[GYTS-CE] Market Regime Detector🧊 Market Regime Detector (Community Edition)
🌸 Part of GoemonYae Trading System (GYTS) 🌸
🌸 --------- INTRODUCTION --------- 🌸
💮 What is the Market Regime Detector?
The Market Regime Detector is an advanced, consensus-based indicator that identifies the current market state to increase the probability of profitable trades. By distinguishing between trending (bullish or bearish) and cyclic (range-bound) market conditions, this detector helps you select appropriate tactics for different environments. Instead of forcing a single strategy across all market conditions, our detector allows you to adapt your approach based on real-time market behaviour.
💮 The Importance of Market Regimes
Markets constantly shift between different behavioural states or "regimes":
• Bullish trending markets - characterised by sustained upward price movement
• Bearish trending markets - characterised by sustained downward price movement
• Cyclic markets - characterised by range-bound, oscillating behaviour
Each regime requires fundamentally different trading approaches. Trend-following strategies excel in trending markets but fail in cyclic ones, while mean-reversion strategies shine in cyclic markets but underperform in trending conditions. Detecting these regimes is essential for successful trading, which is why we've developed the Market Regime Detector to accurately identify market states using complementary detection methods.
🌸 --------- KEY FEATURES --------- 🌸
💮 Consensus-Based Detection
Rather than relying on a single method, our detector employs two complementary detection methodologies that analyse different aspects of market behaviour:
• Dominant Cycle Average (DCA) - analyzes price movement relative to its lookback period, a proxy for the dominant cycle
• Volatility Channel - examines price behaviour within adaptive volatility bands
These diverse perspectives are synthesised into a robust consensus that minimises false signals while maintaining responsiveness to genuine regime changes.
💮 Dominant Cycle Framework
The Market Regime Detector uses the concept of dominant cycles to establish a reference framework. You can input the dominant cycle period that best represents the natural rhythm of your market, providing a stable foundation for regime detection across different timeframes.
💮 Intuitive Parameter System
We've distilled complex technical parameters into intuitive controls that traders can easily understand:
• Adaptability - how quickly the detector responds to changing market conditions
• Sensitivity - how readily the detector identifies transitions between regimes
• Consensus requirement - how much agreement is needed among detection methods
This approach makes the detector accessible to traders of all experience levels while preserving the power of the underlying algorithms.
💮 Visual Market Feedback
The detector provides clear visual feedback about the current market regime through:
• Colour-coded chart backgrounds (purple shades for bullish, pink for bearish, yellow for cyclic)
• Colour-coded price bars
• Strength indicators showing the degree of consensus
• Customizable colour schemes to match your preferences or trading system
💮 Integration in the GYTS suite
The Market Regime Detector is compatible with the GYTS Suite , i.e. it passes the regime into the 🎼 Order Orchestrator where you can set how to trade the trending and cyclic regime.
🌸 --------- CONFIGURATION SETTINGS --------- 🌸
💮 Adaptability
Controls how quickly the Market Regime detector adapts to changing market conditions. You can see it as a low-frequency, long-term change parameter:
Very Low: Very slow adaptation, most stable but may miss regime changes
Low: Slower adaptation, more stability but less responsiveness
Normal: Balanced between stability and responsiveness
High: Faster adaptation, more responsive but less stable
Very High: Very fast adaptation, highly responsive but may generate false signals
This setting affects lookback periods and filter parameters across all detection methods.
💮 Sensitivity
Controls how sensitive the detector is to market regime transitions. This acts as a high-frequency, short-term change parameter:
Very Low: Requires substantial evidence to identify a regime change
Low: Less sensitive, reduces false signals but may miss some transitions
Normal: Balanced sensitivity suitable for most markets
High: More sensitive, detects subtle regime changes but may have more noise
Very High: Very sensitive, detects minor fluctuations but may produce frequent changes
This setting affects thresholds for regime detection across all methods.
💮 Dominant Cycle Period
This parameter allows you to specify the market's natural rhythm in bars. This represents a complete market cycle (up and down movement). Finding the right value for your specific market and timeframe might require some experimentation, but it's a crucial parameter that helps the detector accurately identify regime changes. Most of the times the cycle is between 20 and 40 bars.
💮 Consensus Mode
Determines how the signals from both detection methods are combined to produce the final market regime:
• Any Method (OR) : Signals bullish/bearish if either method detects that regime. If methods conflict (one bullish, one bearish), the stronger signal wins. More sensitive, catches more regime changes but may produce more false signals.
• All Methods (AND) : Signals only when both methods agree on the regime. More conservative, reduces false signals but might miss some legitimate regime changes.
• Weighted Decision : Balances both methods with equal weighting. Provides a middle ground between sensitivity and stability.
Each mode also calculates a continuous regime strength value that's used for colour intensity in the 'unconstrained' display mode.
💮 Display Mode
Choose how to display the market regime colours:
• Unconstrained regime: Shows the regime strength as a continuous gradient. This provides more nuanced visualisation where the intensity of the colour indicates the strength of the trend.
• Consensus only: Shows only the final consensus regime with fixed colours based on the detected regime type.
The background and bar colours will change to indicate the current market regime:
• Purple shades: Bullish trending market (darker purple indicates stronger bullish trend)
• Pink shades: Bearish trending market (darker pink indicates stronger bearish trend)
• Yellow: Cyclic (range-bound) market
💮 Custom Colour Options
The Market Regime Detector allows you to customize the colour scheme to match your personal preferences or to coordinate with other indicators:
• Use custom colours: Toggle to enable your own colour choices instead of the default scheme
• Transparency: Adjust the transparency level of all regime colours
• Bullish colours: Define custom colours for strong, medium, weak, and very weak bullish trends
• Bearish colours: Define custom colours for strong, medium, weak, and very weak bearish trends
• Cyclic colour: Define a custom colour for cyclic (range-bound) market conditions
🌸 --------- DETECTION METHODS --------- 🌸
💮 Dominant Cycle Average (DCA)
The Dominant Cycle Average method forms a key part of our detection system:
1. Theoretical Foundation :
The DCA method builds on cycle analysis and the observation that in trending markets, price consistently remains on one side of a moving average calculated using the dominant cycle period. In contrast, during cyclic markets, price oscillates around this average.
2. Calculation Process :
• We calculate a Simple Moving Average (SMA) using the specified lookback period - a proxy for the dominant cycle period
• We then analyse the proportion of time that price spends above or below this SMA over a lookback window. The theory is that the price should cross the SMA each half cycle, assuming that the dominant cycle period is correct and price follows a sinusoid.
• This lookback window is adaptive, scaling with the dominant cycle period (controlled by the Adaptability setting)
• The different values are standardised and normalised to possess more resolving power and to be more robust to noise.
3. Regime Classification :
• When the normalised proportion exceeds a positive threshold (determined by Sensitivity setting), the market is classified as bullish trending
• When it falls below a negative threshold, the market is classified as bearish trending
• When the proportion remains between these thresholds, the market is classified as cyclic
💮 Volatility Channel
The Volatility Channel method complements the DCA method by focusing on price movement relative to adaptive volatility bands:
1. Theoretical Foundation :
This method is based on the observation that trending markets tend to sustain movement outside of normal volatility ranges, while cyclic markets tend to remain contained within these ranges. By creating adaptive bands that adjust to current market volatility, we can detect when price behaviour indicates a trending or cyclic regime.
2. Calculation Process :
• We first calculate a smooth base channel center using a low pass filter, creating a noise-reduced centreline for price
• True Range (TR) is used to measure market volatility, which is then smoothed and scaled by the deviation factor (controlled by Sensitivity)
• Upper and lower bands are created by adding and subtracting this scaled volatility from the centreline
• Price is smoothed using an adaptive A2RMA filter, which has a very flat and stable behaviour, to reduce noise while preserving trend characteristics
• The position of this smoothed price relative to the bands is continuously monitored
3. Regime Classification :
• When smoothed price moves above the upper band, the market is classified as bullish trending
• When smoothed price moves below the lower band, the market is classified as bearish trending
• When price remains between the bands, the market is classified as cyclic
• The magnitude of price's excursion beyond the bands is used to determine trend strength
4. Adaptive Behaviour :
• The smoothing periods and deviation calculations automatically adjust based on the Adaptability setting
• The measured volatility is calculated over a period proportional to the dominant cycle, ensuring the detector works across different timeframes
• Both the center line and the bands adapt dynamically to changing market conditions, making the detector responsive yet stable
This method provides a unique perspective that complements the DCA approach, with the consensus mechanism synthesising insights from both methods.
🌸 --------- USAGE GUIDE --------- 🌸
💮 Starting with Default Settings
The default settings (Normal for Adaptability and Sensitivity, Weighted Decision for Consensus Mode) provide a balanced starting point suitable for most markets and timeframes. Begin by observing how these settings identify regimes in your preferred instruments.
💮 Finding the Optimal Dominant Cycle
The dominant cycle period is a critical parameter. Here are some approaches to finding an appropriate value:
• Start with typical values, usually something around 25 works well
• Visually identify the average distance between significant peaks and troughs
• Experiment with different values and observe which provides the most stable regime identification
• Consider using cycle-finding indicators to help identify the natural rhythm of your market
💮 Adjusting Parameters
• If you notice too many regime changes → Decrease Sensitivity or increase Consensus requirement
• If regime changes seem delayed → Increase Adaptability
• If a trending regime is not detected, the market is automatically assigned to be in a cyclic state
• If you want to see more nuanced regime transitions → Try the "unconstrained" display mode (note that this will not affect the output to other indicators)
💮 Trading Applications
Regime-Specific Strategies:
• Bullish Trending Regime - Use trend-following strategies, trail stops wider, focus on breakouts, consider holding positions longer, and emphasize buying dips
• Bearish Trending Regime - Consider shorts, tighter stops, focus on breakdown points, sell rallies, implement downside protection, and reduce position sizes
• Cyclic Regime - Apply mean-reversion strategies, trade range boundaries, apply oscillators, target definable support/resistance levels, and use profit-taking at extremes
Strategy Switching:
Create a set of rules for each market regime and switch between them based on the detector's signal. This approach can significantly improve performance compared to applying a single strategy across all market conditions.
GYTS Suite Integration:
• In the GYTS 🎼 Order Orchestrator, select the '🔗 STREAM-int 🧊 Market Regime' as the market regime source
• Note that the consensus output (i.e. not the "unconstrained" display) will be used in this stream
• Create different strategies for trending (bullish/bearish) and cyclic regimes. The GYTS 🎼 Order Orchestrator is specifically made for this.
• The output stream is actually very simple, and can possibly be used in indicators and strategies as well. It outputs 1 for bullish, -1 for bearish and 0 for cyclic regime.
🌸 --------- FINAL NOTES --------- 🌸
💮 Development Philosophy
The Market Regime Detector has been developed with several key principles in mind:
1. Robustness - The detection methods have been rigorously tested across diverse markets and timeframes to ensure reliable performance.
2. Adaptability - The detector automatically adjusts to changing market conditions, requiring minimal manual intervention.
3. Complementarity - Each detection method provides a unique perspective, with the collective consensus being more reliable than any individual method.
4. Intuitiveness - Complex technical parameters have been abstracted into easily understood controls.
💮 Ongoing Refinement
The Market Regime Detector is under continuous development. We regularly:
• Fine-tune parameters based on expanded market data
• Research and integrate new detection methodologies
• Optimise computational efficiency for real-time analysis
Your feedback and suggestions are very important in this ongoing refinement process!
Cerca negli script per "profitable"
Big Boss Order Detector by GSK-VIZAG-AP-INDIABig Boss Order Detector by GSK-VIZAG-AP-INDIA
Overview
The Big Boss Order Detector is designed to help traders identify significant buying and selling activity based on volume and price action. It filters out normal transactions and highlights large institutional orders, helping traders spot potential smart money movements.
This indicator classifies large orders into two categories:
Large Orders – These are detected when the volume exceeds a predefined multiple of the volume SMA, with minimal price movement between open and close.
High Volume Orders – Stricter conditions apply, where volume is even higher, and the price movement remains within a tighter threshold.
By tracking these key market activities, traders can gain insights into potential reversals, breakouts, or the presence of institutional buying and selling.
How It Works
The indicator calculates a Simple Moving Average (SMA) of volume over a user-defined period (default: 50 candles). It then sets two volume-based thresholds:
Large Orders: When the volume is greater than a multiple (default: 2×) of the SMA and price movement between open and close is within a certain percentage threshold (default: 0.05%).
High Volume Orders: When the volume surpasses an even higher threshold (default: 3× the SMA) with stricter price movement (default: 0.02%).
Key Conditions for Order Detection
Large Buy Order: Volume exceeds the threshold, and the closing price is greater than the opening price.
Large Sell Order: Volume exceeds the threshold, and the closing price is lower than the opening price.
High Volume Buy Order: A stricter volume condition is met, and the price closes higher than it opened.
High Volume Sell Order: A stricter volume condition is met, and the price closes lower than it opened.
Indicator Features
🔹 Visual Signals on Chart
Orange Up Arrow (▲) → Large Buy Order
Purple Down Arrow (▼) → Large Sell Order
"Big🐂" (Blue Label Up) → High Volume Buy Order
"Big🐻" (Red Label Down) → High Volume Sell Order
🔹 Alerts for Trading Opportunities
Large Orders Alerts: Notifies when a large buy or sell order is detected.
High Volume Orders Alerts: Identifies potential high volume buy or sell orders.
Traders can set up these alerts in TradingView for real-time notifications.
Use Cases & Trading Insights
Detect High-Impact Trades: Large orders often indicate activity from big market participants who can influence price movements.
Confirm Trend Strength: When large buy orders appear in an uptrend, it may signal trend continuation. Similarly, large sell orders in a downtrend could confirm further weakness.
Spot Potential Reversals: High-volume orders with limited price movement may suggest accumulation (bullish) or distribution (bearish).
🔹 ⚠️ Important Note:
Not every large buy represents fresh buying; some could be short covering. Similarly, large selling could be long liquidation rather than fresh shorting. Always use this indicator with other technical tools and risk management strategies.
