MTF Volume Flow IndicatorThe MTF Volume Flow Indicator (MTF VFI) is an advanced and versatile tool that enhances market analysis by tracking the flow of volume across multiple timeframes. By integrating volume flow with multi-timeframe analysis, this indicator provides traders with a comprehensive understanding of market trends, momentum, and potential reversals.
Key Features
Multi-Timeframe Volume Flow Analysis: The MTF VFI computes the Volume Flow Indicator across various timeframes, ranging from 1 minute to 1 month. This multi-timeframe analysis enables traders to observe and compare volume flow dynamics across different time horizons, offering deeper insights into market behavior.
Customizable VFI Settings: The indicator includes configurable VFI parameters such as length, coefficient, and volume cutoff, allowing users to tailor the analysis to different market conditions and trading strategies. This flexibility ensures that the indicator remains relevant across diverse market environments.
Signal Line and Delta Calculations: The script features a signal line derived from the VFI and calculates the delta values (the difference between VFI and the signal line). These delta values are essential for identifying potential buy or sell signals and are presented as histograms for easy visual interpretation.
Cumulative Delta with Dynamic Bands: The indicator introduces cumulative delta, a powerful tool that combines average and median VFI values to provide a clearer picture of market sentiment. Two standard deviation bands are plotted around the cumulative delta, offering a range within which price movements are likely to remain. These bands are smoothed using a 21-period EMA, providing a more refined view of market volatility.
Multi-Timeframe and Analysis Tables: The MTF VFI includes optional tables that display VFI, signal line, and delta values across all selected timeframes. Additionally, an analysis table presents key statistical metrics such as the highest, lowest, average, standard deviation, range, and median VFI values. These tables provide a concise summary of market conditions, aiding in strategic decision-making.
Dynamic Display Options: The indicator offers extensive customization options, allowing traders to display or hide elements such as delta histograms, delta bands, and tables. This ensures that users can focus on the most relevant information for their trading strategy.
Neutral Candle Coloring Option: Traders can enable neutral candle colors, where bearish candles are gray and bullish candles are white. This feature helps to reduce noise and maintain focus on the overall trend and volume flow analysis.
How It Works
Volume Flow Indicator Calculation: The VFI is calculated using a combination of typical price, volume, and the standard deviation of price changes. The indicator smooths the VFI based on user preferences, allowing traders to adjust the sensitivity of the analysis to better match their trading style.
Multi-Timeframe Integration: The script pulls VFI calculations from multiple timeframes, providing a holistic view of market trends. By analyzing VFI across different timeframes, traders can detect alignments or divergences in volume flow that might indicate trend strength or weakness.
Cumulative Delta and Dynamic Bands: The cumulative delta is computed by combining the average and median VFI values. Dynamic two-standard-deviation bands are plotted around this cumulative delta, providing upper and lower bounds for expected price movements. These bands are further smoothed with a 21-period EMA, enhancing their effectiveness in volatile markets.
Delta Analysis and Histogram Display: The difference between the VFI and its signal line (delta) is calculated and displayed as histograms. This visual representation helps traders quickly assess momentum and identify potential reversals or trend continuations. The cumulative delta is color-coded dynamically based on its direction, adding an extra layer of visual clarity.
Alerts
VFI Crossover Alerts: The indicator includes customizable alerts that notify traders when the VFI crosses above or below its signal line. These alerts are crucial for catching potential trend reversals or continuation signals, even when the trader is not actively monitoring the chart.
Customizable Alert Conditions: Traders can tailor alert conditions to their preferred timeframes and VFI settings, ensuring that the notifications they receive are relevant and timely for their specific trading strategies.
Application
Trend Identification and Confirmation: The MTF VFI aids in identifying and confirming trends by analyzing volume flow across multiple timeframes. This capability is particularly useful for detecting trends that may not be visible on a single timeframe.
Momentum and Divergence Analysis: By comparing VFI and delta values across timeframes, and analyzing cumulative delta with dynamic bands, traders can gain insights into market momentum and potential divergences, which are often precursors to reversals.
Strategic Decision-Making: With its comprehensive multi-timeframe analysis, cumulative delta, and statistical summaries, the MTF VFI equips traders with the information needed to make informed trading decisions, whether for short-term trades or long-term investments.
Visual Clarity and Customization: The indicator’s dynamic display options and neutral candle coloring help traders maintain a clear and focused view of the market, customizing the visualization to match their specific needs.
The MTF Volume Flow Indicator (MTF VFI) by CryptoSea is an essential tool for traders who seek to gain a deeper understanding of market trends and volume dynamics across multiple timeframes. Its advanced features and customization options make it a valuable addition to any trader’s toolkit.
Cerca negli script per "Divergence"
FCNC SpreadTitle: FCNC Spread Indicator
Description:
The FCNC Spread Indicator is designed to help traders analyze the price difference (spread) between two futures contracts: the front contract and the next contract. This type of analysis is commonly used in futures trading to identify market sentiment, arbitrage opportunities, and potential roll yield strategies.
How It Works:
Front Contract: The front contract represents the futures contract closest to expiration, often referred to as the near-month contract.
Next Contract: The next contract is the futures contract that follows the front contract in the expiration cycle, typically the next available month.
Spread Calculation: frontContract - nextContract represents the difference between the price of the front contract and the next contract.
Positive Spread: A positive value means that the front contract is more expensive than the next contract, indicating backwardation.
Negative Spread: A negative value means that the front contract is cheaper than the next contract, indicating contango.
How to Use:
Input Selection: Select your desired futures contracts for the front and next contract through the input settings. The script will fetch and calculate the closing prices of these contracts.
Spread Plotting: The calculated spread is plotted on the chart, with color-coding based on the spread's value (green for positive, red for negative).
Labeling: The spread value is dynamically labeled on the chart for quick reference.
Moving Average: A 20-period Simple Moving Average (SMA) of the spread is also plotted to help identify trends and smooth out fluctuations.
Applications:
Trend Identification: Analyze the spread to determine market sentiment and potential trend reversals.
Divergence Detection: Look for divergences between the spread and the underlying market to identify possible shifts in trend or market sentiment. Divergences can signal upcoming reversals or provide early warning signs of a change in market dynamics.
This indicator is particularly useful for futures traders who are looking to gain insights into the market structure and to exploit differences in contract pricing. By providing a clear visualization of the spread between two key futures contracts, traders can make more informed decisions about their trading strategies.
SqueeZe Score [UAlgo]The "SqueeZe Score" is a script based on the "Squeeze Momentum Indicator". It utilizes Bollinger Bands (BB) and Keltner Channels (KC) to identify periods of low volatility, indicating potential upcoming price movements. The Z-Score method is employed to measure deviations from the mean, highlighting extreme price movements within the context of the current volatility environment. This script provides traders with visual cues for potential bullish and bearish divergences, aiding in decision-making during trading activities.
🔶Key Features:
SqueeZe Settings: Users can customize parameters such as the length and multiplier factors for Bollinger Bands and Keltner Channels, providing flexibility to adapt the indicator to different trading strategies and market conditions.
Divergence Detection: The script includes options to detect and display both bullish and bearish divergences, providing additional insights into potential trend reversals or continuations.
Customizable Z-Score Thresholds: Thresholds for the Z-Score are user-defined, enabling traders to set levels at which extreme price movements are highlighted on the chart, facilitating quick identification of significant market conditions.
🔶Credit:
This script is inspired by the work of @LazyBear, who contributed to the original concept and development of the Squeeze Momentum indicator.
🔶Disclaimer:
- The information provided by this script is for educational and informational purposes only and should not be construed as financial advice.
- Users are encouraged to conduct their own research and analysis before making any investment decisions.
