Smart AI Reversal Hunter🧠 Smart AI Reversal Hunter: Precision Trading with Adaptive Intelligence
In the fast-moving world of technical trading, reacting swiftly isn’t enough—you must adapt intelligently. Enter the Smart AI Reversal Hunter, a next-generation trading strategy engineered to identify key market reversals with surgical accuracy, powered by adaptive volatility logic, multi-timeframe awareness, and a deep understanding of market structure.
Whether you're a scalper, swing trader, or systems developer, this strategy offers a powerful edge—filtering out market noise and zeroing in on high-conviction turning points without emotional bias.
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🚀 Why Smart AI Reversal Hunter Stands Out
📈 Built for Turning Points
This strategy excels at catching early reversals, allowing you to enter positions before the crowd, with smart confirmation from momentum, fractals, and volume surges.
🧠 Adaptive Intelligence at the Core
At the heart of the system lies a dynamic trend engine that automatically recalibrates itself based on prevailing volatility. It slows down in quiet markets and speeds up in wild ones—mimicking how a human would adjust instinctively, but with mathematical consistency.
🧩 Multi-Layered Filtering
The strategy doesn’t rely on a single signal. Instead, it layers multiple confirmation systems to validate each trade:
Directional momentum
Breakout fractal structure
Volatility regime analysis
Volume confirmation
Macro-trend alignment from a higher timeframe
📊 Built-In Visual Dashboard
A sleek diagnostics panel sits quietly in the corner, showing you all the internal metrics—volatility state, momentum shifts, higher timeframe bias, and volume strength—so you’re never guessing.
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🔍 Technical Description
📌 Core Engine: Adaptive Reversal Detector
Based on a custom smoothed trend indicator with triple-weighted filtering logic (a proprietary formula deliberately concealed here for uniqueness).
The length of this engine adapts to market volatility using a real-time ATR-to-SMA ratio, then clamps the value between minimum and maximum bounds to prevent overfitting.
This ensures the trend detector is neither too sluggish in explosive markets nor too reactive during sideways zones.
⚙️ Entry Logic
Bullish Entry: Triggered when the adaptive trend line crosses above its own historical value, alongside:
Positive momentum (Rate of Change > 0)
Price above recent fractal high
Price above lower Keltner Channel boundary
Not in a low-volatility regime
Higher timeframe confirming a bullish bias
Current volume exceeding average volume × multiplier
Bearish Entry: Symmetric to the above, in reverse.
🧰 Customization Tools
Toggle each filter (momentum, fractals, volume, etc.) individually
Choose between “Only Long”, “Only Short”, or “Long & Short” trading styles
Adjustable timeframes for higher-timeframe confirmation
Reversible volume strength criteria
📈 Exit Logic
Longs are closed on bearish signals (and vice versa), with optional logic for one-sided trading.
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📌 Final Thoughts
In an era of overcomplicated indicators and noise-heavy signals, the Smart AI Reversal Hunter brings clarity and logic to the chart. It doesn’t chase candles. It listens, adapts, and then strikes with conviction.
Whether you're automating your trades or visually analyzing reversals, this strategy equips you with everything needed to stay ahead of the curve—and let your strategy think before it trades.
⚠️ Safety & Disclaimer Notice
The Smart AI Reversal Hunter strategy is designed for educational and research purposes only. While every effort has been made to optimize its logic for identifying potential market reversals, past performance is not indicative of future results.
Please keep the following safety points in mind before using this or any trading strategy:
📌 Not Financial Advice
This script does not constitute financial, investment, or trading advice. Always perform your own due diligence.
📌 No Guaranteed Profits
Markets are inherently uncertain. This strategy uses probabilistic logic—not prediction. Losses are possible, and trading carries risk.
📌 Consult a Professional Advisor
Before taking any live positions, especially with real capital, consult with a certified financial or technical advisor who understands your risk profile and financial goals.
📌 Test Before You Trade
Always backtest thoroughly and paper trade in real-time market conditions before deploying on live accounts.
📌 Understand the Logic
Blindly using automated strategies without understanding their conditions can lead to significant loss. Read the code, understand the filters, and adapt to your own trading style if necessary.
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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,
SuperTrend AI Oscillator StrategySuperTrend AI Oscillator Strategy
Overview
This strategy is a trend-following approach that combines the SuperTrend indicator with oscillator-based filtering.
By identifying market trends while utilizing oscillator-based momentum analysis, it aims to improve entry precision.
Additionally, it incorporates a trailing stop to strengthen risk management while maximizing profits.
This strategy can be applied to various markets, including Forex, Crypto, and Stocks, as well as different timeframes. However, its effectiveness varies depending on market conditions, so thorough testing is required.
Features
1️⃣ Trend Identification Using SuperTrend
The SuperTrend indicator (a volatility-adjusted trend indicator based on ATR) is used to determine trend direction.
A long entry is considered when SuperTrend turns bullish.
A short entry is considered when SuperTrend turns bearish.
The goal is to capture clear trend reversals and avoid unnecessary trades in ranging markets.
2️⃣ Entry Filtering with an Oscillator
The Super Oscillator is used to filter entry signals.
If the oscillator exceeds 50, it strengthens long entries (indicating strong bullish momentum).
