Relative Valuation OscillatorThis is a Relative Valuation Oscillator (RVO) this is attempt of replication OTC Valuation - a sophisticated multi-asset comparison indicator designed to measure whether the current asset is overvalued or undervalued relative to up to three reference assets.
Overview
The RVO compares the current chart's asset against reference assets (default: 30-Year Treasury Bonds, Gold, and US Dollar Index) to determine relative strength and valuation extremes. It outputs normalized oscillator values ranging from -100 (undervalued) to +100 (overvalued).
Key Features
Multiple Calculation Methods
The indicator offers 5 different calculation approaches:
Simple Ratio - Normalized ratio deviation from average
Percentage Difference - Percentage change comparison
Ratio Z-Score - Standard deviation-based comparison
Rate of Change Comparison - Momentum differential analysis (default)
Normalized Ratio - Min-max normalized ratio
Configurable Reference Assets
Asset 1: Default ZB (30-Year Treasury Bond Futures) - tracks interest rate sensitivity
Asset 2: Default GC (Gold Futures) - tracks safe-haven and inflation dynamics
Asset 3: Default DXY (US Dollar Index) - tracks currency strength
Each asset can be enabled/disabled independently
Fully customizable symbols
Visual Components
Multiple oscillator lines - One for each active reference asset (color-coded)
Average line - Combined signal from all active assets
Overbought/Oversold zones - Configurable threshold levels (default: ±80)
Zero line - Neutral valuation reference
Background coloring - Visual zones for extreme conditions
Signal line - Optional smoothed average
Entry markers - Long/short signals at key reversals
Signal Generation
Crossover alerts - When crossing overbought/oversold levels
Entry signals - Reversals from extreme zones
Divergence detection - Bullish/bearish divergences between price and oscillator
Zero-line crosses - Trend strength changes
Customization Options
Lookback period (10-500): Controls statistical calculation window
Normalization period (50-1000): Determines scaling sensitivity
Smoothing toggle: Optional EMA/SMA smoothing with adjustable period
Visual customization: Colors, levels, and display options
Information Table
Real-time dashboard showing:
Average oscillator value
Current status (Overvalued/Undervalued/Neutral)
Current asset price
Individual values for each active reference asset
Use Cases
Mean reversion trading - Identify extreme relative valuations for reversal trades
Sector rotation - Compare assets within similar categories
Hedging strategies - Understand correlation dynamics
Multi-asset analysis - Simultaneously compare against bonds, commodities, and currencies
Divergence trading - Spot price/oscillator divergences
Trading Strategy Applications
Long signals: When oscillator crosses above oversold level (asset recovering from undervaluation)
Short signals: When oscillator crosses below overbought level (asset declining from overvaluation)
Confirmation: Use multiple reference assets for stronger signals
Risk management: Avoid trading when all assets show neutral readings
This indicator is particularly useful for traders who want to incorporate inter-market analysis and relative strength concepts into their trading decisions, especially in OTC (Over-The-Counter) and futures markets.
在脚本中搜索"GOLD"
COT IndexTHE HIDDEN INTELLIGENCE IN FUTURES MARKETS
What if you could see what the smartest players in the futures markets are doing before the crowd catches on? While retail traders chase momentum indicators and moving averages, obsess over Japanese candlestick patterns, and debate whether the RSI should be set to fourteen or twenty-one periods, institutional players leave footprints in the sand through their mandatory reporting to the Commodity Futures Trading Commission. These footprints, published weekly in the Commitment of Traders reports, have been hiding in plain sight for decades, available to anyone with an internet connection, yet remarkably few traders understand how to interpret them correctly. The COT Index indicator transforms this raw institutional positioning data into actionable trading signals, bringing Wall Street intelligence to your trading screen without requiring expensive Bloomberg terminals or insider connections.
The uncomfortable truth is this: Most retail traders operate in a binary world. Long or short. Buy or sell. They apply technical analysis to individual positions, constrained by limited capital that forces them to concentrate risk in single directional bets. Meanwhile, institutional traders operate in an entirely different dimension. They manage portfolios dynamically weighted across multiple markets, adjusting exposure based on evolving market conditions, correlation shifts, and risk assessments that retail traders never see. A hedge fund might be simultaneously long gold, short oil, neutral on copper, and overweight agricultural commodities, with position sizes calibrated to volatility and portfolio Greeks. When they increase gold exposure from five percent to eight percent of portfolio allocation, this rebalancing decision reflects sophisticated analysis of opportunity cost, risk parity, and cross-market dynamics that no individual chart pattern can capture.
