Smart Money Concepts + Fibonacci + EMA - AI Enhanced Analysis### █ OVERVIEW
This indicator is not just another "all-in-one" tool; it's a **specialized data visualization layer designed for the new era of AI-driven chart analysis**. The primary purpose of the **"NarmoonAI"** indicator is to structure and display key market information in a clean, consistent, and machine-readable format.
Standard charts can be noisy and ambiguous for AI Vision models (like Google's Gemini or OpenAI's GPT-4). This script solves that problem by consolidating the most crucial technical analysis concepts—Smart Money Concepts, Trend Analysis, and Key Levels—into a clear visual language that an AI can easily interpret from a single screenshot.
This approach allows traders to leverage the power of artificial intelligence for faster, more objective, and deeper market analysis. It's designed to work seamlessly with our custom AI assistant, the **NarmoonAI Telegram Bot**, but can be used with any modern AI vision tool.
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### █ CORE COMPONENTS & LOGIC
This indicator is a "mashup" with a clear purpose: to create a comprehensive yet clean analytical framework. Here is how each component contributes to the overall goal of AI-enhanced analysis:
**1. Smart Money Concepts (Supply & Demand Zones):**
* **How it works:** The script automatically identifies significant market turning points by detecting swing highs and lows using `ta.pivothigh` and `ta.pivotlow` over a user-defined `Swing Length`. These pivots form the basis of our Supply (resistance) and Demand (support) zones.
* **The "Smart" Edge:** To filter out weaker zones, the indicator analyzes the volume profile. Zones that are formed during periods of high volume (defined as >1.5x the 20-period simple moving average of volume) are highlighted in a stronger, more vibrant color. This signals areas of high institutional interest, a key concept in Smart Money analysis.
**2. Multi-Layered Trend Analysis (Exponential Moving Averages - EMAs):**
* **How it works:** We've included a customizable suite of four essential EMAs (20, 50, 100, and 200). These are not just random lines; they provide an instant visual reference for short, medium, and long-term trend direction and dynamic support/resistance.
* **Why it's useful for AI:** An AI can instantly parse the order and slope of these EMAs. For example, it can identify a strong uptrend when the price is above the 20 EMA, which is above the 50 EMA, and so on.
**3. Automatic Fibonacci Retracement:**
* **How it works:** Manually drawing Fibonacci levels is subjective and time-consuming. This script automates the process by identifying the highest high and lowest low over a `Fibonacci Lookback Period` (defaulting to 100 bars) and automatically plots the key retracement levels (0.236, 0.382, 0.5, 0.618, 0.786).
* **Why it's useful for AI:** It provides objective, universally recognized potential support and resistance levels without any manual drawing, ensuring a clean and consistent chart for analysis.
**4. Dynamic Trend Channels:**
* **How it works:** The indicator automatically draws trend channels by connecting the two most recent significant pivot highs (for a downtrend channel) or pivot lows (for an uptrend channel).
* **The "Dynamic" Edge:** The width of the channel is not fixed. It's dynamically calculated using the Average True Range (ATR), allowing the channel to expand and contract based on the market's current volatility. This provides a much more adaptive and realistic view of the trend's boundaries.
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### █ HOW TO USE THIS INDICATOR
There are two primary ways to use the NarmoonAI indicator:
**A) For AI-Powered Analysis (Recommended):**
1. Apply the **NarmoonAI** indicator to any chart.
2. Take a clean screenshot of your chart.
3. Upload the image to your preferred AI Vision model (e.g., Gemini, ChatGPT) or, for the best results, use our specialized **NarmoonAI Telegram bot**.
4. Ask the AI for a detailed analysis. **Example Prompts:**
* *"Based on this chart, what is the current market structure? Identify key support and resistance levels."*
* *"Is there a potential long setup forming according to the information from the NarmoonAI indicator?"*
* *"Summarize the trend direction and strength using the EMAs and trend channels shown."*
**B) For Manual Trading:**
Traders can use the confluence of signals for high-probability setups:
* **High-Probability Long:** Look for the price to enter a **Strong Demand Zone** that aligns with a key **Fibonacci level** (e.g., 0.618) and is respected by a major **EMA** (e.g., the 50 or 100 EMA).
* **High-Probability Short:** Look for the price to test a **Strong Supply Zone** near the top of a **descending trend channel**, with EMAs confirming the bearish momentum.
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*This script was created by NarmoonAI to bridge the gap between traditional technical analysis and the powerful capabilities of modern artificial intelligence. We believe this is the future of trading analysis.*
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Volume SuperTrend AI (Expo)█ Overview
The Volume SuperTrend AI is an advanced technical indicator used to predict trends in price movements by utilizing a combination of traditional SuperTrend calculation and AI techniques, particularly the k-nearest neighbors (KNN) algorithm.
The Volume SuperTrend AI is designed to provide traders with insights into potential market trends, using both volume-weighted moving averages (VWMA) and the k-nearest neighbors (KNN) algorithm. By combining these approaches, the indicator aims to offer more precise predictions of price trends, offering bullish and bearish signals.
█ How It Works
Volume Analysis: By utilizing volume-weighted moving averages (VWMA), the Volume SuperTrend AI emphasizes the importance of trading volume in the trend direction, allowing it to respond more accurately to market dynamics.
Artificial Intelligence Integration - k-Nearest Neighbors (k-NN) Algorithm: The k-NN algorithm is employed to intelligently examine historical data points, measuring distances between current parameters and previous data. The nearest neighbors are utilized to create predictive modeling, thus adapting to intricate market patterns.
█ How to use
Trend Identification
The Volume SuperTrend AI indicator considers not only price movement but also trading volume, introducing an extra dimension to trend analysis. By integrating volume data, the indicator offers a more nuanced and robust understanding of market trends. When trends are supported by high trading volumes, they tend to be more stable and reliable. In practice, a green line displayed beneath the price typically suggests an upward trend, reflecting a bullish market sentiment. Conversely, a red line positioned above the price signals a downward trend, indicative of bearish conditions.
Trend Continuation signals
The AI algorithm is the fundamental component in the coloring of the Volume SuperTrend. This integration serves as a means of predicting the trend while preserving the inherent characteristics of the SuperTrend. By maintaining these essential features, the AI-enhanced Volume SuperTrend allows traders to more accurately identify and capitalize on trend continuation signals.
TrailingStop
The Volume SuperTrend AI indicator serves as a dynamic trailing stop loss, adjusting with both price movement and trading volume. This approach protects profits while allowing the trade room to grow, taking into account volume for a more nuanced response to market changes.
█ Settings
AI Settings:
Neighbors (k):
This setting controls the number of nearest neighbors to consider in the k-Nearest Neighbors (k-NN) algorithm. By adjusting this parameter, you can directly influence the sensitivity of the model to local fluctuations in the data. A lower value of k may lead to predictions that closely follow short-term trends but may be prone to noise. A higher value of k can provide more stable predictions, considering the broader context of market trends, but might lag in responsiveness.
Data (n):
This setting refers to the number of data points to consider in the model. It allows the user to define the size of the dataset that will be analyzed. A larger value of n may provide more comprehensive insights by considering a wider historical context but can increase computational complexity. A smaller value of n focuses on more recent data, possibly providing quicker insights but might overlook longer-term trends.
AI Trend Settings:
Price Trend & Prediction Trend:
These settings allow you to adjust the lengths of the weighted moving averages that are used to calculate both the price trend and the prediction trend. Shorter lengths make the trends more responsive to recent price changes, capturing quick market movements. Longer lengths smooth out the trends, filtering out noise, and highlighting more persistent market directions.
AI Trend Signals:
This toggle option enables or disables the trend signals generated by the AI. Activating this function may assist traders in identifying key trend shifts and opportunities for entry or exit. Disabling it may be preferred when focusing on other aspects of the analysis.
Super Trend Settings:
Length:
This setting determines the length of the SuperTrend, affecting how it reacts to price changes. A shorter length will produce a more sensitive SuperTrend, reacting quickly to price fluctuations. A longer length will create a smoother SuperTrend, reducing false alarms but potentially lagging behind real market changes.
Factor:
This parameter is the multiplier for the Average True Range (ATR) in SuperTrend calculation. By adjusting the factor, you can control the distance of the SuperTrend from the price. A higher factor makes the SuperTrend further from the price, giving more room for price movement but possibly missing shorter-term signals. A lower factor brings the SuperTrend closer to the price, making it more reactive but possibly more prone to false signals.
Moving Average Source:
This setting lets you choose the type of moving average used for the SuperTrend calculation, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), etc.
Different types of moving averages provide various characteristics to the SuperTrend, enabling customization to align with individual trading strategies and market conditions.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
NeoTrend AI- Advanced Trading SignalsNeoTrend AI – Advanced Trading Signals
Overview
NeoTrend AI is an advanced trading signal indicator that uniquely integrates a kernel-based predictive model with adaptive volatility analysis. By processing historical price data through a Gaussian kernel matrix, NeoTrend AI produces a statistically informed predicted price. This prediction is then used to generate dynamic volatility bands that serve as adaptive support and resistance levels, leading to clear BUY and SELL signals.
Originality and Usefulness
Innovative Mashup: NeoTrend AI isn’t a mere combination of common indicators; it fuses a novel kernel-based forecasting method with volatility analysis. This creates a tool that not only tracks trends but also identifies key market zones with enhanced precision.
Actionable Insights: The indicator’s design helps traders understand both the underlying trend and the market’s volatility, providing a robust framework for making informed trading decisions.
Customizable Approach: With user-adjustable settings for lookback periods, prediction offsets, smoothness factors, and volatility multipliers, NeoTrend AI adapts to various markets and trading styles.
Omissions and Realistic Claims
Transparent Methodology: NeoTrend AI’s signals are generated solely from historical data analysis using well-established mathematical techniques. There are no unrealistic promises—past performance does not guarantee future results.
No Unsubstantiated Claims: All performance metrics and signal accuracy are clearly derived from the underlying methodology. This script is designed to provide useful insights rather than definitive trading outcomes.
Strategy Results
Kernel Forecasting:
The script builds a Gaussian kernel matrix over a chosen lookback period, smoothing historical price data and generating a predictive price that adjusts dynamically.
Adaptive Volatility Bands:
A volatility band is calculated based on the difference between the actual price and the predicted price, scaled by a user-defined multiplier. These bands change in real time, acting as dynamic support and resistance levels.
