladium (XPDUSD).
✅ Custom-built by a professional trader: Developed by Shavarie Gordon after extensive testing.
Summary
Shavarie’s MCV Indicator is a powerful and reliable trading tool that combines momentum, trend, and volume analysis. By ensuring that MACD, CCI, and Volume Delta align, it eliminates false signals and increases trade accuracy. Whether used for swing trading or scalping, this indicator helps traders enter high-probability trades with confidence.
Sector/Industry Relative StrengthOverview
The Sector/Industry Relative Strength (RS) Indicator is a powerful tool designed to help traders and investors analyze the performance of sectors and industries relative to the broader market (SPY). It provides real-time insights into sector and industry strength, helping you identify leading and lagging areas of the market.
Key Features
Sector and Industry Analysis:
Automatically detects the sector and industry of the current symbol.
Displays the corresponding sector and industry ETF.
Relative Strength (STS) Calculation:
Calculates the Sector/Industry Trend Strength (STS) by comparing the sector or industry ETF to SPY over the past 20 days.
STS is expressed as a percentile (0-100), indicating how strong the sector/industry ETF has been relative to SPY over the past 20 days.
Example: An STS of 70 means that during the past 20 days, the ETF’s relative strength against SPY was stronger than 70% of those days.
Sector Rank:
Ranks the current sector ETF against a predefined list of major sector ETFs.
Highlights whether the sector is outperforming or underperforming SPY (green if outperforming, red if underperforming).
Customizable Display:
Choose which elements to display (e.g., sector, industry, ETFs, STS, sector rank).
Customize table position, size, text alignment, and colors.
Real-Time Performance:
Tracks daily price changes for sector and industry ETFs.
Displays percentage change from open to close.
How to Use
Add the Indicator:
Apply the indicator to any stock or ETF chart.
The script will automatically detect the sector and industry of the selected symbol.
Interpret the Data:
Sector/Industry: Displays the current sector and industry.
ETF: Shows the corresponding sector and industry ETF.
STS (Sector/Industry Trend Strength): A percentile score (0-100) indicating the relative strength of the sector/industry ETF compared to SPY over the past 20 days.
Sector Rank: Ranks the sector ETF against other major sectors (e.g., "3/12" means the sector is ranked 3rd out of 12).
Customize the Display:
Use the input settings to:
Show/hide specific elements (e.g., sector, industry, ETFs, STS, sector rank).
Adjust the table position, size, and text alignment.
Change colors for positive/negative changes.
Make Informed Decisions:
Use the STS score and sector rank to identify potential trading opportunities.
Focus on sectors and industries with high STS scores and strong rankings (green).
Input Parameters
Table Settings:
Table Position: Choose where to display the table (Top Left, Top Right, Bottom Left, Bottom Right).
Table Size: Adjust the size of the table (Tiny, Small, Normal, Large).
Text Color: Customize the text color.
Background Color: Set the table background color.
Display Options:
Show ETFs: Toggle the display of sector and industry ETFs.
Show STS: Toggle the display of the Sector/Industry Trend Strength (STS) score.
Show Sector/Industry: Toggle the display of sector and industry information.
Show Sector Rank: Toggle the display of the sector rank.
Parameters:
Sector Rank Time Length: Set the number of days used for calculating the sector rank (default: 20).
Example Use Cases
Sector Rotation:
Identify sectors with high STS scores and strong rankings (green) to allocate capital.
Avoid sectors with low STS scores and weak rankings (red).
Industry Analysis:
Compare the STS scores of different industries within the same sector.
Use the STS score to gauge relative strength and identify potential opportunities.
Market Timing:
Use the STS score and sector rank to time entries and exits in sector-specific ETFs.
Combine with other technical indicators for confirmation.
Quantum Momentum FusionPurpose of the Indicator
"Quantum Momentum Fusion" aims to combine the strengths of RSI (Relative Strength Index) and Williams %R to create a hybrid momentum indicator tailored for volatile markets like crypto:
RSI: Measures the strength of price changes, great for understanding trend stability but can sometimes lag.
Williams %R: Assesses the position of the price relative to the highest and lowest levels over a period, offering faster responses but sensitive to noise.
Combination: By blending these two indicators with a weighted average (default 50%-50%), we achieve both speed and reliability.
Additionally, we use the indicator’s own SMA (Simple Moving Average) crossovers to filter out noise and generate more meaningful signals. The goal is to craft a simple yet effective tool, especially for short-term trading like scalping.
