Market Sentiment Technicals [LuxAlgo]The Market Sentiment Technicals indicator synthesizes insights from diverse technical analysis techniques, including price action market structures, trend indicators, volatility indicators, momentum oscillators, and more.
The indicator consolidates the evaluated outputs from these techniques into a singular value and presents the combined data through an oscillator format, technical rating, and a histogram panel featuring the sentiment of each component alongside the overall sentiment.
🔶 USAGE
The Market Sentiment Technicals indicator is a tool able to swiftly and easily gauge market sentiment by consolidating the individual sentiment from multiple technical analysis techniques applied to market data into a single value, allowing users to asses if the market is uptrending, consolidating, or downtrending.
The tool includes various components and presentation formats, each described in the sub-sections below.
🔹Indicators Sentiment Panel
The indicators sentiment panel provides normalized sentiment scores for each supported indicator, along with a synthesized representation derived from the average of all individual normalized sentiments.
🔹Market Sentiment Meter
The market sentiment meter is obtained from the synthesized representation derived from the average of all individual normalized sentiments. It allows users to quickly and easily gauge the overall market sentiment.
🔹Market Sentiment Oscillator
The market sentiment oscillator provides a visual means to monitor the current and historical strength of the market. It assists in identifying the trend direction, trend momentum, and overbought and oversold conditions, aiding in the anticipation of potential trend reversals.
Divergence occurs when there is a difference between what the price action is indicating and what the market sentiment oscillator is indicating, helping traders assess changes in the price trend.
🔶 DETAILS
The indicator employs a range of technical analysis techniques to interpret market data. Each group of indicators provides valuable insights into different aspects of market behavior.
🔹Momentum Indicators
Momentum indicators assess the speed and change of price movements, often indicating whether a trend is strengthening or weakening.
Relative Strength Index (RSI): Measures the magnitude of recent price changes to evaluate overbought or oversold conditions.
Stochastic %K: Compares the closing price to the range over a specified period to identify potential reversal points.
Stochastic RSI Fast: Combines features of Stochastic oscillators and RSI to gauge both momentum and overbought/oversold levels efficiently.
Commodity Channel Index (CCI): Measures the deviation of an asset's price from its statistical average to determine trend strength and overbought and oversold conditions.
Bull Bear Power: Evaluates the strength of buying and selling pressure in the market.
🔹Trend Indicators
Trend indicators help traders identify the direction of a market trend.
Moving Averages: Provides a smoothed representation of the underlying price data, aiding in trend identification and analysis.
Bollinger Bands: Consists of a middle band (typically a simple moving average) and upper and lower bands, which represent volatility levels of the market.
Supertrend: A trailing stop able to identify the current direction of the trend.
Linear Regression: Fits a straight line to past data points to predict future price movements and identify trend direction.
🔹Market Structures
Market Structures: Analyzes the overall pattern of price movements, including Break of Structure (BOS), Market Structure Shifts (MSS), also referred to as Change of Character (CHoCH), aiding in identifying potential market turning and continuation points.
🔹The Normalization Technique
The normalization technique employed for trend indicators relies on buy-sell signals. The script tracks price movements and normalizes them based on these signals.
normalize(buy, sell, smooth)=>
var os = 0
var float max = na
var float min = na
os := buy ? 1 : sell ? -1 : os
max := os > os ? close : os < os ? max : math.max(close, max)
min := os < os ? close : os > os ? min : math.min(close, min)
ta.sma((close - min)/(max - min), smooth) * 100
In this Pine Script snippet:
The variable os tracks market sentiment, taking a value of 1 for buy signals and -1 for sell signals, indicating bullish and bearish sentiments, respectively.
max and min are used to identify extremes in sentiment and are updated based on changes in os . When market sentiment shifts from buying to selling (or vice versa), max and min adjust accordingly.
Normalization is achieved by comparing current price levels to historical extremes in sentiment. The result is smoothed by default using a 3-period simple moving average. Users have the option to customize the smoothing period via the script settings input menu.
🔶 SETTINGS
🔹Generic Settings
Timeframe: This option selects the timeframe for calculating sentiment. If a timeframe lower than the chart's is chosen, calculations will be based on the chart's timeframe.
Horizontal Offset: Determines the distance at which the visual components of the indicator will be displayed from the primary chart.
Gradient Colors: Allows customization of gradient colors.
🔹Indicators Sentiment Panel
Indicators Sentiment Panel: Toggle the visibility of the indicators sentiment panel.
Panel Height: Determines the height of the panel.
🔹Market Sentiment Meter
Market Sentiment Meter: Toggle the visibility of the market sentiment meter (technical ratings in the shape of a speedometer).
🔹Market Sentiment Oscillator
Market Sentiment Oscillator: Toggle the visibility of the market sentiment oscillator.
Show Divergence: Enables detection of divergences based on the selected option.
Oscillator Line Width: Customization option for the line width.
Oscillator Height: Determines the height of the oscillator.
🔹Settings for Individual Components
In general,
Source: Determines the data source for calculations.
Length: The period to be used in calculations.
Smoothing: Degree of smoothness of the evaluated values.
🔹Normalization Settings - Trend Indicators
Smoothing: The period used in smoothing normalized values, where normalization is applied to moving averages, Bollinger Bands, Supertrend, VWAP bands, and market structures.
🔶 LIMITATIONS
Like any technical analysis tool, the Market Sentiment Technicals indicator has limitations. It's based on historical data and patterns, which may not always accurately predict future market movements. Additionally, market sentiment can be influenced by various factors, including economic news, geopolitical events, and market psychology, which may not be fully captured by technical analysis alone.
Cari dalam skrip untuk "Divergence"
RSI Wave Function Ultimate OscillatorEnglish Explanation of the "RSI Wave Function Ultimate Oscillator" Pine Script Code
Understanding the Code
Purpose:
This Pine Script code creates a custom indicator that combines the Relative Strength Index (RSI) with a wave function to potentially provide more nuanced insights into market dynamics.
Key Components:
* Wave Function: This is a custom calculation that introduces a sinusoidal wave component to the price data. The frequency parameter controls the speed of the oscillation, and the decay factor determines how quickly the influence of past prices diminishes.
* Smoothed Signal: The wave function is applied to the closing price to create a smoothed signal, which is essentially a price series modulated by a sine wave.
* RSI: The traditional RSI is then calculated on this smoothed signal, providing a measure of the speed and change of price movements relative to recent price changes.
Calculation Steps:
* Wave Function Calculation:
* A sinusoidal wave is generated based on the bar index and the frequency parameter.
* The wave is combined with the closing price using a weighted average, where the decay factor determines the weight given to previous values.
* RSI Calculation:
* The RSI is calculated on the smoothed signal using a standard RSI formula.
* Plotting:
* The RSI values are plotted on a chart, along with horizontal lines at 70 and 30 to indicate overbought and oversold conditions.
* The area between the RSI line and the overbought/oversold lines is filled with color to visually represent the market condition.
Interpretation and Usage
* Wave Function: The wave function introduces cyclical patterns into the price data, which can help identify potential turning points or momentum shifts.
* RSI: The RSI provides a measure of the speed and change of price movements relative to recent price changes. When applied to the smoothed signal, it can help identify overbought and oversold conditions, as well as potential divergences between price and momentum.
* Combined Indicator: The combination of the wave function and RSI aims to provide a more sensitive and potentially earlier indication of market reversals.
* Signals:
* Crossovers: Crossovers of the RSI line above or below the overbought/oversold lines can be used to generate buy or sell signals.
* Divergences: Divergences between the price and the RSI can indicate a weakening trend.
* Oscillations: The amplitude and frequency of the oscillations in the RSI can provide insights into the strength and duration of market trends.
How it Reflects Market Volatility
* Amplified Volatility: The wave function can amplify the volatility of the price data, making it easier to identify potential turning points.
* Smoothing: The decay factor helps to smooth out short-term fluctuations, allowing the indicator to focus on longer-term trends.
* Sensitivity: The combination of the wave function and RSI can make the indicator more sensitive to changes in market momentum.