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
Composite MomentumComposite Momentum Indicator - Enhancing Trading Insights with RSI & Williams %R
The Composite Momentum Indicator is a powerful technical tool that combines the Relative Strength Index (RSI) and Williams %R indicators from TradingView. This unique composite indicator offers enhanced insights into market momentum and provides traders with a comprehensive perspective on price movements. By leveraging the strengths of both RSI and Williams %R, the Composite Momentum Indicator offers distinct advantages over a simple RSI calculation.
1. Comprehensive Momentum Analysis:
The Composite Momentum Indicator integrates the RSI and Williams %R indicators to provide a comprehensive analysis of market momentum. It takes into account both the strength of recent price gains and losses (RSI) and the relationship between the current closing price and the highest-high and lowest-low price range (Williams %R). By combining these two momentum indicators, traders gain a more holistic view of market conditions.
2. Increased Accuracy:
While the RSI is widely used for measuring overbought and oversold conditions, it can sometimes generate false signals in certain market environments. The Composite Momentum Indicator addresses this limitation by incorporating the Williams %R, which focuses on the price range and can offer more accurate signals in volatile market conditions. This combination enhances the accuracy of momentum analysis, allowing traders to make more informed trading decisions.
3. Improved Timing of Reversals:
One of the key advantages of the Composite Momentum Indicator is its ability to provide improved timing for trend reversals. By incorporating both RSI and Williams %R, traders can identify potential turning points more effectively. The Composite Momentum Indicator offers an early warning system for identifying overbought and oversold conditions and potential trend shifts, helping traders seize opportunities with better timing.
4. Enhanced Divergence Analysis:
Divergence analysis is a popular technique among traders, and the Composite Momentum Indicator strengthens this analysis further. By comparing the RSI and Williams %R within the composite calculation, traders can identify divergences between the two indicators more easily. Divergence between the RSI and Williams %R can signal potential trend reversals or the weakening of an existing trend, providing valuable insights for traders.
5. Customizable Moving Average:
The Composite Momentum Indicator also features a customizable moving average (MA), allowing traders to further fine-tune their analysis. By incorporating the MA, traders can smooth out the composite momentum line and identify longer-term trends. This additional layer of customization enhances the versatility of the indicator, catering to various trading styles and timeframes.
The Composite Momentum Indicator, developed using the popular TradingView indicators RSI and Williams %R, offers a powerful tool for comprehensive momentum analysis. By combining the strengths of both indicators, traders can gain deeper insights into market conditions, improve accuracy, enhance timing for reversals, and leverage divergence analysis. With the added customization of the moving average, the Composite Momentum Indicator provides traders with a versatile and effective tool to make more informed trading decisions.
On-Balance Accumulation Distribution (Volume-Weighted)The On-Balance Accumulation Distribution (OBAD) indicator is designed to analyze the accumulation and distribution of assets based on volume-weighted price movements. The indicator helps traders identify periods of buying and selling pressure and assess the strength of market trends. By incorporating volume and price data, the OBAD indicator provides valuable insights into the flow of funds in the market.
To calculate the OBAD, the indicator multiplies the volume, price, and volume factor (user-defined) with the price change and aggregates the values over a specified length. This results in a histogram and a line plot representing the OBAD values. The OBAD signal line is derived by applying a simple moving average (SMA) to the OBAD values over a shorter period (9 by default). The crossover of the OBAD line and signal line can indicate potential entry or exit points.
The OBAD indicator utilizes coloration to enhance its visual representation and interpretation. The OBAD background is colored based on the relationship between the OBAD values and the OBAD signal line. When the OBAD values are above the signal line, the background is displayed in lime, suggesting a bullish accumulation scenario. Conversely, when the OBAD values are below the signal line, the background is colored fuchsia, indicating a bearish distribution pattern. The bar coloration is also applied to provide further visual cues, with lime representing bullish conditions and fuchsia denoting bearish conditions. When the OBAD signal line is above 0, it is colored green. Conversely, if the signal line is below 0, it is colored maroon.
The length parameter in the OBAD indicator determines the number of periods used in the calculation. Shorter lengths, such as 10 or 20, can make the indicator more responsive to recent price and volume changes, providing quicker signals. This can be beneficial for short-term traders or in fast-paced markets. Conversely, longer lengths, such as 50 or 100, smooth out the indicator and provide a broader view of accumulation and distribution over a more extended period. This may suit longer-term traders or when analyzing trends in less volatile markets. Traders should experiment with different lengths to find the optimal balance between responsiveness and smoothness that aligns with their trading goals.
The volume factor parameter allows traders to adjust the weighting of volume in the OBAD calculation. By modifying this factor, traders can emphasize the impact of volume on the indicator. Increasing the volume factor amplifies the influence of volume in the OBAD calculation, making it more sensitive to volume changes. This can be advantageous when volume is considered a significant driver of price movements, such as during news events or market catalysts. On the other hand, decreasing the volume factor reduces the impact of volume, making the indicator less sensitive to volume fluctuations. Traders can experiment with different volume factors to align the indicator's responsiveness with their analysis of volume patterns and its importance in their trading decisions.
The signal line period parameter determines the number of periods used to calculate the moving average of the OBAD values. Adjusting this parameter can help smooth out the indicator and filter out short-term noise or provide more timely signals. A shorter signal line period, such as 5 or 7, provides more sensitive and frequent crossovers with the OBAD values, potentially offering early entry or exit signals. This can be useful for traders seeking shorter-term trades or more agile trading strategies. Conversely, a longer signal line period, such as 9 or 14, smooths out the indicator and provides more stable signals. This may suit traders who prefer longer-term trends or a more conservative approach. Traders should consider their trading timeframe and the desired balance between responsiveness and stability when adjusting the signal line period.
The OBAD indicator can be applied in various trading strategies and scenarios. It helps traders identify potential trend reversals, confirm existing trends, and generate entry and exit signals. For example, when the OBAD histogram transitions from fuchsia to lime, it may suggest a shift from selling to buying pressure, signaling a potential buying opportunity. Traders can also use the OBAD indicator in conjunction with other technical analysis tools, such as trendlines or support/resistance levels, to confirm signals and make more informed trading decisions.
-- Trend Reversal Identification : The OBAD indicator can be useful in identifying potential trend reversals. When the OBAD values cross above the signal line after being below it, it may suggest a shift from bearish distribution to bullish accumulation. Conversely, when the OBAD values cross below the signal line after being above it, it may indicate a transition from bullish accumulation to bearish distribution. Traders can use these crossovers as potential signals to enter or exit trades in anticipation of a trend reversal.
-- Confirmation of Trend Strength : The OBAD indicator can act as a confirmation tool for assessing the strength of existing trends. When the OBAD values remain consistently above the signal line, it confirms the presence of strong bullish accumulation and validates the upward trend. Similarly, when the OBAD values stay consistently below the signal line, it confirms the presence of strong bearish distribution and validates the downward trend. Traders can use this confirmation to have more confidence in the prevailing trend and adjust their trading strategies accordingly.
-- Divergence Analysis : Divergence between the price and the OBAD indicator can provide valuable insights. Bullish divergence occurs when the price forms lower lows while the OBAD indicator forms higher lows, suggesting a potential trend reversal to the upside. Conversely, bearish divergence occurs when the price forms higher highs while the OBAD indicator forms lower highs, indicating a potential trend reversal to the downside. Traders can use these divergences as additional confirmation signals in their trading decisions.
-- Volume Analysis : The OBAD indicator incorporates volume data, making it particularly useful for volume analysis. Traders can analyze the relationship between OBAD values and volume levels to gauge the strength and validity of price movements. Higher OBAD values accompanied by higher volume can indicate strong accumulation or distribution, providing confirmation for potential trade setups. On the other hand, lower OBAD values accompanied by low volume may suggest a lack of participation and potentially signal caution in trading decisions.
