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KP Support ResistneComprehensive Disclaimer and User Responsibility Statement for Indicators and Algorithmic Trading Tools We are an independent indicator and algorithm (algo) development service provider, engaged solely in the technical development of trading tools based on specific requirements received from users. Our role is strictly limited to designing, coding, and delivering custom-built indicators, scripts, scanners, or algorithmic tools as per user-defined inputs. We do not act as financial advisors, investment advisors, portfolio managers, or trading mentors in any capacity. It is extremely important for every user to clearly understand the scope, limitations, responsibilities, and risks associated with the use of any indicator, algorithm, or trading-related tool developed or shared by us. 1. No Investment Advice or Recommendations We do not recommend, suggest, endorse, or advise the use of any indicator, strategy, or algorithm developed by us for live trading purposes. Any tool created by us is purely technical in nature and must not be interpreted as financial, investment, or trading advice. We strongly advise all users to consult a SEBI-registered investment advisor (RIA) or a SEBI-registered research analyst (RA) before making any trading or investment decisions. Our services do not replace professional financial guidance. 2. Tools Are Developed Based on User Requirements Only All indicators and algorithms are developed strictly based on requirements received from users, which may include: Specific entry or exit logic Custom conditions Indicator combinations Risk management formulas Automation logic Visual plotting requirements These requirements are subjective and vary from user to user. A tool developed for one user is tailored to their personal assumptions, preferences, and expectations. As such, the same tool may not be suitable or effective for another user. We do not evaluate whether a particular logic is profitable, safe, or appropriate for any individual. 3. No Guarantee of Profit or Performance There is no guarantee of profit, accuracy, consistency, or success when using any indicator or algorithm developed by us. Financial markets are uncertain, volatile, and influenced by numerous unpredictable factors including but not limited to: Market sentiment Economic events News and announcements Liquidity conditions Broker execution quality Slippage and latency Past performance of any indicator or algorithm does not guarantee future results. Any perceived success in backtesting or paper trading does not ensure similar results in live market conditions. 4. Trading Involves High Risk Trading and investing in financial markets involves substantial risk, including the potential loss of partial or entire capital. Users must clearly understand that: Losses can exceed expectations Capital erosion can occur rapidly Emotional and psychological stress is common Overtrading and mismanagement can amplify losses Users are solely responsible for assessing whether trading aligns with their financial situation, risk tolerance, and personal circumstances. 5. Differences in Capital Size and Risk Capacity Every trader has a different capital size, which significantly impacts trading outcomes. A strategy that may appear effective for a large capital account may fail for a smaller account due to: Margin requirements Lot size constraints Brokerage costs Risk exposure Similarly, risk-reward capacity differs for each individual. Some users can tolerate drawdowns, while others cannot. A one-size-fits-all approach does not exist in trading. 6. Psychological and Mental Health Factors Trading is not only a technical activity but also a psychological challenge. Factors such as: Emotional discipline Fear and greed Stress management Mental health Decision-making under pressure play a critical role in trading outcomes. We do not assess or account for a user’s psychological readiness or mental health condition. Any tool shared by us may not align with a user’s emotional or mental capacity to handle market fluctuations. 7. Trading Profile and Experience Level Each user has a unique trading profile, which may include: Beginner, intermediate, or advanced experience Intraday, swing, positional, or long-term trading Manual or automated execution Asset preference (equity, options, futures, commodities, forex) A tool developed for a specific trading profile may not work effectively for another profile. Users are fully responsible for determining whether a tool suits their experience level and trading style. 8. No Responsibility for Profit, Loss, or Damages We shall not be held responsible or liable for any of the following: Financial losses or missed profits Incorrect signals or logic behavior Broker-related issues API failures or platform downtime Market gaps or extreme volatility Emotional distress or decision errors The use of any indicator or algorithm is entirely at the user’s own risk. 9. Testing and Validation Are User’s Responsibility Before using any tool in a live trading environment, users must: Conduct proper backtesting Perform forward testing or paper trading Validate results under multiple market conditions Understand all logic and limitations We do not guarantee that a tool has been tested across all scenarios unless explicitly agreed upon in writing. 10. No SEBI Registration or Advisory Role We are not registered with SEBI as an investment advisor, research analyst, or portfolio manager. Our services are limited to technical development only. Any interpretation of our work as advisory services is incorrect and unauthorized. 11. Market Conditions Can Change Market behavior is dynamic. A logic that works in one market phase (trending, sideways, volatile) may completely fail in another. Indicators and algorithms are not adaptive unless specifically designed to be so. Users must continuously monitor and evaluate performance. 12. Automation Does Not Eliminate Risk Automated trading or algorithmic execution does not eliminate risk. In fact, automation can increase risk if: Logic errors exist Market conditions change abruptly Execution happens faster than human intervention Users must supervise automated systems at all times. 13. Acceptance of Terms By using, accessing, or implementing any indicator or algorithm developed or shared by us, the user explicitly agrees that: They understand all risks involved They take full responsibility for all outcomes They will not hold us liable for any loss or damage They will seek advice from a SEBI-registered advisor when needed 14. Final Statement We provide tools, not advice. We develop code, not confidence. We share technology, not guarantees. Trading success depends on multiple personal and external factors including capital, psychology, discipline, experience, and market conditions. Since these factors differ from person to person, the same indicator or algorithm will not work for everyone. Users must make informed decisions responsibly and ethically.