In essence, this custom indicator attempts to enhance traditional RSI analysis by incorporating a cyclical component that can potentially provide earlier signals of market reversals.
Note: The effectiveness of this indicator will depend on various factors, including the specific market, time frame, and the chosen values for the frequency and decay parameters. It is recommended to conduct thorough backtesting and optimize the parameters to suit your specific trading strategy.
Money Wave Script (Visual Adaptive MFI)This Script is a visual modification of the Money Flow Index (MFI)
//@version=5
indicator(title="Money Flow Index", shorttitle="MFI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
length = input.int(title="Length", defval=14, minval=1, maxval=2000)
src = hlc3
mf = ta.mfi(src, length)
plot(mf, "MF", color=#7E57C2)
overbought=hline(80, title="Overbought", color=#787B86)
hline(50, "Middle Band", color=color.new(#787B86, 50))
oversold=hline(20, title="Oversold", color=#787B86)
fill(overbought, oversold, color=color.rgb(126, 87, 194, 90), title="Background")
This Money Wave Script is culled from. the Money Flow Index with visual representation to help traders identify money flow. In addition, the waves can be smoothened. Here’s a detailed overview based on its functionality, color coding, usage, risk management, and a concluding summary.
Functionality
The Money Wave Script operates as an oscillator that measures the inflow and outflow of money into an asset over a specified period. It calculates the MFI by considering both price and volume, which allows it to assess buying and selling pressures more accurately than traditional indicators that rely solely on price data.
Color Coding
The indicator employs a color-coded scheme to enhance visual interpretation:
Green Area: Indicates bullish conditions when the normalized Money wave is above zero, suggesting buying pressure.
Red Area: Indicates bearish conditions when the normalized Money wave is below zero, suggesting selling pressure.
Background Colors: The background changes to green when the MoneyWave exceeds the upper threshold (overbought) and red when it falls below the lower threshold (oversold), providing immediate visual cues about market conditions.
Usage
Traders utilize the Money Wave indicator in various ways:
Identifying Overbought and Oversold Levels: By observing the MFI readings, traders can determine when an asset may be overbought or oversold, prompting potential entry or exit points.
Spotting Divergences: Traders look for divergences between price and the MFI to anticipate potential reversals. For example, if prices are making new highs but the MFI is not, it could indicate weakening momentum.
Trend Confirmation: The indicator can help confirm trends by showing whether buying or selling pressure is dominating.
Customizable Settings: Users can adjust parameters such as the MFI length , Smoothen index and overbought/oversold thresholds to tailor the indicator to their trading strategies.
Conclusion
The Money Wave indicator is a powerful tool for traders seeking to analyze market conditions based on the flow of money into and out of assets. Its combination of price and volume analysis, along with clear visual cues, makes it an effective choice for identifying overbought and oversold conditions, spotting divergences, and confirming trends.
Cumulative Volume Delta (MTF)Cumulative Volume Delta (CVD) Indicator
The Cumulative Volume Delta (CVD) indicator is a powerful analytical tool used to understand the behavior and dynamics of market participants through volume analysis. It tracks the net difference between buying and selling pressure, providing insights into market trends and potential reversals. Here's a detailed description of this indicator and its components:
The Cumulative Volume Delta (CVD) indicator calculates the cumulative net difference between buying and selling volume over a specified period. By analyzing this net difference, traders can gain insights into the underlying strength or weakness of a price movement, helping to identify trends, reversals, and potential breakout points.
Key Components:
Bull & Bear Power Calculation:
Bull Power: Represents the strength of buyers in the market. It is calculated based on the relationship between the current and previous price bars. A higher Bull Power indicates stronger buying pressure.
Bear Power: Represents the strength of sellers in the market. It is also calculated based on the relationship between the current and previous price bars. A higher Bear Power indicates stronger selling pressure.
Bull & Bear Volume Calculation:
Bull Volume: The volume attributed to buying pressure. It is calculated by taking the proportion of Bull Power relative to the total of Bull Power and Bear Power, multiplied by the total volume.
Bear Volume: The volume attributed to selling pressure. It is calculated similarly to Bull Volume but using Bear Power.
Delta Calculation:
Delta: The net difference between Bull Volume and Bear Volume for each bar. A positive Delta indicates more buying pressure, while a negative Delta indicates more selling pressure.
Cumulative Volume Delta (CVD):
CVD: The running total of the Delta values over time. It accumulates the net buying and selling pressure to provide a visual representation of the market's cumulative sentiment.
Moving Average of CVD (CVD MA):
CVD MA: A simple moving average of the CVD, used to smooth out fluctuations and help identify the overall trend. It provides a baseline to compare the current CVD value against, highlighting divergences or convergences.
Multi-Timeframe Functionality:
The enhanced version of the CVD indicator includes multi-timeframe (MTF) capabilities, allowing users to select and analyze data from different timeframes. This feature enhances the versatility of the indicator by providing a broader perspective on market dynamics across various time intervals.
Practical Applications:
Trend Identification: By tracking the CVD and its moving average, traders can identify the prevailing trend. An upward-sloping CVD indicates sustained buying pressure, while a downward-sloping CVD indicates sustained selling pressure.
Divergences: Divergences between the CVD and price can signal potential reversals. For example, if the price is making new highs but the CVD is not, it may indicate weakening buying pressure and a potential reversal.
Breakout Confirmation: Significant changes in the CVD can confirm breakouts. A sharp increase in the CVD during a price breakout indicates strong buying support, adding confidence to the breakout.
Support and Resistance Levels: The CVD can help identify significant support and resistance levels based on changes in volume dynamics. For instance, a notable increase in buying volume at a support level can reinforce its strength.
[OBV] [MACD] [Accelerator/Awesome Oscillator] + PivDiv 2Here is an indicator with 4 options:
- OBV
- MACD (uses default EMA, you can change this to SMA)
- AC
- AO
All accompanied with my "Divergences (Pivots)" with 3 settings:
- 'Long Period', default checks 19 bars to the Left (="History") and 1 bar to the Right (="Future")
- 'Medium Period', default checks 14 bars to the Left (="History") and 1 bar to the Right (="Future")
- 'Short Period', default checks 9 bars to the Left (="History") and 1 bar to the Right (="Future")
When choosing an indicator, it comes with their accompanying "Divergences"!
Each Bar checks an amount of Bars at the Left (="History") and Bars to the Right (="Future"), insuring this particular Bar is the Highest or Lowest of them all at "close",
this is compared to the or or and so we have our Divergences.
There is always a slight delay (number of Bar(s) at the Right side (="Future")
If you like a setting, where the amount of “RightBars” equals the ”LeftBars” you can enable the " > Only change 'LeftBars'" button.
Then you only have to adjust the amount of “LeftBars” and the amount of “RightBars” automatically will be the same.
Bullish divergences are "Green"
- 'Short' - 'Medium' "period" > "▲"
- 'Long' "period" > "⇧"
Bearish divergences are "Red"
- 'Short' - 'Medium' "period" > "▼"
- 'Long' "period" > "⇩"
Hidden divergences ( Bullish and Bearish ) are:
- 'Short' - 'Medium' "period" > "▲▼" - "White"
- 'Long' "period" > "⬆︎⬇︎" - "Yellow"
Since for me, at this moment, it is impossible to let this indicator work as our eyes work, it will miss sometimes. I've tried to solve this by putting 3 different "Periods",
but it is not perfect, so look at it as an aiding tool, a "hint" so you can look in detail if there is something of importance or not.
What also helps is to switch timeframes.
For example on a 1 hour chart a "Highest" point can be missed sometimes, but could be perfectly visible on a 2 or 4 hour chart.
Also, try to change the numbers in a way that suits you the best.
Enjoy!
RACZ-SIGNAL-V2.1RACZ-SIGNAL-V2.1 – Reactive Analytical Confluence Zones
Developed by: RACZ Trading
Indicator Type: Multi-Factor Confluence System
Overlay: Off (separate pane)
Purpose: Detect powerful trade opportunities through confluence of technical signals.
⸻
🔍 What is RACZ?
RACZ stands for Reactive Analytical Confluence Zones.