How Signals Are Generated
The indicator produces signals as follows:
Calculations:
RSI: Standard 14-period RSI based on closing prices.
Williams %R: Calculated over 14 periods using the highest high and lowest low, then normalized to a 0-100 scale.
Quantum Fusion: A weighted average of RSI and Williams %R (e.g., 50% RSI + 50% Williams %R).
Fusion SMA: 5-period Simple Moving Average of Quantum Fusion.
Signal Conditions:
Overbought Signal (Red Background):
Quantum Fusion crosses below Fusion SMA (indicating weakening momentum).
And Quantum Fusion is above 70 (in the overbought zone).
This is a sell signal.
Oversold Signal (Green Background):
Quantum Fusion crosses above Fusion SMA (indicating strengthening momentum).
And Quantum Fusion is below 30 (in the oversold zone).
This is a buy signal.
Filtering:
The background only changes color during crossovers, reducing “fake” signals.
The 70 and 30 thresholds ensure signals trigger only in extreme conditions.
On the chart:
Purple line: Quantum Fusion.
Yellow line: Fusion SMA.
Red background: Sell signal (overbought confirmation).
Green background: Buy signal (oversold confirmation).
Overall Assessment
This indicator can be a fast-reacting tool for scalping. However:
Volatility Warning: Sudden crypto pumps/dumps can disrupt signals.
Confirmation: Pair it with price action (candlestick patterns) or another indicator (e.g., volume) for validation.
Timeframe: Works best on 1-5 minute charts.
Suggested Settings for Long Timeframes
Here’s a practical configuration for, say, a 4-hour chart:
RSI Period: 20
Williams %R Period: 20
RSI Weight: 60%
Williams %R Weight: 40% (automatically calculated as 100 - RSI Weight)
SMA Period: 15
Overbought Level: 75
Oversold Level: 25
Price Change IndicatorPrice Change Indicator (PCI)
Version: 1.0
Author: LazyTrader 🚀
🔍 Overview
The Price Change Indicator (PCI) helps traders visualize and compare price changes between the current bar and the previous bar. It provides a customizable display of price changes in two formats:
Percentage (%) Change – Relative price movement.
Natural Change – Absolute difference in price units.
⚙️ Key Features
✅ Customizable Calculation Method: Choose how the price change is calculated:
Opening Price
Closing Price
High
Low
✅ Flexible Display Format:
Show Percentage (%) Change.
Show Natural (Absolute) Change in price.
✅ Adjustable Sensitivity with Multiplier:
100 (Standard Change)
1000 (Small Change)
10000 (Tiny Change)
✅ Intuitive Labeling:
Green label (above bar) for increase.
Red label (below bar) for decrease.
No label if no change.
Large, easy-to-read labels for better visibility.
✅ Perfect for Any Market:
Stocks 📈
Forex 💱
Crypto 🚀
Commodities 🛢️
📊 How It Works
The indicator calculates the difference between the current and previous bar’s price based on your chosen method.
The result is displayed as either a percentage (%) or a natural price change.
If the price has increased, a green label is displayed above the bar.
If the price has decreased, a red label is displayed below the bar.
⚡ How to Use
Add the indicator to your chart.
Go to settings and customize:
Select calculation method (Open, Close, High, Low).
Choose display format (% or Natural Change).
Adjust multiplier for more sensitivity.
Analyze the labels to see price movements easily!
🔧 Settings Explained
Setting Description
Price Calculation Method: Choose Open, Close, High, or Low price for comparison.
Display Format: Show either % Change or Natural Change.
Multiplier: Apply 100, 1000, or 10000 to scale small price changes.
Show Labels: Toggle labels on/off.
🎯 Best Use Cases
🔹 Identifying strong price movements
🔹 Spotting trends and momentum shifts
🔹 Comparing price movement intensity
🔹 Works for scalping, swing trading, and long-term analysis
Hanzo_Wave_Price %Hanzo_Wave_Price % is a custom indicator for the TradingView platform that combines RSI (Relative Strength Index) and Stochastic RSI while also displaying the percentage price change over a specified period. This indicator helps traders identify overbought and oversold conditions, analyze price waves, and forecast potential market movements.
How It Works
1. RSI and Stochastic RSI Calculation
RSI is calculated based on the selected price source (default: close) with a user-defined Main Line period.
Stochastic RSI is then applied and smoothed using a moving average.