Signal Generation:
BUY Signal: Issued when the current price moves above the upper volatility band and the predicted price is trending upward.
SELL Signal: Issued when the price falls below the lower volatility band while the predicted price is trending downward.
Visual Examples
Buy and sell signals are generated, as clearly shown on the chart
Usage Tips
Parameter Customization: Adjust the lookback period, smoothness factor, and volatility multiplier to fit your trading timeframe and market conditions.
Combine with Other Tools: Use NeoTrend AI alongside additional technical indicators and robust risk management strategies for best results.
Backtest Thoroughly: Always perform comprehensive backtesting to understand how the indicator behaves under different market scenarios.
Final Remarks
NeoTrend AI is built to offer traders an original, data-driven insight into market trends without resorting to exaggerated or misleading claims. Its design emphasizes both innovation and practicality, ensuring that you receive actionable signals based on sound statistical methods.
TradingIQ - Counter Strike IQIntroducing "Counter Strike IQ" by TradingIQ
Counter Strike IQ is an exclusive trading algorithm developed by TradingIQ, designed to trade upside/downside breakouts of varying significance. By integrating artificial intelligence and IQ Technology, Counter Strike IQ analyzes historical and real-time price data to construct a dynamic trading system adaptable to various asset and timeframe combinations.
Philosophy of Counter Strike IQ
Counter Strike IQ operates on a single premise: Support and resistance levels cannot hold forever. At some point either side must break for the underlying asset to exhibit trends; otherwise, prices would be confined to an infinitely narrowing range.
Counter Strike IQ is designed to work straight out of the box. In fact, its simplicity requires just four user settings to manage output, making it incredibly straightforward to manage.
Minimum ATR Profit, Minimum ATR Stop, EMA Filter and EMA Filter Length are the only settings that manage the performance of Counter Strike IQ!
Traders don’t have to spend hours adjusting settings and trying to find what works best - Counter Strike IQ handles this on its own.
Key Features of Counter Strike IQ
Self-Learning Breakout Detection
Employs AI and IQ Technology to identify notable breakouts in real-time.
AI-Generated Trading Signals
Provides breakout 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
Counter Strike IQ learns where to exit positions.
Long and Short Trading Capabilities
Supports both long and short positions to trade various market conditions.
Strike Channel
The Strike Channel represents what Counter Strike IQ considers a tradable long opportunity or a tradable short opportunity. The Strike Channel is dynamic and adjusts from chart to chart.
IQ Graph Gradient
Introduces the IQ Graph Gradient, designed to classify extreme values in price on a grand scale.
How It Works
Counter Strike IQ operates on a straightforward heuristic: go long during significant upside price moves that break established resistance levels and go short during significant downside price moves that break established support levels.
IQ Technology, TradingIQ's proprietary AI algorithm, defines what constitutes a “significant price move” and what’s considered a tradable breakout. For Counter Strike IQ, this algorithm evaluates all historical support/resistance breaks and any subsequent breakouts. For instance, the price move following up to a breakout is measured and learned from, including the significance of the identified support/resistance level (how long it’s been active, how far price moved away from it, etc). By analyzing these patterns, Counter Strike IQ adapts to identify and trade similar future breakout sequences.
In simple terms, Counter Strike IQ learns from violations of historical support/resistance levels to identify potential entry points at currently established support/resistance levels. Using this knowledge, it determines the optimal, current support/resistance price level where a breakout has a higher chance of occurring.
For long positions, Counter Strike IQ places a stop-market order at the AI-identified resistance point. If price violates 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 closed over, the initial stop loss is converted to a trailing stop, and the long position remains active so long as price continues to uptrend.
For short positions, Counter Strike IQ places a stop-market order at the AI-identified support point. If price violates 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 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 closed over, the initial stop loss is converted to a trailing stop, and the short position remains active so long as price continues to downtrend.
As a trading system, Counter Strike IQ exits TP1 using a limit order, with all stop losses exited as stop market orders.
What Classifies As a Tradable Upside Breakout or Tradable Downside Breakout?
For Counter Strike IQ, tradable price breakouts are not manually set but are instead learned by the system. What qualifies as a significant upside or downside breakout in one market might not hold the same significance in another. Counter Strike IQ continuously analyzes historical and current support/resistance levels, how far price has extended from those levels, the raw-dollar price move leading up to a violation of those levels, their longevity, and more, to determine which future levels have a higher chance of breaking out when retested!
The image above illustrates the Strike Channel and explains the corresponding prices and levels
The green upper line represents the Long Breakout Point.
The pink lower line represents the Short Breakout Point.
Any price between the two deviation points is considered “Acceptable”.
The image above shows a long position being entered after the Upside Breakout Point was reached.
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 indicate the TP1 level for the current trade. Red lines indicate the initial stop loss price.
If price closes above TP1, the initial stop loss will be replaced with a trailing stop. A blue line (similar to the blue line shown for TP1) will trail price and correspond to the trailing stop price of the trade.
The image above shows the trailing stop price, represented by a blue 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 shows a short position being entered after the Downside Breakout Point was reached.
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 TP1, the initial stop loss, or at the trailing stop.
Blue lines indicate the TP1 level for the current trade. Red lines indicate the initial stop loss price.
If price closes below TP1, the initial stop loss will be replaced with a trailing stop. A blue line (similar to the blue line shown for TP1) will trail price and correspond to the trailing stop price of the trade.
The image above shows the trailing stop price, represented by a blue line, used for the short position!
You can also hover over the trade labels to get more information about the trade—such as the entry price and exit price.
IQ Gradient Graph
The IQ Gradient Graph provides a macro characterization of extreme prices.
The lower macro extremity of the IQ Gradient Graph is colored green, while the upper macro extremity is colored red.
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, Counter Strike 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 Counter Strike IQ is allowed to take.
“Trade Longs” allows for long trades.
“Trade Shorts” allows for short trades.
EMA Filter
The EMA Filter setting controls whether the AI should implement an EMA trading filter. Simply, if the EMA Filter is active, long trades can only initiate if price is trading above the user-defined EMA. Conversely, short trades can only initiate if price is trading below the user-defined EMA.
The image above shows the EMA Filter in action!
Verifying Counter Strike IQ’s Effectiveness
Counter Strike 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 Counter Strike 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 Counter Strike IQ
While Counter Strike 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 Counter Strike IQ is its ability to signal a breakout near its origin point. Long entries are often signaled near the start of a large upside price move; short entries are often signaled near the start of a large downside price move.
For live analysis, the Strike Channel serves as a valuable tool for identifying breakout points.
The further price moves toward the Upside Breakout Point (green), the stronger the indication that price might breakout to the upside. Conversely, the deeper price reaches toward the Downside Breakout Point (red), the stronger the indication that price might breakout to the downside.
Of course, should buying or selling pressure stall, price may fail to breakout at the identified breakout level. This is a natural consequence of any breakout trading strategy!
With this information at hand, traders can quickly switch between charts and timeframes to identify optimized areas of interest.
Pro Scalper AI [BullByte]The Pro Scalper AI is a powerful, multi-faceted scalping indicator designed to assist active traders in identifying short-term trading opportunities with precision. By combining trend analysis, momentum indicators, dynamic weighting, and optional AI forecasting, this tool provides both immediate and latched trading signals based on confirmed (closed bar) data—helping to avoid repainting issues. Its flexible design includes customizable filters such as a higher timeframe trend filter, and adjustable settings for ADX, ATR, and Hull Moving Average (HMA), giving traders the ability to fine-tune the strategy to different markets and timeframes.
Key Features :
- Confirmed Data Processing :
Utilizes a helper function to lock in price and volume data only from confirmed (closed) bars, ensuring the reliability of signals without the risk of intrabar repainting.
- Trend Analysis :
Employs ADX and Directional Movement (DI) calculations along with a locally computed HMA to detect short-term trends. An optional higher timeframe trend filter can further refine the analysis.
- Flexible Momentum Modes :
Choose between three momentum calculation methods—Stochastic RSI, Fisher RSI, or Williams %R—to match your preferred style of analysis. This versatility allows you to optimize the indicator for different market conditions.
- Dynamic Weighting & Volatility Adjustments :
Adjusts the contribution of trend, momentum, volatility, and volume through dynamic weighting. This ensures that the indicator responds appropriately to varying market conditions by scaling its sensitivity with user-defined maximum factors.
- Optional AI Forecast :
For those who want an extra edge, the built-in AI forecasting module uses linear regression to predict future price moves and adjusts oscillator thresholds accordingly. This feature can be toggled on or off, with smoothing options available for more stable output.
- Latching Mode for Signal Persistenc e:
The script features a latching mechanism that holds signals until a clear reversal is detected, preventing whipsaws and providing more reliable trade entries and exits.
- Comprehensive Visualizations & Dashboard :
- Composite Oscillator & Dynamic Thresholds : The oscillator is plotted with dynamic upper and lower thresholds, and the area between them is filled with a color that reflects the active trading signal (e.g., Strong Buy, Early Sell).
- Signal Markers : Both immediate (non-latching) and stored (latched) signals are marked on the chart with distinct shapes (circles, crosses, triangles, and diamonds) to differentiate between signal types.
- Real-Time Dashboard : A customizable dashboard table displays key metrics including ADX, oscillator value, chosen momentum mode, HMA trend, higher timeframe trend, volume factor, AI bias (if enabled), and more, allowing traders to quickly assess market conditions at a glance.
How to Use :
1. S ignal Interpretation :
- Immediate Signals : For traders who prefer quick entries, the indicator displays immediate signals such as “Strong Buy” or “Early Sell” based on the current market snapshot.
- Latched Signals : When latching is enabled, the indicator holds a signal state until a clear reversal is confirmed, offering sustained trade setups.
2. Trend Confirmation :
- Use the HMA trend indicator and the optional higher timeframe trend filter to confirm the prevailing market direction before acting on signals.
3. Dynamic Thresholds & AI Forecasting :
- Monitor the dynamically adjusted oscillator thresholds and, if enabled, the AI bias to gauge potential shifts in market momentum.
4. Risk Management :
- Combine these signals with additional analysis and sound risk management practices to determine optimal entry and exit points for scalping trades.