It’s a high-precision trading tool built for traders who rely on multi-signal confirmation, momentum alignment, and market structure awareness.
Rather than relying on a single technical metric, RACZ dynamically combines RSI, VWAP-RSI, Divergence, ADX, and Volume Analytics to produce a composite signal score from 0 to 12 — the higher the score, the stronger the signal.
⸻
🧠 How It Works – Core Components
1. RSI Analysis
• Detects momentum shifts.
• Compares RSI value to overbought (default: 67) and oversold (default: 33) thresholds.
• Adds points to Bullish or Bearish score.
2. VWAP-RSI
• Uses RSI based on VWAP (Volume Weighted Average Price).
• Adds weight to signals influenced by volume-adjusted price movement.
3. Divergence Detection
• Detects potential reversal zones.
• Bullish Divergence: RSI crosses up from low zone.
• Bearish Divergence: RSI crosses down from high zone.
• Strong confluence signal when present.
4. ADX Dynamic Strength Filter
• Custom-calculated ADX (trend strength indicator).
• Uses a dynamic threshold derived from SMA of ADX over a lookback period, scaled by a factor (default 0.9).
• Ensures signals are only validated in strong trend environments.
5. Volume Z-Score
• Detects anomalies in volume behavior.
• Z-score applied to 20-period volume average & deviation.
• Labels spikes, drops, high/low volume conditions.
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📊 Signal Scoring Logic
Each component (RSI, VWAP-RSI, Divergence, ADX) can score up to 3 points each.
• Bullish Score: Total from bullish alignment of each factor.
• Bearish Score: Total from bearish alignment of each factor.
• Signal Power = max(bullish, bearish)
📈 Signal Interpretation
• BUY: Bullish Score > Bearish Score
• SELL: Bearish Score > Bullish Score
• NEUTRAL: Scores are equal
• Signal power is plotted on a 0–12 histogram:
• 0–5 = Weak
• 6–8 = Medium
• 9–12 = Strong (High Confluence Zone)
🖥️ Live Status Panel (Top-Right Corner)
This real-time panel helps you break down the signal:Component
Value Explanation: RSI / VWAP / DIV / ADX
Shows points contributing to signal
SIGNAL: Current market bias (BUY, SELL, NEUTRAL)
VOLUME: Volume classification (Spike, Drop, High, Low, Normal)
Color-coded for quick interpretation.
✅ How to Use
1. Look at Histogram: Bars ≥6 suggest valid setups, especially ≥9.
2. Confirm Panel Agreement: Check which components are supporting the signal.
3. Validate Volume: Unusual spikes/drops often precede strong moves.
4. Follow Direction: Use BUY/SELL signals aligned with signal power and trend.
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⚙️ Customizable Inputs
• RSI period, overbought/oversold levels
• VWAP-RSI period
• ADX period and dynamic threshold settings
• Fully adjustable to fit any trading style
⸻
🚀 Why Choose RACZ?
• Clarity: Scores & signals derived from multiple tools, not just one.
• Confluence Logic: Designed for traders who look for confirmation across indicators.
• Speed: Real-time responsiveness to changing market dynamics.
• Volume Awareness: Integrated volume intelligence gives a deeper edge.
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⚠️ Disclaimer
This indicator is intended strictly for educational and informational purposes only. It is not financial advice and should not be used to make actual investment decisions. Always conduct your own research or consult with a licensed financial advisor before trading or investing. Use of this script is at your own risk.
Rate of Change HistogramExplanation of Modifications
Converting ROC to Histogram:
Original ROC: The ROC is calculated as roc = 100 * (source - source ) / source , plotted as a line oscillating around zero.
Modification: Instead of plotting roc as a line, it’s now plotted as a histogram using style=plot.style_columns. This makes the ROC values visually resemble the MACD histogram, with bars extending above or below the zero line based on momentum.
Applying MACD’s Four-Color Scheme:
Logic: The histogram’s color is determined by:
Above Zero (roc >= 0): Bright green (#26A69A) if ROC is rising (roc > roc ), light green (#B2DFDB) if falling (roc < roc ).
Below Zero (roc < 0): Bright red (#FF5252) if ROC is falling (roc < roc ), light red (#FFCDD2) if rising (roc > roc ).
Implementation: Used the exact color logic and hex codes from the MACD code, applied to the ROC histogram. This highlights momentum ebbs (falling ROC, fading waves) and flows (rising ROC, strengthening waves).
Removing Signal Line:
Unlike the previous attempt, no signal line is added. The histogram is purely the ROC value, ensuring it directly reflects price change momentum without additional smoothing, making it faster and more responsive to pulse waves, as you indicated ROC performs better than other oscillators.
Alert Conditions:
Added alerts to match the MACD’s logic, triggering when the ROC histogram crosses the zero line:
Rising to Falling: When roc >= 0 and roc < 0, signaling a potential wave peak (e.g., end of Wave 3 or C).
Falling to Rising: When roc <= 0 and roc > 0, indicating a potential wave bottom (e.g., start of Wave 1 or rebound).
These alerts help identify transitions in 3-4 wave pulse patterns.
Plotting:
Histogram: Plotted as columns (plot.style_columns) with the four-color scheme, directly representing ROC momentum.
Zero Line: Kept the gray zero line (#787B86) for reference, consistent with the MACD.
Removed ROC Line/Signal Line: Since you want the ROC to act as the histogram itself, no additional lines are plotted.
Inputs:
Retained the original length (default 9) and source (default close) inputs for consistency.
Removed signal-related inputs (e.g., signal_length, sma_signal) as they’re not needed for a pure ROC histogram.
How This ROC Histogram Works for Wave Pulses
Wave Alignment:
Above Zero (Bullish Momentum): Positive ROC bars indicate flows (e.g., impulse Waves 1, 3, or rebounds in Wave B/C). Bright green bars show accelerating momentum (strong pulses), while light green bars suggest fading momentum (potential wave tops).
Below Zero (Bearish Momentum): Negative ROC bars indicate ebbs (e.g., corrective Waves 2, 4, A, or C). Bright red bars show increasing bearish momentum (strong pullbacks), while light red bars suggest slowing declines (potential wave bottoms).
3-4 Wave Pulses:
In a 3-wave A-B-C correction: Wave A (down) shows bright red bars (falling ROC), Wave B (up) shows bright/light green bars (rising ROC), and Wave C (down) shifts back to red bars.
In a 4-wave consolidation: Alternating green/red bars highlight the rhythmic ebbs and flows as momentum oscillates.
Timing:
Zero-line crossovers mark wave transitions (e.g., from Wave 2 to Wave 3).
Color changes (e.g., bright to light green) signal momentum shifts within waves, helping identify pulse peaks/troughs.
Advantages Over MACD:
The ROC histogram is more responsive than the MACD histogram because ROC directly measures price change percentage, while MACD relies on moving average differences, which introduce lag. This makes the ROC histogram better for capturing rapid 3-4 wave pulses, as you noted.
Example Usage
For a stock with 3-4 wave pulses on a 5-minute chart:
Wave 1 (Flow): ROC rises above zero, histogram turns bright green (rising momentum), indicating a strong bullish pulse.
Wave 2 (Ebb): ROC falls below zero, histogram shifts to bright red (falling momentum), signaling a corrective pullback.
Wave 3 (Flow): ROC crosses back above zero, histogram becomes bright green again, confirming a powerful pulse.
Wave 4 (Ebb): ROC dips slightly, histogram turns light green (falling momentum above zero) or light red (rising momentum below zero), indicating consolidation.
Alerts trigger on zero-line crosses (e.g., from Wave 2 to Wave 3), helping time trades.
Settings Recommendations
Default (length=9): Works well for most time frames, balancing sensitivity and smoothness.
Intraday Pulses: Use length=5 or length=7 for faster signals on 5-minute or 15-minute charts.
Daily Charts: Try length=12 or length=14 for broader wave cycles.
Testing: Apply to a stock with clear wave patterns (e.g., tech stocks like AAPL or TSLA) and adjust length to match the pulse frequency you observe.
Notes
Confirmation: Pair the ROC histogram with price action (e.g., Fibonacci retracements, support/resistance) to validate wave counts, as momentum oscillators can be noisy in choppy markets.