If the oscillator drops below 50, it strengthens short entries (indicating strong bearish momentum).
This filter helps reduce trades in uncertain market conditions and improves entry accuracy.
3️⃣ Risk Management with a Trailing Stop
Instead of a fixed stop loss, a SuperTrend-based trailing stop is implemented.
The stop level adjusts automatically based on market volatility.
This allows profits to run while managing downside risk effectively.
4️⃣ Adjustable Risk-Reward Ratio
The default risk-reward ratio is set at 1:2.
Example: A 1% stop loss corresponds to a 2% take profit target.
The ratio can be customized according to the trader’s risk tolerance.
5️⃣ Clear Trade Signals & Visual Support
Green "BUY" labels indicate long entry signals.
Red "SELL" labels indicate short entry signals.
The Super Oscillator is plotted in a separate subwindow to visually assess trend strength.
A real-time trailing stop is displayed to support exit strategies.
These visual aids make it easier to identify entry and exit points.
Trading Parameters & Considerations
Initial Account Balance: Default is $7,000 (adjustable).
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 1,032
Visual Aids for Clarity
This strategy includes clear visual trade signals to enhance decision-making:
Green "BUY" labels for long entries
Red "SELL" labels for short entries
Super Oscillator plotted in a subwindow with a 50 midline
Dynamic trailing stop displayed for real-time trend tracking
These visual aids allow traders to quickly identify trade setups and manage positions with greater confidence.
Summary
The SuperTrend AI Oscillator Strategy is developed based on indicators from Black Cat and LuxAlgo.
By integrating high-precision trend analysis with AI-based oscillator filtering, it provides a strong risk-managed trading approach.
Important Notes
This strategy does not guarantee profits—performance varies based on market conditions.
Past performance does not guarantee future results. Markets are constantly changing.
Always test extensively with backtesting and demo trading before using it in live markets.
Risk management, position sizing, and market conditions should always be considered when trading.
Conclusion
This strategy combines trend analysis with momentum filtering, enhancing risk management in trading.
By following market trends carefully, making precise entries, and using trailing stops, it seeks to reduce risk while maximizing potential profits.
Before using this strategy, be sure to test it thoroughly via backtesting and demo trading, and adjust the settings to match your trading style.
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.
XT AI Trading System for XBTUSD (BitMEX)- Features:
+ XT-AI-TRADE System with special built-in XT-AI Trend line, trend cloud indicator for XBTUSD (BitMEX) with the best performance.
+ Full backtesting from April 2018 with results as below:
Time frame / Net profit / Percent profitable / Profit factor
H1: 450% / 80% / 74.187
H2: 445% / 100% / Max
H3: 778% / 80% / 17.264
H4: 624% / 85.71% / 119.905
D1: 169% / 100% / Max
+ Separately optimized AI trading algorithm for different time frames: H1/H2/H3/H4/D1 (including Margin and Exchange Trading).
+ Trustworthy backtesting accuracy result with 100% non-repainting, no difference between backtesting and live trading.
+ Real-time push notification system: Email / Telegram... to your PC and Smartphone => Enjoy trading life.
+ 24/7 business operation.
*** Sign up for a trial here : goo.gl
Professor-AI[Cryptovarthagam]Professor-AI — Smart Breakout Tracker & Profit Calculator
By: Cryptovarthagam
🔍 Overview
Professor-AI is an advanced real-time support & resistance breakout indicator powered by intelligent filters and trade tracking logic. Built for intraday and short-term traders, it automatically identifies significant breakout opportunities, plots entry, SL, TP1, TP2 levels, and dynamically tracks the profit/loss outcome of each trade on the chart with detailed labels.
This tool is ideal for scalpers, day traders, and momentum traders who want clear, actionable, and data-backed trade setups on any crypto, stock, or forex chart.
✅ Key Features
📈 Smart Support & Resistance Detection
Uses volume filters and pivot/dynamic calculations to draw key levels that matter.
🔔 Real-Time Breakout Signals
Generates instant trade signals on breakout of these levels — not on delay or after confirmation candles.
🧠 Customizable Trade Entry Logic
Choose between dynamic crossover logic or classic pivot breakouts for better control.
🧮 Auto SL, TP1, TP2 Level Calculation
Based on ATR, dynamically adapts to volatility.
💹 Profit/Loss Tracking On Chart
Labels appear on the chart showing gain/loss % and dollar value of each TP1, TP2, or SL hit.
📊 Capital & Leverage-Based PnL Calculation
Set your capital and leverage to see potential dollar outcomes for each trade.
🧰 Built-In Risk Management
SL% limiter to avoid trades with unusually wide stops.
⚙️ Flexible Settings
Customize SL/TP multipliers, enable/disable TP2, choose breakout detection method, and more.
📌 Why This Is Useful
No Guesswork: Clearly shows breakout levels and their outcomes — reduces emotional decision-making.
Data-Backed Decisions: Volume and ATR filters ensure signals are more reliable than basic breakouts.
Perfect for Fast-Paced Trading: Built for 1m–15m timeframes where timing and clarity matter most.
Visual Trade Logs: Easily review past performance without exporting data or checking external tools.
Risk Control Built-In: Automatically prevents trades with excessive SL size.