The Main Line represents the smoothed Stochastic RSI, serving as a wave indicator to help identify potential entry and exit points.
2. Overbought and Oversold Zones
The 70 and 30 levels indicate overbought and oversold zones, displayed as dashed lines on the chart.
Additional 20% and 10% levels provide a visual reference for historical price changes, aiding in future predictions.
3. Percentage Price Change Calculation
The indicator calculates the percentage price change over a Barsback period (default: 30 candles).
Users can choose a multiplier (100 or 1000) for better visualization (1000 scales the values by dividing by 10).
The data is displayed as a colored area:
Red (Short) → Negative price change.
Green (Buy) → Positive price change.
Settings & Parameters
Multiplier 💪 – Selects the scaling factor (100 or 1000) for percentage values.
Main Line ✈️ – Stochastic smoothing period (smoothK).
Don't touch ✋ – Reserved value (do not modify).
RSI 🔴 – RSI calculation period.
Stochastic 🔵 – Stochastic RSI calculation period.
Source ⚠️ – Price source for calculations (default: close).
Price changes % 🔼🔽 – Enables percentage price change display.
Barsback ↩️ – Number of candles used to calculate price change.
Visual Representation
Gray Line (Takeprofit Line 🎯) – Smoothed Stochastic RSI.
Red Dashed Line (70) – Overbought zone.
Blue Dashed Line (30) – Oversold zone.
Percentage Price Change Display:
Green Fill → Price increase.
Red Fill → Price decrease.
Advantages
✅ Combined Analysis – Uses RSI and Stochastic RSI for more accurate market condition identification.
✅ Flexibility – Customizable parameters allow adaptation for different markets and strategies.
✅ Visual Clarity – Clearly defined zones and dynamic percentage change display.
✅ Additional Market Insights – The percentage price change helps assess market volatility.
Disadvantages
⚠ Lagging Signals – Smoothing may cause delayed response.
⚠ False Breakouts – The 70/30 levels may not always work effectively for all assets.
⚠ IMPORTANT!
This indicator is for informational and educational purposes only. Past performance does not guarantee future profits! Use it in combination with other technical analysis tools. 🚀
Example 1: Identifying a Long Position
📌 Scenario:
The asset price has dropped significantly (1-hour timeframe), and the Main Line (gray line) crosses below the 30 level. This signals oversold conditions, which may indicate a potential reversal or upward correction.
✅ How to Use:
1️⃣ Identifying the Entry Zone:
If the Main Line is below 30, consider looking for a long entry point.
2️⃣ Confirming the Signal:
Place a vertical line at the moment when the Main Line crosses the 30 level from below.
3️⃣ Confirmation on a Lower Timeframe:
Switch to a 30-minute timeframe and wait for the Main Line to cross above the 70 level.
Enter a long position at this point.
4️⃣ Analyzing Percentage Price Change:
Check the historical indicator behavior:
If a similar past movement resulted in a ~10% price increase (green fill), this may indicate potential upward momentum.
5️⃣ Setting Take-Profit:
Set a take-profit level at 10%, based on previous price movements.
Also, monitor when the Main Line crosses the 70 level, as this may signal a potential profit-taking point.
📊 Conclusion:
This method helps to precisely determine entry points by confirming signals across multiple timeframes and analyzing the historical volatility of the asset. 🚀
Example 2: Analyzing Percentage Price Change
📌 Scenario:
You have set the Barsback parameter to 30, and the indicator shows +3.5%. This means that over the last 30 candles, the price has increased by 3.5%.
However, such small changes might be visually difficult to notice. To improve visibility, you can enable the multiplier (1000), which will scale the displayed percentage change to 35%. This is purely for visual convenience—the actual price movement remains 3.5%.
✅ How to Use:
1️⃣ Identifying Trend Direction:
If the percentage change is positive (green area) → Uptrend.
If the percentage change is negative (red area) → Downtrend.
2️⃣ Analyzing Movement Strength:
Compare the current percentage change with previous waves to evaluate the strength of the movement.
For example:
If previous waves reached 10% or more, a current wave of 3.5% might indicate a weak trend or a local correction.
3️⃣ Additional Filtering with the Main Line (Gray Line):
Use the Main Line to confirm the trend.
If the percentage change shows an increase, but the Main Line is still below 30, further upward movement can be expected.
If the percentage change indicates a decline, but the Main Line is above 70, there is a higher probability of a downward reversal.
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