Disclaimer :
This script is provided for educational and informational purposes only and does not constitute financial advice. Trading involves risk, and past performance is not indicative of future results. Always perform your own analysis and use proper risk management strategies before trading.
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.
Support & Resistance AI LevelScopeSupport & Resistance AI LevelScope
Support & Resistance AI LevelScope is an advanced, AI-driven tool that automatically detects and highlights key support and resistance levels on your chart. This indicator leverages smart algorithms to pinpoint the most impactful levels, providing traders with a precise, real-time view of critical price boundaries. Save time and enhance your trading edge with effortless, intelligent support and resistance identification.
Key Features:
AI-Powered Level Detection: The LevelScope algorithm continuously analyzes price action, dynamically plotting support and resistance levels based on recent highs and lows across your chosen timeframe.
Sensitivity Control: Customize the sensitivity to display either major levels for a macro view or more frequent levels for detailed intraday analysis. Easily adjust to suit any trading style or market condition.
Level Strength Differentiation: Instantly recognize the strength of each level with visual cues based on how often price has touched each one. Stronger levels are emphasized, highlighting areas with higher significance, while weaker levels are marked subtly.
Customizable Visuals: Tailor the look of your chart with customizable color schemes and line thickness options for strong and weak levels, ensuring clear visibility without clutter.
Proximity Alerts: Receive alerts when price approaches key support or resistance, giving you a heads-up for potential market reactions and trading opportunities.
Who It’s For:
Whether you're a day trader, swing trader, or just want a quick, AI-driven way to identify high-probability levels on your chart, Support & Resistance AI LevelScope is designed to keep you focused and informed. This indicator is the perfect addition to any trader’s toolkit, empowering you to make more confident, data-backed trading decisions with ease.
Upgrade your analysis with AI-powered support and resistance—no more manual lines, only smart levels!
Luxmi AI Ultimate 1 Min Option ScalperThe Luxmi AI Ultimate 1 Min Option Scalper is a specialized trading indicator designed for use in options trading. This tool is particularly focused on providing actionable signals to option buyers within a one-minute timeframe, making it highly suitable for scalping—a trading strategy aimed at profiting from small price changes. Below is an elaboration on how this indicator functions and its significance in trading decisions:
### Key Features of Luxmi AI Ultimate 1 Min Option Scalper
1. **Enter and Don't Signals:**
- **Enter Signals:** These signals indicate the optimal moments to enter a trade, suggesting when to buy an option. They are typically based on sophisticated algorithms that analyze price movements, volume, volatility, and other relevant market data.
- **Don't Signals:** These signals advise traders to refrain from entering a trade. This could be due to market conditions that are not conducive to profitable trading, such as high volatility, low liquidity, or unclear directional trends.
2. **Directional Trading Strategy:**
- The Luxmi AI Ultimate 1 Min Option Scalper focuses on directional trading, which involves making trades based on the expected direction of the market. For option buyers, this means taking positions that profit from upward (call options) or downward (put options) movements in the price of the underlying asset.
3. **Scalping Approach:**
- Scalping is a short-term trading strategy that involves making numerous trades over the course of a trading session, aiming to capitalize on small price changes. The one-minute timeframe is particularly suited for scalping, as it allows traders to quickly enter and exit positions to capture minimal but frequent profits.
### Functionality and Benefits
1. **Real-Time Analysis:**
- The indicator provides real-time analysis and signals, ensuring that traders receive timely information to make quick trading decisions. This is crucial in the fast-paced environment of scalping, where delays can significantly impact profitability.
2. **Automated Decision-Making Support:**
- By automating the signal generation process, the Luxmi AI Ultimate 1 Min Option Scalper helps reduce the cognitive load on traders. This automation can lead to more consistent trading performance, as it mitigates the impact of emotional and psychological factors that often influence human decision-making.
3. **Market Adaptability:**
- The indicator is designed to adapt to changing market conditions, adjusting its signals based on the latest data. This adaptability enhances its effectiveness in various market environments, whether trending, ranging, or highly volatile.
4. **Risk Management:**
- Incorporating "Don't" signals as part of the strategy helps traders avoid entering trades in unfavorable conditions, thereby managing risk more effectively. This feature is particularly valuable in preventing losses and preserving capital.
5. **Educational Value:**
- For less experienced traders, using the Luxmi AI Ultimate 1 Min Option Scalper can provide a learning experience. By observing the signals and their outcomes, traders can develop a better understanding of market dynamics and refine their trading strategies.
### Practical Application
- **Setup:** Traders integrate the Luxmi AI Ultimate 1 Min Option Scalper into their trading platforms. This setup typically involves installing the indicator and configuring it to monitor the specific options and market data relevant to the trader's strategy.
- **Monitoring:** During trading hours, traders monitor the signals provided by the indicator. They prepare to act quickly on "Enter" signals and heed "Don't" signals to avoid unnecessary risks.
- **Execution:** When an "Enter" signal is generated, traders execute the recommended trade, buying the corresponding option. They then manage their positions closely, ready to exit based on their predetermined profit targets or stop-loss levels.
In summary, the Luxmi AI Ultimate 1 Min Option Scalper is a powerful tool for option buyers, providing critical buy and hold signals in a highly time-sensitive manner. Its primary benefits include enhancing decision-making speed, improving trading consistency, and managing risk, all of which are essential for successful scalping in options trading.
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
Luxmi AI Filtered Option Scalping Signals (INDEX)Introduction:
Luxmi AI Filtered Option Scalping Signals (INDEX) is an enhanced iteration of the Luxmi AI Directional Option Buying (Long Only) indicator. It's designed for use on index charts alongside the Luxmi AI Smart Sentimeter (INDEX) indicator to enhance performance. This indicator aims to provide refined signals for option scalping strategies, optimizing trading decisions within index markets.
Understanding directional bias is crucial when trading index and index options because it helps traders align their strategies with the expected movement of the underlying index.
The Luxmi AI Filtered Option Scalping Signals (INDEX) indicator aims to simplify and expedite decision-making through comprehensive technical analysis of various data points on a chart. By leveraging advanced analysis of data points, this indicator scrutinizes multiple factors simultaneously to offer traders clear and rapid insights into market dynamics.
The indicator is specifically designed for option scalping, a trading strategy that aims to profit from short-term price fluctuations. It prioritizes signals that are conducive to quick execution and capitalizes on rapid market movements typical of scalping strategies.
Major Features:
Trend Cloud:
Working Principle:
The script utilizes the Relative Strength Index (RSI) to assess market momentum, identifying bullish and bearish phases based on RSI readings. It calculates two boolean variables, bullmove and bearmove, which signal shifts in momentum direction by considering changes in the Exponential Moving Average (EMA) of the closing price. When RSI indicates bullish momentum and the closing price's EMA exhibits positive changes, bullmove is triggered, signifying the start of a bullish phase. Conversely, when RSI suggests bearish momentum and the closing price's EMA shows negative changes, bearmove is activated, marking the beginning of a bearish phase. This systematic approach helps in understanding the current trend of the price. The script visually emphasizes these phases on the chart using plot shape markers, providing traders with clear indications of trend shifts.
Benefits of Using Trend Cloud:
Comprehensive Momentum Assessment: The script offers a holistic view of market momentum by incorporating RSI readings and changes in the closing price's EMA, enabling traders to identify both bullish and bearish phases effectively.
Structured Trend Recognition: With the calculation of boolean variables, the script provides a structured approach to recognizing shifts in momentum direction, enhancing traders' ability to interpret market dynamics.
Visual Clarity: Plotshape markers visually highlight the start and end of bullish and bearish phases on the chart, facilitating easy identification of trend shifts and helping traders to stay informed.
Prompt Response: Traders can promptly react to changing market conditions as the script triggers alerts when bullish or bearish phases begin, allowing them to seize potential trading opportunities swiftly.
Informed Decision-Making: By integrating various indicators and visual cues, the script enables traders to make well-informed decisions and adapt their strategies according to prevailing market sentiment, ultimately enhancing their trading performance.
How to use this feature:
The most effective way to maximize the benefits of this feature is to use it in conjunction with other key indicators and visual cues. By combining the color-coded clouds, which indicate bullish and bearish sentiment, with other features such as IS candles, microtrend candles, volume candles, and sentimeter candles, traders can gain a comprehensive understanding of market dynamics. For instance, aligning the color of the clouds with the trend direction indicated by IS candles, microtrend candles, and sentimeter candles can provide confirmation of trend strength or potential reversals.
Furthermore, traders can leverage the trend cloud as a trailing stop-loss tool for long entries, enhancing risk management strategies. By adjusting the stop-loss level based on the color of the cloud, traders can trail their positions to capture potential profits while minimizing losses. For long entries, maintaining the position as long as the cloud remains green can help traders stay aligned with the prevailing bullish sentiment. Conversely, a shift in color from green to red serves as a signal to exit the position, indicating a potential reversal in market sentiment and minimizing potential losses. This integration of the trend cloud as a trailing stop-loss mechanism adds an additional layer of risk management to trading strategies, increasing the likelihood of successful trades while reducing exposure to adverse market movements.
Moreover, the red cloud serves as an indicator of decay in option premiums and potential theta effect, particularly relevant for options traders. When the cloud turns red, it suggests a decline in option prices and an increase in theta decay, highlighting the importance of managing options positions accordingly. Traders may consider adjusting their options strategies, such as rolling positions or closing out contracts, to mitigate the impact of theta decay and preserve capital. By incorporating this insight into options pricing dynamics, traders can make more informed decisions about their options trades.
Scalping Cloud:
The scalping cloud serves as a specialized component within the trend cloud feature, specifically designed to pinpoint potential long and short entry points within the overarching trend cloud. Here's how it works:
Trend Identification: The trend cloud feature typically highlights the prevailing trend direction based on various technical indicators, price action, or other criteria. It visually represents the momentum and direction of the market over a given period.
Refined Entry Signals: Within this broader trend context, the scalping cloud narrows its focus to identify shorter-term trading opportunities. It does this by analyzing more granular price movements and shorter timeframes, seeking out potential entry points that align with the larger trend.
Long and Short Entries: The scalping cloud distinguishes between potential long (buy) and short (sell) entry opportunities within the trend cloud. For instance, within an uptrend indicated by the trend cloud, the scalping cloud might identify brief retracements or pullbacks as potential long entry points. Conversely, in a downtrend, it may signal short entry opportunities during temporary upward corrections.