Additional Tip: Using This Indicator on Heikin-Ashi Charts
While this indicator is designed for standard candlestick charts, traders who use Heikin-Ashi candles may find it helpful for smoother trend visualization. Since Heikin-Ashi modifies price calculations, volume-based signals may appear slightly different compared to regular candles. Use it as a complementary tool rather than a strict signal generator.
Customization Options
Volume SMA Length (default: 50 candles) – Adjust the sensitivity of volume detection.
Volume Multipliers – Change the thresholds for detecting large and high-volume orders.
Price Difference Thresholds – Modify how strictly price movements are considered for filtering orders.
This flexibility allows traders to fine-tune the indicator to match different trading styles and asset classes.
Importance of Input Settings.
Setting Recommended Values Purpose
Volume SMA Length 20, 30, 50 Defines the baseline average volume for comparison. A shorter SMA (20) reacts faster, while a longer SMA (50) smooths out fluctuations.
Large Order Multiplier 1, 2, 3 Determines how much higher the volume should be compared to the SMA to qualify as a large order. A lower value captures more signals; a higher value filters out noise.
High Volume Order Multiplier 1.5, 2, 2.5 Stricter volume threshold for detecting high-impact trades. Use higher values for highly liquid markets.
Price Difference Threshold (Points) 5, 10, or more Defines the max allowed difference between open and close for large orders. Higher values capture more trades but may include noise.
High Volume Price Threshold (Points) 20 or based on price Stricter price movement condition for high-volume orders. For low-priced stocks, 20 points may be too much—adjust based on asset volatility.
The effectiveness of this indicator depends on its input settings, as they allow traders to fine-tune the detection of high-impact trades based on market conditions. Adjusting parameters like Volume SMA Length, Volume Multipliers, and Price Difference Thresholds can help optimize signals for different assets, timeframes, and volatility levels.
For best results, experiment with these settings and adapt them to suit your trading strategy.
Final Thoughts
The Big Boss Order Detector is a powerful tool for tracking institutional activity and understanding volume dynamics in the market. However, it should be used alongside other indicators and price action analysis to make informed trading decisions.
Give it a try and enhance your market insights! 🚀📈
📢 Share Your Experience!
Your feedback is valuable! If you find this indicator useful, leave a comment with your experience—how it worked for you, any improvements you suggest, or the best settings you discovered.
Let’s build a community of traders refining strategies together! 🚀📊
Disclaimer:
This indicator is for educational and informational purposes only. It does not guarantee profitable trades and should be used with proper risk management. Always conduct your own research before making trading decisions.
Democratic MultiAsset Strategy [BerlinCode42]Happy Trade,
Intro
Included Trade Concept
Included Indicators and Compare-Functions
Usage and Example
Settings Menu
Declaration for Tradingview House Rules on Script Publishing
Disclaimer
Conclusion
1. Intro
This is the first multi-asset strategy available on TradingView—a market breadth multi-asset trading strategy with integrated webhooks, backtesting capabilities, and essential strategy components like Take Profit, Stop Loss, Trailing, Hedging, Time & Session Filters, and Alerts.
How It Trades? At the start of each new bar, one asset from a set of eight is selected to go long or short. As long there is available cash and the selected asset meets the minimum criteria.
The selection process works through a voting system, similar to a democracy. Each asset is evaluated using up to five indicators that the user can choose. The asset with the highest overall voting score is picked for the trade. If no asset meets all criteria, no trade is executed, and the cash reserve remains untouched for future opportunities.
How to Set Up This Market Breadth Strategy:
Choose eight assets from the same market (e.g., cryptos or big tech stocks).
Select one to five indicators for the voting system.
Refine the strategy by adjusting Take Profit, Stop Loss, Hedging, Trailing, and Filters.
2. Voting as the included Trade Concept
The world of financial trading is filled with both risks and opportunities, and the key challenge is to identify the right opportunities, manage risks, and do both right on time.
There are countless indicators designed to spot opportunities and filter out risks, but no indicator is perfect—they only work statistically, hitting the right signals more often than the wrong ones.
The goal of this strategy is to increase the accuracy of these Indicators by:
Supervising a larger number of assets
Filtering out less promising opportunities
This is achieved through a voting system that compares indicator values across eight different assets. It doesn't just compare long trades—it also evaluates long vs. short positions to identify the most promising trade.
Why focus on one asset class? While you can randomly select assets from different asset classes, doing so prevents the algorithm from identifying the strongest asset within a single class. Think about, within one asset class there is often a major trend whereby different asset classes has not really such behavior.
And, you don’t necessarily need trading in multiple classes—this algorithm is designed to generate profits in both bullish and bearish markets. So when ever an asset class rise or fall the voting system ensure to jump on the strongest asset. So this focusing on one asset class is an integral part of this strategy. This all leads to more stable and robust trading results compared to handling each asset separately.
3. Included Indicators and Compare-Functions
You can choose from 17 different indicators, each offering different types of signals:
Some provide a directional signal
Some offer a simple on/off signal
Some provide both
Available Indicators: RSI, Stochastic RSI, MFI, Price, Volume, Volume Oscillator, Pressure, Bilson Gann Trend, Confluence, TDI, SMA, EMA, WMA, HMA, VWAP, ZLMA, T3MA
However, these indicators alone do not generate trade signals. To do so, they must be compared with thresholds or other indicators using specific comparison functions.
Example – RSI as a Trade Signal. The RSI provides a value between 0 and 100. A common interpretation is:
RSI over 80 → Signal to go short or exit a long trade
RSI under 20 → Signal to go long or exit a short trade
Here, two comparison functions and two thresholds are used to determine trade signals.
Below is the full set of available comparison functions, where: I represents the indicator’s value and A represents the comparator’s value.
I < A if I smaller A then trade signal
I > A if I bigger A then trade signal
I = A if I equal to A then trade signal
I != A if I not equal to A then trade signal
A <> B if I bigger A and I smaller B then trade signal
A >< B if I smaller A then long trade signal or if I bigger B then short trade signal
Image 1
In Image 1, you can see one of five input sections, where you define an indicator along with its function, comparator, and constants. For our RSI example, we select:
Indicator: RSI
Function: >< (greater/less than)
Comparator: Constant
Constants: A = 20, B = 80
With these settings a go short signal is triggered when RSI crosses above 80. And a go long signal is triggered when RSI crosses below 20.
Relative Strength Indicator: The RSI from the public TradingView library provides a directional trade signal. You can adjust the price source and period length in the indicator settings.
Stochastic Relative Strength Indicator: As above the Stoch RSI offers a trade signal with direction. It is calculated out of the RSI, the stochastic derivation and the SMA from the Tradingview library. You can set the in-going price source and the period length for the RSI, for the Stochastic Derivation and for the SMA as blurring in the Indicator settings section.
Money Flow Indicator: As above the MFI from the public Tradingview library offers a trade signal with direction. You can set the in-going price source and the period length in the Indicator settings section.
Price: The Price as Indicator is as simple as it can be. You can chose Open, High, Low or Close or combinations of them like HLC3 or even you can import an external Indicator. The absolute price or value can later be used to generate a trade signals when certain constant thresholds or other indicators signals are crossed.
Volume: Similar as above the Volume as Indicator offers the average volume as absolute value. You can set the period length for the smoothing and you can chose where it is presented in the base currency $ or is the other. For example the trade pair BTCUSD you can chose to present the value in $ or in BTC.
Volume Oscillator: The Volume Oscillator Indicator offers a value in the range of . Whereby a value close to 0 means that the volume is very low. A value around 1 means the volume is same high as before and Values higher as 1 means the volume is bigger then before. You can set the period length for the smoothing and you can chose where it is presented in the base currency $ or is the other. For example the trade pair BTCUSD you can chose to present the value in $ or in BTC.
Pressure Indicator: The Pressure is an adapted version of LazyBear's script (Squeeze Momentum Indicator) Pressure is a Filter that highlight bars before a bigger price move in any direction. The result are integer numbers between 0 and 4 whereby 0 means no bigger price move excepted, while 4 means huge price move expected. You can set the in-going price source and the period length in the Indicator settings section.
Bilson Gann Trend: The Bilson Gann Trend Indicator is a specific re-implementation of the widely known Bilson Gann Count Algorithm to detect Highs and Lows. On base of the last four Highs and Lows a trend direction can be calculated. It is based on 2 rules to confirm a local pivot candidate. When a local pivot candidate is confirmed, let it be a High then it looks for Lows to confirm. The result range is whereby -1 means down trend, 1 means uptrend and 0 sideways.
Confluence: The Confluence Indicator is a simplified version of Dale Legan's "Confluence" indicator written by Gary Fritz. It uses five SMAs with different periods lengths. Whereby the faster SMA get compared with the (slower) SMA with the next higher period lengths. Is the faster SMA smaller then the slower SMA then -1, otherwise +1. This is done with all SMAs and the final sum range between . Whereby values around 0 means price is going side way, Crossing under 0 means trend change from bull to bear. Is the value>2 means a strong bull trend and <-2 a strong bear trend.
Trades Dynamic Index: The TDI is an adapted version from the "Traders Dynamic Index" of LazyBear. The range of the result is whereby 2 means Top goShort, -2 means Bottom goLong, 0 is neutral, 1 is up trend, -1 is down trend.
Simple Moving Average: The SMA is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source and the period length in the Indicator settings section.
Exponential Moving Average: The EMA as above is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source and the period length in the Indicator settings section.
Weighted Moving Average: The WMA as above is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source and the period length in the Indicator settings section.
Hull Moving Average: HMA as above is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source and the period length in the Indicator settings section.
Volume Weighted Average Price: The VWAP as above is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source in the Indicator settings section.
Zero Lag Moving Average: The ZLMA by John Ehlers and Ric Way describe in their paper: www.mesasoftware.com
As the other moving averages you can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source and the period length in the Indicator settings section.
T3 Moving Average: The T3MA is the one from the Tradingview library. You can compare it with the last close price or any other moving average indicator to indicate up and down trends. You can set the in-going price source, the period length and a factor in the Indicator settings section. Keep this factor at 1 and the T3MA swing in the same range as the input. Bigger 1 and it swings over. Factors close to 0 and the T3MA becomes a center line.
All MA's following the price. The function to compare any MA Indicators would be < or > to generate a trade direction. An example follows in the next section.
4. Example and Usage
In this section, you see how to set up the strategy using a simple example. This example was intentionally chosen at random and has not undergone any iterations to refine the trade results.
We use the RSI as the trade signal indicator and apply a filter using a combination of two moving averages (MAs). The faster MA is an EMA, while the slower MA is an SMA. By comparing these two MAs, we determine a trend direction. If the faster MA is above the slower MA the trend is upwards etc. This trend direction can then be used for filtering trades.
The strategy follows these rules:
If the RSI is below 20, a buy signal is generated.
If the RSI is above 80, a sell signal is generated.
However, this RSI trade signal is filtered so that a trade is only given the maximum voting weight if the RSI trade direction aligns with the trend direction determined by the MA filter.
So first, you need to add your chosen assets or simply keep the default ones. In Image 2, you can see one of the eight asset input sections.
Image 2
This strategy offers some general trade settings that apply equally to all assets and some asset-specific settings. This distinction is necessary because some assets have higher volatility than others, requiring asset-specific Take Profit and Stop Loss levels.
Once you have made your selections, proceed to the Indicators and Compare Functions for the voting. Image 3 shows an example of this setup.
Image 3
Later on go to the Indicator specific settings shown in Image 4 to refine the trade results.
Image 4
For refine the trade results take also a look on the result summary table, development of capital plot, on the list of closed and open trades and screener table shown in Image 5.
Image 5
To locate any trade for any asset in the chronological and scroll-able trade list, each trade is marked with a label:
An opening label displaying the trade direction, ticker ID, trade number, invested amount, and remaining cash reserves.
A closing label showing the closing reason, ticker ID, trade number, trade profit (%), trade revenue ($), and updated cash reserves.
Additionally: a green line marks each Take Profit level. An orange line indicates the (trailing) Stop Loss.
The summary table in the bottom-left corner provides insights into how effective the trade strategy is. By analyzing the trade list, you can identify trades that should be avoided.
To find those bad trades on the chart, use the trade number or timestamp. With replay mode, you can go back in time to review a specific trade in detail.
Image 6
In Image 6, you can see an example where replay mode and the start time filter are used to display specific trades within a narrow time range. By identifying a large number of bad trades, you may recognize patterns and formulate conditions to avoid them in the future.
This is the backtesting tool that allows you to develop and refine your trading strategy continuously. With each iteration—from general adjustments to detailed optimizations—you can use these tools to improve your strategy. You can:
Add other indicators with trade signals and direction
Add more indicators signals as filter
Adjust the settings of your indicators to optimize results
Configure key strategy settings, such as Time and Session Filters, Stop Loss, Take Profit, and more
By doing so, you can identify a profitable strategy and its optimal settings.
5. Settings Menu
In the settings menu you will find the following high-lighted sections. Most of the settings have a i mark on their right side. Move over it with the cursor to read specific explanation.
Backtest Results: Here you can decide about visibility of the trade list, of the Screener Table and of the Results Summary. And the colors for bullish, side ways, bearish and no signal. Go above and see Image 5.
Time Filter: You can set a Start time or deactivate it by leave it unhooked. The same with End Time and Duration Days . Duration Days can also count from End time in case you deactivate Start time.
Session Filter: Here, you can chose to activate trading on a weekly basis, specifying which days of the week trading is allowed and which are excluded. Additionally, you can configure trading on a daily basis, setting the start and end times for when trades are permitted. If activated, no new trades will be initiated outside the defined times and sessions.
Trade Logic: Here you can set an extra time frame for all indicators. You can enable Longs or Shorts or both trades.
The min Criteria percentage setting defines the minimum number of voices an asset has to get to be traded. So if you set this to 50% or less also weak winners of the voting get traded while 100% means that the winner of the voting has to get all possible voices.
Additionally, you have the option to delay entry signals. This feature is particularly useful when trade signals exhibit noise and require smoothing.
Enable Trailing Stop and force the strategy to trade only at bar closing. Other-ways the strategy trade intrabar, so when ever a voting present an asset to trade, it will send the alert and the webhooks.