⚙️ Suggested Use Cases
Crypto scalping (BTC, ETH, altcoins)
Intraday stock trading
Forex breakout strategies
Smart trade journaling directly on chart
🧪 Settings Overview
Period Length: Lookback for S/R zones
SL/TP Multipliers: Define how far SL, TP1, and TP2 levels are from entry
ATR Buffer & Volume Filter: Improve signal accuracy
Capital & Leverage Inputs: Adjust to see personalized PnL tracking
TP2 Visibility Toggle: Show or hide TP2 target level
Breakout Logic Options: Choose between pivot-based or dynamic crossover logic
To get the indicator access please visit www.cryptovarthagam.com
🚫 Disclaimer
This is a technical analysis tool meant to assist in decision-making. It does not guarantee profits or remove the need for proper risk management. Always test strategies in demo environments before trading real capital.
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 !
IsAlgo - AI Trend Strategy► Overview:
The AI Trend Strategy employs a combination of technical indicators to guide trading decisions across various markets and timeframes. It uses a custom Super Trend indicator and an Exponential Moving Average (EMA) to analyze market trends and executes trades based on specific candlestick patterns. This strategy includes options for setting stop losses, take profit levels, and features an alert system for trade notifications.
► Description:
This strategy focuses on identifying the optimal "entry candle," which signals either a potential correction within the ongoing trend or the emergence of a new trend. The entry criteria for this candle are highly customizable, allowing traders to specify dimensions such as the candle's minimum and maximum size and body ratio. Additional settings include whether this candle should be the highest or lowest compared to recent candles and if a confirmation candle is necessary to validate the entry.
The Super Trend indicator is central to the strategy’s operation, dictating the direction of trades by identifying bullish or bearish trends. Traders have the option to configure trades to align with the direction of the trend identified by this indicator, or alternatively, to take positions counter to the trend for potential reversal strategies. This flexibility can be crucial during varying market conditions.
Additionally, the strategy incorporates an EMA alongside the Super Trend indicator to further analyze trend directions. This combined approach aims to reduce the occurrence of false signals and improve the strategy's overall trend analysis.
The learning algorithm is a standout feature of the AI Trend Strategy. After accumulating data from a predefined number of trades (e.g., after the first 100 trades), the algorithm begins to analyze past performances to identify patterns in wins and losses. It considers variables such as the distance from the current price to the trend line, the range between the highest and lowest prices during the trend, and the duration of the trend. This data informs the algorithm's predictions for future trades, aiming to improve accuracy and reduce losses by adapting to the evolving market conditions.
► Examples of Trade Execution:
1. In an Uptrend: The strategy might detect a suitable entry candle during a correction phase, which aligns with the continuing uptrend for a potential long trade.
2. In a Downtrend: Alternatively, the strategy might identify an entry candle at the end of a downtrend, suggesting a potential reversal or correction where a long trade could be initiated.
3. In an Uptrend: The strategy may also spot an entry candle at the end of an uptrend and execute a short trade, anticipating a reversal or significant pullback.
4. In a Downtrend: The strategy might find a suitable entry candle during a correction phase, indicating a continuation of the downtrend for a potential short trade.
These examples illustrate how the strategy identifies potential trading opportunities based on trend behavior and candlestick patterns.
► Features and Settings:
⚙︎ Trend: Utilizes a custom Super Trend indicator to identify the direction of the market trend. Users can configure the strategy to execute trades in alignment with this trend, take positions contrary to the trend, or completely ignore the trend information for their trading decisions.
⚙︎ Moving average: Employs an Exponential Moving Average (EMA) to further confirm the trend direction indicated by the Super Trend indicator. This setting can be used in conjunction with the Super Trend or disabled if preferred.
⚙︎ Entry candle: Defines the criteria for the candle that triggers a trade. Users can customize aspects such as the candle's size, body, and its relative position to previous candles to ensure it meets specific trading requirements before initiating a trade.
⚙︎ Learning algorithm: This component uses historical trade data to refine the strategy. It assesses various aspects of past trades, such as price trends and market conditions, to make more informed trading decisions in the future.
⚙︎ Trading session: Users can define specific trading hours during which the strategy should operate, allowing trades to be executed only during preferred market periods.
⚙︎ Trading days: This option enables users to specify which days the strategy should be active, providing the flexibility to avoid trading on certain days of the week if desired.
⚙︎ Backtesting: Enables a period during which the strategy can be tested over a selected start and end date, with an option to deactivate this feature if not needed.
⚙︎ Trades: Detailed configuration options include the direction of trades (long, short, or both), position sizing (fixed or percentage-based), the maximum number of open trades, and limitations on the number of trades per day or based on trend changes.
⚙︎ Trades Exit: Offers various strategies for exiting trades, such as setting limits on profits or losses, specifying the duration a trade should remain open, or closing trades based on trend reversal signals.
⚙︎ Stop loss: Various methods for setting stop losses are available, including fixed pips, based on Average True Range (ATR), or utilizing the highest or lowest price points within a designated number of previous candles. Another option allows for closing the trade after a specific number of candles moving in the opposite direction.
⚙︎ Break even: This feature adjusts the stop loss to a break-even point under certain conditions, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, aiming to secure gains while potentially capturing further upside.
⚙︎ Take profit: Up to three take profit levels can be established using various methods, such as a fixed amount of pips, risk-to-reward ratios based on the stop loss, ATR, or after a set number of candles that move in the direction of the trade.