Pine Script® indicator
by SRHSTOCKS
KP OPTION ROCKComprehensive Disclaimer and User Responsibility Statement for Indicators and Algorithmic Trading Tools We are an independent indicator and algorithm (algo) development service provider, engaged solely in the technical development of trading tools based on specific requirements received from users. Our role is strictly limited to designing, coding, and delivering custom-built indicators, scripts, scanners, or algorithmic tools as per user-defined inputs. We do not act as financial advisors, investment advisors, portfolio managers, or trading mentors in any capacity. It is extremely important for every user to clearly understand the scope, limitations, responsibilities, and risks associated with the use of any indicator, algorithm, or trading-related tool developed or shared by us. 1. No Investment Advice or Recommendations We do not recommend, suggest, endorse, or advise the use of any indicator, strategy, or algorithm developed by us for live trading purposes. Any tool created by us is purely technical in nature and must not be interpreted as financial, investment, or trading advice. We strongly advise all users to consult a SEBI-registered investment advisor (RIA) or a SEBI-registered research analyst (RA) before making any trading or investment decisions. Our services do not replace professional financial guidance. 2. Tools Are Developed Based on User Requirements Only All indicators and algorithms are developed strictly based on requirements received from users, which may include: Specific entry or exit logic Custom conditions Indicator combinations Risk management formulas Automation logic Visual plotting requirements These requirements are subjective and vary from user to user. A tool developed for one user is tailored to their personal assumptions, preferences, and expectations. As such, the same tool may not be suitable or effective for another user. We do not evaluate whether a particular logic is profitable, safe, or appropriate for any individual. 3. No Guarantee of Profit or Performance There is no guarantee of profit, accuracy, consistency, or success when using any indicator or algorithm developed by us. Financial markets are uncertain, volatile, and influenced by numerous unpredictable factors including but not limited to: Market sentiment Economic events News and announcements Liquidity conditions Broker execution quality Slippage and latency Past performance of any indicator or algorithm does not guarantee future results. Any perceived success in backtesting or paper trading does not ensure similar results in live market conditions. 4. Trading Involves High Risk Trading and investing in financial markets involves substantial risk, including the potential loss of partial or entire capital. Users must clearly understand that: Losses can exceed expectations Capital erosion can occur rapidly Emotional and psychological stress is common Overtrading and mismanagement can amplify losses Users are solely responsible for assessing whether trading aligns with their financial situation, risk tolerance, and personal circumstances. 5. Differences in Capital Size and Risk Capacity Every trader has a different capital size, which significantly impacts trading outcomes. A strategy that may appear effective for a large capital account may fail for a smaller account due to: Margin requirements Lot size constraints Brokerage costs Risk exposure Similarly, risk-reward capacity differs for each individual. Some users can tolerate drawdowns, while others cannot. A one-size-fits-all approach does not exist in trading. 6. Psychological and Mental Health Factors Trading is not only a technical activity but also a psychological challenge. Factors such as: Emotional discipline Fear and greed Stress management Mental health Decision-making under pressure play a critical role in trading outcomes. We do not assess or account for a user’s psychological readiness or mental health condition. Any tool shared by us may not align with a user’s emotional or mental capacity to handle market fluctuations. 7. Trading Profile and Experience Level Each user has a unique trading profile, which may include: Beginner, intermediate, or advanced experience Intraday, swing, positional, or long-term trading Manual or automated execution Asset preference (equity, options, futures, commodities, forex) A tool developed for a specific trading profile may not work effectively for another profile. Users are fully responsible for determining whether a tool suits their experience level and trading style. 8. No Responsibility for Profit, Loss, or Damages We shall not be held responsible or liable for any of the following: Financial losses or missed profits Incorrect signals or logic behavior Broker-related issues API failures or platform downtime Market gaps or extreme volatility Emotional distress or decision errors The use of any indicator or algorithm is entirely at the user’s own risk. 9. Testing and Validation Are User’s Responsibility Before using any tool in a live trading environment, users must: Conduct proper backtesting Perform forward testing or paper trading Validate results under multiple market conditions Understand all logic and limitations We do not guarantee that a tool has been tested across all scenarios unless explicitly agreed upon in writing. 10. No SEBI Registration or Advisory Role We are not registered with SEBI as an investment advisor, research analyst, or portfolio manager. Our services are limited to technical development only. Any interpretation of our work as advisory services is incorrect and unauthorized. 11. Market Conditions Can Change Market behavior is dynamic. A logic that works in one market phase (trending, sideways, volatile) may completely fail in another. Indicators and algorithms are not adaptive unless specifically designed to be so. Users must continuously monitor and evaluate performance. 12. Automation Does Not Eliminate Risk Automated trading or algorithmic execution does not eliminate risk. In fact, automation can increase risk if: Logic errors exist Market conditions change abruptly Execution happens faster than human intervention Users must supervise automated systems at all times. 13. Acceptance of Terms By using, accessing, or implementing any indicator or algorithm developed or shared by us, the user explicitly agrees that: They understand all risks involved They take full responsibility for all outcomes They will not hold us liable for any loss or damage They will seek advice from a SEBI-registered advisor when needed 14. Final Statement We provide tools, not advice. We develop code, not confidence. We share technology, not guarantees. Trading success depends on multiple personal and external factors including capital, psychology, discipline, experience, and market conditions. Since these factors differ from person to person, the same indicator or algorithm will not work for everyone. Users must make informed decisions responsibly and ethically.