The Hedging is basic as shown in the following Image 7 and serves as a catch if price moves fast in the wrong direction. You can activate a hedging mechanism, which opens a trade in the opposite direction if the price moves x% against the entry price. If both the Stop Loss and Hedging are triggered within the same bar, the hedging action will always take precedence.
Image 6
Indicators to use for Trade Signal Generating: Here you chose the Indicators and their Compare Function for the Voting . Any activated asset will get their indicator valuation which get compared over all assets. The asset with the highest valuation is elected for the trade as long free cash is present and as long the minimum criteria are met.
The Screener Table will show all indicators results of the last bar of all assets. Those indicator values which met the threshold get a background color to high light it. Green for bullish, red for bearish and orange for trade signals without direction. If you chose an Indicator here but without any compare function it will show also their results but with just gray background.
Indicator Settings: here you can setup the indicator specific settings. for deeper insights see 3. Included Indicators and Compare-Functions .
Assets, TP & SL Settings: Asset specific settings. Chose here the TickerID of all Assets you wanna trade. Take Profit 1&2 set the target prices of any trade in relation to the entry price. The Take Profit 1 exit a part of the position defined by the quantity value. Stop Loss set the price to step out when a trade goes the wrong direction.
Invest Settings: Here, you can set the initial amount of cash to start with. The Quantity Percentage determines how much of the available cash is allocated to each trade, while the Fee percentage specifies the trading fee applied to both opening and closing positions.
Webhooks: Here, you configure the License ID and the Comment . This is particularly useful if you plan to use multiple instances of the script, ensuring the webhooks target the correct positions. The Take Profit and Stop Loss values are displayed as prices.
6. Declaration for Tradingview House Rules on Script Publishing
The unique feature of this Democratic Multi-Asset Strategy is its ability to trade multiple assets simultaneously. Equipped with a set of different standard Indicators, it's new democratic Voting System does more robust trading decisions compared to single-asset. Interchangeable Indicators and customizable strategy settings allowing for a wide range of trading strategies.
This script is closed-source and invite-only to support and compensate for over a year of development work. Unlike other single asset strategies, this one cannot use TradingView's strategy functions. Instead, it is designed as an indicator.
7. Disclaimer
Trading is risky, and traders do lose money, eventually all. This script is for informational and educational purposes only. All content should be considered hypothetical, selected post-factum and is not to be construed as financial advice. Decisions to buy, sell, hold, or trade in securities, commodities, and other investments involve risk and are best made based on the advice of qualified financial professionals. Past performance does not guarantee future results. Using this script on your own risk. This script may have bugs and I declare don't be responsible for any losses.
8. Conclusion
Now it’s your turn! Chose an asset class and pick 8 of them and chose some indicators to see the trading results of this democratic voting system. Refine your multi-asset strategy to favorable settings. Once you find a promising configuration, you can set up alerts to send webhooks directly. Configure all parameters, test and validate them in paper trading, and if results align with your expectations, you even can deploy this script as your trading bit.
Cheers
Uptrick: Time Based ReversionIntroduction
The Uptrick: Time Based Reversion indicator is designed to provide a comprehensive view of market momentum and potential trend shifts by combining multiple moving averages, a streak-based trend analysis system, and adaptive color visualization. It helps traders identify strong trends, spot potential reversals, and make more informed trading decisions.
Purpose
The primary goal of this indicator is to assist traders in distinguishing between sustained market movements and short-lived fluctuations. By evaluating how price behaves relative to its moving averages, and by measuring consecutive streaks above or below these averages, the indicator highlights areas where trends are likely to continue or lose momentum.
Overview
Uptrick: Time Based Reversion calculates one or more moving averages of price data and then tracks the number of consecutive bars (streaks) above or below these averages. This streak-based detection provides insight into whether a trend is gaining strength or nearing a potential reversal point. The indicator offers:
• Multiple moving average types (SMA, EMA, WMA)
• Optional second and third moving average layers for additional smoothing of first moving average
• A streak detection system to quantify trend intensity
• A dynamic color scheme that changes with streak strength
• Optional buy and sell signals for potential trade entries and exits
• A ribbon mode that applies moving averages to Open, High, Low, and Close prices for a more detailed visualization of overall trend alignment
Originality and Uniqueness
Unlike traditional moving average indicators, Uptrick: Time Based Reversion incorporates a streak measurement system to detect trend strength. This approach helps clarify whether a price movement is merely a quick fluctuation or part of a longer-lasting trend. Additionally, the optional ribbon mode extends this logic to Open, High, Low, and Close prices, creating a layered and intuitive visualization that shows complete trend alignment.
Inputs and Features
1. Enable Ribbon Mode
This input lets you activate or deactivate the ribbon display of multiple moving averages. When enabled, the script plots moving averages for the Open, High, Low, and Close prices and uses color fills to show whether these four data points are collectively above or below their respective moving averages.
2. Color Scheme Selection
Users can choose from several predefined color schemes, such as Default, Emerald, Crimson, Sapphire, Gold, Purple, Teal, Orange, Gray, Lime, or Aqua. Each scheme assigns distinct bullish, bearish and neutral colors..
3. Show Buy/Sell Signals
The indicator can display buy or sell signals based on its streak analysis logic. These signals appear as markers on the chart, indicating a “Safe Uptrend” (buy) or “Safe Downtrend” (sell).
4. Moving Average Types and Lengths
• First MA Type and Length: Choose SMA, EMA, or WMA along with a customizable period.
• Second and Third MA Types and Lengths: You can optionally stack additional moving averages for further smoothing, each with its own customizable type and period.
5. Streak Threshold Multiplier
This numeric input determines how strong a streak must be before the script considers it a “safe” trend. A higher multiplier requires a longer or more intense streak for a buy or sell signal.
6. Dynamic Transparency Calculation
The color intensity adapts to the streak’s strength. Longer streaks increase the transparency of the opposing color, making the current dominant color stand out. This feature ensures that a vigorous uptrend or downtrend is visually distinct from short-lived or weaker moves.
7. Ribbon Moving Averages
In ribbon mode, the script calculates moving averages for the Open, High, Low, and Close prices. Each of these is optionally smoothed again if the second and/or third moving average layers are active. The final result is a ribbon of moving averages that helps confirm whether the market is uniformly aligned above or below these key reference points.
Calculation Methodology
1. Initial Moving Average
The script calculates the first moving average (SMA, EMA, or WMA) of the closing price over a user-defined period.
2. Optional Secondary and Tertiary Averages
If selected, the script then applies a second and/or third smoothing step. Each of these steps can be a different type of moving average (SMA, EMA, or WMA) with its own period length.
3. Streak Detection
The indicator counts consecutive bars above or below the smoothed moving average. A running total (streakUp or streakDown) increments with every bar that remains above or below that average.
4. Reversion Intensity
The script compares the current streak value to its own average (calculated over the final chosen period). This ratio determines whether the streak is nearing a likely reversion or is strong enough to continue.
5. Color Assignment and Signals
The indicator calculates color transparency based on streak intensity. Buy and sell signals appear when the streak meets or exceeds the threshold multiplier, indicating a safe uptrend or downtrend.
Color Schemes and Visualization
This indicator offers multiple predefined color sets. Each scheme specifies a unique bullish color, bearish color and neutral color. The script automatically varies transparency to highlight strong trends and fade weaker ones, making it visually clear when a trend is intensifying or losing momentum.
Smoothing Techniques
By allowing up to three layers of moving average smoothing, the indicator accommodates different trading styles. A single layer provides faster reactions to market changes, while more layers reduce noise at the cost of slower responsiveness. Traders can choose the right balance between responsiveness and stability for their strategy, whether it is short-term scalping or long-term trend following.
Why It Combines Specific Smoothing Techniques
The Uptrick: Time Based Reversion indicator strategically combines specific smoothing techniques—SMA, EMA, and WMA—to leverage their complementary strengths. The SMA provides stable and consistent trend identification by equally weighting all data points, while the EMA emphasizes recent price movements, allowing quicker responses to market changes. WMA enhances sensitivity to recent price shifts, which helps in detecting subtle momentum changes early. By integrating these methods in layers, the indicator effectively balances responsiveness with stability, helping traders clearly identify genuine trend changes while filtering out short-term noise and false signals.
Ribbon Mode
If Open, High, Low, and Close prices remain above or below their respective moving averages consistently, the script colors the bars fully bullish or bearish. When the data points are mixed, a neutral color is applied. This mode provides a thorough perspective on whether the entire price range is aligned in one direction or showing conflicting signals.
Summary
Uptrick: Time Based Reversion combines multiple moving averages, streak detection, and dynamic color adjustments to help traders identify significant trends and potential reversal areas. Its flexibility allows it to be used either in a simpler form, with one moving average and streak analysis, or in a more advanced configuration with ribbon mode that charts multiple smoothed averages for a deeper understanding of price alignment. By adapting color intensities based on streak strength and providing optional buy/sell signals, this indicator delivers a clear and flexible tool suited to various trading strategies.
Disclaimer
This indicator is designed as an analysis aid and does not guarantee profitable trades. Past performance does not indicate future success, and market conditions can change unexpectedly. Users are advised to employ proper risk management and thoroughly evaluate trades before taking positions. Use this indicator as part of a broader strategy, not as a sole decision-making tool.
PnL MonitorThe PnL Monitor is a customizable tool designed to help traders track the Profit and Loss (PnL) of up to 20 currency pairs or assets in real-time. This script provides a clear and organized table that displays the entry price, and PnL percentage for each pair, making it an essential tool for monitoring open positions or tracking potential trades.
Key Features:
Multi-Asset Tracking:
Monitor up to 20 currency pairs or assets simultaneously. Simply input the pair symbol and your entry price, and the script will calculate the PnL in real-time.
Dynamic Table Positioning:
Choose where the table appears on your chart with the Table Position input. Options include:
Top Left
Top Right
Bottom Left
Bottom Right
Real-Time PnL Calculation:
The script fetches the current price of each pair and calculates the PnL percentage based on your entry price. Positive PnL is highlighted in green, while negative PnL is highlighted in red.
Exchange and Pair Separation:
The script automatically separates the exchange name (if provided) from the pair symbol, making it easier to identify the source of the data.
Customizable Inputs:
Add or remove pairs as needed.
Leave the price field blank for pairs you don’t want to track.
How to Use:
Input Your Pairs:
In the script settings, input the symbol of the pair (e.g., NASDAQ:AAPL or BTCUSD) and your entry price. Leave the price field blank for pairs you don’t want to track.
Choose Table Position:
Select where you want the table to appear on your chart.
Monitor PnL:
The table will automatically update with the current price and PnL percentage for each pair.
Why Use This Script?
Efficiency: Track multiple pairs in one place without switching charts.
Clarity: Easily identify profitable and losing positions at a glance.
Flexibility: Customize the table to fit your trading style and preferences.
Ideal For:
Forex, crypto, and stock traders managing multiple positions.
Uwen FX: UWEN StrategyThis Pine Script defines a trading indicator called "Uwen FX: UWEN Strategy" Where ideas coming from Arab Syaukani and modified by Fiki Hafana. It combines a CCI-based T3 Smoothed Indicator with a MACD overlay. Here's a breakdown of what it does:
Key Components of the Script:
1. CCI (Commodity Channel Index) with T3 Smoothing
Uses a T3 smoothing algorithm on the CCI to generate a smoother momentum signal. The smoothing formula is applied iteratively using weighted averages. The final result (xccir) is plotted as a histogram, colored green for bullish signals and red for bearish signals.
2. MACD (Moving Average Convergence Divergence)
The MACD is scaled to match the range of the smoothed CCI for better visualization. Signal Line and MACD Line are plotted if showMACD is enabled. The normalization ensures that MACD values align with the CCI-based indicator.
3. Bar Coloring for Trend Indication
Green bars indicate a positive trend (pos = 1).
Red bars indicate a negative trend (pos = -1).
Blue bars appear when the trend is neutral.
How It Can Be Used:
Buy Signal: When the xccir (smoothed CCI) turns green, indicating bullish momentum.
Sell Signal: When xccir turns red, indicating bearish momentum.
MACD Confirmation: Helps confirm the trend direction by aligning with xccir.
I will add more interesting features if this indicator seems profitable
TrendinatorThis indicator uses a custom Cumulative Delta Volume (CDV) calculation to dynamically generate support and resistance levels on the chart. It calculates CDV by taking the difference between uptick and downtick volumes, then accumulates these differences over time. From the cumulative delta, the indicator computes a MACD-style line by applying fast and slow exponential moving averages, and further smooths this into a signal line. The difference between the MACD line and its signal line (the histogram) is used to detect key crossover events.
When the CDV MACD line crosses below the signal line, the indicator captures the high of that candle as the new resistance level. Conversely, when the CDV MACD line crosses above the signal line, it captures the low of that candle as the new support level. These levels are maintained until the next corresponding crossover occurs, allowing the indicator to adapt to changes in market sentiment. A dynamic mid line is then calculated as the average of the current support and resistance levels, serving as a central pivot for the market.
Important Notice:
The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data before applying them in live trading scenarios.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research before making any trading decisions.
EPS Line Indicator - cristianhkrOverview
The EPS Line Indicator displays the Earnings Per Share (EPS) of a publicly traded company directly on a TradingView chart. It provides a historical trend of EPS over time, allowing investors to track a company's profitability per share.
Key Features
📊 Plots actual EPS data for the selected stock.
📅 Updates quarterly as new EPS reports are released.
🔄 Smooths missing values by holding the last reported EPS.
🔍 Helps track long-term profitability trends.
How It Works
The script retrieves quarterly EPS using request.financial(syminfo.tickerid, "EARNINGS_PER_SHARE", "Q", barmerge.gaps_off).
If EPS data is missing for a given period, the last available EPS value is retained to maintain continuity.
The EPS values are plotted as a continuous green line on the chart.
A baseline at EPS = 0 is included to easily identify profitable vs. loss-making periods.
How to Use This Indicator
If the EPS line is trending upwards 📈 → The company is growing earnings per share, a strong sign of profitability.