This portfolio reweighting activity, multiplied across hundreds of institutional participants, manifests in the aggregate positioning data published weekly by the CFTC. The Commitment of Traders report does not show individual trades or strategies. It shows the collective footprint of how actual commercial hedgers and large speculators have allocated their capital across different markets. When mining companies collectively increase forward gold sales to hedge thirty percent more production than last quarter, they are not reacting to a moving average crossover. They are making strategic allocation decisions based on production forecasts, cost structures, and price expectations derived from operational realities invisible to outside observers. This is portfolio management in action, revealed through positioning data rather than price charts.
If you want to understand how institutional capital actually flows, how sophisticated traders genuinely position themselves across market cycles, the COT report provides a rare window into that hidden world. But understand what you are getting into. This is not a tool for scalpers seeking confirmation of the next five-minute move. This is not an oscillator that flashes oversold at market bottoms with convenient precision. COT analysis operates on a timescale measured in weeks and months, revealing positioning shifts that precede major market turns but offer no precision timing. The data arrives three days stale, published only once per week, capturing strategic positioning rather than tactical entries.
If you need instant gratification, if you trade intraday moves, if you demand mechanical signals with ninety percent accuracy, close this document now. COT analysis rewards patience, position sizing discipline, and tolerance for being early. It punishes impatience, overleveraging, and the expectation that any single indicator can substitute for market understanding.
The premise is deceptively simple. Every Tuesday, large traders in futures markets must report their positions to the CFTC. By Friday afternoon, this data becomes public. Academic research spanning three decades has consistently shown that not all market participants are created equal. Some traders consistently profit while others consistently lose. Some anticipate major turning points while others chase trends into exhaustion. Bessembinder and Chan (1992) demonstrated in their seminal study that commercial hedgers, those with actual exposure to the underlying commodity or financial instrument, possess superior forecasting ability compared to speculators. Their research, published in the Journal of Finance, found statistically significant predictive power in commercial positioning, particularly at extreme levels. This finding challenged the efficient market hypothesis and opened the door to a new approach to market analysis based on positioning rather than price alone.
Think about what this means. Every week, the government publishes a report showing you exactly how the most informed market participants are positioned. Not their opinions. Not their predictions. Their actual money at risk. When agricultural producers collectively hold their largest short hedge in five years, they are not making idle speculation. They are locking in prices for crops they will harvest, informed by private knowledge of weather conditions, soil quality, inventory levels, and demand expectations invisible to outside observers. When energy companies aggressively hedge forward production at current prices, they reveal information about expected supply that no analyst report can capture. This is not technical analysis based on past prices. This is not fundamental analysis based on publicly available data. This is behavioral analysis based on how the smartest money is actually positioned, how institutions allocate capital across portfolios, and how those allocation decisions shift as market conditions evolve.
WHY SOME TRADERS KNOW MORE THAN OTHERS
Building on this foundation, Sanders, Boris and Manfredo (2004) conducted extensive research examining the behaviour patterns of different trader categories. Their work, which analyzed over a decade of COT data across multiple commodity markets, revealed a fascinating dynamic that challenges much of what retail traders are taught. Commercial hedgers consistently positioned themselves against market extremes, buying when speculators were most bearish and selling when speculators reached peak bullishness. The contrarian positioning of commercials was not random noise but rather reflected their superior information about supply and demand fundamentals. Meanwhile, large speculators, primarily hedge funds and commodity trading advisors, exhibited strong trend-following behaviour that often amplified market moves beyond fundamental values. Small traders, the retail participants, consistently entered positions late in trends, frequently near turning points, making them reliable contrary indicators.