It is important to note that the OBAD indicator, like any other technical indicator, has certain limitations. It relies on historical price and volume data, which may not always accurately reflect current market conditions or future price movements. Traders should exercise caution and use the OBAD indicator in conjunction with other analysis techniques and risk management strategies. Additionally, customization of the OBAD parameters, such as adjusting the length or volume factor, can provide flexibility to adapt the indicator to different market conditions and trading preferences.
Overall, the OBAD indicator serves as a valuable tool for traders to gauge the accumulation and distribution patterns in the market. Its calculation based on volume-weighted price movements and the coloration enhancements make it visually appealing and intuitive to interpret. By incorporating the OBAD indicator into trading strategies and considering its limitations, traders can potentially improve their decision-making process and enhance their trading outcomes.
Crypto McClellan Oscillator (SLN Fix)This is an adaption of the Mcclellan Oscillator for crypto. Instead of tracking the S&P500 it tracks a selection of cryptos to make sure the indicator follows this sector instead.
Full credit goes to the creator of this indicator: Fadior. It has since been fixed by SLN.
The following description explains the standard McClellan Oscillator. Full credit to Investopedia , my fav source of financial explanations.
The same principles applies to its use in the crypto sector, but please be cautious of the last point, the limitations. Since crypto is more volatile, that could amplify choppy behavior.
This is not financial advice, please be extremely cautious. This indicator is only suitable as a confirmation signal and needs support of other signals to be profitable.
This indicator usually produces the best signals on slightly above daily time frame. I personally like 2 or 3 day, but you have to find the settings suitable for your trading style.
What Is the McClellan Oscillator?
The McClellan Oscillator is a market breadth indicator that is based on the difference between the number of advancing and declining issues on a stock exchange, such as the New York Stock Exchange (NYSE) or NASDAQ.
The indicator is used to show strong shifts in sentiment in the indexes, called breadth thrusts. It also helps in analyzing the strength of an index trend via divergence or confirmation.
The McClellan Oscillator formula can be applied to any stock exchange or group of stocks.
A reading above zero helps confirm a rise in the index, while readings below zero confirm a decline in the index.
When the index is rising but the oscillator is falling, that warns that the index could start declining too. When the index is falling and the oscillator is rising, that indicates the index could start rising soon. This is called divergence.
A significant change, such as moving 100 points or more, from a negative reading to a positive reading is called a breadth thrust. It may indicate a strong reversal from downtrend to uptrend is underway on the stock exchange.
How to Calculate the McClellan Oscillator
To get the calculation started, track Advances - Declines on a stock exchange for 19 and 39 days. Calculate a simple average for these, not exponential moving average (EMA).
Use these simple values as the Prior Day EMA values in the 19- and 39-day EMA formulas.
Calculate the 19- and 39-day EMAs.
Calculate the McClellan Oscillator value.
Now that the value has been calculated, on the next calculation use this value for the Prior Day EMA. Start calculating EMAs for the formula instead of simple averages.
If using the adjusted formula, the steps are the same, except use ANA instead of using Advances - Declines.
What Does the McClellan Oscillator Tell You?
The McClellan Oscillator is an indicator based on market breadth which technical analysts can use in conjunction with other technical tools to determine the overall state of the stock market and assess the strength of its current trend.
Since the indicator is based on all the stocks in an exchange, it is compared to the price movements of indexes that reflect that exchange, or compared to major indexes such as the S&P 500.
Positive and negative values indicate whether more stocks, on average, are advancing or declining. The indicator is positive when the 19-day EMA is above the 39-day EMA, and negative when the 19-day EMA is below the 39-day EMA.
A positive and rising indicator suggests that stocks on the exchange are being accumulated. A negative and falling indicator signals that stocks are being sold. Typically such action confirms the current trend in the index.
Crossovers from positive to negative, or vice versa, may signal the trend has changed in the index or exchange being tracked. When the indicator makes a large move, typically of 100 points or more, from negative to positive territory, that is called a breadth thrust.
It means a large number of stocks moved up after a bearish move. Since the stock market tends to rise over time, this a positive signal and may indicate that a bottom in the index is in and prices are heading higher overall.
When index prices and the indicator are moving in different directions, then the current index trend may lack strength. Bullish divergence occurs when the oscillator is rising while the index is falling. This indicates the index could head higher soon since more stocks are starting to advance.
Bearish divergence is when the index is rising and the indicator is falling. This means fewer stocks are keeping the advance going and prices may start to head lower.
Limitations of Using the McClellan Oscillator
The indicator tends to produce lots of signals. Breadth thrusts, divergence, and crossovers all occur with some frequency, but not all these signals will result in the price/index moving in the expected direction.
The indicator is prone to producing false signals and therefore should be used in conjunction with price action analysis and other technical indicators.
The indicator can also be quite choppy, moving between positive and negative territory rapidly. Such action indicates a choppy market, but this isn't evident until the indicator has made this whipsaw move a few times.
Good luck and a big thanks to Fadior!
Volume-Supported Linear Regression TrendHello Traders,
Linear Regression gives us some abilities to calculate the trend and if we combine it with volume then we may get very good results. Because if there is no volume support at up/downtrends then the trend may have a reversal soon. we also need to check the trend in different periods. With all this info, I developed Volume-Supported Linear Regression Trend script. The script checks linear regression of price and volume and then calculates trend direction and strength.
You have option to set Source, Short-Term Period and Long-Term Period. you can set them as you wish.
By default:
Close is used as "Source"
Short-Term Period is 20
Long-Term Period is 50
in following screenshot I tried to explain short term trend (for uptrend). Volume supports the trend? any volume pressure on trend? possible reversal? same idea while there is downtrend.
in following screenshot I tried to explain long term trend:
You can also check Positive/Negative Divergences to figure out possible reversals (to automate it, you can use Divergence for Many Indicators v4 , it has ability to check divergences on external indicators)
Enjoy!
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
---
6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
---
7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
---
8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
---
9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
---
10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
---
11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
---
12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
---
13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
---
14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
---
• .
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
---
Advanced Petroleum Market Model (APMM)Advanced Petroleum Market Model (APMM): A Multi-Factor Fundamental Analysis Framework for Oil Market Assessment
## 1. Introduction
The petroleum market represents one of the most complex and globally significant commodity markets, characterized by intricate supply-demand dynamics, geopolitical influences, and substantial price volatility (Hamilton, 2009). Traditional fundamental analysis approaches often struggle to synthesize the multitude of relevant indicators into actionable insights due to data heterogeneity, temporal misalignment, and subjective weighting schemes (Baumeister & Kilian, 2016).
The Advanced Petroleum Market Model addresses these limitations through a systematic, quantitative approach that integrates 16 verified fundamental indicators across five critical market dimensions. The model builds upon established financial engineering principles while incorporating petroleum-specific market dynamics and adaptive learning mechanisms.
## 2. Theoretical Framework
### 2.1 Market Efficiency and Information Integration
The model operates under the assumption of semi-strong market efficiency, where fundamental information is gradually incorporated into prices with varying degrees of lag (Fama, 1970). The petroleum market's unique characteristics, including storage costs, transportation constraints, and geopolitical risk premiums, create opportunities for fundamental analysis to provide predictive value (Kilian, 2009).
### 2.2 Multi-Factor Asset Pricing Theory
Drawing from Ross's (1976) Arbitrage Pricing Theory, the model treats petroleum prices as driven by multiple systematic risk factors. The five-factor decomposition (Supply, Inventory, Demand, Trade, Sentiment) represents economically meaningful sources of systematic risk in petroleum markets (Chen et al., 1986).