If the EPS line is declining 📉 → The company’s EPS is shrinking, which may indicate financial weakness.
If EPS is negative (below zero) ❌ → The company is reporting losses per share, which can be a warning sign.
Limitations
Only works with stocks that report EPS data (not applicable to cryptocurrencies or commodities).
Does not adjust for stock splits or other corporate actions.
Best used on daily, weekly, or monthly charts for clear earnings trends.
Conclusion
This indicator is a powerful tool for investors who want to visualize earnings per share trends directly on a price chart. By showing how EPS evolves over time, it helps assess a company's profitability trajectory, making it useful for both fundamental analysis and long-term investing.
🚀 Use this indicator to track EPS growth and make smarter investment decisions!
DS_Gurukul_5minTrendDS Gurukul (DS_5minTrend) Indicator: A Simple Yet Powerful Trend Tool
The Tushar Daily Bands (DS_5minTrend) indicator is a straightforward tool designed to help traders quickly visualize potential trend reversals and identify profitable trading opportunities. This indicator plots two bands—an upper band (green) and a lower band (red)—based on a small percentage deviation from the closing price of the first candle of each trading day.
How it Works:
The DS_5minTrend indicator calculates these bands at the start of each new trading day. The bands then remain fixed for the rest of that day. This daily reset allows traders to easily see how the current day's price action relates to the opening price and the calculated bands.
Trading Signals:
Potential Reversals: When the price approaches or touches the upper band (green), it can signal a potential overbought condition and a possible reversal to the downside. Conversely, when the price approaches or touches the lower band (red), it can suggest an oversold condition and a possible reversal to the upside.
Trend Confirmation: If the price consistently closes above the upper band for several periods, it may indicate a strong uptrend. Conversely, consistent closes below the lower band can suggest a strong downtrend.
Support and Resistance: The bands can also act as dynamic support and resistance levels. Traders can watch for price bounces off these levels as potential entry points.
How to Use:
Combine with other indicators: While DS_5minTrend can provide valuable insights, it's generally recommended to use it in conjunction with other technical indicators, such as RSI, MACD, or volume analysis, for confirmation.
Consider market context: Always consider the broader market context and news events that may be influencing price action.
Risk Management: Implement proper risk management strategies, including stop-loss orders, to protect your capital.
Disclaimer: The DS_5minTrend indicator is a tool for analysis and should not be the sole basis for making trading decisions. Trading involves substantial risk, and you could lose money. Always do your own research and consult with a financial advisor before making any investment decisions.
Adaptative Volume Weighted Oscillator | QuantumResearchQuantumResearch Adaptative Volume Weighted Oscillator (AVWO)
The Adaptative Volume Weighted Oscillator (AVWO) is an advanced momentum indicator that dynamically adjusts to changing market conditions. By combining Volume-Weighted Moving Averages (VWMA) with adaptive smoothing and volatility-based thresholds, this tool refines trend signals and enhances decision-making for traders.
🚀 Key Features:
Volume Sensitivity: Incorporates VWMA to account for volume-driven price movements, effectively filtering out market noise.
Adaptive Thresholds: Utilizes dynamic upper and lower bounds that adjust based on market volatility.
Momentum Confirmation: Identifies potential trend continuations or reversals with precision.
Customizable Visuals: Offers multiple color themes and bar color settings for clear and personalized visualization.
1. How It Works
The AVWO calculates the percentage difference between the price and the VWMA. This measure helps identify potential shifts in market momentum.
VWMA Calculation: Computes a moving average with volume
Oscillator Derivation: Determines how far the current price deviates from its VWMA.
Dynamic Thresholds: Employs volatility to set adaptive upper and lower limits.
Adaptive Smoothing: Applies a smoothing factor to fine-tune threshold responsiveness to new price movements.
🎯 Bullish Signal: Occurs when the oscillator breaks above the adaptive upper threshold.
⚠️ Bearish Signal: Occurs when the oscillator drops below the adaptive lower threshold.
2. Visual Representation
The AVWO offers clear and intuitive visual cues to aid in market analysis:
Color-Coded Histogram: Momentum bars change colors based on trend direction.
Threshold Lines: Dynamic lines mark overbought and oversold zones.
Bar Coloring: Candle colors adjust to reflect prevailing market conditions.
3. Backtest Performance
Extensive backtesting on major assets has demonstrated the effectiveness of the AVWO indicator:
BTC/USD
ETH/USD
SOL/USD
SUI/USD
📊 Key Results:
High Trend Recognition Accuracy: Captures strong trends with minimal lag.
Versatile Across Timeframes: Performs well in both short-term and long-term strategies.
Volume-Weighted Confirmation: Effectively filters false signals in volatile markets.
4. Customization & Parameters
The AVWO is highly configurable to suit your trading style:
VWMA Length (default: 30)
Adaptive Smoothing Factor (default: 0.85)
Threshold Multipliers
Color Modes (choose from 8 different themes for optimal visibility)
5. Trading Applications
This indicator is versatile and can be used in various trading strategies:
Trend Following: Confirms momentum shifts, helping to stay in profitable trades longer.
6. Final Thoughts
The Adaptative Volume Weighted Oscillator (AVWO) is a powerful tool for traders seeking a refined, volume-based momentum indicator.
Its unique blend of VWMA, dynamic thresholds, and adaptive smoothing enhances trend detection accuracy.
Whether used for scalping, swing trading, or long-term analysis, this indicator adapts seamlessly to various market conditions.
Important Disclaimer: No indicator guarantees future results. Always implement proper risk management and use additional confluences when trading.
Trade SafeTrade Safe: The Ultimate Discipline Tool for Traders
Are you tired of overtrading, revenge trading, or letting emotions ruin your trading plan? Trade Safe is here to transform your trading psychology and help you achieve consistent profitability. Unlike traditional indicators that focus solely on market analysis, Trade Safe addresses the number one reason traders fail: lack of discipline.
With its innovative features, Trade Safe enforces strict trading rules, prevents emotional decision-making, and helps you stick to your plan—no matter how volatile the markets get. If you're serious about becoming a disciplined and profitable trader, this is the tool you've been waiting for.
Enforces Trading Discipline:
Trade Safe ensures you stick to your daily trading plan by visually blocking your charts after a predetermined number of trades or a stop-loss, Take profit event.
No more overtrading or deviating from your strategy—Trade Safe keeps you in check.
Eliminates Emotional Trading:
The screen block feature prevents you from seeing the candles after a loss, helping you avoid the emotional spiral of "tilt" and revenge trading.
This unique approach focuses on the psychological side of trading, which is often overlooked by other tools.
Simple and Intuitive Interface:
Easily set your stop-loss and take-profit level with the red line marker for stop-loss and green for take-profit and choose between long or short positions with just a few clicks.
Trade Safe is designed to be user-friendly, so you can focus on trading without distractions.
Customizable for All Trading Styles:
Whether you're a scalper, swing trader, or long-term investor, Trade Safe can be tailored to fit your strategy.
Set your stop-loss and take-profit, and let Trade Safe handle the rest.
Prevents Revenge Trading:
By locking your screen after a stop-loss, Trade Safe eliminates the temptation to "make back" losses through impulsive trades.
This helps you break the cycle of emotional trading and stay focused on your long-term goals.
Builds Healthy Trading Habits:
Trade Safe encourages you to walk away after a loss, reinforcing the importance of patience and discipline.
Majors Rotation [AlphaAlgos]Majors Rotation System
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Overview
The Majors Rotation System is a trend-following strategy designed to dynamically allocate capital to the strongest-performing assets in the market. By leveraging long-term, medium-term, and equity curve trend filters, this system identifies the top assets and rotates between them based on prevailing market conditions. The system is defaulted for Bitcoin (BTC), Ethereum (ETH), and Solana (SOL) but is fully customizable and can be applied to any asset, trading pair, or asset class across various timeframes.
How It Works
At the core of this strategy are three key trend filters that help determine which assets to allocate capital to:
1. Long-Term Trend Filter:
- The long-term trend filter evaluates the broader market's direction. If the market is in a bullish phase, the system will engage with top assets, while in a bearish phase, it will exit positions to avoid unnecessary risk exposure.
2. Medium-Term Trend Filter:
- This filter assesses the market's momentum over a medium-term period. It ensures that the strategy stays aligned with short-to-medium-term market moves. When positive momentum is detected, the system adjusts its positions accordingly to capture these trends.
3. Equity Curve Trend Filter:
- The system continuously tracks the performance of its portfolio. If the equity curve (the overall portfolio value over time) is trending downward, the system will exit positions to mitigate losses. If the equity curve is trending upward, the system remains active and continues to rotate between top assets based on market strength.
These three filters work together to ensure that the system remains in assets only when market conditions are favorable, avoiding unnecessary risk during downturns while capitalizing on profitable trends.
Flexibility
While the Majors Rotation System is initially set up with BTC, ETH, and SOL, it is fully adaptable. Traders can apply the system to any assets they prefer, whether they’re trading cryptocurrencies, stocks, commodities, or forex. The system is defaulted for the one day timeframe, although, it is designed to be used on any timeframe, making it suitable for both short-term and long-term strategies. This versatility allows users to tailor the system to their specific trading style and asset preferences.
System Features
- Asset Selection and Rotation: The system ranks multiple assets based on the trend filters, allocating capital to the top performers and rotating out of weaker ones.
- Risk Management: Dynamic risk management is integrated, allowing the system to exit positions during unfavorable market conditions, ensuring that capital is only exposed to assets showing strength.
- Performance Metrics: Key metrics such as the Sharpe Ratio, Sortino Ratio, Omega Ratio, and Drawdowns are tracked to provide insight into the system’s performance and risk-adjusted returns.
- Equity Curve Tracking: The system displays the equity curve, allowing users to visualize how the strategy is performing over time and compare it to a simple buy-and-hold strategy.
- Customization: Traders can modify the system’s asset selection to match their trading preferences.
Performance Metrics and Comparison to Buy-and-Hold Bitcoin
The Majors Rotation System tracks several important performance metrics to help traders evaluate its effectiveness:
1. Sharpe Ratio:
- The Sharpe Ratio evaluates the risk-adjusted return, measuring how much excess return the system generates relative to its volatility. A higher Sharpe Ratio indicates that the system is delivering better returns for each unit of risk.
2. Sortino Ratio:
- Similar to the Sharpe Ratio, the Sortino Ratio focuses on downside risk (negative volatility), providing a more accurate measure of how the system generates returns while avoiding significant drawdowns.
3. Omega Ratio:
- The Omega Ratio evaluates both the upside and downside of the system’s performance. It measures the probability of achieving returns higher than a specified threshold, offering a clearer picture of how the strategy manages both risk and reward.
4. Equity Drawdown:
- This metric tracks the peak-to-trough decline in the portfolio’s value. It helps traders understand the worst-case scenario in terms of losses. Lower drawdowns indicate better risk management and smoother performance.
These metrics give traders a clear understanding of the risk-adjusted returns and overall stability of the system. By tracking these figures, traders can assess whether the Majors Rotation System aligns with their investment goals and risk tolerance.
Disclaimer
This script is a technical analysis tool designed to assist with asset rotation and portfolio management. While it uses real-time market data and trend-following strategies to generate asset recommendations, there are no guarantees regarding future performance. The system relies on historical and real-time data, which may not accurately predict future market behavior. Trading and investing inherently involve risk, and past performance is not indicative of future results.
Users should always conduct their own research, use proper risk management strategies, and consult with a qualified financial advisor before making investment decisions. This script is not intended as financial advice and should only be used as part of a broader investment strategy.
Kalman weighted price For Loop | QuantumResearchQuantumResearch Kalman Weighted Price For Loop Indicator
The QuantumResearch Kalman Weighted Price For Loop Indicator is an advanced tool designed for traders looking for precise trend detection and adaptive market analysis. This indicator integrates a Kalman filter, a weighted price calculation, and a for-loop scoring mechanism to dynamically assess price movements and provide clear trading signals.
Overview
Reduce Market Noise: The Kalman filter smooths price fluctuations for a clearer trend assessment.
Detect Trends: A weighted price calculation enhances trend analysis by adjusting dynamically to market conditions.
Adaptive Thresholds: ATR-based dynamic thresholds help traders assess breakout levels effectively.
Generate Trading Signals: A for-loop scoring mechanism evaluates historical price movements to identify long and short opportunities.
How It Works
A. Kalman Filter Smoothing
Purpose: The Kalman filter refines the selected price source (e.g., close price) by reducing short-term fluctuations, offering a clearer view of the underlying price movement.
Customization: Users can adjust key parameters such as:
Process Noise: Controls the filter’s sensitivity to recent changes.
Measurement Noise: Determines how responsive the filter is to incoming price data.
Filter Order: Sets the number of data points considered in the smoothing process.
B. Weighted Price & For-Loop Scoring
Weighted Price Calculation: A smoothing factor (alpha) is applied to blend the Kalman-filtered price with previous data, allowing for a more stable trend evaluation.
For-Loop Mechanism:
A dynamic scoring system iterates through a predefined price range, measuring if the weighted price is higher or lower than past values.
This score determines the overall trend strength and signals potential buy/sell conditions.
C. Threshold-Based Signal Generation
User-defined thresholds classify market conditions into bullish or bearish zones.
Default settings:
Long Signal: Triggered when the for-loop score exceeds the long_threshold.
Short Signal: Triggered when the score falls below the short_threshold.
Threshold bands dynamically adjust based on price behavior.
Visual Representation
The indicator’s design focuses on easy interpretation and usability:
Color-Coded Bar Signals:
Green Bars: Indicate bullish conditions when a long signal is active.
Red Bars: Indicate bearish conditions when a short signal is active.
Trend Confirmation Bands: The indicator plots upper, middle, and lower bands to visually represent market conditions.
Background Fill: The space between bands is shaded to highlight price deviations from equilibrium.
Customization & Parameters
This indicator is highly configurable, allowing traders to customize settings based on their strategy:
Kalman Filter Settings:
Process Noise: Default is 1.0, adjusts how much recent price data affects the filter.
Measurement Noise: Default is 0.05, determines responsiveness to price changes.
Filter Order: Default is 1, defines how many data points are analyzed at once.