⚙︎ Alerts: Includes a comprehensive alert system that informs the user of all significant actions taken by the strategy, such as trade openings and closings. It supports placeholders for dynamic values like take profit levels, stop loss prices, and more.
⚙︎ Dashboard: Provides a visual display of detailed information about ongoing and past trades on the chart, helping users monitor the strategy’s performance and make informed decisions.
► Backtesting Details:
Timeframe: 15-minute BTCUSD chart.
Initial Balance: $10,000.
Order Size: 4% of equity per trade.
Commission: 0.01%.
Slippage: 5 ticks.
Risk Management: Strategic stop loss settings are applied based on the most extreme price points within the last 18 candles.
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
Multi-TF AI SuperTrend with ADX - Strategy [PresentTrading]
## █ Introduction and How it is Different
The trading strategy in question is an enhanced version of the SuperTrend indicator, combined with AI elements and an ADX filter. It's a multi-timeframe strategy that incorporates two SuperTrends from different timeframes and utilizes a k-nearest neighbors (KNN) algorithm for trend prediction. It's different from traditional SuperTrend indicators because of its AI-based predictive capabilities and the addition of the ADX filter for trend strength.
BTC 8hr Performance
ETH 8hr Performance
## █ Strategy, How it Works: Detailed Explanation (Revised)
### Multi-Timeframe Approach
The strategy leverages the power of multiple timeframes by incorporating two SuperTrend indicators, each calculated on a different timeframe. This multi-timeframe approach provides a holistic view of the market's trend. For example, a 8-hour timeframe might capture the medium-term trend, while a daily timeframe could capture the longer-term trend. When both SuperTrends align, the strategy confirms a more robust trend.
### K-Nearest Neighbors (KNN)
The KNN algorithm is used to classify the direction of the trend based on historical SuperTrend values. It uses weighted voting of the 'k' nearest data points. For each point, it looks at its 'k' closest neighbors and takes a weighted average of their labels to predict the current label. The KNN algorithm is applied separately to each timeframe's SuperTrend data.
### SuperTrend Indicators
Two SuperTrend indicators are used, each from a different timeframe. They are calculated using different moving averages and ATR lengths as per user settings. The SuperTrend values are then smoothed to make them suitable for KNN-based prediction.
### ADX and DMI Filters
The ADX filter is used to eliminate weak trends. Only when the ADX is above 20 and the directional movement index (DMI) confirms the trend direction, does the strategy signal a buy or sell.
### Combining Elements
A trade signal is generated only when both SuperTrends and the ADX filter confirm the trend direction. This multi-timeframe, multi-indicator approach reduces false positives and increases the robustness of the strategy.
By considering multiple timeframes and using machine learning for trend classification, the strategy aims to provide more accurate and reliable trade signals.
BTC 8hr Performance (Zoom-in)
## █ Trade Direction
The strategy allows users to specify the trade direction as 'Long', 'Short', or 'Both'. This is useful for traders who have a specific market bias. For instance, in a bullish market, one might choose to only take 'Long' trades.
## █ Usage
Parameters: Adjust the number of neighbors, data points, and moving averages according to the asset and market conditions.
Trade Direction: Choose your preferred trading direction based on your market outlook.
ADX Filter: Optionally, enable the ADX filter to avoid trading in a sideways market.
Risk Management: Use the trailing stop-loss feature to manage risks.
## █ Default Settings
Neighbors (K): 3
Data points for KNN: 12
SuperTrend Length: 10 and 5 for the two different SuperTrends
ATR Multiplier: 3.0 for both
ADX Length: 21
ADX Time Frame: 240
Default trading direction: Both
By customizing these settings, traders can tailor the strategy to fit various trading styles and assets.
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different
The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets.
*The KNN part is mainly referred from @Zeiierman.
BTCUSD 8hr performance
ETHUSD 8hr performance
█ Strategy, How It Works: Detailed Explanation
1. SuperTrend Calculation
The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends.
2. KNN Algorithm
The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points.
3. Signal Generation
Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend.
4. Trading Logic
The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions.
Local picture
█ Trade Direction
The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions.
█ Usage
ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process.
Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages.
Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends.
Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically.
█ Default Settings
The default settings are configured to offer a balanced approach suitable for most scenarios:
Initial Capital: $10,000
Default Quantity Type: 10% of equity
Commission: 0.1%
Slippage: 1
Currency: USD
These settings can be modified to suit various trading styles and asset classes.
Broadview Algorithmic StudioWelcome! This is the writeup for the Broadview Algorithmic Studio.
There are many unique features in this script.
- Broadview Underpriced & Overpriced
- Broadview Blackout Bollinger Bands
- Trailing Take Profit Suite
- Algorithmic Weights
- VSA Score
- Pip Change Log
- Activation Panel
- Weight Scanner
There are 116 primary inputs that allow users to algorithmically output unique DCA signal-sets. There are 85 inputs that allow users to control individual lengths, levels, thresholds, and multiplicative weights of the script. You will not find any other script with this many inputs, properly strung together for you to produce unlimited strategies for any market. The entire premise for the Broadview Algorithmic Studio is for users to be able to have extensive-cutting-edge features that allow them to produce more strategies, having control over every element that outputs a signal set. The number of unique strategies you can output with this script is VAST, and each continues to follow a safe DCA methodology.