Pine Script® indicator
by SRHSTOCKS
Portfolio TrackerDescription The Portfolio Tracker is a utility dashboard designed for traders who need to monitor the performance of a multi-asset portfolio directly from a single chart layout. While TradingView provides excellent charting for individual symbols, tracking the combined Profit & Loss (PnL) of a basket of 20 different securities (stocks, crypto, forex, or indices) usually requires switching tabs, using external spreadsheets, or logging into multiple exchange accounts. This script solves that problem by allowing users to manually input their position details into a customizable table. It fetches real-time price data for each symbol and calculates the individual and total portfolio performance, including commission costs. Why This Tool is Useful This indicator was built to address specific pain points for active traders: Consolidated View: Instead of checking 20 different charts to see how your positions are doing, you get a single, real-time snapshot of your entire portfolio's health on one screen. Risk Management: By seeing the "Total PnL" and "Total Investment" in one place, traders can better understand their overall market exposure, rather than focusing on single winning or losing trades. Flexible Accounting: The ability to switch between "Unit Price" and "Total Cost" inputs accommodates different trading styles—whether you are a scalper entering a single price or an investor averaging down with a specific total capital allocation. CRITICAL: Input Logic & Warnings To ensure accurate PnL calculations, users must understand the relationship between Quantity and Cost, especially when using "Total Cost (Manual)" mode. The Golden Rule: Your Input Cost must always match the Total Quantity entered. Example Scenario: Imagine you buy 2 BTC at a price of $90,000 each. Correct Entry: You must enter Quantity: 2 and Cost: 180000 ($90k x 2). Result: If BTC drops to $85k, your Portfolio Value is $170k. The script correctly shows a PnL of -$10,000. Result: If BTC rises to $95k, your Portfolio Value is $190k. The script correctly shows a PnL of +$10,000. Incorrect Entry: If you enter Quantity: 2 but leave Cost at 90000 (the unit price). Result: The script thinks you bought 2 BTC for a total of only $90k. It will instantly show a massive, incorrect profit because the math implies you bought 2 coins for the price of 1. Please double-check your inputs. The script includes a "Sanity Check" feature to help catch these errors, but accurate data entry is the user's responsibility. Key Features & Benefits Multi-Asset Tracking (20 Slots): Monitor up to 20 different tickers simultaneously. Real-Time Valuation: Uses request.security() to fetch the current market price for every symbol in the list. Your PnL updates with every tick of the market. Flexible Cost Basis Modes: Auto-Calc Mode: Enter Entry Price and Quantity. (Best for simple, single-entry trades). Manual Cost Mode: Enter Total Invested Amount. (Best for averaged-down positions). Advanced Commission Handling: Supports both Global and Individual commission rates. This provides a realistic "Net PnL" by factoring in fees on both the entry (cost basis) and the theoretical exit (current value). Input Safety ("Sanity Check"): A logic check that compares the user's input against the current market value. If a user switches to "Total Cost" mode but leaves a small "Unit Price" value in the input field, the script flags the row to prevent irrational PnL percentages (e.g., >100,000%). Clean & Customizable UI: The table can be positioned in 9 different locations, and inputs are hidden from the chart status line to keep the visual workspace clean. How It Works The script operates using a systematic loop that processes user inputs through a series of mathematical validations: Data Acquisition: The script collects all 20 user inputs and utilizes request.security() to fetch the real-time close price for every non-empty symbol in the list. Cost Basis Calculation: In Auto-Calc Mode: The script calculates Raw Cost = Quantity * Input Price. In Manual Mode: The script takes the Input Value directly as the Raw Cost. "Round-Trip" Commission Modeling: Entry Cost: Raw Cost * (1 + Commission%) (Fees increase your breakeven). Exit Value: (Quantity * Current Price) * (1 - Commission%) (Fees reduce your payout). Net PnL: Exit Value - Entry Cost. Sanity Check Algorithm: Before displaying data, the script compares the Input Cost against the Gross Market Value (Qty * Price). If the Input Cost is less than a user-defined threshold (default 1%) of the Market Value, it triggers a warning, assuming the user forgot to update the field to a "Total Cost" figure. Disclaimer This script is for informational and educational purposes only. It is a tool to assist in tracking hypothetical or real positions based on manual user inputs and standard TradingView data feeds. It should not be relied upon as a primary accounting ledger or tax reporting tool. Past performance is not indicative of future results. Trading involves risk. Always verify your PnL against your actual exchange or broker statements.
Pine Script® indicator
by abgthecoder
1
Z-Score Momentum Dashboard Z-Score Momentum Dashboard: A Comprehensive Technical Analysis Framework Understanding the Z-Score Momentum Dashboard The Z-Score Momentum Dashboard represents a sophisticated evolution in technical analysis indicators, designed to synthesize multiple analytical frameworks into a singular, coherent probabilistic assessment of market conditions. At its core, this indicator is a multi-dimensional analytical engine that processes price action, volume dynamics, cyclical patterns, and statistical anomalies to generate standardized z-scores that measure how far current market behavior deviates from established norms. Unlike traditional single-metric indicators that examine price through one lens, this dashboard constructs a comprehensive probabilistic model by weighting and combining six distinct analytical domains: Ehlers bandpass filtering for cycle detection, momentum calculations across multiple timeframes, mean reversion tendencies, trend strength measurements, volatility regime analysis, and volume confirmation signals. The indicator operates by first calculating individual scores across each of these six domains, normalizing them into comparable z-score formats, then applying user-configurable weights to create a composite probability score that estimates the likelihood of upward price movement. This probability undergoes statistical transformation through hyperbolic tangent functions to ensure bounded outputs between zero and one, which are then compared against historical baselines to generate the final z-score reading. The z-score itself becomes the primary signal, indicating not just direction but the statistical significance of the current market state relative to recent history. When the z-score exceeds predefined thresholds, it suggests the market has entered a regime that statistically differs from the baseline, implying either strong momentum continuation or potential exhaustion depending on accompanying contextual indicators. The dashboard visualization provides traders with immediate access to critical information through a comprehensive table display that shows historical z-scores over the past five days, current probability assessments, trend classification, momentum measurements, acceleration metrics, and distance from moving averages. This multi-temporal perspective allows traders to observe not just the current state but the trajectory of change, identifying whether momentum is building, plateauing, or reversing. The indicator also generates regime classifications such as "PARABOLIC EXT," "OVERSOLD," "STRONG MOM," and "NEUTRAL," which combine z-score readings with price extension metrics to characterize the current market environment. These classifications directly inform suggested actions, ranging from "Ride trend w/ stops" during strong momentum periods to "Watch for reversal" during oversold conditions with increasing momentum, providing traders with contextually appropriate strategic guidance. The Special Nature of This Analytical Approach What distinguishes the Z-Score Momentum Dashboard from conventional technical indicators is its fundamental philosophical approach to market analysis, which embraces probabilistic thinking rather than deterministic prediction. Most traditional indicators generate binary signals or directional recommendations based on threshold crossovers or pattern recognition, implicitly suggesting certainty about future price movement. This dashboard, in contrast, explicitly models uncertainty by generating probability distributions and measuring statistical significance, acknowledging that markets are stochastic systems where edge comes from systematic bias rather than predictive certainty. By converting diverse technical signals into standardized z-scores, the indicator creates a common language for comparing fundamentally different types of market information, whether that information comes from price momentum, volume patterns, or cyclical oscillations. The pseudo-machine learning architecture embedded within the indicator represents another distinctive feature that elevates it beyond standard technical analysis tools. While Pine Script limitations prevent the implementation of actual neural networks or gradient-boosted decision trees, the indicator approximates ensemble learning principles by treating each analytical domain as a separate "model" whose outputs are weighted and combined. Users can adjust these weights based on their market beliefs or through backtesting optimization, effectively training the indicator to emphasize whichever analytical dimensions prove most predictive in their specific trading context. This flexibility means the same indicator can be configured for mean-reversion trading in range-bound markets by increasing mean reversion weights, or for momentum trading in trending markets by emphasizing trend and momentum components, making it adaptable across varying market regimes without requiring entirely different analytical tools. The integration of John Ehlers' digital signal processing concepts, particularly the bandpass filtering and super smoother functions, introduces engineering-grade analytical precision to financial market analysis. Ehlers' work translates aerospace and telecommunications signal processing mathematics into trading applications, allowing the indicator to isolate specific cyclical frequencies within price action while filtering out noise. This is fundamentally different from simple moving averages or oscillators that indiscriminately smooth price data; bandpass filters can extract the 10-day cycle component separately from the 20-day cycle component, identifying when multiple cycles align or diverge. The inclusion of these sophisticated filters alongside more conventional tools creates a hybrid analytical framework that combines the mathematical rigor of quantitative finance with the practical market wisdom embedded in traditional technical analysis. The dashboard's temporal analysis capabilities provide another layer of analytical depth rarely found in standalone indicators. By displaying five days of historical z-scores alongside current readings, the interface enables pattern recognition at the signal level rather than just the price level. Traders can observe whether z-scores are trending, oscillating, or demonstrating divergent behavior relative to price action. For instance, if price continues making new highs while z-scores decline, this suggests deteriorating statistical support for the advance despite superficial price strength, providing early warning of potential reversals. Similarly, rising z-scores during price consolidation indicate building statistical pressure that may soon manifest as directional movement. This meta-analytical capability transforms the indicator from a simple signal generator into a comprehensive framework for understanding the statistical character of market behavior. Algorithmic Superiority and Technical Advantages The algorithmic architecture of the Z-Score Momentum Dashboard demonstrates several technical advantages that contribute to its analytical power and practical utility. The normalization of disparate technical indicators into standardized z-scores solves a fundamental problem in multi-factor analysis: how to combine indicators with different scales and units into a coherent composite signal. A momentum reading measured in price points cannot be directly compared to an RSI reading measured on a 0-100 scale, nor to a volume ratio measured as a multiplier. By converting each measure into a z-score representing standard deviations from its respective mean, the indicator creates dimensional consistency, ensuring that each component contributes proportionally to the final composite score based on its statistical deviation rather than its nominal value. The use of adaptive baselines through rolling statistical windows provides robustness against regime changes and non-stationary market behavior. Rather than comparing current readings against fixed historical values or statically defined overbought/oversold levels, the indicator continuously recalculates mean and standard deviation estimates over the user-defined baseline period. This approach automatically adjusts to changing volatility regimes, market cycles, and structural shifts in price behavior. During high-volatility periods, the standard deviation increases, requiring larger absolute deviations to generate extreme z-scores, appropriately raising the bar for signal generation. Conversely, during low-volatility periods, smaller absolute movements can generate significant z-scores, maintaining signal sensitivity across diverse market conditions. The composite probability calculation employs mathematically sound transformation functions rather than arbitrary scaling. After weighting and combining individual z-scores into a composite score, the indicator applies hyperbolic tangent transformation to convert the unbounded composite score into a bounded probability estimate between zero and one. The tanh function was chosen specifically because its sigmoid-shaped curve smoothly compresses extreme values while maintaining sensitivity around the center, preventing outlier distortion while preserving information about moderate deviations. This is superior to linear scaling or simple threshold clamping, which can create artificial discontinuities or lose information about the magnitude of extreme readings. The subsequent z-score calculation on this probability distribution creates a second-order statistical metric that measures not just "is probability high?" but "is probability statistically significantly higher than typical?" This layered statistical approach provides more nuanced information than single-stage calculations. The incorporation of acceleration metrics alongside momentum measurements adds a crucial dimension to the analytical framework. While momentum measures the first derivative of the z-score (rate of change), acceleration measures the second derivative (rate of change of the rate of change), identifying inflection points where momentum itself shifts. Markets often reverse not when momentum reaches zero but when acceleration reverses, as this indicates the rate of momentum decay is accelerating even while momentum remains positive. By explicitly calculating and displaying acceleration, the