For-Loop Parameters:
Lookback Range: Default is 1 to 50, determines how many past bars are used for scoring.
Scoring Thresholds:
Long Signal: Default threshold set at 40.
Short Signal: Default threshold set at -10.
Color Modes: Eight customizable color themes for individual preferences.
Trading Applications
This indicator is adaptable for various trading strategies:
Trend Following: Helps traders stay aligned with the dominant market direction by filtering noise and detecting sustained movements.
Momentum Analysis: Evaluates price strength and potential breakout conditions using adaptive scoring.
Reversal Detection: Identifies when momentum weakens, signaling possible trend shifts.
Risk Management: Uses for-loop scoring to minimize false signals and improve entry/exit precision.
Final Thoughts
The QuantumResearch Kalman Weighted Price For Loop Indicator combines Kalman filtering, adaptive price weighting, and for-loop scoring to deliver a structured approach to market trend analysis.
This unique methodology provides traders with enhanced noise reduction, improved signal clarity, and a flexible framework adaptable to different market conditions.
By adjusting the Kalman filter parameters, traders can fine-tune responsiveness and optimize settings for their specific trading style.
Important Disclaimer: This indicator is a tool for analysis and does not guarantee profitable outcomes. Traders should use proper risk management strategies and perform extensive backtesting before live trading.
Naive Bayes Candlestick Pattern Classifier v1.1 BETAAn intermezzo on why i made this script publication..
A : Candlestick Pattern took hours to backtest, why not using Machine Learning techniques?
B : Machine Learning, no that's gonna be really heavy bro!
A : Not really, because we use Naive Bayes.
B : The simplest, yet powerful machine learning algorithm to separate (a.k.a classify) multivariate data.
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Hello, everyone!
After deep research in extracting meaningful information from the market, I ended up building this powerful machine learning indicator based on the evolution of Bayesian Statistics. This indicator not only leverages the simplicity of Naive Bayes but also extends its application to candlestick pattern analysis, making it an invaluable tool for traders who are looking to enhance their technical analysis without spending countless hours manually backtesting each pattern on each market!.
What most interesting part is actually after learning all of likely useless methods like fibonacci, supply and demand, volume profile, etc. We always ended up back to basic like support and resistance and candlestick patterns, but with a slight twist on strategy algorithm design and statistical approach. Thus, the only reason why i made this, because i exactly know that you guys will ended up in this position as time goes by.
The essence of this indicator lies in its ability to automate the recognition and statistical evaluation of various candlestick patterns. Traditionally, traders have relied on visual inspection and manual backtesting to determine the effectiveness of patterns like Bullish Engulfing, Bearish Engulfing, Harami variations, Hammer formations, and even more complex multi-candle patterns such as Three White Soldiers, Three Black Crows, Dark Cloud Cover, and Piercing Pattern. However, these conventional methods are both time-consuming and prone to subjective bias.
To address these challenges, I employed Naive Bayes—a probabilistic classifier that, despite its simplicity, offers robust performance in various domains. Naive Bayes assumes that each feature is independent of the others given the class label, which, although a strong assumption, works remarkably well in practice, especially when the dataset is large like market data and the feature space is high-dimensional. In our case, each candlestick pattern acts as a feature that can be statistically evaluated based on its historical performance. The indicator calculates a probability that a given pattern will lead to a price reversal, by comparing the pattern’s close price to the highest or lowest price achieved in a lookahead window.
One of the standout features of this script is its flexibility. Each candlestick pattern is not only coded into the system but also comes with individual toggles to enable or disable them based on your trading strategy. This means you can choose to focus on single-candle patterns like Bullish Engulfing or more complex multi-candle formations such as Three White Soldiers, without modifying the core code. The built-in customization options allow you to adjust colors and labels for each pattern, giving you the freedom to tailor the visual output to your preference. This level of customization ensures that the indicator integrates seamlessly into your existing TradingView setup.
Moreover, the indicator isn’t just about pattern recognition—it also incorporates outcome-based learning. Every time a pattern is detected, it looks ahead a predefined number of bars to evaluate if the expected reversal actually materialized. This outcome is then stored in arrays, and over time, the script dynamically calculates the probability of success for each pattern. These probabilities are presented in a real-time updating table on your chart, which shows not only the percentage probability but also the count of historical occurrences. With this information at your fingertips, you can quickly gauge the reliability of each pattern in your chosen market and timeframe.
Another significant advantage of this approach is its speed and efficiency. While more complex machine learning models like neural networks might require heavy computational resources and longer training times, the Naive Bayes classifier in this script is lightweight, instantaneous and can be updated on the fly with each new bar. This real-time capability is essential for modern traders who need to make quick decisions in fast-paced markets.
Furthermore, by automating the process of backtesting, the indicator frees up your time to focus on other aspects of trading strategy development. Instead of manually analyzing hundreds or even thousands of candles, you can rely on the statistical power of Naive Bayes to provide you with insights on which patterns are most likely to result in profitable moves. This not only enhances your efficiency but also helps to eliminate the cognitive biases that often plague manual analysis.
In summary, this indicator represents a fusion of traditional candlestick analysis with modern machine learning techniques. It harnesses the simplicity and effectiveness of Naive Bayes to deliver a dynamic, real-time evaluation of various candlestick patterns. Whether you are a seasoned trader looking to refine your technical analysis or a beginner eager to understand market dynamics, this tool offers a powerful, customizable, and efficient solution. Welcome to a new era where advanced statistical methods meet practical trading insights—happy trading and may your patterns always be in your favor!
Note : On this current released beta version, you must manually adjust reversal percentage move based on each market. Further updates may include automated best range detection and probability.
Adaptive Sharp Momentum█ Introduction
The Adaptive Sharp Momentum Study has the following all-in-one features:
• A noise-free, trend-following indicator.
• Automatically detects implied tops and bottoms within fast price cycles.
• It identifies price consolidations and periods of indecision; often challenging to spot.
• Includes a unique feature for detecting directional price squeezes.
• An integrated volatility measure helps avoid false signals and clarifies trend direction.
• Lastly, it alerts traders when a volume climax is likely reached during a move.
This study primarily focuses on capturing momentum while concurrently alerting traders to shifting market dynamics, thereby aiding in the decision to either extend a position’s duration or optimize exit timing. The set of analytical tools, deployed alongside the trend-following indicator, are integrated to reflect the concepts outlined above. Furthermore, this framework utilizes distinctive methods for trend identification, consolidation recognition, directional squeeze assessment, and volume climax analysis—approaches that are not currently documented in publicly available resources.
█ Explanation of Core Components
1. Trend Following Consolidated Adaptive Moving Average:
At the core of the study is the Jurik Adaptive Average Curve, a fast-response adaptive moving average refined with an adaptive Relative Strength Index (RSX) function, known as Jurik RSX. This curve displays three trend modes—bullish, bearish, and indecisive—each customizable in color.
Users can adjust parameters such as the Phase and Consolidation Period:
• Phase: Influences the timing of trend signals, accommodating various trading styles. A lower phase value can produce leading signals, while a higher value may result in lagging signals.
• Consolidation Period: Helps filter out false signals. Optimize this period based on the time frame and instrument.
• Momentum Slope Threshold: As mentioned earlier, the Jurik moving average values are consolidated against the Dynamic Jurik RSX. Crossing the slope threshold of the Jurik RSX will trigger consolidation.
The main curve in the middle represents the overall trend. The issue with moving averages is that they work well in trends but when market is in consolidation, many false signals can be generated. The consolidation period acts as a second fast signal curve that helps eliminate the false signals generated through the standard adaptive moving average. This is basically done by measuring the momentum of the move itself through the Jurik RSX. There are other tools in this study that should also help the trader avoid false signals which will be fully described below.
2. Implied Tops and Bottoms
The study also detects Implied Tops and Bottoms during market cycles using the Composite Momentum and Projections. It offers three detection modes:
• Strong Signals: Indicate significant potential reversal points.
• Medium Signals: Typically displayed near the end of a trend, suggesting traders should prepare to exit.
• Rolling Signals: Alert traders to set tight stop losses to secure profits, as the market may be approaching a turning point.
By default, the colors of Rolling Signals and Medium Signals are the same for simplicity.
Note the following:
• The fast and slow period have the most effect on implied tops and bottoms detection.
• Adjusting the main period will also have an overall effect.
The above chart shows rolling tops, rolling bottoms, strong tops, and strong bottoms. A rolling top of bottom indicate an increase in momentum in that direction and thus a tight stoploss would be recommended, while a strong top/bottom indicates that an exit is warranted.
3. Consolidation and Volatility
If enabled, '+' will appear above the ceiling and floor plots if consolidation is detected. Consolidation is detected by using lookback function that determine if price is below a threshold or not. If below, then consolidation would be confirmed. This is accomplished by adjusting the ' Price Consolidation Threshold ' period
The above chart demonstrates detection of consolidation on a 1-minute chart. Also, note the ceiling and floor plot, it expands when volatility is high.
Consolidation detection helps weed out long and short signals indicated by the main curve.
4. Directional Squeeze
Another unique feature of this indicator is the detection of directional price squeeze. Directional squeeze is defined as a price push in the direction indicated by momentum whether upward or downward. This is different from the common squeeze indicators found on the web since this one is detecting a directional push.
The Directional Squeeze feature, indicated by up and down triangles above the main curve, highlights strong trends in the market's current direction:
• Trend Continuation: Allows traders to stay in profitable trades longer during strong trending markets.
• Multiple Modes: Offers single-bar (short-term) and longer-term squeezes. Single-bar squeezes can signal potential market reversals, while longer-term squeezes are useful in sustained trends.
Be mindful that under certain conditions, the directional squeeze could be directionless(sideways) if consolidation is outlined by the indicator. This is another useful feature the trader could utilize. The chart above mostly demonstrates directional squeeze but directionless can also be observed.
5. Volume Volatility and Volume Climax Detection
An essential feature of the Adaptive Sharp Momentum Study is its ability to measure Volume Volatility and detect Volume Climax moments:
• Volume Volatility Measure: Integrated into the study to help avoid false signals by assessing the strength of market moves. It provides better clarity on trend direction by indicating when the market is experiencing significant volume changes.
• Volume Climax Alerts: The study alerts traders when a volume climax is likely reached during a move, which is helpful for identifying potential reversal points or the culmination of a trend. Brighter confirmation signal dots indicate these climaxes, helping traders make timely entry/exit decisions.
• Adjustable Parameters: Traders can set the Volume Volatility Threshold and adjust the Volume Lookback Period to tailor the sensitivity of volume climax detection according to their trading strategy.
5. The indicator contains other useful features:
• Cycles: Helps determine when to enter long or short trades based on upward or downward market cycles. It also aids in recognizing retracement levels during a trend, allowing traders to capitalize on brief counter-trend movements. Those cycles can be observed as the up and down gray lines on the chart.
• Real-Time Table: The table is another visual aid that summarizes the status of each feature in real-time.
█ How to Use this Study Effectively
The main curve in the middle is your final decision point. Prior to entering a trade look for the following:
• Is the market in consolidation? If yes, then you'd be advised not to enter the trade until the study clearly shows no consolidation
• Is the ceil or floor plots showing a strong top or bottom, or even a volume climax in the direction to intend to enter? If yes, then either ensure you enter at a tight stop or don't enter
• Is there an indication of a directional squeeze with no consolidation or volume climax? Then this would be an ideal place to enter. Be mindful though that entering directional squeeze too late is not recommended.
• Once you are in the trade, look at consolidation, implied tops and bottoms, and volume climax to determine exit point. You will quickly realize if you entered a trade prematurely.
• Utilize the directional squeeze and the prevalent trend to help you stay in the trade longer.
• Adjust your stop losses depending on whether you are seeing a rolling implied top/bottom or a strong top/bottom.
• Also, at volume climaxes, be ready to exit. The approach with volume climax detection should be the same as the implied tops/bottoms.
Below is a chart demonstrating trading on a 1-minute chart. The study could be used for any time frame:
** Important Note **
This study relies on volume readings. Incorrect evaluation will be concluded without proper volume data.
█ How the Adaptive Sharp Momentum Works?
---Main Curve - Jurik Moving Average and RSX---
The Jurik Moving Average (JMA) and the Jurik RSX with Fisher transform (Relative Strength Index Extended) are technical tools designed to enhance data processing efficiency. The JMA uses an adaptive smoothing algorithm to dynamically adjust to market conditions, reducing lag while maintaining high responsiveness to price changes. the JMA incorporates a mechanism that determines smoothness based on input volatility. The RSX, on the other hand, tracks relative strength without introducing the overshoots and noise commonly seen in other momentum indicators. It achieves this by applying a yet another JMA smoothing function that ensures stability and consistency, making it a better candidate for identifying shifts.
This is a unique approach, but can simply be equated to two moving averages crossing over, except in this case, the RSX is crossing over with the JMA.
The process of determining market trends and consolidation for the main curve revolves around evaluating multiple conditions and rankings of indicators such as Jurik RSX, Fisher Transform, and Volume-based metrics (Adaptive On Balance Volume and Price Volatility). Here's how consolidation and trends are identified:
1. Trend Override Logic: The core logic evaluates whether specific conditions override the default trend determined by the JMA.
• Bearish Overrides: A trend is classified as bearish if specific conditions involving negative slopes of the RSX, bearish Fisher Transform readings, and other auxiliary rankings (AOBV trend rank or volatility ranks) are met.
• Bullish Overrides: Similarly, bullish trends are determined by the presence of positive RSX slopes, bullish Fisher readings, and supporting AOBV and volatility ranks.
• Neutral Overrides: If neither bullish nor bearish overrides dominate, and conflicting conditions are detected (e.g., a bearish Fisher with a bullish OBV), the trend can be overridden to neutral.
2. Dynamic Slope and Rank Analysis: RSX and Jurik Slopes: The slopes of the RSX and Jurik indicators play an important role. Increasing slopes suggest bullish momentum, while decreasing slopes imply bearish momentum.
3. Narrow Spread Analysis: Consolidation zones are identified by examining conditions like narrow spreads in price action and mixed indicator signals (e.g., a positive RSX slope alongside a neutral or bearish AOBV).