Risk Management: By identifying potential entry points within the context of the trend, the scalping cloud also aids in risk management. Traders can use these signals to place stop-loss orders and manage their positions effectively, reducing the risk of adverse price movements.
The scalping cloud operates by analyzing the crossover and crossunder events between two key indicators: the Double Exponential Moving Average (DEMA) and a Weighted Average. Here's how it works:
Double Exponential Moving Average (DEMA): DEMA is a type of moving average that seeks to reduce lag by applying a double smoothing technique to price data. It responds more quickly to price changes compared to traditional moving averages, making it suitable for identifying short-term trends and potential trading opportunities.
Weighted Average: The weighted average calculates the average price of an asset over a specified period. However, it incorporates a weighting scheme that assigns more significance to recent price data, resulting in a more responsive indicator that closely tracks current market trends.
CE and NO CE Signals:
CE signals typically represent a Long Scalping Opportunity, suggesting that conditions are favorable for entering a long position. These signals indicate a strong upward momentum in the market, which traders can exploit for short-term gains through scalping strategies.
On the other hand, when there are no CE signals present, it doesn't necessarily mean that the trend has reversed or turned bearish. Instead, it indicates that the trend is still bullish, but the market is experiencing an active pullback. During a pullback, prices may temporarily retreat from recent highs as traders take profits or reevaluate their positions. While the overall trend remains upward, the pullback introduces a degree of uncertainty, making it less favorable for entering new long positions.
In such a scenario, traders may opt to exercise caution and refrain from entering new long positions until the pullback phase has concluded. Instead, they might consider waiting for confirmation signals, such as the resumption of CE signals or other bullish indications, before reengaging in long positions.
PE and NO PE Signals:
PE signals typically indicate a Short Entry opportunity, signaling that market conditions are conducive to entering a short position.
Conversely, when there are no PE signals present, it signifies that while the trend remains bearish, the market is currently in an active phase of consolidation or pullback. During such periods, prices may temporarily rise from recent lows, reflecting a pause in the downward momentum. While the overall trend remains downward, the absence of PE signals suggests that it may not be an optimal time to enter new short positions.
In this context, traders may exercise caution and wait for clearer signals before initiating new short positions. They might monitor the market closely for signs of a resumption in bearish momentum, such as the emergence of PE signals or other bearish indications. Alternatively, traders may choose to wait on the sidelines until market conditions stabilize or provide clearer directional signals.
Working Principle Of CE and PE Signals:
The feature calculates candlestick values based on the open, high, low, and close prices of each bar. By comparing these derived candlestick values, it determines whether the current candlestick is bullish or bearish. Additionally, it signals when there is a change in the color (bullish or bearish) of the derived candlesticks compared to the previous bar, enabling traders to identify potential shifts in market sentiment.
Micro Trend Candles:
Working Principle:
This feature begins by initializing variables to determine trend channel width and track price movements. Average True Range (ATR) is then calculated to measure market volatility, influencing the channel's size. Highs and lows are identified within a specified range, and trends are assessed based on price breaches, with potential changes signaled accordingly. The price channel is continually updated to adapt to market shifts, and arrows are placed to indicate potential entry points. Colors are assigned to represent bullish and bearish trends, dynamically adjusting based on current market conditions. Finally, candles on the chart are colored to visually depict the identified micro trend, offering traders an intuitive way to interpret market sentiment and potential entry opportunities.
Benefits of using Micro Trend Candles:
Traders can use these identified micro trends to spot potential short-term trading opportunities. For example:
Trend Following: Traders may decide to enter trades aligned with the prevailing micro trend. If the candles are consistently colored in a certain direction, traders may consider entering positions in that direction.
Reversals: Conversely, if the script signals a potential reversal by changing the candle colors, traders may anticipate trend reversals and adjust their trading strategies accordingly. For instance, they might close existing positions or enter new positions in anticipation of a trend reversal.
It's important to note that these micro trends are short-term in nature and may not always align with broader market trends. Therefore, traders utilizing this script should consider their trading timeframes and adjust their strategies accordingly.
How to use this feature:
This feature assigns colors to candles to represent bullish and bearish trends, with adjustments made based on current market conditions. Green candles accompanied by a green trend cloud signal a potential long entry, while red candles suggest caution, indicating a bearish trend. This visual representation allows traders to interpret market sentiment intuitively, identifying optimal entry points and exercising caution during potential downtrends.
Scalping Candles (Inspired by Elliott Wave and Open Interest Concepts):
Working Principle:
This feature draws inspiration from the Elliot Wave method, utilizing technical analysis techniques to discern potential market trends and sentiment shifts. It begins by calculating the variance between two Exponential Moving Averages (EMAs) of closing prices, mimicking Elliot Wave's focus on wave and trend analysis. The shorter-term EMA captures immediate price momentum, while the longer-term EMA reflects broader market trends. A smoother Exponential Moving Average (EMA) line, derived from the difference between these EMAs, aids in identifying short-term trend shifts or momentum reversals.
Benefits of using Scalping Candles Inspired by Elliott Wave:
The Elliott Wave principle is a form of technical analysis that attempts to predict future price movements by identifying patterns in market charts. It suggests that markets move in repetitive waves or cycles, and traders can potentially profit by recognizing these patterns.
While this script does not explicitly analyze Elliot Wave patterns, it is inspired by the principle's emphasis on trend analysis and market sentiment. By calculating and visualizing the difference between EMAs and assigning colors to candles based on this analysis, the script aims to provide traders with insights into potential market sentiment shifts, which can align with the broader philosophy of Elliott Wave analysis.
How to use this feature:
Candlestick colors are assigned based on the relationship between the EMA line and the variance. When the variance is below or equal to the EMA line, candles are colored red, suggesting a bearish sentiment. Conversely, when the variance is above the EMA line, candles are tinted green, indicating a bullish outlook. Though not explicitly analyzing Elliot Wave patterns, the script aligns with its principles of trend analysis and market sentiment interpretation. By offering visual cues on sentiment shifts, it provides traders with insights into potential trading opportunities, echoing Elliot Wave's emphasis on pattern recognition and trend analysis.
Chart Timeframe Support and Resistance:
Working Principle:
This feature serves to identify and visualize support and resistance levels on the chart, primarily based on the chosen Chart Timeframe (CTF). It allows users to specify parameters such as the number of bars considered on the left and right sides of each pivot point, as well as line width and label color. Moreover, users have the option to enable or disable the display of these levels. By utilizing functions to calculate pivot highs and lows within the specified timeframe, the script determines the highest high and lowest low surrounding each pivot point.
Additionally, it defines functions to create lines and labels for each detected support and resistance level. Notably, this feature incorporates a trading method that emphasizes the concept of resistance turning into support after breakouts, thereby providing valuable insights for traders employing such strategies. These lines are drawn on the chart, with colors indicating whether the level is above or below the current close price, aiding traders in visualizing key levels and making informed trading decisions.
Benefits of Chart Timeframe Support and Resistance:
Identification of Price Levels: Support and resistance levels help traders identify significant price levels where buying (support) and selling (resistance) pressure may intensify. These levels are often formed based on historical price movements and are regarded as areas of interest for traders.
Decision Making: Support and resistance levels assist traders in making informed trading decisions. By observing price reactions near these levels, traders can gauge market sentiment and adjust their strategies accordingly. For example, traders may choose to enter or exit positions, set stop-loss orders, or take profit targets based on price behavior around these levels.
Risk Management: Support and resistance levels aid in risk management by providing reference points for setting stop-loss orders. Traders often place stop-loss orders below support levels for long positions and above resistance levels for short positions to limit potential losses if the market moves against them.
How to use this feature:
Planning Long Positions: When considering long positions, it's advantageous to strategize when the price is in proximity to a support level identified by the script. This suggests a potential area of buying interest where traders may expect a bounce or reversal in price. Additionally, confirm the bullish bias by ensuring that the trend cloud is green, indicating favorable market conditions for long trades.
Waiting for Breakout: If long signals are generated near resistance levels detected by the script, exercise patience and wait for a breakout above the resistance. A breakout above resistance signifies potential strength in the upward momentum and may present a more opportune moment to enter long positions. This approach aligns with trading methodologies that emphasize confirmation of bullish momentum before initiating trades.
StopLoss and Target Lines:
In addition to generating entry signals, this indicator also incorporates predefined stop-loss ray lines and configurable risk-reward (R:R) target lines to enhance risk management and profit-taking strategies. Here's how these features work:
Predefined Stop-loss Ray Lines: The indicator automatically plots stop-loss ray lines on the chart, serving as visual guidelines for setting stop-loss levels. These stop-loss lines are predetermined based on specific criteria, such as volatility levels, support and resistance zones, or predefined risk parameters. Traders can use these lines as reference points to place their stop-loss orders, aiming to limit potential losses if the market moves against their position.
Configurable Risk-Reward (R:R) Target Lines: In addition to stop-loss lines, the indicator allows traders to set configurable risk-reward (R:R) target lines on the chart. These target lines represent predefined price levels where traders intend to take profits based on their desired risk-reward ratio. By adjusting the placement of these lines, traders can customize their risk-reward ratios according to their trading preferences and risk tolerance.
Risk Management: The predefined stop-loss ray lines help traders manage risk by providing clear exit points if the trade goes against their expectations. By adhering to these predetermined stop-loss levels, traders can minimize potential losses and protect their trading capital, thereby enhancing overall risk management.
Profit-taking Strategy: On the other hand, the configurable R:R target lines assist traders in establishing profit-taking strategies. By setting target levels based on their desired risk-reward ratio, traders can aim to capture profits at predefined price levels that offer favorable risk-reward profiles. This allows traders to systematically take profits while ensuring that potential gains outweigh potential losses over the long term.
The stop-loss and target lines incorporated in this indicator are dynamic in nature, providing traders with the flexibility to utilize them as trailing stop-loss and extended take-profit targets. Here's how these dynamic features work:
Trailing Stop-loss: Traders can employ the stop-loss lines as trailing stop-loss levels, allowing them to adjust their stop-loss orders as the market moves in their favor. As the price continues to move in the desired direction, indicator can dynamically adjust the stop-loss line to lock in profits while still allowing room for potential further gains. This trailing stop-loss mechanism helps traders secure profits while allowing their winning trades to continue running as long as the market remains favorable.