indicator provides early warning of potential trend exhaustion before momentum fully dissipates. This mathematical sophistication mirrors concepts from physics and calculus, applying them to financial market dynamics in ways that enhance predictive capability. The multi-timeframe momentum analysis embedded within the indicator examines price changes over five, ten, and twenty periods, capturing different temporal scales of market behavior. Short-term momentum captures immediate price action and trading range dynamics, while longer-term momentum reflects sustained directional bias and major trend development. By combining these timeframes into a weighted average before calculating z-scores, the indicator synthesizes information across temporal scales, avoiding the myopia of single-timeframe analysis. This approach recognizes that market structure exists simultaneously at multiple frequencies, and robust signals often emerge when momentum aligns across timeframes, while divergences between timeframes can signal pending reversals or consolidations. Predictive Power Through Cyclical Analysis The integration of cyclical analysis into the Z-Score Momentum Dashboard represents one of its most powerful predictive capabilities, leveraging the empirical observation that financial markets exhibit periodic behavior driven by fundamental economic cycles, seasonal patterns, trader psychology, and technical feedback loops. The Ehlers bandpass filters implemented in the indicator specifically isolate cyclical components at 10, 15, and 20-day periods, frequencies that correspond to common trading cycles including bi-weekly, monthly, and quarterly rhythms in market activity. By extracting these specific frequency bands and measuring their slope, the indicator identifies when cycles are aligned in the same directional phase versus when they are diverging, with aligned cycles providing stronger predictive signals than single-frequency readings. Cyclical analysis offers predictive power because cycles, by definition, have characteristic wavelengths that enable forecasting of future turning points based on the current phase. If the indicator detects that the 10-day cycle is in a trough phase while the 20-day cycle is also declining, it can anticipate that the shorter cycle should begin turning upward before the longer cycle, potentially creating a bullish divergence or early reversal signal. Conversely, when a shorter cycle reaches a peak while longer cycles continue rising, this suggests the current rally may consolidate before the longer-cycle momentum can drive new highs. This phase relationship analysis transforms cyclical information from descriptive to predictive, allowing traders to position ahead of probable turning points rather than merely reacting to them. The bandpass filtering approach is particularly valuable because it separates signal from noise more effectively than conventional smoothing techniques. Traditional moving averages suppress both high-frequency noise and the actual signal being measured, creating lag and reducing responsiveness. Bandpass filters, in contrast, selectively attenuate frequencies outside the target band while preserving amplitude and phase information within the band, maintaining the timing and magnitude of the actual cyclical component. This means when the bandpass output changes, it reflects genuine change in the underlying cycle rather than random noise or smoothing artifacts. The z-score normalization of bandpass slopes then measures whether the current cyclical momentum is statistically unusual relative to recent history, identifying periods when cyclical forces are particularly strong or weak. The integration of Fisher Transform calculations further enhances cyclical predictive power by converting price oscillations into a nearly Gaussian probability distribution. Financial price data typically exhibits non-normal distributions with fat tails and skewness, which violate the assumptions underlying many statistical techniques. The Fisher Transform specifically addresses this by mapping the price data onto a normal distribution where standard statistical inference tools work more reliably. When applied to cyclical data, this transformation makes it possible to accurately assess the statistical significance of cycle phases and turning points, distinguishing between normal cyclical oscillation and statistically significant deviations that may precede major price movements. The Schaff Trend Cycle component adds another dimension to cyclical analysis by combining MACD calculations with stochastic smoothing to identify trending phases within broader cyclical structures. Markets often exhibit fractal behavior where trends exist within cycles which exist within larger trends. The Schaff indicator specifically addresses this nested structure by detecting when shorter-term trends are emerging within the dominant cycle, providing early identification of trend changes before they become apparent in price action. When the Schaff reading aligns with bandpass filter signals and overall z-score direction, it confirms that multiple analytical perspectives agree on current cyclical phase, increasing confidence in directional predictions. The Detrended Price Oscillator (DPO) calculation removes trend components to isolate pure cyclical behavior, addressing a common challenge in cyclical analysis where strong trends can mask underlying cycles. By comparing current price to a centered moving average, the DPO reveals cyclical patterns that persist regardless of trend direction, allowing the indicator to maintain cyclical awareness in both trending and ranging markets. This is particularly valuable because cycles often continue operating during trends but become invisible to trend-following indicators, yet these cycles can predict pullbacks, consolidations, and acceleration phases within the larger trend. The incorporation of DPO signals into the composite z-score calculation ensures that cyclical information contributes to the final reading even when dominated by strong directional momentum. Practical Trading Application and Strategic Implementation Implementing the Z-Score Momentum Dashboard in practical trading requires understanding both its signal generation logic and the appropriate strategic frameworks for acting on its outputs. The primary trading signal comes from the overall z-score reading relative to the trigger and extreme thresholds, which by default are set at 1.25 and 2.0 respectively. When the z-score exceeds the trigger threshold, it indicates that current market behavior is more than 1.25 standard deviations above the recent baseline, suggesting statistically significant bullish momentum. Traders can interpret this as a regime shift from neutral to bullish conditions, warranting either initiation of long positions or continuation of existing long exposure with trailing stops. The strength of this signal increases when the z-score crosses the extreme threshold, indicating the market has entered a parabolic phase that, while statistically unusual, may represent either climactic buying or unsustainable conditions prone to mean reversion. The regime classifications provide contextual interpretation that modifies how traders should approach z-score signals. A z-score above the trigger threshold combined with moderate price extension from the 20-period moving average generates a "STRONG MOM" regime classification with the recommended action "Ride trend w/ stops," suggesting that traders should maintain directional exposure while using trailing stop-loss orders to protect profits if momentum reverses. In contrast, a z-score above the trigger threshold but with extreme price extension generates a "PARABOLIC EXT" classification