• When consolidation is detected, the system looks for confirming signals (AOBV or Fisher alignment) to determine whether the next move is likely to be bullish or bearish.
4.Fallback Logic:
If no explicit conditions are met for bullish, bearish, or neutral trends, the system defaults to comparing the current and previous values of the Jurik Moving Average. If the JMA is rising, the trend is set to bullish; otherwise, it defaults to bearish.
The process of consolidating The RSX with JMA, attempts to confirm the trend suggested by the Jurik moving average. As shown above, several factors play into this, but it is mostly motivated by the RSX and its slope
-- Detecting Tops and Bottoms --
• Composite Momentum
The Composite Momentum indicator analyzes the market's directional strength to identify implied tops and bottoms, especially at extreme values. It evaluates momentum by categorizing it into ranges that reflect moderate or strong trends for both bullish and bearish conditions. When momentum exceeds a positive threshold, it indicates a strong top, whereas values below a negative threshold then it's a strong bottom.
• Laguerre Dynamic Projection Bands
The Laguerre Dynamic Projection Bands focuses on price positioning within calculated dynamic boundaries. By applying linear regression, it projects upper and lower price bands, which serve as potential resistance and support levels. The oscillator value ranges from 0 to 100, representing the relative position of the current price. A value above 70 indicates the price is near a projected top, while a value below 30 suggests proximity to a projected bottom. Through custom Laguerre smoothing, the setup ensures that its signals remain stable and actionable.
• How They Work Together
The Composite Momentum and Projection Oscillator complement each other in detecting market tops and bottoms. The Projection Oscillator provides an early indication when price nears a critical level, while the Composite Momentum confirms whether the momentum supports the formation of a significant top or bottom.
-- Consolidation Detection, Volatility, and Volume Climax Detection --
• Summary of Consolidation Detection:
Consolidation is identified through a combination of statistical and smoothing applied to price data. The approach calculates deviations around the main plot using squared price inputs, smoothed averages, and adaptive multipliers. These deviations form dynamic upper and lower boundaries that adapt to changing market conditions. The system further evaluates these boundaries against historical bars to calculate a volume percentage, which indicates how often recent price action remains within these bands. A low percentage suggests consolidation, characterized by reduced volatility and price movement confined within a tighter range.
The bands around the main plot are derived from the calculated maximum deviations, creating adaptive ceilings and floors that expand or contract based on market dynamics. The Ceiling and Floor plots represent the outermost boundaries, while additional retracement plots are drawn based on the Composite Momentum wave rank. For example, during an uptrend, the retrace levels adjust upward in fractional steps relative to the deviation, signaling possible resistance levels. In downtrends, similar logic applies in reverse to determine support levels. These bands visually represent the volatility envelope and help contextualize price movements relative to expected ranges. Whenever, low volatility is detected, a visual "+" indicator is added to the plot to highlight that the market is likely in consolidation mode.
• How the Adaptive OBV Applies the Same Logic:
The Adaptive On-Balance Volume (OBV) uses a similar mechanism to detect volume climaxes by analyzing deviations in volume data. Instead of price, the OBV logic applies the squared input and smoothing methods to volume flows. By comparing these deviations to historical norms, the system identifies periods of high or low volatility in volume, which often coincide with potential breakouts or consolidation zones.
• How They Work Together
The consolidation detection process and the adaptive bands work in tandem to provide traders with a clear visualization of market conditions. When consolidation is detected, the dynamic bands narrow and a "+" sign is visualized, signaling reduced volatility and potential breakout opportunities. Similarly, volume-based analysis through the adaptive OBV helps confirm whether a breakout is accompanied by significant volume, adding confidence to trade decisions. Together, they enable anticipation of market shifts.
-- Directional Squeeze --
A directional price squeeze refers to a market condition where price compresses in a particular direction. This provides traders with an opportunity to stay in trades longer by aligning with the prevailing directional bias. This unique concept generates dynamic limits based on lookback period. Their convergence upward or downward is typically a strong indication of a price push toward the respective direction.
In this approach, the system looks at the highest and lowest values of a smoothed momentum reading over a recent period and measures the distance between them. Instead of relying on a static “overbought” or “oversold” line, it calculates new boundaries as a fraction of that distance, scaling the thresholds to match the price behavior. When these dynamically adjusted limits converge, it suggests a “directional squeeze”—meaning price is moving within a more compressed or focused range. Because these boundaries adapt to the market’s own highs and lows, they provide a more responsive indication of when price may be shifting into or out of a strong directional move.
• Determining the Directional Squeeze
Directional squeeze is identified using dynamic limits derived from two key factors:
Schaff Trend Cycle (STC) for single-bar squeezes. and the Slow RSI (SRSI) for multi-bar or longer-term squeezes. Both are utilizing a custom alpha factor for adaptability and conformance with the JMA and Dynamic RSX studies.
• Directional Trend Confirmation:
If the SRSI or STC approaches the limits, additional conditions such as Fisher RSX (momentum signals) and AOBV (volume signals) and the trend already established by the JMA are aligned. If so, then a squeezed in that trend directional is established.
█ Why These Components All Work Together?
The Adaptive Sharp Momentum Study integrates multiple components to provide a framework for analyzing market dynamics. Each feature addresses specific challenges in trading:
• Core Trend Identification:
The Jurik Adaptive Moving Average (JMA) and Jurik RSX ensure better trend detection by reducing noise and dynamically confirming momentum, thus minimizing lag and false signals.
• Implied Tops and Bottoms:
The combination of Composite Momentum and Laguerre Dynamic Projection Bands highlights critical turning points. This dual-layered approach identifies potential reversals and key support/resistance levels with improved clarity.
• Consolidation and Volatility:
Adaptive ceilings, floors, and consolidation detection filter out indecisive market phases. This helps avoid unreliable signals and provides a better perspective on potential breakouts or continuations.
• Directional Squeeze:
The Directional Squeeze feature identifies directional bias in price compression. Its dynamic thresholds adapt to market conditions, aiding in the assessment of strong directional moves.
• Volume Climax:
Volume volatility and climax detection highlight key moments of market activity, aiding in the evaluation of trend strength and potential turning points.
• Integrated Framework:
The integration of these components creates a system where each element complements the others.
This study offers a methodical approach to analyzing trends, momentum, and volatility while filtering noise. It is a tool designed to assist traders in navigating complex market conditions.
█ Disclaimer
This script is provided for educational and informational purposes only and should not be considered financial advice. Trading financial instruments carries a high level of risk and may not be suitable for all investors. Before using this script, please consult with a qualified financial advisor to ensure it aligns with your individual circumstances. The author does not guarantee the accuracy or completeness of the script and is not responsible for any losses or damages that may occur from its use. Use this script at your own risk.
[Excalibur] Advanced Polynomial Regression Trend ChannelIt's been a long time coming... Regression channel enthusiasts, it's 'ultimately' here! Welcome to my Apophis page. But first, let me explain the origins of its attributed name blending both descriptive & engaging content with concise & technical topics...
EGYPTIAN ROOTED TALES:
Apophis (Greek) or Apep (Egyptian) was known by many cultures to be a mighty Egyptian archetype of chaos, darkness, and destruction. In ancient Egyptian mythology, Apophis was often depicted in the form of a fearsome menacing serpent, in those days, with an insatiable appetite for relentless malevolence. This dreaded entity was considered a formidable enemy and was also believed to appear as a giant serpent arising from the underworld.
Forever engaging in eternal battle, according to lore, Apophis' adversarial attributes represented the forces of disorder and anarchy clashing with the forces of order and harmony. This serpent's wickedly described figure was significantly symbolic of the disruptive, treacherous powers that Apophis embodied, those which threatened to plunge the perceivable archaic world into darkness. To the ancients, the legendary cyclical struggles against Apophis served as allegory reflecting on the macrocosm of the larger conflict between good and evil disparities that shaped early ancient civilization, much like the tree serpent.
One of Apophis’ mythological roots was immortally depicted on tomb stone. On one particular hieroglyphic wall tableau, in the second chamber of Inherkau’s tomb at Deir el-Medina, within the Theban Necropolis, portrays a mural of a serpent (Apep) under an edible fruit tree being slain in defeat. The species of snake depicted on various locations of tomb walls appears to me to bear a striking resemblance to the big eyed Echis pyramidum (Egyptian saw-scaled viper) native to regions of North Africa and the Middle East. It's a species of viper notoriously contributing to the most snake bite fatalities in the world still to this day; talk about a true harbinger of chaos incarnate. You do NOT want to cross paths with this asp in the dark of night, ever! Nor the other species of Echis found around Echid trees in the garden.
As we all know, fabled archaic storytelling can be misconstruing. Yet, these archaic serpent narratives still have echoes of significant notions and wisdom to learn from, especially in a modern technological society still rife with miscalculating deep snakes slithering about with intent to specifically plot disorder on national scales, and then profitably capitalize on it. Many deep black snakes are hiding in plain sight and under rocks. They do indeed speak and spell with forked tongues and malfeasance to the masses. I have great news. Tools now exist in the realms of AI combined with fractal programming circles to uncover these venomous viper mesh networks and investigatively monitor their subversive activities, so their days are surely numbered for... GAME OVER. Prepare to meet the doom you vain vipers have sought!
The arrival of the great and powerful international storm of the century has come, clothed in vindication. It's the only just way for the globe to clean house and move forward economically into the evolving herafter unobstructed by rampant evils and corruption. The foundations of future architectures are being established, and these nefarious obstacles MUST NOT hinder that path ahead.
With my former days of serpent wrangling being behind me, I now explore avenues of history, philosophy, programming, and mathematics, weaving them all into my daily routine. Now is the time to make some mathematical history unfold and get to the good and spicy stuff that you as the reader seek...
CALCULATING ON CHAOS:
Perhaps frightful characteristics of serpents (their maneuverability to adapt to any swervy situation) could be harnessed and channeled into a powerful tool for navigating the treacherous waters of data chaos. What if taming a monstrous beast of mayhem was not only possible, but fully achievable? Well, I think I have improved upon an approach to better tackle fractal chaos handling and observation within a modest PSv6 float environment without doubles. Finally, I've successfully turned my pet anaconda, Apophis, into a docile form of mathematical charting resilience beyond anything I have ever visually witnessed before. This novel work clearly deprecates ALL of my prior regression works by performing everything those delivered AND more, but it doesn't necessarily eliminate them into extinction.
INTRODUCTION:
Allow me to introduce Apophis! What you see showcased above is also referred to as 'Advanced Polynomial Regression Trend Channel' (APRTC) for technical minds. I would describe it as an avant-garde trend channel obtaining accurate polynomial approximations on market data with Pine v6.0. APRTC is a fractal following demystifier that I can only describe as being a signal trajectory tracking stalker manifesting as a data devouring demon. My full-fledged 'Excalibur' version of poly-regression swiftly captures undulating patterns present in market data with ease and at warp speed faster than you can blink. Now unchained, this is my rendering of polynomial wrath employing the "Immense Power of Pine".
By pushing techniques of regression to extremes, I am able to trace the serpentine trajectory of chaos up to a 50th order with 100s or 1000s of samples via "advanced polynomial regression" (APR), aka Apophis. This uniquely reactive trend channel method is designed to enhance the way we engage with the complex challenge of observably interpreting chaotic price behavior. While this is the end of the road for my revolutionary trend channel technology, that doesn't imply that future polynomial regression upgrades won't/might occur... There are a number of other supplementary concepts I have in my mind that could potentially prove useful eventually, who knows. However, for the moment, I feel it's wisest to monitor how accommodating APRTC is towards servers for the present time.
HISTORICAL ENDEAVORS:
Having wrangled countless wild serpents in my youth by the handfuls, tackling this was one multi-headed regression challenge temptation I couldn't resist. Besides, serpents in reality are more than often scared of us in the wild, so I assumed this shouldn't be too terribly hard. Wrong! It's been a complex struggle indeed. APRTC gave me many stinging bites for a LONG time. I had unknowingly opened Pandora's box of polynomials unprepared for what was to follow.
Long have I wrestled with Apophis throughout many nights for years with adversity, at last having arrived at a current grand solution and ultimately emerging victorious. Now, does the significance of the entitled name Apophis become more apparent at this point of reading? What you can now witness above is a very powerful blend of precision combined with maneuverability, concluding my dreamy expectations of a maximal experience with polynomial regression in TV charts. With all of my wizardry components finally assembled, Apophis genuinely is the most phenomenal indicator I ever devised in my life... as of yet.
How was this accomplished? By unlocking a deep understanding of the mathematical principles that govern regression, combined with an arsenal of mathemagical trickeries through sheer determination. I also spent an incredible amount of time flexing the unbendable 64bit float numerics to obtain a feasible order/degree of up to 50 polynomials or up to 4000 bars of regression (never simultaneously) on a labyrinth of samples. Lastly, what was needed was a pinch of mathematical pixie dust with a pleasant dose of Pine upgrades (lots of line re-drawings) that millions of other members can also utilize. Thank you so much, Pine developers, for once again turning meager proposed visions into materialized reality by leveraging the "Power of Pine" for the many!
DESCRIBING POLYNOMIAL REGRESSION:
APRTC is a visual guide for navigating noisy markets, providing both trajectory and structure through the power of mathematical modeling. Polynomial regression, especially at higher orders, exhibits obvious sidewinder/serpentine like characteristics. Even the channel extremities, on swift one second charts, resemble scales in motion with a pair of dashed exterior lines. This poly version presently yields the best quality of fit, providing an extreme "visual analysis" of your price action in high noise environments. The greater the order of the polynomial, the more pronounced the meandering regression characteristics become, as the algorithm strives to visually capture the fundamental fractal patterns most effectively.
Polynomial Regression in Action:
The medial line displays the core polynomial regression approximation in similarity to spinal backbones of serpents when following the movements of market data. Encasing the central structure, the channel's skin consists of enveloping lines having upper and lower extremes. To further enhance visualization, background fill colors distinguish the breadth between positive and negative territories of potential movement.