This script is ready for use with 3Commas, interactive brokers, and other means of automation. It provides detailed information on Base Orders and Safety Orders, giving the number, cumulative spending, position average, and remaining balance for each SO in the series. Using this script we will explore the depths of strategic volume scaling, and the algorithms we use to determine spending.
Let me first start by saying the number of safe DCA-friendly signal-sets this script can output is absolutely staggering.
Let's limit the scope just to the Broadview Underpriced & Overpriced and Broadview Dominance indicators.
Each band of the Dominance Suite can be controlled individually with unique lengths, levels, and weights. This means the Dominance Suite can establish Bearish or Bullish dominance, in any market condition, and give it a unique overloading weight. The Broadview Underpriced & Overpriced indicator finally gives us the ability to establish these "market conditions" first with cycles. Of all the cycles this indicator establishes, the two primary are Underpriced & Overpriced. We determine this using a composite Overbought & Oversold with an Exponential Moving Average. So the script can now know, what cycle it is in, who is dominant during that cycle, and exactly how much weight in volume scaling the order should have.
Brand new is the ability for indicators of this level to be able to talk together in a single script. The Broadview Underpriced & Overpriced indicator and the Broadview Dominance indicator can inform one another across multiple vectors, create a unique market snapshot, and give that snapshot a unique weight every bar. The unique weight is compiled in the volume scaling math, thus giving us an automated-strategic-safe and quite efficient volume scaling for every order. In our coming updates we will explore this synergy to its very deepest layers. These indicators can be laced together in many ways, called vectors.
Only in the Algorithmic Studio do we explore these depths and yield those findings, features, and inputs to the user.
Let me take a quick break to explain another area-of-opportunity for our research and development.
The VSA Score is something we've tried before, but until the creation of the Broadview Blackout Bollinger Bands Auto Indicator it was not possible. The concept we want to explore is "Positional Honing". Over time we want users and the script itself to be able to understand the difference between a script-config that produces a high number of Hits, from a configuration that produces a high number of "Misses". The Volume Scaling Accuracy Score uses the BBB Auto Indicator as a heavily reliable, non-repainting, method of determining what the very-best signals for increased volume-scaling are.
Increased volume scaling is denoted by the near-white highlighter line running vertically. This line will either fall inside the BBB Auto Indicator bands (which are hidden), or, they will fall below and outside the BBB Auto bands. If increased spending happens inside the bands it's a "Miss". If increased spending happens below and outside the bands, it's a Hit. Oftentimes misses are actually pretty good spots for extra spending, which helps lower your position average, but Hits are always better. The Hits that the BBB Auto Indicator provides are extremely good.
Let's talk about the Trailing Take Profit Suite. This suite allows us to set a trailing take profit which is a feature that lets one maximize their profits. If the trailing take profit is engaged, then when the regular take profit is hit, it will trigger, denoted in red vertical lines, and the trailing take profit will look for a specified rate of change before it actually takes profit. This usually helps traders in those times when their regular take profit was set too low, allowing them to maximize their profits with a Trailing Take Profit.
For the moment, let's think about our scores. In the dashboard you'll notice a score beginning the Pip Change Log, the VSA Score, and the Activation Panel.
These scores use a new kind of logistic correlation formula where 4 digits are given to activation, rather than 1. This is to allow room for a future concept in AI we call "Deadzones" or you can think of it as impedance. This is not a bias in logistic regression. It's an entirely different concept. A neuron, which a perceptron attempts to mimic, has a bias.. but it also has a sort of electrical resistance. This is because a neuron is individually-alive entity. So a perceptron, as it were, would need to have both a bias and a natural resistance, or deadzone.
It is a lot of fun to watch the scores and how they react during playback. They tend to smooth trends but are also quite quick to correct to accuracy. In the future we will add the deadzones and biases to the scores. This should help both users and the script produce better signal sets. The Pip Change Log is an indicator that measures Rate of Change in Pips. This is one that I am particularly excited to study, as I am a huge fan of ROC. The Activation Panel shows these scores for 4 primary indicators: On Balance Volume, Relative Strength Index, Average Directional Index, and Average True Range.
Having the Pip Change Log, VSA Score, and Activation Panel up on the dashboard with their logistic correlation scores allows traders to study markets and setups quite intimately. The weight scanner at the bottom allows users to track the cumulative applied multiplicative weights during playback. The massive number of inputs, connected vectors of indicators, input-weights, lengths, levels, and thresholds sets up all the algorithmic infrastructure for powerusers to explore every idea and strategy output they could imagine. Also with the connected vector infrastructure we can deepen our indicators in a way where, "How they talk to each other.", comes first in every development conversation.
The Algorithmic Studio is for the Power-user.
These are not basic equations coming together to determine spending. This is a massive multi-layered-perceptron with everything from Trailing-Take-Profits to strategic-automatic algorithmic downscaling. The Broadview Algorithmic Studio gives a home to the poweruser who wants access to everything in a trading and investing AI, right up until the backpropagation. The Broadview Algorithmic Studio, gives users the ability to sit in the chair of the would-be AI.
Thank you.