Extended Take Profit Targets: Similarly, traders can utilize the target lines as extended take-profit targets, enabling them to capture additional profits beyond their initial profit targets. By adjusting the placement of these target lines based on evolving market conditions or technical signals, traders can extend their profit-taking strategy to capitalize on potential price extensions or trend continuations. This flexibility allows traders to maximize their profit potential by capturing larger price movements while managing their risk effectively.
Rangebound Bars:
When the Rangebound Bars feature is enabled, the indicator represents candles in a distinct purple color to visually denote periods of sideways or range-bound price action. This visual cue helps traders easily identify when the market is consolidating and lacking clear directional momentum. Here's how it works:
Purple Candle Color: When the Rangebound Bars feature is active, the indicator displays candlesticks in a purple color to highlight periods of sideways price movement. This color differentiation stands out against the usual colors used for bullish (e.g., green or white) and bearish (e.g., red or black) candles, making it easier for traders to recognize range-bound conditions at a glance.
Signaling Sideways Price Action: The purple coloration of candles indicates that price movements are confined within a relatively narrow range and lack a clear upward or downward trend. This may occur when the market is consolidating, experiencing indecision, or undergoing a period of accumulation or distribution.
Working Principle:
The Rangebound Bars feature of this indicator is designed to assist traders in identifying and navigating consolidating market conditions, where price movements are confined within a relatively narrow range. This feature utilizes Pivot levels and the Average True Range (ATR) concept to determine when the market is range-bound and provides signals to stay out of such price action. Here's how it works:
Pivot Levels: Pivot levels are key price levels derived from the previous period's high, low, and closing prices. They serve as potential support and resistance levels and are widely used by traders to identify significant price levels where price action may stall or reverse. The Rangebound Bars feature incorporates Pivot levels into its analysis to identify ranges where price tends to consolidate.
Average True Range (ATR): The Average True Range is a measure of market volatility that calculates the average range between the high and low prices over a specified period. It provides traders with insights into the level of price volatility and helps set appropriate stop-loss and take-profit levels. In the context of the Rangebound Bars feature, ATR is used to gauge the extent of price fluctuations within the identified range.
Luxmi AI Smart Sentimeter (Index) "Performance or the direction of indices depend on the performance or direction of its constituents"
The above statement succinctly highlights the fundamental relationship between the movements of stock indices and the individual stocks that comprise them. Essentially, the statement underscores the fact that the overall performance and direction of an index are directly influenced by the collective performance and direction of its constituent stocks.
In essence, when the majority of stocks within an index experience positive movements, such as price increases or upward trends, the index itself tends to rise. Conversely, if a significant number of constituent stocks exhibit negative movements, such as price decreases or downward trends, the index is likely to decline.
This interdependence between indices and their constituents reflects the broader market sentiment and economic conditions. Individual stock movements contribute to the overall market sentiment, which is reflected in the movements of the index. Therefore, investors and traders often analyze the performance of underlying constituents to gain insights into market trends, sentiment shifts, and potential trading opportunities.
In summary, the statement emphasizes the integral role that individual stocks play in shaping the performance and direction of stock indices, highlighting the importance of monitoring constituent stocks when analyzing and trading in the financial markets.
Analyzing the performance of underlying constituents is crucial when trading index futures and options due to several reasons:
Index Composition Impact: Index futures and options derive their value from the performance of the underlying index, which, in turn, is determined by the constituent stocks. Understanding how individual stocks within the index are performing provides insights into the broader market sentiment and direction.
Diversification Assessment: Indices typically consist of a diverse range of stocks across various sectors. Analyzing the performance of these constituent stocks allows traders to assess the overall health of the market and identify sector-specific trends or weaknesses. This information is vital for constructing a well-diversified portfolio and managing risk effectively.
Sector Rotation Strategies: Different sectors perform differently under various market conditions. Analyzing the performance of underlying constituents enables traders to identify sectors that are outperforming or underperforming relative to the broader market. This insight can be utilized to implement sector rotation strategies, where traders adjust their portfolio allocations based on the expected performance of different sectors.
Options Pricing and Hedging: In options trading, the performance of underlying constituents directly affects the pricing of options contracts. Volatility, correlation among stocks, and individual stock movements all influence options prices. By analyzing the performance of underlying constituents, traders can better understand the factors driving options pricing and implement more effective hedging strategies.
Technical Analysis Confirmation: Technical analysis techniques often rely on price movements and patterns observed in individual stocks. Analyzing the performance of underlying constituents can confirm or invalidate technical signals generated by the index itself, providing additional conviction for trading decisions.
In summary, analyzing the performance of underlying constituents when trading index futures and options is essential for understanding market dynamics, identifying trading opportunities, managing risk, and making informed trading decisions. By staying informed about individual stock movements within an index, traders can gain a deeper understanding of market trends and position themselves for success in the ever-changing financial markets.
Workng Principle of Luxmi AI Smart Sentimeter:
The Luxmi AI Smart Sentimeter indicator is a powerful tool designed for traders to gain insights into market sentiment and trend strength. This indicator amalgamates data from multiple stocks to provide a comprehensive overview of market conditions. Let's delve into its components, functionalities, and potential applications.
Firstly, the indicator allows users to input symbols for up to ten different stocks. These symbols serve as the basis for retrieving closing prices, which are essential for conducting technical analysis. The flexibility to choose symbols empowers traders to tailor their analysis according to their preferences and market focus.
The indicator's core functionality revolves around the calculation of a combined Moving Averages of various lenghts, which aggregates the closing prices of the selected stocks. This combined combined analysis serves as a pivotal metric for assessing overall market trends and sentiment. By incorporating data from multiple stocks, the indicator offers a holistic view of market dynamics, reducing the impact of individual stock fluctuations.
To further refine the analysis, the combined Moving Average Data undergoes a smoothing process using another additional Moving Average (SMA). This smoothing mechanism helps filter out noise and provides a clearer depiction of underlying trends, thereby enhancing the indicator's effectiveness.
Moreover, the indicator computes an oscillator by measuring the difference between the combined MA and the smoothed MA. This oscillator serves as a valuable tool for gauging trend strength and identifying potential reversal points in the market, offering further insights into market momentum and directionality.
The indicator's graphical representation includes plots of the oscillator and its MA, facilitating visual interpretation of trend dynamics and momentum shifts. Furthermore, the script generates visual signals, such as UP and DOWN triangles, to highlight crossover and crossunder events on the oscillator, aiding traders in making timely and informed trading decisions.
In practice, the Luxmi AI Smart Sentimeter indicator offers a myriad of applications for traders across various trading styles and timeframes. Traders can utilize it to assess market sentiment, identify trend reversals, and confirm trade signals generated by other technical indicators. Additionally, the indicator can serve as a valuable tool for conducting market analysis, formulating trading strategies, and managing risk effectively.
In conclusion, the Luxmi AI Smart Sentimeter indicator represents a sophisticated yet accessible tool for traders seeking to navigate the complexities of the financial markets. With its robust features, customizable parameters, and insightful analysis, this indicator stands as a testament to the potential of data-driven approaches in trading and investment.
Settings:
The Index Constituent Analysis setting empowers users to input the constituents of a specific index, facilitating the analysis of market sentiments based on the performance of these individual components. An index serves as a statistical measure of changes in a portfolio of securities representing a particular market or sector, with constituents representing the individual assets or securities comprising the index.
By providing the constituent list, users gain insights into market sentiments by observing how each constituent performs within the broader index. This analysis aids traders and investors in understanding the underlying dynamics driving the index's movements, identifying trends or anomalies, and making informed decisions regarding their investment strategies.
This setting empowers users to customize their analysis based on specific indexes relevant to their trading or investment objectives, whether tracking a benchmark index, sector-specific index, or custom index. Analyzing constituent performance offers a valuable tool for market assessment and decision-making.
Example: BankNifty Index and Its Constituents
Illustratively, the BankNifty index represents the performance of the banking sector in India and includes major banks and financial institutions listed on the National Stock Exchange of India (NSE). Prominent constituents of the BankNifty index include:
State Bank of India (SBIN)
HDFC Bank
ICICI Bank
Kotak Mahindra Bank
Axis Bank
IndusInd Bank
Punjab National Bank (PNB)
Yes Bank
Federal Bank
IDFC First Bank
By utilizing the Index Constituent Analysis setting and inputting these constituent stocks of the BankNifty index, traders and investors can assess the individual performance of these banking stocks within the broader banking sector index. This analysis enables them to gauge market sentiments, identify trends, and make well-informed decisions regarding their trading or investment strategies in the banking sector.
Example: NAS100 Index and Its Constituents
Similarly, the NAS100 index, known as the NASDAQ-100, tracks the performance of the largest non-financial companies listed on the NASDAQ stock exchange. Prominent constituents of the NAS100 index include technology and consumer discretionary stocks such as:
Apple Inc. (AAPL)
Microsoft Corporation (MSFT)
Amazon.com Inc. (AMZN)
Alphabet Inc. (GOOGL)
Facebook Inc. (FB)
Tesla Inc. (TSLA)
NVIDIA Corporation (NVDA)
PayPal Holdings Inc. (PYPL)
Netflix Inc. (NFLX)
Adobe Inc. (ADBE)
By inputting these constituent stocks of the NAS100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these technology and consumer discretionary stocks within the broader NASDAQ-100 index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the technology and consumer sectors.
Example: FTSE 100 Index and Its Constituents
The FTSE 100 index represents the performance of the 100 largest companies listed on the London Stock Exchange (LSE) by market capitalization. Some notable constituents of the FTSE 100 index include:
HSBC Holdings plc
BP plc
GlaxoSmithKline plc
Unilever plc
Royal Dutch Shell plc
AstraZeneca plc
Diageo plc
Rio Tinto plc
British American Tobacco plc
Reckitt Benckiser Group plc
Timeframe Selection:
If a traders wshes to analyze the constituent in a higher timeframe they can simply switch to HTF from the dropdown without changing the chart timeframe.
Weight:
Weight needs to be a positive number when applied on the index future or call option charts.
Weight must be configured to a negative number when this indicator is applied on a put option chart (Put options move in the opposite direction compared to it's stock or index).