Divergences: Watch for divergences (e.g., price makes a higher high, but ROC histogram bars are lower) to spot wave reversals, especially at Wave 3 or C ends.
Comparison to MACD: The ROC histogram is faster and more direct, making it ideal for short-term pulse waves, but it may be more volatile, so use with technical levels for precision.
Relative Volume Indicator (RVOL)Relative Volume Indicator (RVOL)
The Relative Volume Indicator (RVOL) helps traders identify unusual volume activity by comparing the current volume to the average historical volume. This makes it easier to spot potential breakouts, reversals, or significant market events that are accompanied by volume confirmation.
What This Indicator Shows
This indicator displays volume as a multiple of average volume, where:
- 1.0x means 100% of average volume
- 2.0x means 200% of average volume (twice the average)
- 0.5x means 50% of average volume (half the average)
Color Coding
The volume bars are color-coded based on configurable thresholds:
- Red: Below average volume (< Average Volume Threshold)
- Yellow: Average volume (between Average Volume and Above Average thresholds)
- Green: Above average volume (between Above Average and Extreme thresholds)
- Magenta: Extreme volume (> Extreme Volume Threshold)
Horizontal Reference Lines
Three dotted horizontal reference lines help you visualize the thresholds:
- Lower gray line: Average Volume Threshold (default: 0.8x)
- Upper gray line: Above Average Threshold (default: 1.25x)
- Magenta line: Extreme Volume Threshold (default: 4.0x)
How To Use This Indicator
1. Volume Confirmation: Use green bars to confirm breakouts or trend changes - stronger moves often come with above-average volume.
2. Low Volume Warning: Red bars during price movements may indicate weak conviction and potential reversals.
3. Extreme Volume Events: Magenta bars (extreme volume) often signal major market events or potential exhaustion points that could lead to reversals.
4. Volume Divergence: Look for divergences between price and volume - for example, if price makes new highs but volume is decreasing (more yellow/red bars), the move may be losing strength.
Settings Configuration
- Average Volume Lookback Period: Number of bars used to calculate the average volume (default: 20)
- Average Volume Threshold: Volume below this level is considered below average (default: 0.8x)
- Above Average Threshold: Volume above this level is considered above average (default: 1.25x)
- Extreme Volume Threshold: Volume above this level is considered extreme (default: 4.0x)
- Colors: Customize colors for each volume category
Important Note: Adjust threshold values only through the indicator settings (not in the Style tab). Changing values in the Style tab will not adjust the coloring of the volume bars.
Adjust these settings based on the specific asset being analyzed and your trading timeframe. More volatile assets may require higher thresholds, while less volatile ones might need lower thresholds.
Volume Delta DashboardHow It Works:
This script creates a Volume Delta Dashboard on TradingView, which helps traders visualize the balance between buying and selling volume (Volume Delta) directly on the chart. Here's a breakdown of the key components:
Volume Delta Calculation:
The script calculates the Volume Delta by comparing the volume of bars where the price closed higher (buying pressure) to those where the price closed lower (selling pressure).
Positive Volume Delta (green background) indicates more buying activity than selling, suggesting upward price movement. Negative Volume Delta (red background) indicates more selling than buying, signaling a potential downward move.
Smoothing with EMA:
To make the volume delta trend smoother and more consistent, an Exponential Moving Average (EMA) of the Volume Delta is used. This helps to reduce noise and highlight the prevailing buying or selling pressure over a 14-period.
Dynamic Position Selection:
The user can choose where the Volume Delta dashboard table will appear on the chart by selecting a position: top-left, top-right, bottom-left, or bottom-right. This makes the indicator adaptable to different chart setups.
Coloring:
The background of the table changes color based on the value of the Volume Delta. Green indicates a positive delta (more buyers), and Red indicates a negative delta (more sellers).
Use of This Strategy:
This Volume Delta Dashboard strategy is particularly useful for traders who want to:
Monitor Market Sentiment:
By observing the volume delta, traders can get a sense of whether there is more buying or selling pressure in the market. Positive volume delta can indicate a bullish sentiment, while negative delta can point to bearish sentiment.
Confirm Price Action:
The Volume Delta can be used alongside price action to confirm the strength of a price move. For example, if the price is moving up and the volume delta is positive, it suggests that the price increase is supported by buying pressure.
Identify Divergences:
Volume delta can help traders spot divergences between price and volume. For example, if the price is moving higher but the volume delta is negative, it may suggest a weakening trend and a potential reversal.
Optimize Entry/Exit Points:
By understanding the relationship between price movement and volume, traders can make more informed decisions about entering or exiting positions. For instance, a sudden increase in buying volume (positive delta) may indicate a good entry point for a long position.
Overall, the Volume Delta Dashboard can serve as a powerful tool for improving decision-making, by providing real-time insights into market dynamics and trading sentiment.
RSI & DPO support/resistanceThis indicator combines the Relative Strength Index (RSI) to identify overbought and oversold conditions with the Detrended Price Oscillator (DPO) to highlight support and resistance levels.
Unlike traditional indicators that display these metrics in a separate window, this tool integrates them directly onto the main price chart.
This allows for a more cohesive analysis, enabling traders to easily visualize the relationship between price movements and momentum indicators in one unified view.
How to Use It:
Identify Overbought and Oversold Conditions:
Look for RSI values above 70 to identify overbought conditions, suggesting a potential price reversal or pullback. Conversely, RSI values below 30 indicate oversold conditions, which may signal a potential price bounce or upward movement.
Analyze Support and Resistance Levels:
Observe the DPO lines on the main chart to identify key support and resistance levels. When the price approaches these levels, it can provide insights into potential price reversals or breakouts.
Combine Signals for Trading Decisions:
Use the RSI and DPO signals together to make informed trading decisions. For example, if the RSI indicates an overbought condition while the price is near a resistance level identified by the DPO, it may be a good opportunity to consider selling or taking profits.
Monitor Divergences:
Watch for divergences between the RSI and price movements. If the price is making new highs while the RSI is not, it could indicate weakening momentum and a potential reversal.
Set Alerts:
Consider setting alerts for when the RSI crosses above or below the overbought or oversold thresholds, or when the price approaches significant support or resistance levels indicated by the DPO.
Practice Risk Management:
Always use proper risk management techniques, such as setting stop-loss orders and position sizing, to protect your capital while trading based on these indicators.
By following these steps, traders can effectively utilize this indicator to enhance their market analysis and improve their trading strategies.
Enhanced Cumulative Volume Delta + MAThe Enhanced Cumulative Volume Delta (CVD) indicator is designed to help traders analyze the cumulative buying and selling pressure in the market by examining the delta between the up and down volume. By tracking this metric, traders can gain insights into the strength of a trend and potential reversals. This indicator uses advanced volume analysis combined with customizable moving averages to provide a more detailed view of market dynamics.
How to Use This Indicator:
Volume Delta Visualization:
The indicator plots the cumulative volume delta (CVD) using color-coded candles, where teal represents positive delta (buying pressure) and soft red represents negative delta (selling pressure).
Moving Averages:
Use the moving averages to smooth the CVD data and identify long-term trends. You can choose between SMA and EMA for each of the three available moving averages. The first and third moving averages are typically used for short-term and long-term trend analysis, respectively, while the second moving average can serve as a medium-term filter.
Arrow Markers:
The indicator will display arrows (green triangle up for crossing above, red triangle down for crossing below) when the CVD volume crosses the 3rd moving average. You can control the visibility of these arrows through the input parameters.
Volume Data:
The indicator provides error handling in case no volume data is available for the selected symbol, ensuring that you're not misled by incomplete data.
Practical Applications:
Trend Confirmation: Use the CVD and moving averages to confirm the overall trend direction and strength. Positive delta and a rising CVD can confirm an uptrend, while negative delta and a falling CVD indicate a downtrend.
Volume Breakouts: The arrows marking when the CVD crosses the 3rd moving average can help you spot potential volume breakouts or reversals, making them useful for entry or exit signals.
Volume Divergence: Pay attention to divergences between price and CVD, as these can often signal potential trend reversals or weakening momentum.