## 3. Methodology
### 3.1 Data Sources and Quality Framework
The model integrates 16 fundamental indicators sourced from verified TradingView economic data feeds:
Supply Indicators:
- US Oil Production (ECONOMICS:USCOP)
- US Oil Rigs Count (ECONOMICS:USCOR)
- API Crude Runs (ECONOMICS:USACR)
Inventory Indicators:
- US Crude Stock Changes (ECONOMICS:USCOSC)
- Cushing Stocks (ECONOMICS:USCCOS)
- API Crude Stocks (ECONOMICS:USCSC)
- API Gasoline Stocks (ECONOMICS:USGS)
- API Distillate Stocks (ECONOMICS:USDS)
Demand Indicators:
- Refinery Crude Runs (ECONOMICS:USRCR)
- Gasoline Production (ECONOMICS:USGPRO)
- Distillate Production (ECONOMICS:USDFP)
- Industrial Production Index (FRED:INDPRO)
Trade Indicators:
- US Crude Imports (ECONOMICS:USCOI)
- US Oil Exports (ECONOMICS:USOE)
- API Crude Imports (ECONOMICS:USCI)
- Dollar Index (TVC:DXY)
Sentiment Indicators:
- Oil Volatility Index (CBOE:OVX)
### 3.2 Data Quality Monitoring System
Following best practices in quantitative finance (Lopez de Prado, 2018), the model implements comprehensive data quality monitoring:
Data Quality Score = Σ(Individual Indicator Validity) / Total Indicators
Where validity is determined by:
- Non-null data availability
- Positive value validation
- Temporal consistency checks
### 3.3 Statistical Normalization Framework
#### 3.3.1 Z-Score Normalization
The model employs robust Z-score normalization as established by Sharpe (1994) for cross-indicator comparability:
Z_i,t = (X_i,t - μ_i) / σ_i
Where:
- X_i,t = Raw value of indicator i at time t
- μ_i = Sample mean of indicator i
- σ_i = Sample standard deviation of indicator i
Z-scores are capped at ±3 to mitigate outlier influence (Tukey, 1977).
#### 3.3.2 Percentile Rank Transformation
For intuitive interpretation, Z-scores are converted to percentile ranks following the methodology of Conover (1999):
Percentile_Rank = (Number of values < current_value) / Total_observations × 100
### 3.4 Exponential Smoothing Framework
Signal smoothing employs exponential weighted moving averages (Brown, 1963) with adaptive alpha parameter:
S_t = α × X_t + (1-α) × S_{t-1}
Where α = 2/(N+1) and N represents the smoothing period.
### 3.5 Dynamic Threshold Optimization
The model implements adaptive thresholds using Bollinger Band methodology (Bollinger, 1992):
Dynamic_Threshold = μ ± (k × σ)
Where k is the threshold multiplier adjusted for market volatility regime.
### 3.6 Composite Score Calculation
The fundamental score integrates component scores through weighted averaging:
Fundamental_Score = Σ(w_i × Score_i × Quality_i)
Where:
- w_i = Normalized component weight
- Score_i = Component fundamental score
- Quality_i = Data quality adjustment factor
## 4. Implementation Architecture
### 4.1 Adaptive Parameter Framework
The model incorporates regime-specific adjustments based on market volatility:
Volatility_Regime = σ_price / μ_price × 100
High volatility regimes (>25%) trigger enhanced weighting for inventory and sentiment components, reflecting increased market sensitivity to supply disruptions and psychological factors.
### 4.2 Data Synchronization Protocol
Given varying publication frequencies (daily, weekly, monthly), the model employs forward-fill synchronization to maintain temporal alignment across all indicators.
### 4.3 Quality-Adjusted Scoring
Component scores are adjusted for data quality to prevent degraded inputs from contaminating the composite signal:
Adjusted_Score = Raw_Score × Quality_Factor + 50 × (1 - Quality_Factor)
This formulation ensures that poor-quality data reverts toward neutral (50) rather than contributing noise.
## 5. Usage Guidelines and Best Practices
### 5.1 Configuration Recommendations
For Short-term Analysis (1-4 weeks):
- Lookback Period: 26 weeks
- Smoothing Length: 3-5 periods
- Confidence Period: 13 weeks
- Increase inventory and sentiment weights
For Medium-term Analysis (1-3 months):
- Lookback Period: 52 weeks
- Smoothing Length: 5-8 periods
- Confidence Period: 26 weeks
- Balanced component weights
For Long-term Analysis (3+ months):
- Lookback Period: 104 weeks
- Smoothing Length: 8-12 periods
- Confidence Period: 52 weeks
- Increase supply and demand weights
### 5.2 Signal Interpretation Framework
Bullish Signals (Score > 70):
- Fundamental conditions favor price appreciation
- Consider long positions or reduced short exposure
- Monitor for trend confirmation across multiple timeframes
Bearish Signals (Score < 30):
- Fundamental conditions suggest price weakness
- Consider short positions or reduced long exposure
- Evaluate downside protection strategies
Neutral Range (30-70):
- Mixed fundamental environment
- Favor range-bound or volatility strategies
- Wait for clearer directional signals
### 5.3 Risk Management Considerations
1. Data Quality Monitoring: Continuously monitor the data quality dashboard. Scores below 75% warrant increased caution.
2. Regime Awareness: Adjust position sizing based on volatility regime indicators. High volatility periods require reduced exposure.
3. Correlation Analysis: Monitor correlation with crude oil prices to validate model effectiveness.
4. Fundamental-Technical Divergence: Pay attention when fundamental signals diverge from technical indicators, as this may signal regime changes.
### 5.4 Alert System Optimization
Configure alerts conservatively to avoid false signals:
- Set alert threshold at 75+ for high-confidence signals
- Enable data quality warnings to maintain system integrity
- Use trend reversal alerts for early regime change detection
## 6. Model Validation and Performance Metrics
### 6.1 Statistical Validation
The model's statistical robustness is ensured through:
- Out-of-sample testing protocols
- Rolling window validation
- Bootstrap confidence intervals
- Regime-specific performance analysis
### 6.2 Economic Validation
Fundamental accuracy is validated against:
- Energy Information Administration (EIA) official reports
- International Energy Agency (IEA) market assessments
- Commercial inventory data verification
## 7. Limitations and Considerations
### 7.1 Model Limitations
1. Data Dependency: Model performance is contingent on data availability and quality from external sources.
2. US Market Focus: Primary data sources are US-centric, potentially limiting global applicability.
3. Lag Effects: Some fundamental indicators exhibit publication lags that may delay signal generation.
4. Regime Shifts: Structural market changes may require model recalibration.
### 7.2 Market Environment Considerations
The model is optimized for normal market conditions. During extreme events (e.g., geopolitical crises, pandemics), additional qualitative factors should be considered alongside quantitative signals.
## References
Baumeister, C., & Kilian, L. (2016). Forty years of oil price fluctuations: Why the price of oil may still surprise us. *Journal of Economic Perspectives*, 30(1), 139-160.
Bollinger, J. (1992). *Bollinger on Bollinger Bands*. McGraw-Hill.
Brown, R. G. (1963). *Smoothing, Forecasting and Prediction of Discrete Time Series*. Prentice-Hall.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. *Journal of Business*, 59(3), 383-403.
Conover, W. J. (1999). *Practical Nonparametric Statistics* (3rd ed.). John Wiley & Sons.
Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. *Journal of Finance*, 25(2), 383-417.
Hamilton, J. D. (2009). Understanding crude oil prices. *Energy Journal*, 30(2), 179-206.