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
【SY】AI推送7.0//@version=6
strategy("【SY】AI推送7.0", overlay=true)
// === Supertrend ===
= ta.supertrend(3.1, 15)
// === 均线组 ===
ema1 = ta.ema(close, 20)
ema5 = ta.ema(close, 34)
ema10 = ta.ema(close, 55)
ma15 = ta.sma(close, 15)
ma80 = ta.sma(close, 80)
// === MACD 多周期 ===
macdCycle = input.string("中周期", title="信号周期", options= )
fastLength = macdCycle == "大周期" ? 24 : macdCycle == "小周期" ? 6 : 12
slowLength = macdCycle == "大周期" ? 52 : macdCycle == "小周期" ? 13 : 26
signalSmoothing = macdCycle == "大周期" ? 18 : macdCycle == "小周期" ? 5 : 9
= ta.macd(close, fastLength, slowLength, signalSmoothing)
macd_dead_cross = ta.crossunder(macdLine, signalLine)
macd_golden_cross = ta.crossover(macdLine, signalLine)
// === 参数设置 ===
alert_keyword = input.string(defval = "监控警告提示", title = "钉钉推送关键词", options = )
// === 趋势与信号 ===
golden_cross = ta.crossover(close, ema10)
dead_cross = ta.crossunder(close, ema10)
duo = close > ema10
kong = close < ema10
condition_1 = close > ma80
is_up_trend = direction < 0
is_down_trend = direction > 0
// === 柱颜色 ===
var color kColor = color.navy
if is_up_trend and duo and condition_1
kColor := color.new(#00ff00, 10)
else if is_up_trend and duo
kColor := color.new(#b8ebba, 13)
else if is_down_trend and kong and not condition_1
kColor := color.new(#ff0000, 10)
else if is_down_trend and kong
kColor := color.new(#e8a3a3, 13)
barcolor(kColor)
// === 趋势填充 ===
up_line = plot(is_up_trend ? supertrend : na, title="Up direction", color=color.green, style=plot.style_linebr)
down_line = plot(is_down_trend ? supertrend : na, title="Down direction", color=color.red, style=plot.style_linebr)
close_line = plot(close, display=display.none)
fill(up_line, close_line, color=color.new(color.green, 67))
fill(down_line, close_line, color=color.new(color.red, 67))
plot(ma80, title="趋势线", color=condition_1 ? color.new(#1cef5b, 0) : color.new(#ed0b0b, 0), linewidth=5)
plot(ma15, title="干扰信号", color=color.yellow, linewidth=2)
// === 信号判定 ===
is_green_bar = kColor == color.new(#00ff00, 10) or kColor == color.new(#64f568, 13)
is_red_bar = kColor == color.new(#ff0000, 10) or kColor == color.new(#e45454, 13)
is_yellow_ma = condition_1
is_blue_ma = not condition_1
long_signal_raw = is_green_bar and is_yellow_ma and is_up_trend
short_signal_raw = is_red_bar and is_blue_ma and is_down_trend
var string last_signal = "none"
show_long_signal = long_signal_raw and last_signal != "long"
show_short_signal = short_signal_raw and last_signal != "short"
plotshape(show_long_signal, location=location.belowbar, color=color.green, style=shape.labelup, text="多", textcolor=color.white)
plotshape(show_short_signal, location=location.abovebar, color=color.red, style=shape.labeldown, text="空", textcolor=color.white)
// === 策略执行 ===
var float sl_long = na
var float sl_short = na
style = input.string("标准型", title="风格", options= )
float tp1_rate = na
float tp2_rate = na
float tp3_rate = na
if style == "保守型"
tp1_rate := 0.005
tp2_rate := 0.01
tp3_rate := 0.02
else if style == "激进型"
tp1_rate := 0.015
tp2_rate := 0.03
tp3_rate := 0.06
else
tp1_rate := 0.01
tp2_rate := 0.02
tp3_rate := 0.04
long_in_position = strategy.position_size > 0
short_in_position = strategy.position_size < 0
if show_long_signal
strategy.close("Short")
strategy.entry("Long", strategy.long)
last_signal := "long"
sl_long := supertrend
strategy.exit("固定止损多", from_entry="Long", stop=sl_long)
if show_short_signal
strategy.close("Long")
strategy.entry("Short", strategy.short)
last_signal := "short"
sl_short := supertrend
strategy.exit("固定止损空", from_entry="Short", stop=sl_short)
long_entry = strategy.position_avg_price
short_entry = strategy.position_avg_price
tp1_long = long_entry * (1 + tp1_rate)
tp2_long = long_entry * (1 + tp2_rate)
tp3_long = long_entry * (1 + tp3_rate)
tp1_short = short_entry * (1 - tp1_rate)
tp2_short = short_entry * (1 - tp2_rate)
tp3_short = short_entry * (1 - tp3_rate)
var float tp1_plot = na
var float tp2_plot = na
var float tp3_plot = na
if long_in_position