Multi SMA EMA VWAP1. Moving Average Crossover
This is one of the most common strategies with moving averages, and it involves observing crossovers between EMAs and SMAs to determine buy or sell signals.
Buy signal: When a faster EMA (like a short-term EMA) crosses above a slower SMA, it can indicate a potential upward movement.
Sell signal: When a faster EMA crosses below a slower SMA, it can indicate a potential downward movement.
With 4 EMAs and 5 SMAs, you can set up crossovers between different combinations, such as:
EMA(9) crosses above SMA(50) → buy.
EMA(9) crosses below SMA(50) → sell.
2. Divergence Confirmation Between EMAs and SMAs
Divergence between the EMAs and SMAs can offer additional confirmation. If the EMAs are pointing in one direction and the SMAs are still in the opposite direction, it is a sign that the movement could be stronger and continue in the same direction.
Positive divergence: If the EMAs are making new highs while the SMAs are still below, it could be a sign that the market is in a strong trend.
Negative divergence: If the EMAs are making new lows and the SMAs are still above, you might consider that the market is in a downtrend or correction.
3. Using EMAs as Dynamic Support and Resistance
EMAs can act as dynamic support and resistance in strong trends. If the price approaches a faster EMA from above and doesn’t break it, it could be a good entry point for a long position (buy). If the price approaches a slower EMA from below and doesn't break it, it could be a good point to sell (short).
Buy: If the price is above all EMAs and approaches the fastest EMA (e.g., EMA(9)), it could be a good buy point if the price bounces upward.
Sell: If the price is below all EMAs and approaches the fastest EMA, it could be a good sell point if the price bounces downward.
4. Combining SMAs and EMAs to Filter Signals
SMAs can serve as a trend filter to avoid trading in sideways markets. For example:
Bullish trend condition: If the longer-term SMAs (such as SMA(100) or SMA(200)) are below the price, and the shorter EMAs are aligned upward, you can look for buy signals.
Bearish trend condition: If the longer-term SMAs are above the price and the shorter EMAs are aligned downward, you can look for sell signals.
5. Consolidation Zone Between EMAs and SMAs
When the price moves between EMAs and SMAs without a clear trend (consolidation zone), you can expect a breakout. In this case, you can use the EMAs and SMAs to identify the direction of the breakout:
If the price is in a narrow range between the EMAs and SMAs and then breaks above the fastest EMA, it’s a sign that an upward trend may begin.
If the price breaks below the fastest EMA, it could indicate a potential downward trend.
6. "Golden Cross" and "Death Cross" Strategy
These are classic strategies based on crossovers between moving averages of different periods.
Golden Cross: Occurs when a faster EMA (e.g., EMA(50)) crosses above a slower SMA (e.g., SMA(200)), which suggests a potential bullish trend.
Death Cross: Occurs when a faster EMA crosses below a slower SMA, which suggests a potential bearish trend.
Additional Recommendations:
Combining with other indicators: You can combine EMA and SMA signals with other indicators like the RSI (Relative Strength Index) or MACD (Moving Average Convergence/Divergence) for confirmation and to avoid false signals.
Risk management: Always use stop-loss and take-profit orders to protect your capital. Moving averages are trend-following indicators but don’t guarantee that the price will move in the same direction.
Timeframe analysis: It’s recommended to use different timeframes to confirm the trend (e.g., use EMAs on hourly charts along with SMAs on daily charts).
VWAP
1. VWAP + EMAs for Trend Confirmation
VWAP can act as a trend filter, confirming the direction provided by the EMAs.
Buy Signal: If the price is above the VWAP and the EMAs are aligned in an uptrend (e.g., short-term EMAs are above longer-term EMAs), this indicates that the trend is bullish and you can look for buy opportunities.
Sell Signal: If the price is below the VWAP and the EMAs are aligned in a downtrend (e.g., short-term EMAs are below longer-term EMAs), this suggests a bearish trend and you can look for sell opportunities.
In this case, VWAP is used to confirm the overall trend. For example:
Bullish: Price above VWAP, EMAs aligned to the upside (e.g., EMA(9) > EMA(50) > EMA(200)), buy.
Bearish: Price below VWAP, EMAs aligned to the downside (e.g., EMA(9) < EMA(50) < EMA(200)), sell.
2. VWAP as Dynamic Support and Resistance
VWAP can act as a dynamic support or resistance level during the day. Combining this with EMAs and SMAs helps you refine your entry and exit points.
Support: If the price is above VWAP and starts pulling back to VWAP, it could act as support. If the price bounces off the VWAP and aligns with bullish EMAs (e.g., EMA(9) crossing above EMA(50)), you can consider entering a buy position.
Resistance: If the price is below VWAP and approaches VWAP from below, it can act as resistance. If the price fails to break through VWAP and aligns with bearish EMAs (e.g., EMA(9) crossing below EMA(50)), it could be a good signal for a sell.
RSI BB StdDev SignalOverview
The RSI BB StdDev Signal Indicator is a powerful tool designed to enhance your trading strategy by combining the Relative Strength Index (RSI) with Bollinger Bands (BB). This unique combination allows traders to identify potential buy and sell signals more accurately by leveraging the strengths of both indicators. The RSI helps in identifying overbought and oversold conditions, while the Bollinger Bands provide a dynamic range to assess volatility and potential price reversals.
Key Features
— RSI Calculation: The indicator calculates the RSI based on user-defined parameters, allowing for customization to fit different trading styles.
— Bollinger Bands Integration: The RSI values are smoothed using a moving average, and Bollinger Bands are applied to this smoothed RSI to generate buy and sell signals.
— Divergence Detection: The indicator includes an optional feature to detect and alert on bullish and bearish divergences between the RSI and price action.
— Customizable Alerts: Users can set up alerts for buy and sell signals, as well as for divergences, ensuring they never miss a trading opportunity.
— Visual Aids: The indicator plots the RSI, Bollinger Bands, and signals on the chart, making it easy to visualize and interpret the data.
How It Works
1. RSI Calculation:
— The RSI is calculated using the change in the source input (default is close price) over a specified period.
— The RSI values are then plotted on the chart with customizable overbought and oversold levels.
2. Smoothing and Bollinger Bands:
— The RSI values are smoothed using a moving average (SMA, EMA, SMMA, WMA, VWMA) selected by the user.
— Bollinger Bands are applied to the smoothed RSI to create dynamic upper and lower bands.
3. Signal Generation:
—Buy signals are generated when the RSI crosses above the lower Bollinger Band.
—Sell signals are generated when the RSI crosses below the upper Bollinger Band.
—These signals are plotted on both the RSI pane and the main price chart for easy reference.
4. Divergence Detection:
— The indicator can detect and alert on regular bullish and bearish divergences between the RSI and price action.
— Bullish divergences occur when the price makes a lower low, but the RSI makes a higher low.
— Bearish divergences occur when the price makes a higher high, but the RSI makes a lower high.
Usage
1. Setting Up:
— Add the indicator to your TradingView chart.
— Customize the RSI length, source, and other parameters in the settings panel.
— Enable or disable the divergence detection based on your trading strategy.
2. Interpreting Signals:
— Use the buy and sell signals generated by the RSI crossing the Bollinger Bands as potential entry and exit points.
— Pay attention to divergences for additional confirmation of trend reversals.
3. Alerts:
— Set up alerts for buy and sell signals to receive notifications in real-time.
— Enable divergence alerts to be notified of potential trend reversals.
Conclusion
The RSI BB StdDev Signal Indicator is a comprehensive tool that combines the strengths of the RSI and Bollinger Bands to provide traders with more accurate and reliable signals. Whether you are a beginner or an experienced trader, this indicator can enhance your trading strategy by offering clear visual cues and customizable alerts.
Note
This indicator is provided with open-source code, allowing users to understand its logic and customize it further if needed. The detailed description and customizable settings ensure that traders of all levels can benefit from its unique features.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
WVAD (Optimized Log Scaled)The WVAD (Optimized Log Scaled) indicator is a refined version of the classic Williams' Volume Accumulation/Distribution (WVAD). This version introduces logarithmic scaling for better visualization and usability, especially when dealing with large value ranges. It also includes EMA smoothing to highlight trends and reduce noise, providing traders with a more precise and clear representation of market dynamics.