Wang (2003) extended this research by demonstrating that the predictive power of commercial positioning varies significantly across different commodity sectors. His analysis of agricultural commodities showed particularly strong forecasting ability, with commercial net positions explaining up to fifteen percent of return variance in subsequent weeks. This finding suggests that the informational advantages of hedgers are most pronounced in markets where physical supply and demand fundamentals dominate, as opposed to purely financial markets where information asymmetries are smaller. When a corn farmer hedges six months of expected harvest, that decision incorporates private observations about rainfall patterns, crop health, pest pressure, and local storage capacity that no distant analyst can match. When an oil refinery hedges crude oil purchases and gasoline sales simultaneously, the spread relationships reveal expectations about refining margins that reflect operational realities invisible in public data.
The theoretical mechanism underlying these empirical patterns relates to information asymmetry and different participant motivations. Commercial hedgers engage in futures markets not for speculative profit but to manage business risks. An agricultural producer selling forward six months of expected harvest is not making a bet on price direction but rather locking in revenue to facilitate financial planning and ensure business viability. However, this hedging activity necessarily incorporates private information about expected supply, inventory levels, weather conditions, and demand trends that the hedger observes through their commercial operations (Irwin and Sanders, 2012). When aggregated across many participants, this private information manifests in collective positioning.
Consider a gold mining company deciding how much forward production to hedge. Management must estimate ore grades, recovery rates, production costs, equipment reliability, labor availability, and dozens of other operational variables that determine whether locking in prices at current levels makes business sense. If the industry collectively hedges more aggressively than usual, it suggests either exceptional production expectations or concern about sustaining current price levels or combination of both. Either way, this positioning reveals information unavailable to speculators analyzing price charts and economic data. The hedger sees the physical reality behind the financial abstraction.
Large speculators operate under entirely different incentives and constraints. Commodity Trading Advisors managing billions in assets typically employ systematic, trend-following strategies that respond to price momentum rather than fundamental supply and demand. When crude oil rallies from sixty dollars to seventy dollars per barrel, these systems generate buy signals. As the rally continues to eighty dollars, position sizes increase. The strategy works brilliantly during sustained trends but becomes a liability at reversals. By the time oil reaches ninety dollars, trend-following funds are maximally long, having accumulated positions progressively throughout the rally. At this point, they represent not smart money anticipating further gains but rather crowded money vulnerable to reversal. Sanders, Boris and Manfredo (2004) documented this pattern across multiple energy markets, showing that extreme speculator positioning typically marked late-stage trend exhaustion rather than early-stage trend development.
Small traders, the retail participants who fall below reporting thresholds, display the weakest forecasting ability. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns, meaning their aggregate positioning served as a reliable contrary indicator. The explanation combines several factors. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, entering trends after mainstream media coverage when institutional participants are preparing to exit. Perhaps most importantly, they trade with emotion, buying into euphoria and selling into panic at precisely the wrong times.
At major turning points, the three groups often position opposite each other with commercials extremely bearish, large speculators extremely bullish, and small traders piling into longs at the last moment. These high-divergence environments frequently precede increased volatility and trend reversals. The insiders with business exposure quietly exit as the momentum traders hit maximum capacity and retail enthusiasm peaks. Within weeks, the reversal begins, and positions unwind in the opposite sequence.
FROM RAW DATA TO ACTIONABLE SIGNALS
The COT Index indicator operationalizes these academic findings into a practical trading tool accessible through TradingView. At its core, the indicator normalizes net positioning data onto a zero to one hundred scale, creating what we call the COT Index. This normalization is critical because absolute position sizes vary dramatically across different futures contracts and over time. A commercial trader holding fifty thousand contracts net long in crude oil might be extremely bullish by historical standards, or it might be quite neutral depending on the context of total market size and historical ranges. Raw position numbers mean nothing without context. The COT Index solves this problem by calculating where current positioning stands relative to its range over a specified lookback period, typically two hundred fifty-two weeks or approximately five years of weekly data.
The mathematical transformation follows the methodology originally popularized by legendary trader Larry Williams, though the underlying concept appears in statistical normalization techniques across many fields. For any given trader category, we calculate the highest and lowest net position values over the lookback period, establishing the historical range for that specific market and trader group. Current positioning is then expressed as a percentage of this range, where zero represents the most bearish positioning ever seen in the lookback window and one hundred represents the most bullish extreme. A reading of fifty indicates positioning exactly in the middle of the historical range, suggesting neither extreme optimism nor pessimism relative to recent history (Williams and Noseworthy, 2009).