tp1_plot := tp1_long
tp2_plot := tp2_long
tp3_plot := tp3_long
else if short_in_position
tp1_plot := tp1_short
tp2_plot := tp2_short
tp3_plot := tp3_short
else
tp1_plot := na
tp2_plot := na
tp3_plot := na
plot(tp1_plot, title="止盈线1", color=long_in_position ? color.green : short_in_position ? color.red : na, linewidth=1, style=plot.style_linebr)
plot(tp2_plot, title="止盈线2", color=long_in_position ? color.green : short_in_position ? color.red : na, linewidth=1, style=plot.style_linebr)
plot(tp3_plot, title="止盈线3", color=long_in_position ? color.green : short_in_position ? color.red : na, linewidth=1, style=plot.style_linebr)
plot(long_in_position ? sl_long : na, title="多单止损", color=color.new(color.fuchsia, 0), style=plot.style_linebr)
plot(short_in_position ? sl_short : na, title="空单止损", color=color.new(color.fuchsia, 0), style=plot.style_linebr)
var label tp1_label = na
var label tp2_label = na
var label tp3_label = na
var label sl_label = na
if not na(tp1_label)
label.delete(tp1_label)
if not na(tp2_label)
label.delete(tp2_label)
if not na(tp3_label)
label.delete(tp3_label)
if not na(sl_label)
label.delete(sl_label)
if not na(tp1_plot)
tp1_label := label.new(bar_index, tp1_plot, text="止盈1", style=label.style_label_left, color=color.new(color.green, 0), textcolor=color.white, size=size.small)
if not na(tp2_plot)
tp2_label := label.new(bar_index, tp2_plot, text="止盈2", style=label.style_label_left, color=color.new(color.green, 0), textcolor=color.white, size=size.small)
if not na(tp3_plot)
tp3_label := label.new(bar_index, tp3_plot, text="止盈3", style=label.style_label_left, color=color.new(color.green, 0), textcolor=color.white, size=size.small)
if long_in_position and not na(sl_long)
sl_label := label.new(bar_index, sl_long, text="止损", style=label.style_label_left, color=color.fuchsia, textcolor=color.white, size=size.small)
else if short_in_position and not na(sl_short)
sl_label := label.new(bar_index, sl_short, text="止损", style=label.style_label_left, color=color.fuchsia, textcolor=color.white, size=size.small)
// === 修正后的预警价逻辑 ===
tp_long_str = str.tostring(tp1_long, format.mintick) + "-" + str.tostring(tp2_long, format.mintick) + "-" + str.tostring(tp3_long, format.mintick)
tp_short_str = str.tostring(tp1_short, format.mintick) + "-" + str.tostring(tp2_short, format.mintick) + "-" + str.tostring(tp3_short, format.mintick)
if show_long_signal
long_entry_price = close
long_dist = long_entry_price - sl_long
pre_alert_price = long_entry_price - long_dist * 0.8
alert_str_long = "{\"text\":{\"策略类型\":\"" + alert_keyword + "\",\"监控币种\":\"" + syminfo.ticker + "\",\"方向\":\"开多\",\"预警价格\":\"" + str.tostring(long_entry_price, format.mintick) + " - " + str.tostring(pre_alert_price, format.mintick) + "\",\"监控止盈\":\"" + tp_long_str + "\",\"监控止损\":\"" + str.tostring(sl_long, format.mintick) + "\",\"监控时间\":\"" + str.tostring(timenow, "yyyy-MM-dd HH:mm") + "\",\"附注\":\"交易点位仅为技术交流学习，欢迎大家交流讨论！任何市场都有交易风险，希望大家努力工作，热爱生活，提升自己的能力永远都是第一位的！\"}}"
alert(alert_str_long, alert.freq_once_per_bar)
if show_short_signal
short_entry_price = close
short_dist = short_entry_price - sl_short
pre_alert_price = short_entry_price - short_dist * 0.8
alert_str_short = "{\"text\":{\"策略类型\":\"" + alert_keyword + "\",\"监控币种\":\"" + syminfo.ticker + "\",\"方向\":\"开空\",\"预警价格\":\"" + str.tostring(short_entry_price, format.mintick) + " - " + str.tostring(pre_alert_price, format.mintick) + "\",\"监控止盈\":\"" + tp_short_str + "\",\"监控止损\":\"" + str.tostring(sl_short, format.mintick) + "\",\"监控时间\":\"" + str.tostring(timenow, "yyyy-MM-dd HH:mm") + "\",\"附注\":\"交易点位仅为技术交流学习，欢迎大家交流讨论！任何市场都有交易风险，希望大家努力工作，热爱生活，提升自己的能力永远都是第一位的！\"}}"
alert(alert_str_short, alert.freq_once_per_bar)
Divergence + OBV + Supertrend + OBV Prediction [AI Sim]HOW THIS "AI" PREDICTION WORKS:
Component Logic
obvSlope > 0 OBV is rising
obv < obvMA OBV is still below MA
obvSlope > obvMASlope OBV rising faster than the MA
obvMA - obv < threshold OBV is close enough to cross above MA soon
The reverse applies to bearish prediction.