Key Features:
1.Logarithmic Scaling:
Applies a log-based transformation to the WVAD values, ensuring extreme values are compressed while maintaining the overall structure of the data.
The log scaling allows better readability and interpretation, particularly for volatile or high-volume markets.
2.EMA Smoothing:
Uses an exponential moving average (EMA) to smooth the logarithmic WVAD values.
Helps reduce noise while preserving short-term trends, making it suitable for both trend-following and reversal strategies.
3.Customizable Parameters:
N (Lookback Period): Defines the accumulation period for calculating WVAD.
EMA Smoothing Period: Controls the sensitivity of the EMA applied to the logarithmic WVAD.
Decimal Places: Adjusts the precision of the displayed values for clearer visualization.
Line Colors: Fully customizable colors for both the raw WVAD line and the smoothed EMA.
4.Directional Preservation:
Keeps the positive and negative signs of WVAD to reflect accumulation (buying pressure) or distribution (selling pressure) in the market.
5.Zero Line Reference:
A horizontal zero line is plotted to help traders easily identify bullish (above 0) or bearish (below 0) market conditions.
How to Use:
Identify Trends: The smoothed WVAD line (EMA) can help detect trends or shifts in buying/selling pressure.
Crossovers: Use crossovers of the WVAD with the zero line as potential buy or sell signals.
Divergence: Spot divergences between price and the WVAD for early indications of reversals.
Applications:
Suitable for intraday, swing, or longer-term trading strategies.
Works across various asset classes, including stocks, commodities, and cryptocurrencies.
Adaptive DEMA Momentum Oscillator (ADMO)Overview:
The Adaptive DEMA Momentum Oscillator (ADMO) is an open-source technical analysis tool developed to measure market momentum using a Double Exponential Moving Average (DEMA) and adaptive standard deviation. By dynamically combining price deviation from the moving average with normalized standard deviation, ADMO provides traders with a powerful way to interpret market conditions.
Key Features:
Double Exponential Moving Average (DEMA):
The core calculation of the indicator is based on DEMA, which is known for being more responsive to price changes compared to traditional moving averages. This makes the ADMO capable of capturing trend momentum effectively.
Standard Deviation Integration:
A normalized standard deviation is used to adaptively weight the oscillator. This makes the indicator more sensitive to market volatility, enhancing responsiveness during high volatility and reducing sensitivity during calmer periods.
Oscillator Representation:
The final oscillator value is derived from the combination of the DEMA-based Z-score and the normalized standard deviation. This final value is visualized as a color-coded histogram, reflecting bullish or bearish momentum.
Color-Coded Histogram:
Bullish Momentum: Values above zero are colored using a customizable bullish color (default: light green).
Bearish Momentum: Values below zero are colored using a customizable bearish color (default: red).
How It Works:
Inputs:
DEMA Length: Defines the period used for calculating the Double Exponential Moving Average. It can be adjusted from 1 to 200 to suit different trading styles.
Standard Deviation Length: Sets the lookback period for standard deviation calculations, which influences the responsiveness of the oscillator.
Standard Deviation Weight (StdDev Weight): Controls the weight given to the normalized standard deviation, allowing customization of the oscillator's sensitivity to volatility.
Calculation Steps:
Double Exponential Moving Average Calculation:
The DEMA is calculated using two exponential moving averages, which helps in reducing lag compared to a simple moving average.
Z-score Calculation:
The Z-score is derived by comparing the difference between the DEMA and its smoothed average (LSMA) to the standard deviation. This indicates how far the current value is from the mean in units of standard deviation.
Normalized Standard Deviation:
The standard deviation is normalized by subtracting the mean standard deviation and dividing by the standard deviation of the values. This helps to make the oscillator adaptive to recent changes in volatility.
Final Oscillator Value:
The final value is calculated by multiplying the Z-score with a factor based on the normalized standard deviation, resulting in a momentum indicator that adapts to different market conditions.
Visualization:
Histogram: The oscillator is plotted as a histogram, with color-coded bars showing the strength and direction of market momentum.
Positive (bullish) values are shown in green, indicating upward momentum.
Negative (bearish) values are shown in red, indicating downward momentum.
Zero Line: A zero line is plotted to provide a reference point, helping users quickly determine whether the current momentum is bullish or bearish.
Example Use Cases:
Momentum Identification:
ADMO helps identify the current market momentum by dynamically adapting to changes in market volatility. When the histogram is above zero and green, it indicates bullish conditions, whereas values below zero and red suggest bearish momentum.
Volatility-Adjusted Signals:
The normalized standard deviation weighting allows the ADMO to provide more reliable signals during different market conditions. This makes it particularly useful for traders who want to be responsive to market volatility while avoiding false signals.
Trend Confirmation and Divergence:
ADMO can be used to confirm the strength of a trend or identify potential divergences between price and momentum. This helps traders spot potential reversal points or continuation signals.
Summary:
The Adaptive DEMA Momentum Oscillator (ADMO) offers a unique approach by combining momentum analysis with adaptive standard deviation. The integration of DEMA makes it responsive to price changes, while the standard deviation adjustment helps it stay relevant in both high and low volatility environments. It's a versatile tool for traders who need an adaptive, momentum-based approach to technical analysis.
Feel free to explore the code and adapt it to your trading strategy. The open-source nature of this tool allows you to adjust the settings and visualize the output to fit your personal trading preferences.
Chaikin's Money FlowOverview : Chaikin's Money Flow (CMF) is a momentum indicator that measures the buying and selling pressure of a financial instrument over a specified period. By incorporating both price and volume, CMF provides a comprehensive view of market sentiment, helping traders identify potential trend reversals and confirm the strength of existing trends.
Key Features:
Volume-Weighted : Unlike price-only indicators, CMF accounts for trading volume, offering deeper insights into the forces driving price movements.
Oscillatory Nature : CMF oscillates between positive and negative values, typically ranging from -100 to +100, indicating the balance between buying and selling pressure.
Trend Confirmation : Positive CMF values suggest accumulating buying pressure, while negative values indicate distributing selling pressure. This aids in confirming the direction and strength of trends.
Calculation Details :
Intraday Intensity (II) = 100 × (2×Close−High−Low) / (High−Low) × Volume
Condition: If High=Low, II is set to 0 to prevent division by zero.
II_smoothed = SMA(II, lookback)
Applies a Simple Moving Average (SMA) to the Intraday Intensity over the defined lookback period to smooth out short-term fluctuations.
Volume Smoothing:
V_smoothed = EMA(Volume, Volume Smoothing Period)
Utilizes an Exponential Moving Average (EMA) to smooth the volume over the specified smoothing period, giving more weight to recent data.
Money Flow Calculation:
Money Flow = II_smoothed / V_smoothed
Condition: If Vsmoothed=0Vsmoothed=0, Money Flow is set to 0 to avoid division by zero.
Usage Instructions:
Parameters Configuration:
Lookback Period: Determines the number of periods over which Intraday Intensity is averaged. A higher value results in a smoother indicator, reducing sensitivity to short-term price movements.
Volume Smoothing Period: Defines the period for the EMA applied to Volume. Adjusting this parameter affects the responsiveness of the Money Flow indicator to changes in trading volume.
Interpreting the Indicator:
Positive Values (>0): Indicate buying pressure. The higher the value, the stronger the buying interest.
Negative Values (<0): Signal selling pressure. The lower the value, the more intense the selling activity.
Crossovers: Watch for Money Flow crossing above the zero line as potential buy signals and crossing below as potential sell signals.
Divergence: Identify divergences between Money Flow and price movements to anticipate possible trend reversals.
Complementary Analysis:
Confluence with Other Indicators: Use CMF in conjunction with trend indicators like Moving Averages or oscillators like RSI to enhance signal reliability.
Volume Confirmation: CMF's volume-weighted approach makes it a powerful tool for confirming the validity of price trends and breakouts.