Kilian, L. (2009). Not all oil price shocks are alike: Disentangling demand and supply shocks in the crude oil market. *American Economic Review*, 99(3), 1053-1069.
Lopez de Prado, M. (2018). *Advances in Financial Machine Learning*. John Wiley & Sons.
Ross, S. A. (1976). The arbitrage theory of capital asset pricing. *Journal of Economic Theory*, 13(3), 341-360.
Sharpe, W. F. (1994). The Sharpe ratio. *Journal of Portfolio Management*, 21(1), 49-58.
Tukey, J. W. (1977). *Exploratory Data Analysis*. Addison-Wesley.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
Rendon1 Swing Market Turns**Swing Market Turns Indicator**
This indicator identifies potential swing highs and swing lows by integrating Relative Strength Index (RSI), volume confirmation, and higher timeframe (HTF) levels to accurately detect market reversals and turning points. Specifically optimized for swing traders, this tool aims to pinpoint moments when price momentum is shifting, providing clear signals for trade entries and exits.
### How It Works:
- **RSI Divergence:** Detects momentum shifts through RSI overbought and oversold conditions.
- **Higher Timeframe Levels:** Confirms reversals using support and resistance levels from higher timeframes.
- **Volume Confirmation:** Ensures stronger validity of signals by checking if current volume exceeds the moving average of recent volume.
### Key Features:
- Visual labels on chart clearly indicating potential swing highs and lows.
- Customizable RSI period, RSI overbought/oversold thresholds, volume moving average length, and higher timeframe selections.
- Built-in alert conditions for immediate notifications when swing opportunities are detected.
### Recommended Use:
- Ideal for traders focusing on swing trading strategies, particularly those looking for high-probability turning points.
- Effective across multiple assets including forex, stocks, commodities, and crypto.
- Suitable for various intraday and higher timeframes, with customization options available.
### Settings:
- **RSI Period:** Adjust the sensitivity of RSI calculation.
- **Higher Timeframe:** Select the timeframe used for support/resistance reference.
- **RSI Overbought/Oversold:** Customize thresholds defining extreme RSI values.
- **Volume MA Length:** Specify the length for volume moving average calculation.
Feel free to customize the parameters to best fit your trading style and asset of choice.
**Disclaimer:**
This indicator does not guarantee profitable trades and should be used in conjunction with proper risk management and additional analysis methods.
Nasan Ultimate Health Index (NUHI)The Nasan Ultimate Health Index (NUHI) is a technical indicator designed to measure the relative health of a stock compared to a benchmark index or sector. By incorporating price action, volume dynamics, and volatility, NUHI provides traders with a clearer picture of a stock’s performance relative to the broader market.
The NUHI is based on the idea that a stock’s relative strength and momentum can be assessed more effectively when adjusted for volume behavior and benchmark comparison. Instead of looking at price movement alone, this indicator factors in:
The stock’s price trend (via EMA)
Volume participation (green vs. red volume) and volume ratio - SMA(volume, 21)/ SMA(volume, 252)
Volatility-adjusted performance (ATR-based scaling)
Comparison with a selected benchmark (e.g., SPX, NDX, sector ETFs)
This results in a normalized and comparative score that helps traders identify outperforming, neutral, and underperforming stocks within a specific market environment.
The NUHI is constructed using the following elements:
1️⃣ Stock Raw Score (Unadjusted Momentum)
The exponential moving average (EMA) of the hlc3 (average of high, low, close) is used to define the price trend.
The difference between the current EMA and the EMA from n bars ago shows whether the stock is gaining or losing momentum.
This difference is divided by the ATR (Average True Range) to adjust for volatility.
2️⃣ Volume Behavior Adjustment
Volume is split into green volume (up candles) and red volume (down candles).
The ratio of green to red volume determines whether buyers or sellers dominate over the selected period (n bars).
If the stock is in an uptrend, green volume is weighted higher; if in a downtrend, red volume is weighted higher.
The stock’s Volume Ratio (short-term SMA divided by long-term SMA) is adjusted based on this weight.
3️⃣ Benchmark Comparison
A similar Raw Score calculation is performed on the selected benchmark (SPX, NDX, or sector ETF).
Benchmark price movements, volume behavior, and ATR adjustments mirror the stock’s calculations.
This provides a reference point for evaluating the stock’s relative strength.
4️⃣ Normalization Process
Both the stock and benchmark raw scores are min-max normalized over the past 252 bars (1-year lookback).
This scales values between 0 and 1, ensuring fair comparisons regardless of absolute price differences.
5️⃣ NUHI Calculation
The final NUHI value is computed using a logarithmic ratio between the normalized stock score and the normalized benchmark score:
This transformation ensures a more symmetrical representation of overperformance and underperformance.
Performance Zones
Strong Outperforming (NUHI between >0.41 and 0.69)
Leading (NUHI between >0.10 and 0.41)
Transitioning Outperformance (NUHI between 0.10 and 0)
Equilibrium (NUHI 0)
Transitioning Underperformance (NUHI between -0.10 and 0)
Lagging (NUHI between < -0.1 and -0.41)
Strong Underperforming (NUHI between< -0.41 and -0.69 )
How to Use NUHI
✅ Identifying Strong Stocks
If NUHI > 0, the stock is outperforming its benchmark.
If NUHI < 0, the stock is underperforming the benchmark.
✅ Trend Confirmation
A steadily rising NUHI and raw score (colored green) suggests sustained strength bullish conditions.
A falling NUHI and raw score (colored orange) indicates weakness and possible rotation into other assets.
✅ Finding Reversals
Bullish Divergence: If NUHI is improving while the stock’s raw score is negative, it may signal a bottoming opportunity.
Bearish Signs: If NUHI is dropping despite price strength, it could hint at underlying weakness.
Why a Stock in a Downtrend Can Have NUHI > 0 (and Vice Versa )
NUHI measures performance relative to both its own history and the benchmark.
A stock’s recent movement is compared to how it usually behaves and how the benchmark is performing.
Example Scenarios:
Stock in a Downtrend but NUHI > 0
The stock may still be in a downtrend (negative raw score), but it’s performing better relative to its past downtrend behavior and better than the benchmark over the same period.
This could mean it’s showing relative strength compared to the broader market or sector.
Stock in an Uptrend but NUHI < 0
Even in a uptrend (positive raw score), the stock might be underperforming relative to its past uptrend behavior and underperforming the benchmark.
What This Means:
NUHI > 0 in a downtrend → The stock is falling less aggressively than usual and/or holding up better than the benchmark.
NUHI < 0 in an uptrend → The stock is gaining less than expected based on its history and/or lagging behind the benchmark.
NUHI helps identify relative strength or weakness .
GSD by MATAGSD by MATA - Gold-Sensitive Divergence Indicator
Overview:
The GSD by MATA indicator is designed to analyze the inverse correlation between an instrument’s price movement and gold (XAU/USD) over a selected time period. It helps traders identify whether the instrument tends to move in the opposite direction of gold, providing insights into potential hedging opportunities or market sentiment shifts.
How It Works:
User-Defined Time Period:
The user selects a time frame for comparison (1 Day, 1 Week, 1 Month, 3 Months, 6 Months, or 12 Months).
The indicator calculates the percentage change in both the instrument’s price and gold price over this period.
Inverse Movement Calculation:
If gold increases and the instrument decreases, the indicator registers a negative inverse change.
If gold decreases and the instrument increases, the indicator registers a positive inverse change.
If both move in the same direction, no inverse movement is recorded.
Cumulative Tracking:
The Reverse Change line shows the instant inverse movement.
The Total Change line accumulates the inverse movements over time, helping traders spot trends and long-term divergences.