Happy Trading,
MAHA Luxmi AI Candles [Overlay]The MAHA Luxmi AI Candles trading indicator is a sophisticated tool designed to assist traders in identifying potential trading opportunities by utilizing a combination of Moving Average (MA) and Heikin-Ashi (HA) techniques, further enhanced with a custom formula. Here’s a detailed breakdown of its functionalities:
1. Integration of MA and HA Techniques
MAHA stands for Moving Average and Heikin-Ashi. This indicator modifies these traditional techniques with a unique custom formula, aiming to provide more accurate and reliable signals for traders. The combination enhances the smoothing effect of Moving Averages with the trend indication of Heikin-Ashi candles.
2. Four-Colored Candles for Trend Indication
The indicator uses a color-coded system to denote different market conditions and potential trading opportunities:
- Green Candles: These candles indicate a potential long opportunity. The appearance of a green candle suggests that the market is showing bullish tendencies, prompting traders to consider entering a long position.
- Blue Candles: These candles signify an active pullback within a bullish trend. The blue candle warns traders of a possible temporary reversal within the overall bullish trend, suggesting caution and the need for confirmation before continuing with a long position or preparing for a potential reversal.
- Red Candles: These candles represent a potential short opportunity. A red candle indicates bearish market conditions, signaling traders to consider entering a short position.
- Yellow Candles: These candles denote an active pullback within a bearish trend. The presence of a yellow candle indicates a temporary reversal within the bearish trend, urging traders to be cautious with short positions and look for signs of continuation or reversal.
3. MAHA Bars for Distance and Area of Interest
In addition to the colored candles, the MAHA Luxmi AI Candles indicator also plots MAHA bars. These bars share the same color coding and usage as the candles, providing a consistent visual representation of market conditions:
- Green Bars: Indicate a potential long opportunity, aligning with green candles.
- Blue Bars: Show an active pullback in a bullish trend, aligning with blue candles.
- Red Bars: Represent a potential short opportunity, aligning with red candles.
- Yellow Bars: Indicate an active pullback in a bearish trend, aligning with yellow candles.
The MAHA bars help traders gauge the distance between the current price and the area of interest, enhancing their understanding of how close or far the price is from key levels identified by the MAHA formula. This aids in making better decisions regarding entry and exit points.
4. Trailing Stop Loss Feature
The base of the MAHA Bars can also be used as a trailing stop loss. This feature provides a dynamic stop loss level that adjusts with the market, helping traders lock in profits and limit losses by following the trend. When the price moves favorably, the trailing stop loss adjusts accordingly, ensuring that traders can capitalize on market movements while minimizing risk.
Usage and Benefits
- Trend Identification: The color-coded system simplifies the identification of market trends and potential reversals, making it easier for traders to understand market dynamics at a glance.
- Pullback and Reversal Alerts: The blue and yellow candles/bars alert traders to potential pullbacks and reversals, providing crucial information for managing trades and avoiding false signals.
- Distance Measurement: The MAHA bars help traders measure the distance between the current price and the areas of interest, enhancing their ability to assess the risk and potential reward of trades.
- Trailing Stop Loss: The base of the MAHA Bars can be used as a trailing stop loss, providing a dynamic risk management tool that adapts to market conditions.
Overall, the MAHA Luxmi AI Candles trading indicator is a powerful tool for traders looking to leverage the combined strengths of Moving Averages and Heikin-Ashi techniques. The intuitive color-coded system, additional MAHA bars, and the trailing stop loss feature make it an essential component of a trader’s toolkit for identifying trends, managing risk, and identifying trading opportunities.
Intelligent Exponential Moving Average (AI)Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Exponential Moving Average (EMA) is one of the most used indicators on the planet, yet no one really knows what pair of exponential moving average lengths works best in combination with each other.
A reason for this is because no two EMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Exponential Moving Average" solves the moving average problem by adapting the period length to match the most profitable combination of exponential moving averages in real time.
How does the Intelligent Exponential Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these exponential moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent EMA. Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The exponential moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of exponential moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
Intelligent Moving Average (AI)
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Moving Average is the most used indicator on the planet, yet no one really knows what pair of moving average lengths works best in combination with each other.
A reason for this is because no two moving averages are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of moving averages in real time.
How does the Intelligent Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent Moving Average. Most will come with time as it is still a new concept.
Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
Super AI signal"Super AI Signal" indicator - Unveiling the Hidden Secrets of the Market
Picture this: amidst the chaotic noise of the market, navigating the turbulent waves of charts, you hold a secret weapon in your hands. is not just an indicator—it’s a masterpiece born from the fusion of a trader’s intuition and the magic of data.
This indicator captures the subtle whispers of the market, delivering crystal-clear trading signals. With its sophisticated algorithms and intuitive design, it uncovers hidden patterns in price movements, illuminating opportunities in the fog of volatility. Whether you’re a novice trader or a seasoned pro, transforms your charts into a trusted ally.
Why is it special?
Precision: Filters out market noise to pinpoint genuine opportunities with razor-sharp accuracy.
- Simplicity: Let the indicator handle the complex analysis—you just make the decisions.
- Versatility: Shines across all assets and timeframes—stocks, crypto, forex, you name it!
- Visual Appeal: Intuitive design with signals that captivate at a glance.
"Super AI Signal" indicator is more than just numbers and lines. It’s a reliable compass for your trading journey, guiding you through the labyrinth of the market. Add it to your TradingView now and unlock the market’s secrets at your fingertips. Your next big win is already waiting on the charts—ready to seize it?
Then, you'd better use this indicator!
Machine Learning Moving Average [LuxAlgo]The Machine Learning Moving Average (MLMA) is a responsive moving average making use of the weighting function obtained Gaussian Process Regression method. Characteristic such as responsiveness and smoothness can be adjusted by the user from the settings.
The moving average also includes bands, used to highlight possible reversals.
🔶 USAGE
The Machine Learning Moving Average smooths out noisy variations from the price, directly estimating the underlying trend in the price.
A higher "Window" setting will return a longer-term moving average while increasing the "Forecast" setting will affect the responsiveness and smoothness of the moving average, with higher positive values returning a more responsive moving average and negative values returning a smoother but less responsive moving average.
Do note that an excessively high "Forecast" setting will result in overshoots, with the moving average having a poor fit with the price.
The moving average color is determined according to the estimated trend direction based on the bands described below, shifting to blue (default) in an uptrend and fushia (default) in downtrends.
The upper and lower extremities represent the range within which price movements likely fluctuate.
Signals are generated when the price crosses above or below the band extremities, with turning points being highlighted by colored circles on the chart.
🔶 SETTINGS
Window: Calculation period of the moving average. Higher values yield a smoother average, emphasizing long-term trends and filtering out short-term fluctuations.
Forecast: Sets the projection horizon for Gaussian Process Regression. Higher values create a more responsive moving average but will result in more overshoots, potentially worsening the fit with the price. Negative values will result in a smoother moving average.
Sigma: Controls the standard deviation of the Gaussian kernel, influencing weight distribution. Higher Sigma values return a longer-term moving average.
Multiplicative Factor: Adjusts the upper and lower extremity bounds, with higher values widening the bands and lowering the amount of returned turning points.
🔶 RELATED SCRIPTS
Machine-Learning-Gaussian-Process-Regression
SuperTrend-AI-Clustering
Ocs Ai TraderThis script perform predictive analytics from a virtual trader perspective!
It acts as an AI Trade Assistant that helps you decide the optimal times to buy or sell securities, providing you with precise target prices and stop-loss level to optimise your gains and manage risk effectively.
System Components
The trading system is built on 4 fundamental layers :
Time series Processing layer
Signal Processing layer
Machine Learning
Virtual Trade Emulator
Time series Processing layer
This is first component responsible for handling and processing real-time and historical time series data.
In this layer Signals are extracted from
averages such as : volume price mean, adaptive moving average
Estimates such as : relative strength stochastics estimates on supertrend
Signal Processing layer
This second layer processes signals from previous layer using sensitivity filter comprising of an Probability Distribution Confidence Filter
The main purpose here is to predict the trend of the underlying, by converging price, volume signals and deltas over a dominant cycle as dimensions and generate signals of action.
Key terms
Dominant cycle is a time cycle that has a greater influence on the overall behaviour of a system than other cycles.
The system uses Ehlers method to calculate Dominant Cycle/ Period.
Dominant cycle is used to determine the influencing period for the underlying.
Once the dominant cycle/ period is identified, it is treated as a dynamic length for considering further calculations
Predictive Adaptive Filter to generate Signals and define Targets and Stops
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimisation algorithm. Because of the complexity of the optimisation algorithms, almost all adaptive filters are digital filters. Thus Helping us classify our intent either long side or short side
The indicator use Adaptive Least mean square algorithm, for convergence of the filtered signals into a category of intents, (either buy or sell)
Machine Learning
The third layer of the System performs classifications using KNN K-Nearest Neighbour is one of the simplest Machine Learning algorithms based on Supervised Learning technique.
K-NN algorithm assumes the similarity between the new case/data and available cases and put the new case into the category that is most similar to the available categories.
K-NN algorithm stores all the available data and classifies a new data point based on the similarity. This means when new data appears then it can be easily classified into a well suite category by using K- NN algorithm. K-NN algorithm can be used for Regression as well as for Classification but mostly it is used for the Classification problems.
Virtual Trade Emulator
In this last and fourth layer a trade assistant is coded using trade emulation techniques and the Lines and Labels for Buy / Sell Signals, Targets and Stop are forecasted!
How to use
The system generates Buy and Sell alerts and plots it on charts
Buy signal
Buy signal constitutes of three targets {namely T1, T2, T3} and one stop level
Sell signal
Sell signal constitutes of three targets {namely T1, T2, T3} and one stop level
What Securities will it work upon ?
Volume Informations must be present for the applied security
The indicator works on every liquid security : stocks, future, forex, crypto, options, commodities
What TimeFrames To Use ?
You can use any Timeframe, The indicator is Adaptive in Nature,
I personally use timeframes such as : 1m, 5m 10m, 15m, ..... 1D, 1W
This Script Uses Tradingview Premium features for working on lower timeframes
In case if you are not a Tradingview premium subscriber you should tell the script that after applying on chart, this can be done by going to settings and unchecking "Is your Tradingview Subscription Premium or Above " Option
How To Get Access ?
You will need to privately message me for access mentioning you want access to "Ocs Ai Trader" Use comment box only for constructive comments. Thanks !