This index-based approach allows for meaningful comparison across different markets and time periods, overcoming the scaling problems inherent in analyzing raw position data. A commercial index reading of eighty-five in gold carries the same interpretive meaning as an eighty-five reading in wheat or crude oil, even though the absolute position sizes differ by orders of magnitude. This standardization enables systematic analysis across entire futures portfolios rather than requiring market-specific expertise for each contract.
The lookback period selection involves a fundamental tradeoff between responsiveness and stability. Shorter lookback periods, perhaps one hundred twenty-six weeks or approximately two and a half years, make the index more sensitive to recent positioning changes. However, it also increases noise and produces more false signals. Longer lookback periods, perhaps five hundred weeks or approximately ten years, create smoother readings that filter short-term noise but become slower to recognize regime changes. The indicator settings allow users to adjust this parameter based on their trading timeframe, risk tolerance, and market characteristics.
UNDERSTANDING CFTC DATA STRUCTURES
The indicator supports both Legacy and Disaggregated COT report formats, reflecting the evolution of CFTC reporting standards over decades of market development. Legacy reports categorize market participants into three broad groups: commercial traders (hedgers with underlying business exposure), non-commercial traders (large speculators seeking profit without commercial interest), and non-reportable traders (small speculators below reporting thresholds). Each category brings distinct motivations and information advantages to the market (CFTC, 2020).
The Disaggregated reports, introduced in September 2009 for physical commodity markets, provide finer granularity by splitting participants into five categories (CFTC, 2009). Producer and merchant positions capture those actually producing, processing, or merchandising the physical commodity. Swap dealers represent financial intermediaries facilitating derivative transactions for clients. Managed money includes commodity trading advisors and hedge funds executing systematic or discretionary strategies. Other reportables encompasses diverse participants not fitting the main categories. Small traders remain as the fifth group, representing retail participation.
This enhanced categorization reveals nuances invisible in Legacy reports, particularly distinguishing between different types of institutional capital and their distinct behavioural patterns. The indicator automatically detects which report type is appropriate for each futures contract and adjusts the display accordingly.
Importantly, Disaggregated reports exist only for physical commodity futures. Agricultural commodities like corn, wheat, and soybeans have Disaggregated reports because clear producer, merchant, and swap dealer categories exist. Energy commodities like crude oil and natural gas similarly have well-defined commercial hedger categories. Metals including gold, silver, and copper also receive Disaggregated treatment (CFTC, 2009). However, financial futures such as equity index futures, Treasury bond futures, and currency futures remain available only in Legacy format. The CFTC has indicated no plans to extend Disaggregated reporting to financial futures due to different market structures and participant categories in these instruments (CFTC, 2020).
THE BEHAVIORAL FOUNDATION
Understanding which trader perspective to follow requires appreciation of their distinct trading styles, success rates, and psychological profiles. Commercial hedgers exhibit anticyclical behaviour rooted in their fundamental knowledge and business imperatives. When agricultural producers hedge forward sales during harvest season, they are not speculating on price direction but rather locking in revenue for crops they will harvest. Their business requires converting volatile commodity exposure into predictable cash flows to facilitate planning and ensure survival through difficult periods. Yet their aggregate positioning reveals valuable information because these hedging decisions incorporate private information about supply conditions, inventory levels, weather observations, and demand expectations that hedgers observe through their commercial operations (Bessembinder and Chan, 1992).
Consider a practical example from energy markets. Major oil companies continuously hedge portions of forward production based on price levels, operational costs, and financial planning needs. When crude oil trades at ninety dollars per barrel, they might aggressively hedge the next twelve months of production, locking in prices that provide comfortable profit margins above their extraction costs. This hedging appears as short positioning in COT reports. If oil rallies further to one hundred dollars, they hedge even more aggressively, viewing these prices as exceptional opportunities to secure revenue. Their short positioning grows increasingly extreme. To an outside observer watching only price charts, the rally suggests bullishness. But the commercial positioning reveals that the actual producers of oil find these prices attractive enough to lock in years of sales, suggesting skepticism about sustaining even higher levels. When the eventual reversal occurs and oil declines back to eighty dollars, the commercials who hedged at ninety and one hundred dollars profit while speculators who chased the rally suffer losses.