Additional internal dotted variability lines are available with multiple customizable settings to adjust dynamic dispersion, color, etc. One other exciting feature I added is the the ability to see the polynomial values with up to 50 (adjustable) decimal places if available. Witnessing Xⁿ values tapering near to 0.0 may indicate overfitting. Linear regression is available at order=1 and quadratic regression is invoked using order=2.
Information Criterion:
A toggleable label provides a multitude of information such as Bayesian Information Criterion (BIC), order, period, etc. BIC serves as an polynomial regression fit metric, with lesser values indicating a better balance between polynomial order adjustments, reflecting a more accurate fit in relation to the channel's girth. One downside of BIC values is their often large numerical values, making visual comparisons challenging, and then also their rare occurrence as negative values.
Furthermore, I formulated my own "EXPERIMENTAL" Simpler Information Criterion (SIC) fit metric, which seems to offer better visual interpretability when adjusting order settings on a selected regression period, especially on minuscule price numerics. Positive valued SIC numerics with lesser digits also reflect a preferred better fit during order adjustment, same as applying BIC principles of the minimum having a superior calulation tendency. I'll let members be the judge of deciding whether my SIC is actually a superior information criterion compared to BIC.
TECHNICAL INTERPRETATION and APPLICATION:
The Apophis indicator utilizes high-order polynomial regression, up to a maximum 50th order ability to deliver a nuanced, visual representation of complex market dynamics. I would caution against using upwards toward a 50th order, because opting for a 50th order polynomial is categorically speaking "wildly unsane" in real-world practice. As the polynomial degree increases from lesser orders, the regression line exhibits more pronounced curvature and undulations.
Visually analyzing the regression curve can provide insights into prevailing trends, as well as volatility regimes. For example, a gently sloping line may signal a steady directional trend, while a tightly curled oscillating curve may indicate heightened volatility and range-bound trading. Settings are rather straight forward, and comparable to my former "Quadratic Regression Trend Channel" efforts, although one torturous feature from QRTC is omitted due too computational complexity concerns.
Notice: Trial invite only access will not be granted for this indicator. Those who are familiar with recognizing what APRTC is, you will either want it or not, to add to your arsenal of trading approaches.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
RISK DISCLAIMER:
My scripts and indicators are specifically intended for informational and educational use only. This script uses historical data points to perform calculations to derive real-time calculations. They do not infer, indicate, or guarantee future results or performance.
By utilizing this script/indicator or any portion of it, you agree to accept 100% responsibly and liability for your investment or financial decisions, and I will not be held liable for your subjective analytic interpretations incurring sustained monetary losses. The opinions and information visual or otherwise provided by this script/indicator is not investment advice, nor does it constitute recommendation.
Reversal rehersal v1This indicator was designed to identify potential market reversal zones using a combination of RSI thresholds (shooting range/falling range), candlestick patterns, and Fair Value Gaps (FVGs). By combining all these elements into one indicator, it allow for outputting high probability buy/sell signals for use by scalpers on low timeframes like 1-15 mins, for quick but small profits.
Note: that this has been mainly tested on DE40 index on the 1 min timeframe, and need to be adjusted to whichever timeframe and symbol you intend to use. Refer to the backtester feature for checking if this indicator may work for you.
The indicator use RSI ranges from two timeframes to highlight where momentum is building up. During these areas, it will look for certain candlestick patterns (Sweeps as the primary one) and check for existance of fair value gaps to further enhance the hitrate of the signal.
The logic for FVG detection was based on ©pmk07's work with MTF FVG tiny indicator. Several major changes was implemented though and incorporated into this indicator. Among these are:
Automatically adjustments of FVG boxes when mitigated partially and options to extend/cull boxes for performance and clarity.
Backtesting Table (Experimental):
This indicator also features an optional simplified table to review historical theoretical performance of signals, including win rate, profit/loss, and trade statistics. This does not take commision or slippage into consideration.
Usage Notes:
Setup:
1. Add the indicator to your chart.
2. Decide if you want to use Long or Short (or both).
3. If you're scalping on ie. 1 min time frame, make sure to set FVG's to higher timeframes (ie. 5, 15, 60).
4. Enable the 'Show backtest results' and adjust the 'Signals' og 'Take profit' and 'Stop loss' values until you are satisfied with the results.
Use:
1. Setup an alert based on either of the 'BullishShooting range' or 'BearishFalling range' alerts. This will draw your attention to watch for the possible setups.
2. Verify if there's a significant imbalance prior to the signal before taking the trade. Otherwise this may invalidate the setup.
3. Once a signal is shown on the graph (either Green arrow up for buys/Red arrow down for sells) - you should enter a trade with the given 'Take profit' and 'Stop loss' values.
4. (optional) Setup an alert for either the Strong/Weak signals. Which corresponds to when one of the arrows are printed.
Important: This is the way I use it myself, but use at own risk and remember to combine with other indicators for further confluence. Remember this is no crystal ball and I do not guarantee profitable results. The indicator merely show signals with high probability setups for scalping.
Daily COC Strategy with SHERLOCK WAVESThis indicator implements a unique trading strategy known as the "Daily COC (Candle Over Candle) Strategy" enhanced with "SHERLOCK WAVES" for pattern recognition. It's designed for traders looking to capitalize on specific candlestick formations with a negative risk-reward ratio, with the aim of achieving a high win rate (over 70%) through numerous trading opportunities, despite each trade having a higher risk relative to the reward.
Key Features:
Pattern Recognition: Identifies a setup based on three consecutive candles - a red candle followed by a shooting star, then an entry candle that does not break below the shooting star's low.
Negative Risk/Reward Trade Selection: Focuses on entries where the potential stop loss is greater than the take profit, banking on a high win rate to offset the individual trade's negative risk-reward ratio.
Visual Signals:
Green Label: Marks potential entry points at the high of the candle before the entry.
Green Dot: Indicates a winning trade closure.
Red Dot: Signals a losing trade closure.
Blue Circle: Warns when the current candle is within 2% of breaking above the previous candle's high, suggesting a potential setup is developing.
Green Circle: Plots the take profit level.
Red Circle: Plots the stop loss level.
Dynamic Statistics: A live updating label showing the number of trades, wins, losses, open trades, current account balance, and win percentage.
Customizable Parameters:
Risk % per Trade: Adjust the percentage of your account balance you're willing to risk on each trade.
Initial Account Balance: Set your starting balance for tracking performance.
Start Date for Strategy: Define when the strategy should start calculating from, allowing for backtesting.
Alerts:
An alert condition is set for when a potential trade setup is developing, helping traders prepare for entries.
Usage Tips:
This strategy is predicated on the idea that a high win rate can compensate for the negative risk-reward ratio of individual trades. It might not suit all market conditions or traders' risk profiles.
Use this strategy in conjunction with other analysis methods to validate trade setups.
Note: Always backtest thoroughly before applying to live markets. Consider this tool as part of a broader trading strategy, not a standalone solution. Monitor your win rate and adjust your risk management accordingly to ensure the strategy remains profitable over time.
This description now correctly explains the purpose behind the negative risk-reward ratio in the context of your trading strategy.
KRI For Loop | QuantumResearchIntroducing Rocheur’s KRI For Loop Indicator
The KRI For Loop indicator is an advanced trend-following tool that enhances the traditional Kairi Relative Index (KRI) with a for-loop scoring mechanism. The Kairi Relative Index (KRI) measures the percentage deviation of price from its smoothed moving average, helping traders identify market trends and reversals. By incorporating a for-loop calculation, this version refines trend detection, making it a powerful tool for traders seeking precise entry and exit points.
Understanding the KRI For Loop
The Kairi Relative Index (KRI) is a momentum-based indicator that calculates how far the current price deviates from its moving average, expressed as a percentage. It is widely used to identify overbought and oversold conditions, as well as potential trend reversals.
In this enhanced version, a for-loop scoring mechanism systematically evaluates KRI values within a defined range to determine trend strength:
KRI Calculation: The formula computes the percentage difference between price and an Exponential Moving Average (EMA) of a user-defined length.
For-Loop Scoring: A dynamic scoring system assesses the strength of KRI values across a range (default: -20 to 20), helping to refine market trend analysis.
Threshold-Based Signal Generation:
Long Signal: Triggered when the for-loop score surpasses the long threshold (default: 8).
Short Signal: Triggered when the score falls below the short threshold (default: -5).
Visual Representation
The KRI For Loop indicator provides a clear, color-coded trend analysis:
Green Bars: Indicate bullish conditions when the score surpasses the long threshold, signaling a potential buy opportunity.
Red Bars: Indicate bearish conditions when the score drops below the short threshold, suggesting a sell opportunity.
Gray Bars: Show neutral conditions when the score remains within the defined range.
KRI Bands: Three horizontal bands help visualize market structure:
Upper Band: Represents the bullish threshold.
Middle Band: Zero line for neutral conditions.
Lower Band: Represents the bearish threshold.
Background Fill: A shaded area between the bands highlights trend intensity.
Customization & Parameters
The KRI For Loop indicator offers multiple user-configurable settings for flexibility:
KRI Length: Default set to 27, determines the EMA smoothing period.
Source Price: Selectable input price for calculations (default: close).
Scoring Range (a, b): Defines the range of KRI values assessed in the for-loop (default: -20 to 20).
Long & Short Thresholds:
Long Threshold: Default set to 8, determines when bullish conditions are strong enough for a buy signal.
Short Threshold: Default set to -5, identifies bearish conditions for sell signals.
Color Modes: Choose from eight distinct color schemes to personalize the indicator’s appearance.
Trading Applications
This indicator is highly adaptable and can be applied to various trading strategies, including:
Momentum Trading: Evaluates trend strength based on KRI deviation and for-loop scoring.
Trend Following: Helps traders stay in profitable trends by identifying strong bullish and bearish conditions.
Reversal Detection: The crossing of key KRI thresholds can signal potential market reversals.
Risk Management: Clearly defined entry and exit rules help traders manage risk effectively.
Final Note
Rocheur’s KRI For Loop indicator combines the power of the Kairi Relative Index (KRI) with an advanced for-loop scoring method to deliver a refined market trend analysis. This structured approach offers traders a dynamic and visually intuitive tool for detecting momentum shifts and trend reversals. As always, backtesting and strategic adjustments are essential to fully optimize this indicator for real-world trading.
Scalping trading system based on 4 ema linesScalping Trading System Based on 4 EMA Lines
Overview:
This is a scalping trading strategy built on signals from 4 EMA moving averages: EMA(8), EMA(12), EMA(24) and EMA(72).
Conditions:
- Time frame: H1 (1 hour).
- Trading assets: Applicable to major currency pairs with high volatility
- Risk management: Use a maximum of 1-2% of capital for each transaction. The order holding time can be from a few hours to a few days, depending on the price fluctuation amplitude.
Trading rules:
Determine the main trend:
Uptrend: EMA(8), EMA(12) and EMA(24) are above EMA(72).
Downtrend: EMA(8), EMA(12) and EMA(24) are below EMA(72).
Trade in the direction of the main trend** (buy in an uptrend and sell in a downtrend).
Entry conditions:
- Only trade in a clearly trending market.
Uptrend:
- Wait for the price to correct to the EMA(24).
- Enter a buy order when the price closes above the EMA(24).
- Place a stop loss below the bottom of the EMA(24) candle that has just been swept.
Downtrend:
- Wait for the price to correct to the EMA(24).
- Enter a sell order when the price closes below the EMA(24).
- Place a stop loss above the top of the EMA(24) candle that has just been swept.
Take profit and order management:
- Take profit when the price moves 20 to 40 pips in the direction of the trade.
Use Trailing Stop to optimize profits instead of setting a fixed Take Profit.
Note:
- Do not trade within 30 minutes before and after the announcement of important economic news, as the price may fluctuate abnormally.
Additional filters:
To increase the success rate and reduce noise, this strategy uses additional conditions:
1. The price is calculated only when the candle closes (no repaint).
2. When sweeping through EMA(24), the price needs to close above EMA(24).
3. The closing price must be higher than 50% of the candle's length.
4. **The bottom of the candle sweeping through EMA(24) must be lower than the bottom of the previous candle (liquidity sweep).
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Alert function:
When the EMA(24) sweep conditions are met, the system will trigger an alert if you have set it up.
- Entry point: The closing price of the candle sweeping through EMA(24).
- Stop Loss:
- Buy Order: Place at the bottom of the sweep candle.
- Sell Order: Place at the top of the sweep candle.
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Note:
This strategy is designed to help traders identify profitable trading opportunities based on trends. However, no strategy is 100% guaranteed to be successful. Please test it thoroughly on a demo account before using it.
ZenAlgo - Advanced Open InterestZenAlgo - Advanced Open Interest combines open interest, price changes, and volume dynamics into a single, powerful TradingView indicator. By integrating these key market metrics and enhancing them with proprietary algorithms, it provides traders with actionable insights that streamline decision-making and enhance market analysis.
Features
Open Interest Change (%): Tracks changes in open interest, a key indicator of market participation and sentiment.
Price Change (%): Monitors price momentum, providing clarity on trend directions.
Volume Analysis: Aggregates upward and downward volume for detailed sentiment analysis.
Delta Calculation: Highlights the net difference between upward and downward volume, offering instant insights into buying or selling dominance.
Proprietary Trend Detection: Suggests "Long Enter," "Short Enter," "Long Close," or "Short Close" signals based on a synergy of open interest, price, and volume.
Market Sentiment Insights: Indicates whether new long or short positions dominate.
Customizable Display: Features themes, sizes, and positions for a tailored interface.
Added Value: Why Is This Indicator Original/Why Shall You Pay for This Indicator?
Integrated Synergy: Combining open interest, price, and volume into a single indicator reduces complexity and offers enhanced clarity. Instead of toggling between multiple charts, users receive actionable insights from a unified view.
Proprietary Rules-Based Algorithm: The algorithm synthesizes data from sub-indicators, creating trends and signals not available in free tools. For instance, the "Long Enter" or "Short Close" signals are generated by evaluating relationships between metrics, offering a predictive edge.
Enhanced Trend Confirmation: By correlating open interest changes with price movements and volume imbalances, the indicator provides a more robust confirmation of market trends compared to individual metrics.