Acknowledgment: This implementation of Chaikin's Money Flow Indicator is inspired by and derived from the methodologies presented in "Statistically Sound Indicators" by Timothy Masters. The indicator has been meticulously translated to Pine Script to maintain the statistical integrity and effectiveness outlined in the source material.
Disclaimer: The Chaikin's Money Flow Indicator is a tool designed to assist in trading decisions. It does not guarantee profits and should be used in conjunction with other analysis methods. Trading involves risk, and it's essential to perform thorough testing and validation before deploying any indicator in live trading environments.
Composite Oscillation Indicator Based on MACD and OthersThis indicator combines various technical analysis tools to create a composite oscillator that aims to capture multiple aspects of market behavior. Here's a breakdown of its components:
* Individual RSIs (xxoo1-xxoo15): The code calculates the RSI (Relative Strength Index) of numerous indicators, including volume-based indicators (NVI, PVI, OBV, etc.), price-based indicators (CCI, CMO, etc.), and moving averages (WMA, ALMA, etc.). It also includes the RSI of the MACD histogram (xxoo14).
* Composite RSI (xxoojht): The individual RSIs are then averaged to create a composite RSI, aiming to provide a more comprehensive view of market momentum and potential turning points.
* MACD Line RSI (xxoo14): The RSI of the MACD histogram incorporates the momentum aspect of the MACD indicator into the composite measure.
* Double EMA (co, coo): The code employs two Exponential Moving Averages (EMAs) of the composite RSI, with different lengths (9 and 18 periods).
* Difference (jo): The difference between the two EMAs (co and coo) is calculated, aiming to capture the rate of change in the composite RSI.
* Smoothed Difference (xxp): The difference (jo) is further smoothed using another EMA (9 periods) to reduce noise and enhance the signal.
* RSI of Smoothed Difference (cco): Finally, the RSI is applied to the smoothed difference (xxp) to create the core output of the indicator.
Market Applications and Trading Strategies:
* Overbought/Oversold: The indicator's central line (plotted at 50) acts as a reference for overbought/oversold conditions. Values above 50 suggest potential overbought zones, while values below 50 indicate oversold zones.
* Crossovers and Divergences: Crossovers of the cco line above or below its previous bar's value can signal potential trend changes. Divergences between the cco line and price action can also provide insights into potential trend reversals.
* Emoji Markers: The code adds emoji markers ("" for bullish and "" for bearish) based on the crossover direction of the cco line. These can provide a quick visual indication of potential trend shifts.
* Colored Fill: The area between the composite RSI line (xxoojht) and the central line (50) is filled with color to visually represent the prevailing market sentiment (green for above 50, red for below 50).
Trading Strategies (Examples):
* Long Entry: Consider a long entry (buying) signal when the cco line crosses above its previous bar's value and the composite RSI (xxoojht) is below 50, suggesting a potential reversal from oversold conditions.
* Short Entry: Conversely, consider a short entry (selling) signal when the cco line crosses below its previous bar's value and the composite RSI (xxoojht) is above 50, suggesting a potential reversal from overbought conditions.
* Confirmation: Always combine the indicator's signals with other technical analysis tools and price action confirmation for better trade validation.
Additional Notes:
* The indicator offers a complex combination of multiple indicators. Consider testing and optimizing the parameters (EMAs, RSI periods) to suit your trading style and market conditions.
* Backtesting with historical data can help assess the indicator's effectiveness and identify potential strengths and weaknesses in different market environments.
* Remember that no single indicator is perfect, and the cco indicator should be used in conjunction with other forms of analysis to make informed trading decisions.
By understanding the logic behind this composite oscillator and its potential applications, you can incorporate it into your trading strategy to potentially identify trends, gauge market sentiment, and generate trading signals.
Hodrick-Prescott Cycle Component (YavuzAkbay)The Hodrick-Prescott Cycle Component indicator in Pine Script™ is an advanced tool that helps traders isolate and analyze the cyclical deviations in asset prices from their underlying trend. This script calculates the cycle component of the price series using the Hodrick-Prescott (HP) filter, allowing traders to observe and interpret the short-term price movements around the long-term trend. By providing two views—Percentage and Price Difference—this indicator gives flexibility in how these cyclical movements are visualized and interpreted.
What This Script Does
This indicator focuses exclusively on the cycle component of the price, which is the deviation of the current price from the long-term trend calculated by the HP filter. This deviation (or "cycle") is what traders analyze for mean-reversion opportunities and overbought/oversold conditions. The script allows users to see this deviation in two ways:
Percentage Difference: Shows the deviation as a percentage of the trend, giving a normalized view of the price’s distance from its trend component.
Price Difference: Shows the deviation in absolute price terms, reflecting how many price units the price is above or below the trend.
How It Works
Trend Component Calculation with the HP Filter: Using the HP filter, the script isolates the trend component of the price. The smoothness of this trend is controlled by the smoothness parameter (λ), which can be adjusted by the user. A higher λ value results in a smoother trend, while a lower λ value makes it more responsive to short-term changes.
Cycle Component Calculation: Percentage Deviation (cycle_pct) calculated as the difference between the current price and the trend, divided by the trend, and then multiplied by 100. This metric shows how far the price deviates from the trend in relative terms. Price Difference (cycle_price) simply the difference between the current price and the trend component, displaying the deviation in absolute price units.
Conditional Plotting: The user can choose to view the cycle component as either a percentage or a price difference by selecting the Display Mode input. The indicator will plot the chosen mode in a separate pane, helping traders focus on the preferred measure of deviation.
How to Use This Indicator
Identify Overbought/Oversold Conditions: When the cycle component deviates significantly from the zero line (shown with a dashed horizontal line), it may indicate overbought or oversold conditions. For instance, a high positive cycle component suggests the price may be overbought relative to the trend, while a large negative cycle suggests potential oversold conditions.
Mean-Reversion Strategy: In mean-reverting markets, traders can use this indicator to spot potential reversal points. For example, if the cycle component shows an extreme deviation from zero, it could signal that the price is likely to revert to the trend. This can help traders with entry and exit points when the asset is expected to correct back toward its trend.
Trend Strength and Cycle Analysis: By comparing the magnitude and duration of deviations, traders can gauge the strength of cycles and assess if a new trend might be forming. If the cycle component remains consistently positive or negative, it may indicate a persistent market bias, even as prices fluctuate around the trend.
Percentage vs. Price Difference Views: Use the Percentage Difference mode to standardize deviations and compare across assets or different timeframes. This is especially helpful when analyzing assets with varying price levels. Use the Price Difference mode when an absolute deviation (price units) is more intuitive for spotting overbought/oversold levels based on the asset’s actual price.
Using with Hodrick-Prescott: You can also use Hodrick-Prescott, another indicator that I have adapted to the Tradingview platform, to see the trend on the chart, and you can also use this indicator to see how far the price is deviating from the trend. This gives you a multifaceted perspective on your trades.
Practical Tips for Traders
Set the Smoothness Parameter (λ): Adjust the λ parameter to match your trading timeframe and asset characteristics. Lower values make the trend more sensitive, which might suit short-term trading, while higher values smooth out the trend for long-term analysis.
Cycle Component as Confirmation: Combine this indicator with other momentum or trend indicators for confirmation of overbought/oversold signals. For example, use the cycle component with RSI or MACD to validate the likelihood of mean-reversion.
Observe Divergences: Divergences between price movements and the cycle component can indicate potential reversals. If the price hits a new high, but the cycle component shows a smaller deviation than previous highs, it could signal a weakening trend.
Jason's Simple Moving Averages WaveUnderstanding the Script:
Purpose: This script identifies potential trend direction and momentum using a moving average and wave amplitude calculation. It shows a green line when the price is trending upwards and a red line when trending downwards.
Strategy: This script doesn't provide a complete trading strategy. It's an indicator designed to be used alongside other tools.
Parameters: You can adjust the "Moving Average Length" input to change the sensitivity of the indicator. A shorter length will react quicker to price changes, while a longer length will be smoother but less responsive.
How to Use it:
Load the Script: In TradingView, navigate to the indicator creation section and paste the provided script code.