Large speculators or managed money traders operate under entirely different incentives and constraints. Their systematic, momentum-driven strategies mean they amplify existing trends rather than anticipate reversals. Trend-following systems, the most common approach among large speculators, by definition require confirmation of trend through price momentum before entering positions (Sanders, Boris and Manfredo, 2004). When crude oil rallies from sixty dollars to eighty dollars per barrel over several months, trend-following algorithms generate buy signals based on moving average crossovers, breakouts, and other momentum indicators. As the rally continues, position sizes increase according to the systematic rules.
However, this approach becomes a liability at turning points. By the time oil reaches ninety dollars after a sustained rally, trend-following funds are maximally long, having accumulated positions progressively throughout the move. At this point, their positioning does not predict continued strength. Rather, it often marks late-stage trend exhaustion. The psychological and mechanical explanation is straightforward. Trend followers by definition chase price momentum, entering positions after trends establish rather than anticipating them. Eventually, they become fully invested just as the trend nears completion, leaving no incremental buying power to sustain the rally. When the first signs of reversal appear, systematic stops trigger, creating a cascade of selling that accelerates the downturn.
Small traders consistently display the weakest track record across academic studies. Wang (2003) found that small trader positioning exhibited negative correlation with subsequent returns in his analysis across multiple commodity markets. This result means that whatever small traders collectively do, the opposite typically proves profitable. The explanation for small trader underperformance combines several factors documented in behavioral finance literature. Retail traders often lack the capital reserves to weather normal market volatility, leading to premature exits from positions that would eventually prove profitable. They tend to receive information through slower channels, learning about commodity trends through mainstream media coverage that arrives after institutional participants have already positioned. Perhaps most importantly, retail traders are more susceptible to emotional decision-making, buying into euphoria and selling into panic at precisely the wrong times (Tharp, 2008).
SETTINGS, THRESHOLDS, AND SIGNAL GENERATION
The practical implementation of the COT Index requires understanding several key features and settings that users can adjust to match their trading style, timeframe, and risk tolerance. The lookback period determines the time window for calculating historical ranges. The default setting of two hundred fifty-two bars represents approximately one year on daily charts or five years on weekly charts, balancing responsiveness with stability. Conservative traders seeking only the most extreme, highest-probability signals might extend the lookback to five hundred bars or more. Aggressive traders seeking earlier entry and willing to accept more false positives might reduce it to one hundred twenty-six bars or even less for shorter-term applications.
The bullish and bearish thresholds define signal generation levels. Default settings of eighty and twenty respectively reflect academic research suggesting meaningful information content at these extremes. Readings above eighty indicate positioning in the top quintile of the historical range, representing genuine extremes rather than temporary fluctuations. Conversely, readings below twenty occupy the bottom quintile, indicating unusually bearish positioning (Briese, 2008).
However, traders must recognize that appropriate thresholds vary by market, trader category, and personal risk tolerance. Some futures markets exhibit wider positioning swings than others due to seasonal patterns, volatility characteristics, or participant behavior. Conservative traders seeking high-probability setups with fewer signals might raise thresholds to eighty-five and fifteen. Aggressive traders willing to accept more false positives for earlier entry could lower them to seventy-five and twenty-five.
The key is maintaining meaningful differentiation between bullish, neutral, and bearish zones. The default settings of eighty and twenty create a clear three-zone structure. Readings from zero to twenty represent bearish territory where the selected trader group holds unusually bearish positions. Readings from twenty to eighty represent neutral territory where positioning falls within normal historical ranges. Readings from eighty to one hundred represent bullish territory where the selected trader group holds unusually bullish positions.
The trading perspective selection determines which participant group the indicator follows, fundamentally shaping interpretation and signal meaning. For counter-trend traders seeking reversal opportunities, monitoring commercial positioning makes intuitive sense based on the academic research discussed earlier. When commercials reach extreme bearish readings below twenty, indicating unprecedented short positioning relative to recent history, they are effectively betting against the crowd. Given their informational advantages demonstrated by Bessembinder and Chan (1992), this contrarian stance often precedes major bottoms.