with the action "Mean rev UP expected," warning that despite strong statistical momentum, the price has deviated too far from its moving average and may soon consolidate or reverse toward the mean. This nuanced interpretation prevents traders from blindly chasing extended moves even when z-scores remain elevated. The trend classification system—identifying RISING, FALLING, BOTTOMING, and TOPPING patterns—provides crucial information about the trajectory of statistical momentum rather than just its current level. A RISING classification indicates that not only is the z-score positive, but it has been consistently increasing over recent periods, suggesting accelerating momentum and increasing statistical support for directional movement. Traders can use this to distinguish between stable momentum that may continue and deteriorating momentum that may reverse, informing position sizing and stop-loss placement decisions. BOTTOMING and TOPPING classifications specifically identify potential inflection points where the direction of z-score movement is changing, generating early reversal signals before z-scores cross back through neutral territory. For mean reversion traders, the indicator provides exceptional value when z-scores reach extreme negative levels (below -2.0) while showing BOTTOMING trend patterns and positive acceleration. This combination suggests that statistical momentum has reached an extreme oversold condition and is beginning to reverse, creating favorable risk-reward opportunities for counter-trend long positions. The extension metric provides additional confirmation, as extreme negative extension from the moving average creates mechanical pull toward the mean independent of momentum considerations. Traders can enter positions when these factors align, using the moving average as an initial profit target and the z-score returning to neutral as a signal for position closure or transition to trend-following mode. For trend-following traders, the indicator is most valuable when z-scores remain elevated above the trigger threshold for extended periods with RISING or stable trend patterns and positive momentum readings. This indicates persistent statistical support for the trend rather than a temporary spike, justifying larger position sizes and wider stop-loss placement. The momentum and acceleration metrics help trend followers distinguish between healthy trends with sustained momentum and exhausted trends where momentum is decelerating, allowing for timely exit before reversals occur. When momentum and acceleration both turn negative while z-scores remain positive, it signals that the statistical foundation of the trend is eroding even though the trend nominally persists, prompting trend followers to tighten stops or take partial profits. The component scores displayed in the dashboard enable advanced traders to perform qualitative analysis of what factors are driving the composite z-score reading. If the composite z-score is positive but the breakdown shows that bandpass and momentum scores are negative while mean reversion scores are strongly positive, this indicates that the bullish reading is driven primarily by oversold mean reversion potential rather than directional momentum. Traders can use this information to adjust their trading approach, perhaps favoring short-term reversal trades over longer-term trend follows. Conversely, if all components show aligned readings, it suggests broad-based agreement across analytical dimensions, increasing confidence in the signal and potentially warranting larger position sizes or longer holding periods. Integration with broader trading systems can enhance the indicator's effectiveness. Traders might use the z-score as a filter for other strategies, taking long signals from separate systems only when the z-score is positive or trading reversal patterns only when z-scores are extreme. Alternatively, the indicator can serve as a portfolio allocation tool, increasing equity exposure when z-scores are positive and reducing exposure or shifting to defensive positions when z-scores turn negative. The probability estimates can be directly incorporated into Kelly Criterion or other position sizing formulas, scaling position sizes proportionally to the estimated probability of upward movement adjusted for risk-reward ratios of specific trade setups. Alert conditions built into the indicator provide automated monitoring capabilities, notifying traders when z-scores cross critical thresholds or when trend patterns change from FALLING to BOTTOMING or RISING to TOPPING. These alerts enable traders to monitor multiple instruments without constant chart watching, maintaining awareness of regime changes across a diversified portfolio. The alerts for extreme z-scores specifically warn of potential climactic conditions that may require immediate attention, whether to take profits on existing positions or to prepare for reversal opportunities. The customization options allow traders to optimize the indicator for specific instruments and market conditions. The baseline period parameter controls the lookback window for calculating statistical norms, with shorter periods making the indicator more responsive to recent conditions at the cost of increased noise, while longer periods provide stability but slower adaptation to regime changes. The weight parameters enable traders to emphasize whichever analytical dimensions prove most predictive in their specific markets, potentially increasing trend weights for strongly trending instruments like technology stocks while increasing mean reversion weights for range-bound commodities or currencies. Through systematic backtesting and forward validation, traders can develop instrument-specific configurations that maximize the indicator's predictive accuracy. Ultimately, the Z-Score Momentum Dashboard functions most effectively as a comprehensive analytical framework rather than a standalone trading system, providing rich statistical context that enhances decision-making across diverse trading approaches. Whether used for discretionary trade timing, systematic signal generation, risk management, or portfolio allocation, the indicator's multi-dimensional analysis, cyclical awareness, and probabilistic framework offer traders a sophisticated tool for understanding and responding to statistical patterns in market behavior that persist across timeframes, instruments, and market regimes.
Pine Script® indicator
by jaydesaigu
Multi-Filter Slope Master CareEA professional-grade momentum indicator that combines smart EMA slope calculations with multiple confirmation filters to deliver clean, actionable trading signals. It analyzes the rate of change of key EMAs (9, 20, 50) using advanced slope calculations, filters out noise with customizable thresholds, and adds multi-timeframe trend alignment, volume confirmation, and session-based filters to ensure you only trade high-probability setups. Perfect for scalpers and swing traders who want to catch momentum shifts while avoiding false signals during choppy markets.
Pine Script® indicator
by CareExtended
QQQ 2025 Bucket ATR (Price & Volume) + Today ComparisonHow to interpret the table For each bucket row (e.g. 09:30–10:30): Price ATR (Y) → typical price move for that bucket across all 2025 sessions Vol ATR (Y) → typical change in that bucket’s volume vs the previous day Avg Vol (Y) → average total volume traded in that bucket Today Price TR → today’s actual true range move in that bucket Today Vol ATR → today’s volume change vs yesterday’s volume in that bucket Today Vol → today’s raw volume for that bucket So you can eyeball stuff like: “9:30–10:30 today did 1.5× its usual range and 2× its usual volume, but midday buckets were dead.”