How to Use:
A rising Total Change line (green) suggests that the instrument frequently moves in the opposite direction of gold, indicating a possible hedge effect.
A falling Total Change line (red) means the instrument has been moving in sync with gold rather than diverging.
The 0 reference line helps identify whether the cumulative effect is positive or negative over time.
ELHAI Futures Trend Checker (ES, NQ, YM)The ELHAI Futures Trend Checker is a powerful TradingView indicator designed for futures traders who want to monitor the trend synchronization of the three major U.S. futures indices:
✅ E-mini S&P 500 (ES1!)
✅ E-mini Nasdaq 100 (NQ1!)
✅ E-mini Dow Jones (YM1!)
This indicator checks whether all three futures indices are bullish or bearish during each candle formation. If one of them is out of sync (e.g., two indices are bullish while one is bearish), the indicator triggers an alert and highlights the background in red, helping traders identify potential market indecision or divergence.
Key Features
📌 Designed for Futures Traders – Focuses on ES, NQ, and YM futures contracts.
📌 Live Market Monitoring – Works in real-time and updates dynamically with each tick.
📌 Bullish/Bearish Trend Confirmation – Detects when all three indices are in sync.
📌 Mismatch Detection – Alerts you when at least one index is out of trend.
📌 Custom Alerts – Set up TradingView alerts to be notified instantly when a trend mismatch occurs.
📌 Visual Background Highlight – A red background warns of a market divergence.
How It Works
The script retrieves open and close prices for ES, NQ, and YM.
Determines whether each futures index is bullish (close > open) or bearish (close < open).
If all three indices are bullish or all are bearish, it remains neutral.
If one index is different, an alert is triggered and the background turns red.
How to Use
Apply the indicator to your TradingView chart.
Choose any timeframe – Works well on intraday, daily, or higher timeframes.
Enable alerts: Go to Alerts → Create Alert, select "Futures Trend Mismatch", and set your preferred alert frequency.
Use alongside other indicators like moving averages, RSI, or MACD for better trade confirmation.
Best Use Cases
✔ Day traders & scalpers – Quickly spot market divergence in live trading.
✔ Swing traders – Identify when futures markets lose synchronization.
✔ Trend followers – Confirm if all major futures markets are aligned before making a move.
Final Notes
This indicator was built for Elhai to provide real-time trend analysis across major U.S. futures indices. Use it as a confirmation tool to improve market timing and decision-making.
Multi-indicator Signal Builder [Skyrexio]Overview
Multi-Indicator Signal Builder is a versatile, all-in-one script designed to streamline your trading workflow by combining multiple popular technical indicators under a single roof. It features a single-entry, single-exit logic, intrabar stop-loss/take-profit handling, an optional time filter, a visually accessible condition table, and a built-in statistics label. Traders can choose any combination of 12+ indicators (RSI, Ultimate Oscillator, Bollinger %B, Moving Averages, ADX, Stochastic, MACD, PSAR, MFI, CCI, Heikin Ashi, and a “TV Screener” placeholder) to form entry or exit conditions. This script aims to simplify strategy creation and analysis, making it a powerful toolkit for technical traders.
Indicators Overview
1. RSI (Relative Strength Index)
Measures recent price changes to evaluate overbought or oversold conditions on a 0–100 scale.
2. Ultimate Oscillator (UO)
Uses weighted averages of three different timeframes, aiming to confirm price momentum while avoiding false divergences.
3. Bollinger %B
Expresses price relative to Bollinger Bands, indicating whether price is near the upper band (overbought) or lower band (oversold).
4. Moving Average (MA)
Smooths price data over a specified period. The script supports both SMA and EMA to help identify trend direction and potential crossovers.
5. ADX (Average Directional Index)
Gauges the strength of a trend (0–100). Higher ADX signals stronger momentum, while lower ADX indicates a weaker trend.
6. Stochastic
Compares a closing price to a price range over a given period to identify momentum shifts and potential reversals.
7. MACD (Moving Average Convergence/Divergence)
Tracks the difference between two EMAs plus a signal line, commonly used to spot momentum flips through crossovers.
8. PSAR (Parabolic SAR)
Plots a trailing stop-and-reverse dot that moves with the trend. Often used to signal potential reversals when price crosses PSAR.
9. MFI (Money Flow Index)
Similar to RSI but incorporates volume data. A reading above 80 can suggest overbought conditions, while below 20 may indicate oversold.
10. CCI (Commodity Channel Index)
Identifies cyclical trends or overbought/oversold levels by comparing current price to an average price over a set timeframe.
11. Heikin Ashi
A type of candlestick charting that filters out market noise. The script uses a streak-based approach (multiple consecutive bullish or bearish bars) to gauge mini-trends.
12. TV Screener
A placeholder condition designed to integrate external buy/sell logic (like a TradingView “Buy” or “Sell” rating). Users can override or reference external signals if desired.
Unique Features
1. Multi-Indicator Entry and Exit
You can selectively enable any subset of 12+ classic indicators, each with customizable parameters and conditions. A position opens only if all enabled entry conditions are met, and it closes only when all enabled exit conditions are satisfied, helping reduce false triggers.
2. Single-Entry / Single-Exit with Intrabar SL/TP
The script supports a single position at a time. Once a position is open, it monitors intrabar to see if the price hits your stop-loss or take-profit levels before the bar closes, making results more realistic for fast-moving markets.
3. Time Window Filter
Users may specify a start/end date range during which trades are allowed, making it convenient to focus on specific market cycles for backtesting or live trading.
4. Condition Table and Statistics
A table at the bottom of the chart lists all active entry/exit indicators. Upon each closed trade, an integrated statistics label displays net profit, total trades, win/loss count, average and median PnL, etc.
5. Seamless Alerts and Automation
Configure alerts in TradingView using “Any alert() function call.”
The script sends JSON alert messages you can route to your own webhook.
The indicator can be integrated with Skyrexio alert bots to automate execution on major cryptocurrency exchanges
6. Optional MA/PSAR Plots
For added visual clarity, optionally plot the chosen moving averages or PSAR on the chart to confirm signals without stacking multiple indicators.
Methodology
1. Multi-Indicator Entry Logic
When multiple entry indicators are enabled (e.g., RSI + Stochastic + MACD), the script requires all signals to align before generating an entry. Each indicator can be set for crossovers, crossunders, thresholds (above/below), etc. This “AND” logic aims to filter out low-confidence triggers.
2. Single-Entry Intrabar SL/TP
One Position At a Time: Once an entry signal triggers, a trade opens at the bar’s close.
Intrabar Checks: Stop-loss and take-profit levels (if enabled) are monitored on every tick. If either is reached, the position closes immediately, without waiting for the bar to end.
3. Exit Logic
All Conditions Must Agree: If the trade is still open (SL/TP not triggered), then all enabled exit indicators must confirm a closure before the script exits on the bar’s close.
4. Time Filter
Optional Trading Window: You can activate a date/time range to constrain entries and exits strictly to that interval.
Justification of Methodology
Indicator Confluence: Combining multiple tools (RSI, MACD, etc.) can reduce noise and false signals.
Intrabar SL/TP: Capturing real-time spikes or dips provides a more precise reflection of typical live trading scenarios.
Single-Entry Model: Straightforward for both manual and automated tracking (especially important in bridging to bots).
Custom Date Range: Helps refine backtesting for specific market conditions or to avoid known irregular data periods.
How to Use
1. Add the Script to Your Chart
In TradingView, open Indicators , search for “Multi-indicator Signal Builder”.
Click to add it to your chart.
2. Configure Inputs
Time Filter: Set a start and end date for trades.
Alerts Messages: Input any JSON or text payload needed by your external service or bot.