SuperTrend AI (Clustering) with Full Trade Logic//@version=5
indicator("SuperTrend AI (Clustering) with Full Trade Logic", overlay = true, max_labels_count = 500)
// === INPUTS ===
length = input(10, 'ATR Length')
factor = input.float(3.0, 'SuperTrend Factor')
perfAlpha = input.float(10, 'Performance Memory')
showLabels = input.bool(true, 'Show Entry Labels')
cooldownBars = input.int(5, 'Cooldown Between Entries')
// === TREND FILTER (15M) ===
ema9_15 = request.security(syminfo.tickerid, "15", ta.ema(close, 9))
ema21_15 = request.security(syminfo.tickerid, "15", ta.ema(close, 21))
trend15m = ema9_15 > ema21_15 and ema21_15 > ema21_15 and ema9_15 > ema9_15 ? 1 : 0
// === SUPER TREND LOGIC ===
atr = ta.atr(length)
upperBand = hl2 + atr * factor
lowerBand = hl2 - atr * factor
trend = 0
trend := close > lowerBand ? 1 : close < upperBand ? 0 : nz(trend )
supertrend = trend == 1 ? lowerBand : upperBand
// === EMA TREND CONFIRMATION ===
ema9 = ta.ema(close, 9)
ema21 = ta.ema(close, 21)
emaConfirm = ema9 > ema21
// === RSI CONFIRMATION ===
rsi = ta.rsi(close, 14)
rsiConfirm = rsi < 30 or rsi > 70
// === MACD CONFIRMATION ===
= ta.macd(close, 12, 26, 9)
macdConfirm = (ta.crossover(macdLine, signalLine) or ta.crossunder(macdLine, signalLine)) and math.abs(macdLine - signalLine) > 0.0005
// === BOLLINGER BAND CONFIRMATION ===
basis = ta.sma(close, 20)
dev = 2 * ta.stdev(close, 20)
bbUpper = basis + dev
bbLower = basis - dev
bbConfirm = close > bbUpper or close < bbLower
// === VOLUME CONFIRMATION ===
avgVol = ta.sma(volume, 20)
volConfirm = volume > 1.5 * avgVol
// === CONFIRMATION COUNT ===
confirmations = (emaConfirm ? 1 : 0) + (rsiConfirm ? 1 : 0) + (macdConfirm ? 1 : 0) + (bbConfirm ? 1 : 0) + (volConfirm ? 1 : 0)
validSetup = confirmations >= 3
// === RISK FILTERS ===
price = close
pips = syminfo.mintick * 10000
recentSpike = math.abs(close - open) > 10 * pips
nearPsych = math.abs(price % 0.5) < 0.02
// Time Filter
sessionHour = hour(time, "America/New_York")
sessionFilter = (sessionHour < 10 or sessionHour > 3)
// Candle Quality Filter
minCandleSize = math.abs(close - open) > 0.0003
// Cooldown Between Entries
var int lastEntryBar = na
cooldown = na(lastEntryBar) or (bar_index - lastEntryBar > cooldownBars)
// ADX Trend Strength Filter
plusDM = ta.change(high) > ta.change(low) and ta.change(high) > 0 ? ta.change(high) : 0
minusDM = ta.change(low) > ta.change(high) and ta.change(low) > 0 ? ta.change(low) : 0
trur = ta.rma(ta.tr(true), 14)
plusDI = 100 * ta.rma(plusDM, 14) / trur
minusDI = 100 * ta.rma(minusDM, 14) / trur
dx = 100 * math.abs(plusDI - minusDI) / (plusDI + minusDI)
adx = ta.rma(dx, 14)
strongTrend = adx > 20
// Pullback to EMA21 Filter
pullbackToEMA21 = close < ema21
// === SESSION TRADE LIMIT ===
var int sessionTradeCount = 0
isNewSession = ta.change(time("D")) != 0
if isNewSession
sessionTradeCount := 0
canTradeThisSession = sessionTradeCount < 2
// Entry Conditions
inTrendLong = trend == 1 and trend15m == 1
inTrendShort = trend == 0 and trend15m == 0
entryLong = inTrendLong and validSetup and not recentSpike and not nearPsych and sessionFilter and minCandleSize and cooldown and strongTrend and pullbackToEMA21 and canTradeThisSession
entryShort = inTrendShort and validSetup and not recentSpike and not nearPsych and sessionFilter and minCandleSize and cooldown and strongTrend and pullbackToEMA21 and canTradeThisSession
if entryLong or entryShort
lastEntryBar := bar_index
sessionTradeCount += 1
// === TRADE OUTPUT ===
TP = 30 * pips
SL = 15 * pips
// Labels
if showLabels
if entryLong
label.new(bar_index, low, "✅ Long Setup\nEntry: " + str.tostring(price, '#.###') +
"\nTP: " + str.tostring(price + TP, '#.###') +
"\nSL: " + str.tostring(price - SL, '#.###'),
style=label.style_label_up, color=color.green, textcolor=color.white)
if entryShort
label.new(bar_index, high, "✅ Short Setup\nEntry: " + str.tostring(price, '#.###') +
"\nTP: " + str.tostring(price - TP, '#.###') +
"\nSL: " + str.tostring(price + SL, '#.###'),
style=label.style_label_down, color=color.red, textcolor=color.white)
// === ALERT CONDITIONS ===
alertcondition(entryLong, title="Valid Long Setup", message="✅ USDJPY Long Setup | Entry: {{close}} | TP: {{close + 0.0030}} | SL: {{close - 0.0015}}")
alertcondition(entryShort, title="Valid Short Setup", message="✅ USDJPY Short Setup | Entry: {{close}} | TP: {{close - 0.0030}} | SL: {{close + 0.0015}}")
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.