Pine Script® indicator
by joe_craig
Master in Trading, version 1.7// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © GowriShankar //@version=6 indicator("Master in Trading, version 1.7", overlay = true, max_lines_count = 500, dynamic_requests = true) color_of_lines_12 = input.color(title = "Color of Lines 1-2", defval = color.new(#fec500,0)) width_of_lines_12 = input.int(title = "Width", defval = 2, minval = 1) style_of_lines_12 = input.string(title = "Style", defval = "Solid", options = ) selected_style_of_lines_12 = style_of_lines_12 == "Solid" ? line.style_solid : style_of_lines_12 == "Dotted" ? line.style_dotted : style_of_lines_12 == "Dashed" ? line.style_dashed : na color_of_lines_34 = input.color(title = "Color of Lines 3-4", defval = color.new(#0b00ff,0)) width_of_lines_34 = input.int(title = "Width", defval = 2, minval = 1) style_of_lines_34 = input.string(title = "Style", defval = "Solid", options = ) selected_style_of_lines_34 = style_of_lines_34 == "Solid" ? line.style_solid : style_of_lines_34 == "Dotted" ? line.style_dotted : style_of_lines_34 == "Dashed" ? line.style_dashed : na text_size = input.string(title = "Text Size", defval = "Normal", options = ) selected_text_size = if(text_size == "Auto") size.auto else if(text_size == "Tiny") size.tiny else if(text_size == "Small") size.small else if(text_size == "Normal") size.normal else if(text_size == "Large") size.large else if(text_size == "Huge") size.huge = request.security(ticker.heikinashi(syminfo.tickerid), "15", [open, close , close , session.isfirstbar , session.isfirstbar , session.isfirstbar , barstate.isconfirmed], lookahead = barmerge.lookahead_on, gaps = barmerge.gaps_off) var float close_prev_day_last_candle = na var float close_1st_candle = na var float close_2nd_candle = na var float open_3rd_candle = na if session.isfirstbar close_prev_day_last_candle := h_prev_day_last_close if is_first_bar_of_15_min close_1st_candle := h_close if is_2nd_first_bar_of_15_min close_2nd_candle := h_close if is_3rd_first_bar_of_15_min open_3rd_candle := h_open if session.islastbar or session.islastbar_regular close_prev_day_last_candle := na close_1st_candle := na close_2nd_candle := na open_3rd_candle := na var line close_prev_day_last_candle_line = na var line close_1st_candle_line = na var line close_2nd_candle_line = na var line open_3rd_candle_line = na var label close_prev_day_last_candle_label = na var label close_1st_candle_label = na var label close_2nd_candle_label = na var label open_3rd_candle_label = na if session.isfirstbar line.set_extend(id = close_prev_day_last_candle_line, extend = extend.none) line.set_extend(id = close_1st_candle_line, extend = extend.none) line.set_extend(id = close_2nd_candle_line, extend = extend.none) line.set_extend(id = open_3rd_candle_line, extend = extend.none) line.set_x2(id = close_prev_day_last_candle_line, x = bar_index ) line.set_x2(id = close_1st_candle_line, x = bar_index ) line.set_x2(id = close_2nd_candle_line, x = bar_index ) line.set_x2(id = open_3rd_candle_line, x = bar_index ) close_prev_day_last_candle_line := na close_1st_candle_line := na close_2nd_candle_line := na open_3rd_candle_line := na label.delete(id = close_prev_day_last_candle_label) label.delete(id = close_1st_candle_label) label.delete(id = close_2nd_candle_label) label.delete(id = open_3rd_candle_label) if session.isfirstbar close_prev_day_last_candle_line := line.new(bar_index, close_prev_day_last_candle, bar_index+1, close_prev_day_last_candle, color = color_of_lines_12, extend = extend.right, width = width_of_lines_12, style = selected_style_of_lines_12) close_prev_day_last_candle_label := label.new(bar_index+5, close_prev_day_last_candle, color = color_of_lines_12, size = selected_text_size, style = label.style_label_lower_left, text = "Prev. " + str.tostring(close_prev_day_last_candle,"#.##"), textcolor = color.black) if is_first_bar_of_15_min and not is_first_bar_of_15_min close_1st_candle_line := line.new(bar_index, close_1st_candle, bar_index+1, close_1st_candle, color = color_of_lines_12, extend = extend.right, width = width_of_lines_12, style = selected_style_of_lines_12) close_1st_candle_label := label.new(bar_index+5, close_1st_candle, color = color_of_lines_12, size = selected_text_size, style = label.style_label_lower_left, text = "1st " + str.tostring(close_1st_candle,"#.##"), textcolor = color.black) if is_2nd_first_bar_of_15_min and not is_2nd_first_bar_of_15_min close_2nd_candle_line := line.new(bar_index, close_2nd_candle, bar_index+1, close_2nd_candle, color = color_of_lines_34, extend = extend.right, width = width_of_lines_34, style = selected_style_of_lines_34) close_2nd_candle_label := label.new(bar_index+5, close_2nd_candle, color = color_of_lines_34, size = selected_text_size, style = label.style_label_upper_left, text = "2nd " + str.tostring(close_2nd_candle,"#.##"), textcolor = color.white) if is_3rd_first_bar_of_15_min and not is_3rd_first_bar_of_15_min open_3rd_candle_line := line.new(bar_index, open_3rd_candle, bar_index+1, open_3rd_candle, color = color_of_lines_34, extend = extend.right, width = width_of_lines_34, style = selected_style_of_lines_34) open_3rd_candle_label := label.new(bar_index+5, open_3rd_candle, color = color_of_lines_34, size = selected_text_size, style = label.style_label_upper_left, text = "3rd " + str.tostring(open_3rd_candle,"#.##"), textcolor = color.white) label.set_x(id = close_prev_day_last_candle_label, x = bar_index+1) label.set_x(id = close_1st_candle_label, x = bar_index+1) label.set_x(id = close_2nd_candle_label, x = bar_index+1) label.set_x(id = open_3rd_candle_label, x = bar_index+1)
Pine Script® indicator
by goldentradeselvakumar