Adjust Parameters: Set the "Moving Average Length" based on your preferred timeframe and trading style.
Combine with Other Tools: Use the indicator along with other technical indicators or price action analysis to confirm potential entry and exit points for trades.
Here are some additional points to consider:
Crossovers: You could look for buy signals when the price crosses above the green line and sell signals when it crosses below the red line. However, these can be prone to false signals.
Divergence: Look for divergences between the price movement and the wave indicator. For example, a rising price with a falling wave could indicate overbought conditions and a potential reversal.
Confirmation: Don't rely solely on this indicator. Use it alongside other confirmations from price action, volume analysis, or other indicators to identify higher probability trades.
Important Note:
Relative Strength with 3 SMAMansfield RS with 3 SMAs
Overview
The Mansfield Relative Strength (RS) indicator with three Simple Moving Averages (SMAs) enhances traditional RS analysis by adding more clarity and precision to trend identification. This personalized version aims to define RS trends more clearly and end them sooner, helping traders make better-informed decisions.
Key Features
Relative Strength Calculation:
Comparison: Calculates the RS of a chosen symbol against a benchmark (default: S&P 500).
Normalization: Uses the stock’s closing price divided by the closing price of the benchmark over a specified period.
Three SMAs:
Periods: Configurable periods for three SMAs (default: 10, 20, 50).
Trend Smoothing: SMAs help smooth the RS line, making it easier to spot trends and potential reversals.
Visualization:
Area Plot: The RS line is displayed as an area plot.
Color Coding: Different colors for each SMA to distinguish them easily (yellow, orange, purple).
Customization Options:
Comparative Symbol: Choose any benchmark symbol.
Period Adjustment: Customize the periods for both the RS calculation and the SMAs.
Visibility: Option to show or hide the SMAs.
How to Use
Setup:
Add to Chart: Apply the indicator to your TradingView chart.
Customize: Adjust the comparative symbol, RS period, and SMA periods as per your preference.
Interpretation:
Rising RS Line: Indicates the stock is outperforming the benchmark.
Falling RS Line: Suggests underperformance.
SMA Crossovers: Watch for the RS line crossing above or below the SMAs to signal potential buy or sell points.
Trend Direction: SMAs help confirm the trend direction. A rising RS line above the SMAs indicates a strong relative performance.
Trading Strategy:
Trend Confirmation: Use SMA crossovers to confirm trends.
Divergence: Identify divergences between the price action and the RS line for potential reversal signals.
Slow Volume Strength Index (SVSI)The Slow Volume Strength Index (SVSI), introduced by Vitali Apirine in Stocks & Commodities (Volume 33, Chapter 6, Page 28-31), is a momentum oscillator inspired by the Relative Strength Index (RSI). It gauges buying and selling pressure by analyzing the disparity between average volume on up days and down days, relative to the underlying price trend. Positive volume signifies closes above the exponential moving average (EMA), while negative volume indicates closes below. Flat closes register zero volume. The SVSI then applies a smoothing technique to this data and transforms it into an oscillator with values ranging from 0 to 100.
Traders can leverage the SVSI in several ways:
1. Overbought/Oversold Levels: Standard thresholds of 80 and 20 define overbought and oversold zones, respectively.
2. Centerline Crossovers and Divergences: Signals can be generated by the indicator line crossing a midline or by divergences from price movements.
3. Confirmation for Slow RSI: The SVSI can be used to confirm signals generated by the Slow Relative Strength Index (SRSI), another oscillator developed by Apirine.
🔹 Algorithm
In the original article, the SVSI is calculated using the following formula:
SVSI = 100 - (100 / (1 + SVS))
where:
SVS = Average Positive Volume / Average Negative Volume
* Volume is considered positive when the closing price is higher than the six-day EMA.
* Volume is considered negative when the closing price is lower than the six-day EMA.
* Negative volume values are expressed as absolute values (positive).
* If the closing price equals the six-day EMA, volume is considered zero (no change).
* When calculating the average volume, the indicator utilizes Wilder's smoothing technique, as described in his book "New Concepts In Technical Trading Systems."
Note that this indicator, the formula has been simplified to be
SVSI = 100 * Average Positive Volume / (Average Positive Volume + Average Negative Volume)
This formula achieves the same result as the original article's proposal, but in a more concise way and without the need for special handling of division by zero
🔹 Parameters
The SVSI calculation offers configurable parameters that can be adjusted to suit individual trading styles and goals. While the default lookback periods are 6 for the EMA and 14 for volume smoothing, alternative values can be explored. Additionally, the standard overbought and oversold thresholds of 80 and 20 can be adapted to better align with the specific security being analyzed.
Standardized Orderflow [AlgoAlpha]Introducing the Standardized Orderflow indicator by AlgoAlpha. This innovative tool is designed to enhance your trading strategy by providing a detailed analysis of order flow and velocity. Perfect for traders who seek a deeper insight into market dynamics, it's packed with features that cater to various trading styles. 🚀📊
Key Features:
📈 Order Flow Analysis: At its core, the indicator analyzes order flow, distinguishing between bullish and bearish volume within a specified period. It uses a unique standard deviation calculation for normalization, offering a clear view of market sentiment.
🔄 Smoothing Options: Users can opt for a smoothed representation of order flow, using a Hull Moving Average (HMA) for a more refined analysis.
🌪️ Velocity Tracking: The indicator tracks the velocity of order flow changes, providing insights into the market's momentum.
🎨 Customizable Display: Tailor the display mode to focus on either order flow, order velocity, or both, depending on your analysis needs.
🔔 Alerts for Critical Events: Set up alerts for crucial market events like crossover/crossunder of the zero line and overbought/oversold conditions.
How to Use:
1. Setup: Easily configure the indicator to match your trading strategy with customizable input parameters such as order flow period, smoothing length, and moving average types.
2. Interpretation: Watch for bullish and bearish columns in the order flow chart, utilize the Heiken Ashi RSI candle calculation, and look our for reversal notations for additional market insights.
3. Alerts: Stay informed with real-time alerts for key market events.
Code Explanation:
- Order Flow Calculation:
The core of the indicator is the calculation of order flow, which is the sum of volumes for bullish or bearish price movements. This is followed by normalization using standard deviation.
orderFlow = math.sum(close > close ? volume : (close < close ? -volume : 0), orderFlowWindow)
orderFlow := useSmoothing ? ta.hma(orderFlow, smoothingLength) : orderFlow
stdDev = ta.stdev(orderFlow, 45) * 1
normalizedOrderFlow = orderFlow/(stdDev + stdDev)
- Velocity Calculation:
The velocity of order flow changes is calculated using moving averages, providing a dynamic view of market momentum.
velocityDiff = ma((normalizedOrderFlow - ma(normalizedOrderFlow, velocitySignalLength, maTypeInput)) * 10, velocityCalcLength, maTypeInput)
- Display Options:
Users can choose their preferred display mode, focusing on either order flow, order velocity, or both.
orderFlowDisplayCond = displayMode != "Order Velocity" ? display.all : display.none
wideDisplayCond = displayMode != "Order Flow" ? display.all : display.none
- Reversal Indicators and Divergences:
The indicator also includes plots for potential bullish and bearish reversals, as well as regular and hidden divergences, adding depth to your market analysis.
bullishReversalCond = reversalType == "Order Flow" ? ta.crossover(normalizedOrderFlow, -1.5) : (reversalType == "Order Velocity" ? ta.crossover(velocityDiff, -4) : (ta.crossover(velocityDiff, -4) or ta.crossover(normalizedOrderFlow, -1.5)) )
bearishReversalCond = reversalType == "Order Flow" ? ta.crossunder(normalizedOrderFlow, 1.5) : (reversalType == "Order Velocity" ? ta.crossunder(velocityDiff, 4) : (ta.crossunder(velocityDiff, 4) or ta.crossunder(normalizedOrderFlow, 1.5)) )
In summary, the Standardized Orderflow indicator by AlgoAlpha is a versatile tool for traders aiming to enhance their market analysis. Whether you're focused on short-term momentum or long-term trends, this indicator provides valuable insights into market dynamics. 🌟📉📈