Trend Sentinel BarrierEveryone in the market wants to take profits from the trend. It is easy to think but hard to execute. In fact, some callbacks or rebounds may cause you to close the position out of fear and let you miss bigger profits.
Indicator: Trend Sentinel Barri er solves this problem for you! It use AI algorithm to help you seize profits.
It is a trend indicator, using AI algorithm to calculate the cumulative trading volume of bulls and bears, identify trend direction and opportunities, and calculate short-term average cost in combination with changes of turnover ratio in multi-period trends, so as to grasp the profit from the trend more effectively without being cheated.
💠Usage：
Signal: "BUY" means bullish trend, "SELL" means bearish trend.
Support and resistance range: "red area" represents strong support or resistance for long-term fluctuation costs, and "blue area" represents moderate support of resistance for short-term fluctuation costs.
🎈Tip I：
When the BUY and SELL signal appear, it means that the direction of the trend will change, and the color of the candles will also change. Don't care about the color of the candles, let's just focus on the price, support and resistance.
🎈Tip II：
Take the BUY signal as an example. When the signal appears and you hold long position, you need to pay attention to the blue and red support range. If the price returns to this range but there is no SELL signal, you can consider holding the long position for a while.
If the price pump with long candles, and then pulls back to the range, you need to be vigilant. You can consider taking the profit when the price breakthrough the support range, or wait for the SELL signal.
🎈Advanced tip I：
In most cases, the trend market is not smooth, there will be a lot of callbacks or rebounds, but because of this, we have many opportunities to do swing trading.
Continuing to take the BUY signal as an example, when this signal appears, every time the price falls back to the blue or red support area, you can consider adding positions. There are two ways to deal with these newly added positions.
One is to do swing trading. You can consider taking profits near the previous high when the price rises. The advantage of this operation is that you can get more profits in the same trend market.
The second is to continue to hold it as the bottom position until the general trend is completely over, and then close the position after obtaining huge profits.
🎈Advanced tip II：
When using advanced tips I, you can consider adding some momentum indicators to assist you in judging whether pullbacks or rebounds have failed, so as to increase your position. Similarly, the momentum indicator can also help you find a take-profit point for newly added positions
For details, please refer to the momentum indicator: KD Momentum Matrix
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
Update-
Optimize the alarm function. If you need to monitor the "Buy" or "Sell" signal, when creating an alarm, set the condition bar to:
Trend Sentinel Barrier --> "Buy" or "Sell" --> Crossing Up --> value --> 1
Intelligent Supertrend (AI) - Buy or Sell SignalIntroduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The artificial intelligence that operates this Supertrend was created by an algorithm that tests every single combination of input values across the entire chart history of an instrument for maximum profitability in real-time.
The Supertrend is one of the most popular indicators on the planet, yet no one really knows what input values work best in combination with each other. A reason for this is because not one set of input values is always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Supertrend" solves this problem by constantly adapting the input values to match the most profitable combination so that no matter what happens, this Supertrend will be the most profitable.
Indicator Utility
The Intelligent Supertrend does not change what has already been plotted and does not repaint in any way which means that it is fully functional for trading in real-time.
Ultimately, there are no limiting factors within the range of combinations that have been programmed. The Supertrend will operate normally but will change input values according to what is currently the most profitable strategy.
Input Values
While a normal Supertrend would include two user-defined input values, the Intelligent Supertrend automates the input values according to what is currently the most profitable combination.
Additional Tools
The Optimised Supertrend is a tool that can be used to visual what input values the Supertrend AI is currently using. Additional tools to back-test this indicator will be added to this product soon.
For more information on how this indicator works, view the documentation here:
www.kenzing.com
For more information on the Supertrend view these fun facts:
www.marketcalls.in
Auto AI Trendlines [TradingFinder] Clustering & Filtering Trends🔵 Introduction
Auto AI trendlines Clustering & Filtering Trends Indicator, draws a variety of trendlines. This auto plotting trendline indicator plots precise trendlines and regression lines, capturing trend dynamics.
Trendline trading is the strongest strategy in the financial market.
Regression lines, unlike trendlines, use statistical fitting to smooth price data, revealing trend slopes. Trendlines connect confirmed pivots, ensuring structural accuracy. Regression lines adapt dynamically.
The indicator’s ascending trendlines mark bullish pivots, while descending ones signal bearish trends. Regression lines extend in steps, reflecting momentum shifts. As the trend is your friend, this tool aligns traders with market flow.
Pivot-based trendlines remain fixed once confirmed, offering reliable support and resistance zones. Regression lines, adjusting to price changes, highlight short-term trend paths. Both are vital for traders across asset classes.
🔵 How to Use
There are four line types that are seen in the image below; Precise uptrend (green) and downtrend (red) lines connect exact price extremes, while Pivot-based uptrend and downtrend lines use significant swing points, both remaining static once formed.
🟣 Precise Trendlines
Trendlines only form after pivot points are confirmed, ensuring reliability. This reduces false signals in choppy markets. Regression lines complement with real-time updates.
The indicator always draws two precise trendlines on confirmed pivot points, one ascending and one descending. These are colored distinctly to mark bullish and bearish trends. They remain fixed, serving as structural anchors.
🟣 Dynamic Regression Lines
Regression lines, adjusting dynamically with price, reflect the latest trend slope for real-time analysis. Use these to identify trend direction and potential reversals.
Regression lines, updated dynamically, reflect real-time price trends and extend in steps. Ascending lines are green, descending ones orange, with shades differing from trendlines. This aids visual distinction.
🟣 Bearish Chart
A Bullish State emerges when uptrend lines outweigh or match downtrend lines, with recent upward momentum signaling a potential rise. Check the trend count in the state table to confirm, using it to plan long positions.
🟣 Bullish Chart
A Bearish State is indicated when downtrend lines dominate or equal uptrend lines, with recent downward moves suggesting a potential drop. Review the state table’s trend count to verify, guiding short position entries. The indicator reflects this shift for strategic planning.
🟣 Alarm
Set alerts for state changes to stay informed of Bullish or Bearish shifts without constant monitoring. For example, a transition to Bullish State may signal a buying opportunity. Toggle alerts On or Off in the settings.
🟣 Market Status
A table summarizes the chart’s status, showing counts of ascending and descending lines. This real-time overview simplifies trend monitoring. Check it to assess market bias instantly.
Monitor the table to track line counts and trend dominance.
A higher count of ascending lines suggests bullish bias. This helps traders align with the prevailing trend.
🔵 Settings
Number of Trendlines : Sets total lines (max 10, min 3), balancing chart clarity and trend coverage.
Max Look Back : Defines historical bars (min 50) for pivot detection, ensuring robust trendlines.
Pivot Range : Sets pivot sensitivity (min 2), adjusting trendline precision to market volatility.
Show Table Checkbox : Toggles display of a table showing ascending/descending line counts.
Alarm : Enable or Disable the alert.
🔵 Conclusion
The multi slopes indicator, blending pivot-based trendlines and dynamic regression lines, maps market trends with precision. Its dual approach captures both structural and short-term momentum.
Customizable settings, like trendline count and pivot range, adapt to diverse trading styles. The real-time table simplifies trend monitoring, enhancing efficiency. It suits forex, stocks, and crypto markets.
While trendlines anchor long-term trends, regression lines track intraday shifts, offering versatility. Contextual analysis, like price action, boosts signal reliability. This indicator empowers data-driven trading decisions.
Nyx-AI Market Intelligence DashboardNyx AI Market Intelligence Dashboard is a non-signal-based environmental analysis tool that provides real-time insight into short-term market behavior. It is designed to help traders understand the quality of current price action, volume dynamics, volatility conditions, and structural behavior. It informs the trader whether the current market environment is supportive or hostile to trading and whether any active signal (from other tools) should be trusted, filtered, or avoided altogether.
Nyx is composed of seven intelligent modules. Each module operates independently but is visually unified through a floating dashboard panel on the chart. This panel renders live diagnostics every few bars, maintaining a low visual footprint without drawing overlays or modifying price.
Market Posture Engine
This module reads individual candlesticks using real-time candle anatomy to interpret directional bias and sentiment. It examines body-to-range ratio, wick imbalances, and compares them to prior bars. If the current candle is a large momentum body with minimal wick, it is interpreted as a directional thrust. If it is a small body with equal wicks, it is considered indecision. Engulfing patterns are used to detect potential liquidity tests. The system outputs a plain-text posture signal such as Building Bullish Intent, Bearish Momentum, Indecision Zone, Testing Liquidity (Up or Down), or Neutral.
Flow Reversal Engine
This module monitors short-term structural shifts and volume contraction to detect early signs of reversal or exhaustion. It looks for lower highs or higher lows paired with weakening volume and closing behavior that implies loss of momentum. It also monitors divergence between price and volume, as well as bar-to-bar momentum stalls (where highs and lows stop expanding). When these conditions are met, it outputs one of several states including Top Forming, Bottom Forming, Flow Divergence, Momentum Stall, or Neutral. This is useful for detecting inflection points before they manifest on trend indicators.
Fractal Context Engine
This engine compares the current bar’s range to its surrounding structural context. It uses a dynamic lookback length based on volatility. It determines whether the market is in expansion (strong directional trend), compression (shrinking range), or a transitional phase. A special case called Flip In Progress is triggered when the current high and low exceed the entire recent range, which often precedes sharp reversals or volatility expansion. The result is one of the following: Trend Expansion, Trend Breakdown, Sideways or Coil, Flip In Progress, or Expansion to Coil.
Candle Behavior Analyzer
This module analyzes the last five candles as a set to detect behavioral traits that a single candle may not reveal. It calculates average body and wick size, and counts how many recent candles show thrust (large body dominance), trap behavior (price returns inside wicks), or weakness (small bodies with high wick ratios). The module outputs one of the following behaviors: Aggressive Buying, Aggressive Selling, Trap Pattern, Trap During Coil, Low Participation, Low Energy, or Fakeout Candle. This helps the trader assess sentiment quality and the reliability of price movement.
Volatility Forecast and Compression Memory
This module predicts whether a breakout is likely based on recent compression behavior. It tracks how many of the last 10 bars had significantly reduced range compared to average. If a certain threshold is met without any recent large expansion bar, the system forecasts that a volatility expansion is likely in the near future. It also records how many bars ago the last high volatility impulse occurred and classifies whether current conditions are compressing. The outputs are Expansion Likely, Active Compression, and Last Burst memory, which provide breakout timing and energy insights.