Time-Saving and Simplicity: Freely available sub-indicators require manual setup, interpretation, and customization. ZenAlgo - Advanced Open Interest offers pre-configured analysis, reducing the learning curve and decision time.
Unique Customization: With themes, positions, and table sizes, users can adapt the interface to their preferences, enhancing usability.
How It Works
1. Open Interest and Price Change
Retrieves historical open interest and price data for the selected timeframe.
Calculates percentage changes between bars to indicate market participation (open interest) and directional momentum (price).
Combines these metrics to assess whether price movements are supported by increasing or decreasing participation.
2. Volume Aggregation
Splits the selected timeframe into smaller sub-timeframes to analyze granular volume data.
Aggregates upward (price closes above open) and downward (price closes below open) volumes, calculating their totals and percentage contributions to overall volume.
3. Delta Calculation
Computes Delta as the difference between upward and downward volume.
Highlights buyer or seller dominance using color-coded visuals for quick interpretation.
4. Trend Analysis
Uses a proprietary algorithm to classify market states:
"Long Enter": Rising price, increasing open interest, and dominant upward volume.
"Short Enter": Falling price, increasing open interest, and dominant downward volume.
Neutral States: Generated when no strong alignment is found among metrics.
5. Market Sentiment
Correlates open interest and price to indicate if new long or short positions dominate.
Outputs simplified insights like "More longs opened" or "Shorts closing."
6. Customizable Table
Displays real-time updates with user-controlled themes, sizes, and positions for a tailored experience.
Usage Examples
Detecting Bullish Trends: Identify "Long Enter" signals when open interest and price rise, supported by strong upward volume.
Spotting Bearish Reversals: Use "Short Enter" signals when price declines, open interest rises, and downward volume dominates.
Analyzing Volume Shifts: Leverage Delta to uncover significant shifts in buying or selling pressure.
Validating Trends: Use the combination of open interest and volume trends to confirm price movements.
Exiting Profitable Trades: Look for "Long Close" or "Short Close" signals to time exits during profit-taking phases.
Avoiding Choppy Markets: Use "Neutral" signals to stay out of indecisive markets and avoid unnecessary risks.
Identifying Sentiment Swings: Follow "Positions" insights to detect a transition in market dominance from longs to shorts or vice versa.
High-Volume Trend Confirmation: Confirm strong trends during high trading volumes.
Short-Term Scalping: Use sub-timeframes to spot rapid entry and exit points.
Event-Based Trading: Correlate indicator signals with major market events for timely trades.
Settings
ZenAlgo Theme: Toggle a branded theme for better visual integration.
Table Size: Adjust display size (Tiny, Small, Normal, Large) based on preference.
Table Position: Choose between four positions (e.g., Bottom Right, Top Left).
Table Mode: Switch between Dark and Light themes for optimal readability.
Important Notes
This indicator is a technical analysis tool and does not guarantee trading success. Use it with other indicators and fundamental analysis for a comprehensive strategy.
Always validate signals in conjunction with other market factors to ensure informed trading decisions.
Scenarios of Potential Underperformance:
Low-Volume Markets: Signals may lack reliability due to insufficient data granularity.
Extreme Volatility: Rapid price movements can distort short-term insights.
Exchange Variations: Data discrepancies between exchanges may affect calculations.
Choppy Markets: During indecisive phases, the indicator may generate more neutral signals.
Volume Weighted HMA Index | mad_tiger_slayerTitle: 🍉 Volume Weighted HMA Index | mad_tiger_slayer 🐯
Description:
The Volume Weighted HMA Index is a cutting-edge indicator designed to enhance the accuracy and responsiveness of trading signals by combining the power of volume with the Hull Moving Average (HMA). This indicator adjusts the HMA based on volume-weighted price changes, providing faster and more reliable entry and exit signals while reducing the likelihood of false signals.
Intended and Best Uses:
Used for Strategy Creation:
Extremely Quick Entries and Exits
Intended for Higher timeframe however can be used for scalping paired with additional scripts.
Can be paired to create profitable strategies
TREND FOLLOWING NOT MEAN REVERTING!!!!
[Key Features:
Volume Integration: Dynamically adjusts the HMA using volume data to prioritize higher-volume bars, ensuring that market activity plays a crucial role in signal generation.
Enhanced Signal Clarity: The indicator calculates precise long and short signals by detecting volume-weighted HMA crossovers.
Bar Coloring: Visually differentiate bullish and bearish conditions with customizable bar colors, making trends easier to identify.
Custom Signal Plotting: Optional long and short signal markers for a clear visual representation of potential trade opportunities.
Highly Configurable: Adjust parameters such as volume length and calculation source to tailor the indicator to your trading preferences and strategy.
How It Works:
Volume Weighting: The indicator calculates the HMA using a volume-weighted price change, amplifying the influence of high-volume periods on the moving average.
Trend Identification: Crossovers of the volume-weighted HMA with zero determine trend direction, where:
A bullish crossover signals a long condition.
A bearish crossunder signals a short condition.
Visual Feedback: Bar colors and optional signal markers provide real-time insights into trend direction and trading signals.
Use Cases:
Trend Following: Quickly identify emerging trends with volume-accelerated HMA calculations.
Trade Confirmation: Use the indicator to confirm the strength and validity of your trade setups.
Custom Signal Integration: Combine this indicator with your existing strategies to refine entries and exits.
Notes:
Ensure that your trading instrument provides volume data for accurate calculations. If no volume is available, the script will notify you.
This script works best when combined with other indicators or trading frameworks for a comprehensive market view.
Inspired by the community and designed for traders looking to stay ahead of the curve, the Volume Weighted HMA Index is a versatile tool for traders of all levels.
Trading IQ - Razor IQIntroducing TradingIQ's first dip buying/shorting all-in-one trading system: Razor IQ.
Razor IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade upside/downside price dips of varying significance in trending markets. By integrating artificial intelligence and IQ Technology, Razor IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Razor IQ
Razor IQ operates on a single premise: Trends must retrace, and these retracements offer traders an opportunity to join in the overarching trend. At some point traders will enter against a trend in aggregate and traders in profitable positions entered during the trend will scale out. When occurring simultaneously, a trend will retrace against itself, offering an opportunity for traders not yet in the trend to join in the move and continue the trend.
Razor IQ is designed to work straight out of the box. In fact, its simplicity requires just a few user settings to manage output, making it incredibly straightforward to manage.
Long Limit Order Stop Loss and Minimum ATR TP/SL are the only settings that manage the performance of Razor IQ!
Traders don’t have to spend hours adjusting settings and trying to find what works best - Razor IQ handles this on its own.
Key Features of Razor IQ
Self-Learning Retracement Detection
Employs AI and IQ Technology to identify notable price dips in real-time.
AI-Generated Trading Signals
Provides retracement trading signals derived from self-learning algorithms.
Comprehensive Trading System
Offers clear entry and exit labels.
Performance Tracking
Records and presents trading performance data, easily accessible for user analysis.
Self-Learning Trading Exits
Razor IQ learns where to exit positions.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
How It Works
Razor IQ operates on a straightforward heuristic: go long during the retracement of significant upside price moves and go short during the retracement of significant downside price moves.
IQ Technology, TradingIQ's proprietary AI algorithm, defines what constitutes a “trend” and a “retracement” and what’s considered a tradable dip buying/shorting opportunity. For Razor IQ, this algorithm evaluates all historical trends and retracements, how much trends generally retrace and how long trends generally persist. For instance, the "dip" following an uptrend is measured and learned from, including the significance of the identified trend level (how long it has been active, how much price has increased, etc). By analyzing these patterns, Razor IQ adapts to identify and trade similar future retracements and trends.
In simple terms, Razor IQ clusters previous trend and retracement data in an attempt to trade similar price sequences when they repeat in the future. Using this knowledge, it determines the optimal, current price level where joining in the current trend (during a retracement) has a calculated chance of not stopping out before trend continuation.
For long positions, Razor IQ enters using a market order at the AI-identified long entry price point. If price closes beneath this level a market order will be placed and a long position entered. Of course, this is how the algorithm trades, users can elect to use a stop-limit order amongst other order types for position entry. After the position is entered TP1 is placed (identifiable on the price chart). TP1 has a twofold purpose:
Acts as a legitimate profit target to exit 50% of the position.
Once TP1 is achieved, a stop-loss order is immediately placed at breakeven, and a trailing stop loss controls the remainder of the trade. With this, so long as TP1 is achieved, the position will not endure a loss. So long as price continues to uptrend, Razor IQ will remain in the position.
For short positions, Razor IQ provides an AI-identified short entry level. If price closes above this level a market order will be placed and a short position entered. Again, this is how the algorithm trades, users can elect to use a stop-limit order amongst other order types for position entry. Upon entry Razor IQ implements a TP order and SL order (identifiable on the price chart).
Downtrends, in most markets, usually operate differently than uptrends. With uptrends, price usually increases at a modest pace with consistency over an extended period of time. Downtrends behave in an opposite manner - price decreases rapidly for a much shorter duration.
With this observation, the long dip entry heuristic differs slightly from the short dip entry heuristic.
The long dip entry heuristic specializes in identifying larger, long-term uptrends and entering on retracement of the uptrends. With a dedicated trailing stop loss, so long as the uptrend persists, Razor IQ will remain in the position.
The short dip entry heuristic specializes in identifying sharp, significant downside price moves, and entering short on upside volatility during these moves. A fixed stop loss and profit target are implemented for short positions - no trailing stop is used.
As a trading system, Razor IQ exits all TP orders using a limit order, with all stop losses exited as stop market orders.
What Classifies As a Tradable Dip?
For Razor IQ, tradable price dips are not manually set but are instead learned by the system. What qualifies as an exploitable price dip in one market might not hold the same significance in another. Razor IQ continuously analyzes historical and current trends (if one exists), how far price has moved during the trend, the duration of the trend, the raw-dollar price move of price dips during trends, and more, to determine which future price retracements offer a smart chance to join in any current price trend.
The image above illustrates the Razor Line Long Entry point.
The green line represents the Long Retracement Entry Point.
The blue upper line represents the first profit target for the trade.
The blue lower line represents the trailing stop loss start point for the long position.
The position is entered once price closes below the green line.
The green Razor Lazor long entry point will only appear during uptrends.
The image above shows a long position being entered after the Long Razor Lazor was closed beneath.
Green arrows indicate that the strategy entered a long position at the highlighted price level.
Blue arrows indicate that the strategy exited a position, whether at TP1, the initial stop loss, or at the trailing stop.
Blue lines above the entry price indicate the TP1 level for the current long trade. Blue lines below the current price indicate the initial stop loss price.
If price reaches TP1, a stop loss will be immediately placed at breakeven, and the in-built trailing stop will determine the future exit price.
A blue line (similar to the blue line shown for TP1) will trail price and correspond to the trailing stop price of the trade.
If the trailing stop is above the breakeven stop loss, then the trailing stop will be hit before the breakeven stop loss, which means the remainder of the trade will be exited at a profit.
If the breakeven stop loss is above the trailing stop, then the breakeven stop loss will be hit first. In this case, the remainder of the position will be exited at breakeven.
The image above shows the trailing stop price, represented by a blue line, and the breakeven stop loss price, represented by a pink line, used for the long position!
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
The image above exemplifies Razor IQ's output when a downtrend is active.
When a downtrend is active, Razor IQ will switch to "short mode". In short mode, Razor IQ will display a neon red line. This neon red line indicates the Razor Lazor short entry point. When price closes above the red Razor Lazor line a short position is entered.
The image above shows Razor IQ during an active short position.
The image above shows Razor IQ after completing a short trade.
Red arrows indicate that the strategy entered a short position at the highlighted price level.
Blue arrows indicate that the strategy exited a position, whether at the profit target or the fixed stop loss.
Blue lines indicate the profit target level for the current trade when below price. and blue lines above the current price indicate the stop loss level for the short trade.
Short traders do not utilize a trailing stop - only a fixed profit target and fixed stop loss are used.
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
Minimum Profit Target And Stop Loss
The Minimum ATR Profit Target and Minimum ATR Stop Loss setting control the minimum allowed profit target and stop loss distance. On most timeframes users won’t have to alter these settings; however, on very-low timeframes such as the 1-minute chart, users can increase these values so gross profits exceed commission.
After changing either setting, Razor IQ will retrain on historical data - accounting for the newly defined minimum profit target or stop loss.
AI Direction
The AI Direction setting controls the trade direction Razor IQ is allowed to take.
“Trade Longs” allows for long trades.
“Trade Shorts” allows for short trades.
Verifying Razor IQ’s Effectiveness
Razor IQ automatically tracks its performance and displays the profit factor for the long strategy and the short strategy it uses. This information can be found in the table located in the top-right corner of your chart showing.
This table shows the long strategy profit factor and the short strategy profit factor.
The image above shows the long strategy profit factor and the short strategy profit factor for Razor IQ.
A profit factor greater than 1 indicates a strategy profitably traded historical price data.
A profit factor less than 1 indicates a strategy unprofitably traded historical price data.
A profit factor equal to 1 indicates a strategy did not lose or gain money when trading historical price data.
Using Razor IQ
While Razor IQ is a full-fledged trading system with entries and exits - manual traders can certainly make use of its on chart indications and visualizations.
The hallmark feature of Razor IQ is its ability to signal an acceptable dip entry opportunity - for both uptrends and downtrends. Long entries are often signaled near the bottom of a retracement for an uptrend; short entries are often signaled near the top of a retracement for a downtrend.
Razor IQ will always operate on exact price levels; however, users can certainly take advantage of Razor IQ's trend identification mechanism and retracement identification mechanism to use as confluence with their personally crafted trading strategy.
Of course, every trend will reverse at some point, and a good dip buying/shorting strategy will often trade the reversal in expectation of the prior trend continuing (retracement). It's important not to aggressively filter retracement entries in hopes of avoiding an entry when a trend reversal finally occurs, as this will ultimately filter out good dip buying/shorting opportunities. This is a reality of any dip trading strategy - not just Razor IQ.
Of course, you can set alerts for all Razor IQ entry and exit signals, effectively following along its systematic conquest of price movement.