Entry Conditions: Enable and configure any indicators (e.g., RSI, MACD) for a confluence-based entry.
Close Conditions: Enable exit indicators, along with optional SL (negative %) and TP (positive %) levels.
3. Set Up Alerts
In TradingView, select “Create Alert” → Condition = “Any alert() function call” → choose this script.
Entry Alert: Triggers on the script’s entry signal.
Close Alert: Triggers on the script’s close signal (or if SL/TP is hit).
Skyrexio Alert Bots: You can route these alerts via webhook to Skyrexio alert bots to automate order execution on major crypto exchanges (or any other supported broker).
4. Visual Reference
A condition table at the bottom summarizes active signals.
Statistics Label updates automatically as trades are closed, showing PnL stats and distribution metrics.
Backtesting Guidelines
Symbol/Timeframe: Works on multiple assets and timeframes; always do thorough testing.
Realistic Costs: Adjust commissions and potential slippage to match typical exchange conditions.
Risk Management: If using the built-in stop-loss/take-profit, set percentages that reflect your personal risk tolerance.
Longer Test Horizons: Verify performance across diverse market cycles to gauge reliability.
Example of statistic calculation
Test Period: 2023-01-01 to 2025-12-31
Initial Capital: $1,000
Commission: 0.1%, Slippage ~5 ticks
Trade Count: 468 (varies by strategy conditions)
Win rate: 76% (varies by strategy conditions)
Net Profit: +96.17% (varies by strategy conditions)
Disclaimer
This indicator is provided strictly for informational and educational purposes .
It does not constitute financial or trading advice.
Past performance never guarantees future results.
Always test thoroughly in demo environments before using real capital.
Enjoy exploring the Multi-Indicator Signal Builder! Experiment with different indicator combinations and adjust parameters to align with your trading preferences, whether you trade manually or link your alerts to external automation services. Happy trading and stay safe!
Momentum Matrix (BTC-COIN)The Momentum Matrix (BTC-COIN) indicator analyzes the momentum relationship between Coinbase stock ( NASDAQ:COIN ) and Bitcoin ( CRYPTOCAP:BTC ). By combining RSI, correlation, and dominance metrics, it identifies bullish and bearish macro trends to align trades with market momentum.
How It Works
Price Inputs: Pulls weekly price data for CRYPTOCAP:BTC and NASDAQ:COIN for macro analysis.
Metrics Calculated:
• RSI Divergence: Measures momentum differences between CRYPTOCAP:BTC and $COIN.
• Price Ratio: Tracks the $COIN/ CRYPTOCAP:BTC relationship relative to its long-term average (SMA).
• Correlation: Analyzes price co-movement between CRYPTOCAP:BTC and $COIN.
• Dominance Impact: Incorporates CRYPTOCAP:BTC dominance for broader crypto trends.
Composite Momentum Score: Combines these metrics into a smoothed macro momentum value.
Thresholds for Trend Detection: Upper and lower thresholds dynamically adapt to market conditions.
Signals and Visualization:
• Buy Signal: Momentum exceeds the upper threshold, indicating bullish trends.
• Sell Signal: Momentum falls below the lower threshold, indicating bearish trends.
• Background Colors: Green (bullish), Red (bearish).
Strengths
Integrates multiple metrics for robust macro analysis.
Dynamic thresholds adapt to market conditions.
Effective for identifying macro momentum shifts.
Limitations
Lag in high volatility due to smoothing.
Less effective in choppy, sideways markets.
Assumes CRYPTOCAP:BTC dominance drives NASDAQ:COIN momentum, which may not always hold true.
Improvements
Multi-Timeframe Analysis: Add daily or monthly data for precision.
Volume Filters: Include volume thresholds for signal validation.
Additional Metrics: Consider MACD or Stochastics for further confirmation.
Complementary Tools
Volume Indicators: OBV or cumulative delta for confirmation.
Trend-Following Systems: Pair with moving averages for timing.
Market Breadth Metrics: Combine with CRYPTOCAP:BTC dominance trends for context.
BTCUSD Price Overextension from Configurable SMAsBTCUSD Price Overextension Indicator with Configurable SMAs
This indicator helps identify potential correction points for BTCUSD by detecting overextended conditions based on customizable short-term and long-term SMAs, average price deviation, and divergence.
Key Features:
Customizable SMAs: Set your own lengths for short-term (default 20) and long-term (default 50) SMAs, allowing you to tailor the indicator to different market conditions.
Overextension Detection: Detects when the average price over a set period (default 10 bars) is overextended above the short-term SMA by a configurable adjustment factor.
Divergence Threshold: Highlights when the short-term and long-term SMAs diverge beyond a specified threshold, signaling potential trend continuation.
Conditional Highlight: Displays a red background only when all conditions are met, and the current candle closes at or above the previous candle. A label "Overextended" appears only on the first bar of each overextended sequence for clear identification.
How to Use:
Identify Correction Signals: Look for red background highlights, which indicate a potential overextension based on the configured SMA and divergence thresholds.
Adjust Parameters: Use the adjustment factor, divergence threshold, and SMA lengths to fine-tune the indicator for different market environments or trading strategies.
This tool is ideal for BTCUSD traders looking to spot potential pullback areas or continuation zones by analyzing trend strength and overextension relative to key moving averages.
5-9-20-100 Day EMAIndicator Name: "5-9-20-100 Day EMA"
Purpose: This indicator plots four key EMAs (5, 9, 20, and 100-day) on a daily chart, providing a clear visualization of both short-term and long-term trends. The EMAs serve as critical triggers for identifying potential entry and exit points based on price interactions with these moving averages.
Technical Details:
Version: Pine Script v5
EMAs Used:
5-Day EMA (Lime): Captures the most recent price trends, useful for identifying short-term momentum.
9-Day EMA (Yellow): Offers a slightly broader view, often used to confirm the short-term trend.
20-Day EMA (Orange): Represents a medium-term trend, commonly used as a signal for trend reversals.
100-Day EMA (Red): Indicates the long-term trend, often serving as strong support or resistance levels.
Trigger Points:
Crossovers: Price crossing above or below these EMAs can trigger potential buy or sell signals.
Convergence/Divergence: The interaction between the EMAs, such as a faster EMA crossing a slower one, can signal trend reversals or continuations.
Utility: This indicator is ideal for traders who rely on EMA crossovers and the relationship between different EMAs to make informed trading decisions.
ATR by Time [QuantVue]"ATR by Time" incorporates time-specific volatility patterns by calculating the Average True Range (ATR) over a customizable period and comparing it to historical ATR values
at specific times of the day.
The Average True Range (ATR) is a popular technical indicator that measures market volatility by decomposing the entire range of an asset price for that period.
By taking the ATR at certain times of the day and comparing it to the current bar's ATR, traders can gain several potential advantages:
Volatility Pattern Recognition: Different times of the trading day often exhibit different levels of volatility. For instance, markets might be more volatile at the open and close compared to midday. By tracking ATR at specific times, traders can recognize these patterns and better predict periods of high or low volatility.
Risk Management: Understanding volatility trends throughout the day helps in better risk management. During periods of high expected volatility (indicated by higher ATR compared to the historical average), traders can adjust their stop-loss levels and position sizes accordingly to protect their capital.
Trend Confirmation and Divergence: This indicator can help confirm trends or identify potential reversals. For example, if the current ATR consistently exceeds the average ATR at specific times, it may confirm a strong trend. Conversely, if the current ATR falls below the historical average, it could signal a potential slowdown or reversal.
This indicator will work on all markets on all time frames. User can customize ATR length as well as the lookback period.
This script utilizes TradingView's RelativeValue library and averageAtTime function, which is used to compare a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
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We hope you enjoy.