Entry Filter
This module scores the current bar based on four adaptive criteria: body size relative to range, volume strength relative to average, current volatility versus historical volatility, and price position relative to a 20-period moving average. Each factor is scored as either 1 or 2. The total score is adjusted by a behavioral modifier that adds or subtracts a point if recent candles show aggression or trap behavior. Final scores range from 4 to 8 and are classified into Optimal, Mixed, or Avoid categories. This module is not a trade signal. It is a confluence filter that evaluates whether conditions are favorable for entry. It is particularly effective when layered with other indicators to improve precision.
Liquidity Intent Engine
This engine checks for price behavior around recent swing highs and lows. It uses adaptive pivots based on volatility to determine if price has swept above a recent high or below a recent low. This behavior is often associated with institutional liquidity hunts. If a sweep is detected and price has moved away from the sweep level, the engine infers directional intent and compares current distance to the high and low to determine which liquidity pool is more dominant. The output is Magnet Above, Magnet Below, or Conflict Zone. This is useful for anticipating directional bias driven by smart money activity.
Sticky Memory Tracking
To avoid flickering between states on low volatility or noisy price action, Nyx includes a sticky memory system. Each module’s output is preserved until a meaningful change is detected. For example, if Market Posture is Neutral and remains so for several bars, the previous non-neutral value is retained. This makes the dashboard more stable and easier to interpret without misleading noise.
Dashboard Rendering
All module outputs are displayed in a clean two-column panel anchored to any corner of the chart. Text values are color-coded, tooltips are added for context, and the data refreshes every few bars to maintain speed. The dashboard avoids clutter and blends seamlessly with other chart tools.
This tool is intended for informational and educational purposes only. It does not provide financial advice or trading signals. Nyx analyzes price, volume, structure, and volatility to offer context about the current market environment. It is not designed to predict future price movements or guarantee profitable outcomes. Traders should always use independent judgment and risk management. Past performance of any analysis logic does not guarantee future results.
Helacator Ai ThetaHelacator Ai Theta is a state-of-the-art advanced script. It helps the trader find the possibility of a trend reversal in the market. By finding that point at which the three black crows pattern combines with the three white soldiers pattern, it is the most cherished pattern in technical analysis for its signal of strong bullish or bearish momentum. Therefore, it is a very strong predictive tool in the ability of shifting markets.
Key Highlights: Three White Soldiers and Three Black Crows Patterns
The script identifies these candlestick formations that consist of three consecutive candles, either bullish (Three White Soldiers) or bearish (Three Black Crows). These patterns help the trader identify possible trend reversal points as they provide an early signal of a change in the market direction. It is with great care that the script is written to evaluate the position and relationship between the candlesticks for maintaining the accuracy of pattern recognition. Moving Averages for Trend Filtering:
Two important ones used are moving averages for filtering any signals not in accordance with the general trend. The length of these MAs is variable, allowing the traders to be in a position to adapt the script for use under different market conditions. The moving averages ensure that signals are only taken in the direction that supports the general market flow, so it leads to more reliability within the signals. The MAs are not plotted on the chart for the sake of clarity, but they still perform a crucial function in signal filtering and can be displayed optionally for a more detailed investigation. Cooldown filter to reduce over-trading
This is part of what is implemented in the script to prevent generation of consecutive signals too quickly. All this helps to reduce market noise and not overtrade—only when market conditions are at their best. The cooldown period can be set to be adjusted according to the trader's preference, making the script more versatile in its use. Practical Considerations: Educational Purpose: This script is for educational purposes only and should be part of a comprehensive trading approach. Proper risk management techniques should be observed while at the same time taking into consideration prevailing market conditions before making any trading decision.
No Guaranteed Results: The script is aimed at bringing signal accuracy into improvement to align with the broader market trend and reducing noise, but past performance cannot guarantee future success. Traders should use this script within their broad trading approach. Clean and Simple Chart Display: The primary goal of this script is to have a clear and simple display on the chart. The signals are prominently marked with "BUY" and "SELL," and the color of the bars has changed according to the last signal, thus traders can easily read the output. Community and Open Source Open Source Contribution: This script is open for contribution by the TradingView community. Any suggestions regarding improvements are highly welcomed. Candlestick patterns, moving averages, and the combination of the cooldown filter are presented in such a way as to give traders something special, and any modifications or extra touch by the community is appreciated. Attribution and Transparency: The script is based on standard technical analysis principles and for all parts inspired by or derivated from other available open-source scripts, credit is given where it is due. In this way, transparency ensures that the script adheres to TradingView's standards and promotes a collaborative community environment.
Edge AI Forecast [Edge Terminal]This indicator inputs the previous 150 closing prices in a simple two-layer neural network, normalizes the network inputs using a sigmoid function, uses a feedforward calculation to send it to the second layer, shows the MSE loss curve and uses both automatic and manual backpropagation (user input) to find the most likely forecast values and uses the analog forecasting algorithm to adjust and optimize the data furthermore to display potential prices on the chart.
Here's how it works:
The idea behind this script is to train a simple neural network to predict the future x values based on the sample data. For this, we use 2 types of data, Price and Volume.
The thinking behind this is that price alone can’t be used in this case because it doesn’t provide enough meaningful pattern data for the network but price and volume together can change the game. We’re planning to use more different data sets and expand on this in the future.
To avoid a bad mix of results, we technically have two neural networks, each processing a different data type, one for volume data and one for price data.
The actual prediction is decided by the way price and volume of the closing price relate to each other. Basically, the network passes the price and volume and finds the best relation between the two data set outputs and predicts where the price could be based on the upcoming volume of the latest candle.
The network adjusts the weights and biases using optimization algorithms like gradient descent to minimize the difference between the predicted and actual stock prices, typically measured by a loss function, (in this case, mean squared error) which you can see using the error rate bubble.
This is a good measure to see how well the network is performing and the idea is to adjust the settings inputs such as learning rate, epochs and data source to get the lowest possible error rate. That’s when you’re getting the most accurate prediction results.
For each data set, we use a multi-layer network. In a multi-layer neural network, the outputs of neurons in one layer serve as inputs to neurons in the next layer. Initially, the input layer of the neural network receives the historical data. Each input neuron represents a feature, such as previous stock prices and trading volumes over a specific period.
The hidden layers perform feature extraction and transformation through a series of weighted connections and activation functions. Each neuron in a hidden layer computes a weighted sum of the inputs from the previous layer, applies an activation function to the sum, and passes the result to the next layer using the feedforward (activation) function.
For extraction, we use a normalization function. This function takes a value or data (such as bar price) and divides it up by max scale which is the highest possible value of the bar. The idea is to take a normalized number, which is either below 1 or under 2 for simple use in the neural network layers.
For the activation, after computing the weighted sum, the neuron applies an activation function a(x). To introduce non-linearity into the model to pass it to the next layer. We use sigmoid activation functions in this case. The main reason we use sigmoid function is because the resulting number is between 0 to 1 and is better for models where we have to predict the probability as an output.
The final output of the network is passed as an input to the analog forecasting function. This is an algorithm commonly used in weather prediction systems. In this case, this is used to make predictions by comparing current values and assuming the patterns might repeat in the future.
There are many different ways to build an analog forecasting function but in our case, we’re used similarity measurement model:
X, as the current situation or set of current variables.
Y, as the outcome or variable of interest.
Si as the historical situations or patterns, where i ranges from 1 to n.
Vi as the vector of variables describing historical situation Si.
Oi as the outcome associated with historical situation Si.
First, we define a similarity measure sim(X,Vi) that quantifies the similarity between the current situation X and historical situation Si based on their respective variables Vi.
Then we select the K most similar historical situations (KNN Machine learning) based on the similarity measure sim(X,Vi). We denote the rest of the selected historical situations as {Si1, Si2,...Sik).
Then we examine the outcomes associated with the selected historical situations {Oi1, Oi2,...,Oik}.
Then we use the outcomes of the selected historical situations to forecast the future outcome Y^ using weighted averaging.
Finally, the output value of the analog forecasting is standardized using a standardization function which is the opposite of the normalization function. This function takes a normalized number and turns it back to its original value by multiplying it by the max scale (highest value of the bar). This function is used when the final number is produced by the network output at the end of the analog forecasting to turn the final value back into a price so it can be displayed on the chart with PineScript.
Settings:
Data source: Source of the neural network's input data.
Sample Bars: How many historical bars do you want to input into the neural network
Prediction Bars: How many bars you want the script to forecast
Show Training Rate: This shows the neural network's error rate for the optimization phase
Learning Rate: how many times you want the script to change the model in response to the estimated error (automatic)
Epochs: the network cycle or how many times you want to run the data through the network from the first layer to the last one.
Usage:
The sample bars input determines the number of historical bars to be used as a reference for the network. You need to change the Epochs and Learning Rate inputs for each asset and chart timeframe to get the lowest error rate.
On the surface, the highest possible epoch and learning rate should produce the most effective results but that's not always the case.
If the epochs rate is too high, there is a chance we face overfitting. Essentially, you might be over processing good data which can make it useless.
On the other hand, if the learning rate is too high, the network may overshoot the optimal solution and diverge. This is almost like the same issue I mentioned above with a high epoch rate.
Access:
It took over 4 months to develop this script and we’re constantly improving it so it took a lot of manpower to develop this script. Also when it comes to neural networks, Pine Script isn’t the most optimal language to build a neural network in, so we had to resort to a few proprietary mathematical formulas to ensure this runs smoothly without giving out an error for overprocessing, specially when you have multiple neural networks with many layers.
The optimization done to make this script run on Pine Script is basically state of the art and because of this, we would like to keep the code closed source at the moment.
On the other hand we don’t want to publish the code publicly as we want to keep the trading edge this script gives us in a closed loop, for our own small group of members so we have to keep the code closed. We only accept invites from expert traders who understand how this script and algo trading works and the type of edge it provides.
Additionally, at the moment we don’t want to share the code as some of the parts of this network, specifically the way we hand the data from neural network output into the analog method formula are proprietary code and we’d like to keep it that way.
You can contact us for access and if we believe this works for your trading case, we will provide you with access.