Market Trend Strength Indicator1. The current stock price is above both the 150-day (30-week) and the 200- day (40- week) moving average price lines. 2. The 150-day moving average is above the 200-day moving average. 3. The 200-day moving average line is trending up for at least 1 month ( preferably 4–5 months minimum in most cases). 4. The 50-day (10-week) moving average is above both the 150-day and 200-day moving averages 5. The current stock price is trading above the 50-day moving average. 6. The current stock price is at least 30 percent above its 52-week low. (Many of the best selections will be 100 percent, 300 percent, or greater above their 52-week low before they emerge from a solid consolidation period and mount a large scale advance.) 7. The current stock price is within at least 25 percent of its 52-week high(the closer to a new high the better). 8. It also indicates if the volumes are decreasing during price consolidation or retracement. This is based on Mark Minervini's strategy
Pine Script® indicator
by AzeezF
PDH/PDL + PSH/PSL + Session Opens (UTC+10)PDH / PDL (Previous Day High/Low) “Day” = your trade day that starts at Asia open 09:00 Brisbane. At each new Asia open, it: Locks yesterday’s high/low as PDH/PDL Draws two horizontal lines labeled PDH and PDL PSH / PSL (Previous Session High/Low) Tracks the High/Low of each session: Asia 09:00–17:00 London 18:00–23:00 NY Futures 23:00–00:30 NYSE 00:30–01:00 When a session ends, it stores that high/low. At the next session open, it prints the previous session levels: At London open → shows PSH/PSL ASIA At NY Futures open → shows PSH/PSL LON At NYSE open → shows PSH/PSL NY At Asia open → shows PSH/PSL NYSE Session open markers (vertical lines) Draws an opaque-ish vertical line + tiny label at: 09:00 “ASIA 09:00” 18:00 “LON 18:00” 23:00 “NY 23:00” 00:30 “NYSE 00:30” Line behavior Horizontal lines extend to the right by extendBars (default 500 bars). Labels are small and minimal (left-anchored on the line).
Pine Script® indicator
by jbot-bit
DAS Levels and BoxesTrading levels mainly used to trade MNQ Futures plus 1-Hour & 4-Hour price range boxes. I define the day trading range from 6:30AM PST to 1PM PST. I define the overnight range from midnight PST to 6:30AM PST. I define the futures market entire range as starting at 3PM PST going overnight and ending at 2PM PST the following day. The 1-hour box is for scalping and catching smaller moves and are more risky. Enter long or short trade upon 1-hour candle close above & below the mid-line, respectively. The 4-hour box is for catching larger moves and require more patience. Enter long or short trade upon 4-hour candle close above & below the mid-line, respectively. This is my first indicator so be patient. These are the lines and boxes that I use to trade so I thought it would save time to have them all present in one indicator. This is set up with Pacific Standard Time as default. I may need to adjust later for day light savings time. Levels include: Previous Day Low (PDL) Previous Day High (PDH) Overnight Low (ONL) Overnight High (ONH) Open AM Price Open PM Price
Pine Script® indicator
by videocheez
Dynamic Band (UA)Dynamic Band — Multi-TF RSI Context Indicator Dynamic Band is a market-structure and context indicator that combines ATR-based dynamic price bands with multi-timeframe RSI signals plotted directly on the chart. Instead of using static levels, the indicator builds adaptive bands around EMA, reflecting real volatility and liquidity behavior. These bands act as dynamic reaction zones, not fixed support or resistance. 🔹 Dynamic Band Structure The indicator forms three adaptive zones: Outer Band – extreme volatility / liquidity exhaustion Mid Band – transition / decision zone Inner Band – mean-reversion and reaction area Each band expands and contracts automatically with ATR, keeping relevance across different market regimes. 🔹 Multi-Timeframe Support Dynamic Bands can be displayed from: the current timeframe up to two higher timeframes (MTF overlays) This allows traders to see HTF structure directly on LTF charts, without switching timeframes. 🔹 RSI Signals on Price RSI is used as a trigger, not a standalone oscillator: Overbought / oversold events are plotted on price, not in a sub-window Signals can be shown for: current timeframe multiple higher timeframes simultaneously Each marker includes its origin timeframe, enabling instant confluence reading 🔹 Signal Anchoring & Clarity RSI markers can be anchored to: candle high / low specific Dynamic Band levels (Inner / Mid / Outer) Markers automatically stack with adaptive spacing, keeping the chart readable even with multiple timeframe signals. 🔹 Designed Use-Cases Dynamic Band is built for: identifying reaction zones instead of exact entries aligning LTF execution with HTF context spotting liquidity extremes and RSI exhaustion avoiding indicator noise and repainting traps 🔹 Key Philosophy Price reacts to zones, not lines. RSI confirms context, not direction. Dynamic Band provides a clean structural framework for discretionary, systematic, and hybrid trading approaches.
Pine Script® indicator
by yulche02
Last Swing Anchor Zones - EnhancedLast Swing Anchor Zones automatically identifies major swing highs and lows on your chart and draws shaded reaction zones around them. These zones represent potential support and resistance areas where price may react. How It Works: • Detects pivot points using a customizable lookback period (default: 6 bars) • Creates semi-transparent zones around each swing point • Displays up to 3 most recent zones (configurable) • Shows price labels for quick reference • Zones extend forward to highlight future price interaction areas How to Use: • Teal/cyan zones = resistance levels (swing highs) • Red/pink zones = support levels (swing lows) • Look for price reactions when approaching these zones • Use as confluence with your existing trading strategy • Adjust zone width % to match your timeframe and volatility Customizable Settings: • Pivot Lookback: Change sensitivity (lower = more zones, higher = fewer major swings) • Zone Width %: Adjust zone thickness • Max Zones: Display 1-10 recent zones • Colors: Customize zone and label colors • Show Labels: Toggle price labels on/off
Pine Script® indicator
by jumbalia86