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Market Internals & InfoThis script provides various information on Market Internals and other related info. It was a part of the Daily Levels script but that script was getting very large so I decided to separate this piece of it into its own indicator. I plan on adding some additional features in the near future so stay tuned for those!
The script provides customizability to show certain market internals, tickers, and even Market Profile TPO periods.
Here is a summary of each setting:
NASDAQ and NYSE Breadth Ratio
- Ratio between Up Volume and Down Volume for NASDAQ and NYSE markets. This can help inform about the type of volume flowing in and out of these exchanges.
Advance/Decline Line (ADL)
The ADL focuses specifically on the number of advancing and declining stocks within an index, without considering their trading volume.
Here's how the ADL works:
It tracks the daily difference between the number of stocks that are up in price (advancing) and the number of stocks that are down in price (declining) within a particular index.
The ADL is a cumulative measure, meaning each day's difference is added to the previous day's total.
If there are more advancing stocks, the ADL goes up.
If there are more declining stocks, the ADL goes down.
By analyzing the ADL, investors can get a sense of how many stocks are participating in a market move.
Here's what the ADL can tell you:
Confirmation of Trends: When the ADL moves in the same direction as the underlying index (e.g., ADL rising with a rising index), it suggests broad participation in the trend and potentially stronger momentum.
Divergence: If the ADL diverges from the index (e.g., ADL falling while the index is rising), it can be a warning sign. This suggests that fewer stocks are participating in the rally, which could indicate a weakening trend.
Keep in mind:
The ADL is a backward-looking indicator, reflecting past market activity.
It's often used in conjunction with other technical indicators for a more complete picture.
TRIN Arms Index
The TRIN index, also called the Arms Index or Short-Term Trading Index, is a technical analysis tool used in the stock market to gauge market breadth and sentiment. It essentially compares the number of advancing stocks (gaining in price) to declining stocks (losing price) along with their trading volume.
Here's how to interpret the TRIN:
High TRIN (above 1.0): This indicates a weak market where declining stocks and their volume are dominating the market. It can be a sign of a potential downward trend.
Low TRIN (below 1.0): This suggests a strong market where advancing stocks and their volume are in control. It can be a sign of a potential upward trend.
TRIN around 1.0: This represents a more balanced market, where it's difficult to say which direction the market might be headed.
Important points to remember about TRIN:
It's a short-term indicator, primarily used for intraday trading decisions.
It should be used in conjunction with other technical indicators for a more comprehensive market analysis. High or low TRIN readings don't guarantee future price movements.
VIX/VXN
VIX and VXN are both indexes created by the Chicago Board Options Exchange (CBOE) to measure market volatility. They differ based on the underlying index they track:
VIX (Cboe Volatility Index): This is the more well-known index and is considered the "fear gauge" of the stock market. It reflects the market's expectation of volatility in the S&P 500 index over the next 30 days.
VXN (Cboe Nasdaq Volatility Index): This is a counterpart to the VIX, but instead gauges volatility expectations for the Nasdaq 100 index over the coming 30 days. The tech-heavy Nasdaq can sometimes diverge from the broader market represented by the S&P 500, hence the need for a separate volatility measure.
Both VIX and VXN are calculated based on the implied volatilities of options contracts listed on their respective indexes. Here's a general interpretation:
High VIX/VXN: Indicates a high level of fear or uncertainty in the market, suggesting investors expect significant price fluctuations in the near future.
Low VIX/VXN: Suggests a more complacent market with lower expectations of volatility.
Important points to remember about VIX and VXN:
They are forward-looking indicators, reflecting market sentiment about future volatility, not necessarily current market conditions.
High VIX/VXN readings don't guarantee a market crash, and low readings don't guarantee smooth sailing.
These indexes are often used by investors to make decisions about portfolio allocation and hedging strategies.
Inside/Outside Day
This provides a quick indication of it we are still trading inside or outside of yesterdays range and will show "Inside Day" or "Outside Day" based upon todays range vs. yesterday's range.
Custom Ticker Choices
Ability to add up to 5 other tickers that can be tracked within the table
Show Market Profile TPO
This only shows on timeframes less than 30m. It will show both the current TPO period and the remaining time within that period.
Table Customization
Provided drop downs to change the text size and also the location of the table.
Confluence Buy-Sell Indicator with Fibonacci The script is a "Confluence Indicator with Fibonacci" designed to work on the TradingView platform. This indicator combines multiple technical analysis strategies to generate buy and sell signals based on user-defined confluence criteria. Here's a breakdown of its features:
Confluence Criteria: Users can enable or disable various strategies like MACD, RSI, Bollinger Bands, Divergence, Fibonacci, and Moving Average. The number of strategies that need to align for a signal to be generated can be set by the user.
Strategies Included:
MACD Strategy: Uses the Moving Average Convergence Divergence method to identify buy/sell opportunities.
RSI Strategy: Utilizes the Relative Strength Index to detect overbought or oversold conditions.
Bollinger Bands Strategy: Incorporates Bollinger Bands to identify volatility and potential buy/sell signals.
Divergence Strategy: A basic implementation that detects bullish and bearish divergences using the RSI.
Fibonacci Strategy: Uses Fibonacci retracement levels to determine potential support and resistance levels.
Moving Average Strategy: Employs a crossover system between the 50-period and 200-period simple moving averages.
Additional Features:
Support & Resistance: Identifies major support and resistance levels from the last 50 bars.
Pivot Points: Calculates pivot points to determine potential turning points.
Stop Loss Levels: Automatically calculates and plots stop-loss levels for buy and sell signals.
NYC Midnight Level: Option to display the New York City midnight price level.
Visualization: Plots buy and sell signals on the chart with green and red markers respectively.
Adequate Category:
"Technical Analysis Indicators & Overlays" or "Strategy & Scripting Tools".
Bias RatioA simple indicator, but look like no one share, so I build it.
The description is copy from: baike.baidu.hk
The bias ratio is an indicator used in finance to analyze the returns of investment portfolios, and in performing due diligence.
Eight key points:
1. The deviation rate approaches zero
When the deviation rate between the stock price per share and the average line reaches the maximum percentage, it will approach the zero value, or even be lower than or higher than zero, which is a normal phenomenon.
2. 30-day average deviation rate
When the deviation rate of the stock price and the 30-day average line exceeds +16%, it is an overbought phenomenon, which is the time to sell; when it reaches below -16%, it is an oversold phenomenon and it is a time to buy.
3. The deviation rate is high
Due to the influence of the fierce battle between long and short positions, individual stocks are prone to deviate from various averages, but the number of occurrences is not large.
4. Characteristics of positive and negative deviation rate
The deviation ratio can be divided into positive deviation ratio and negative deviation ratio. If the stock price is above the average line, it is positive deviation; if the stock price is below the average line, it is negative deviation; when the stock price intersects the average line, the deviation ratio is zero. The greater the positive divergence rate, the greater the short-term profit, the higher the possibility of profit taking; the greater the negative divergence rate, the higher the possibility of short covering.
5.10-day average deviation rate
When the deviation rate between the stock price and the 10-day average line exceeds +8%, it is an overbought phenomenon, which is the time to sell; when it reaches below -8%, it is an oversold phenomenon and it is a time to buy.
6. Application of negative deviation rate
In case of negative divergence in the rising market, you can buy at the falling price, because the risk of entering the market is small.
7. Positive deviation rate application
If there is a positive deviation in the general downward trend, you can hold it back and sell it at a high price.
8. Skyrocketing
A boom in a bull market and a plunge in a bear market can lead to divergences of unexpected percentages, but they occur very rarely and for a short period of time, and can be considered a special case.