Trend followers might instead monitor large speculator positioning, but with inverted logic compared to commercials. When managed money reaches extreme bullish readings above eighty, the trend may be exhausting rather than accelerating. This seeming paradox reflects their late-cycle participation documented by Sanders, Boris and Manfredo (2004). Sophisticated traders thus use speculator extremes as fade signals, entering positions opposite to speculator consensus.
Small trader monitoring serves primarily as a contrary indicator for all trading styles. Extreme small trader bullishness above seventy-five or eighty typically warns of retail FOMO at market tops. Extreme small trader bearishness below twenty or twenty-five often marks capitulation bottoms where the last weak hands have sold.
VISUALIZATION AND USER INTERFACE
The visual design incorporates multiple elements working together to facilitate decision-making and maintain situational awareness during active trading. The primary COT Index line plots in bold with adjustable line width, defaulting to two pixels for clear visibility against busy price charts. An optional glow effect, controlled by a simple toggle, adds additional visual prominence through multiple plot layers with progressively increasing transparency and width.
A twenty-one period exponential moving average overlays the index line, providing trend context for positioning changes. When the index crosses above its moving average, it signals accelerating bullish sentiment among the selected trader group regardless of whether absolute positioning is extreme. Conversely, when the index crosses below its moving average, it signals deteriorating sentiment and potentially the beginning of a reversal in positioning trends.
The EMA provides a dynamic reference line for assessing positioning momentum. When the index trades far above its EMA, positioning is not only extreme in absolute terms but also building with momentum. When the index trades far below its EMA, positioning is contracting or reversing, which may indicate weakening conviction even if absolute levels remain elevated.
The data table positioned at the top right of the chart displays eleven metrics for each trader category, transforming the indicator from a simple index calculation into an analytical dashboard providing multidimensional market intelligence. Beyond the COT Index itself, users can monitor positioning extremity, which measures how unusual current levels are compared to historical norms using statistical techniques. The extremity metric clarifies whether a reading represents the ninety-fifth or ninety-ninth percentile, with values above two standard deviations indicating genuinely exceptional positioning.
Market power quantifies each group's influence on total open interest. This metric expresses each trader category's net position as a percentage of total market open interest. A commercial entity holding forty percent of total open interest commands significantly more influence than one holding five percent, making their positioning signals more meaningful.
Momentum and rate of change metrics reveal whether positions are building or contracting, providing early warning of potential regime shifts. Position velocity measures the rate of change in positioning changes, effectively a second derivative providing even earlier insight into inflection points.
Sentiment divergence highlights disagreements between commercial and speculative positioning. This metric calculates the absolute difference between normalized commercial and large speculator index values. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals.
The table also displays concentration metrics when available, showing how positioning is distributed among the largest handful of traders in each category. High concentration indicates a few dominant players controlling most of the positioning, while low concentration suggests broad-based participation across many traders.
THE ALERT SYSTEM AND MONITORING
The alert system, comprising five distinct alert conditions, enables systematic monitoring of dozens of futures markets without constant screen watching. The bullish and bearish COT signal alerts trigger when the index crosses user-defined thresholds, indicating the selected trader group has reached extreme positioning worthy of attention. These alerts fire in real-time as new weekly COT data publishes, typically Friday afternoon following the Tuesday measurement date.
Extreme positioning alerts fire at ninety and ten index levels, representing the top and bottom ten percent of the historical range, warning of particularly stretched readings that historically precede reversals with high probability. When commercials reach a COT Index reading below ten, they are expressing their most bearish stance in the entire lookback period.
The data staleness alert notifies users when COT reports have not updated for more than ten days, preventing reliance on outdated information for trading decisions. Government shutdowns or federal holidays can interrupt the normal Friday publication schedule. Using stale signals while believing them current creates dangerous false confidence.
The indicator's watermark information display positioned in the bottom right corner provides essential context at a glance. This persistent display shows the symbol and timeframe, the COT report date timestamp, days since last update, and the current signal state. A trader analyzing a potential short entry in crude oil can glance at the watermark to instantly confirm positioning context without interrupting analysis flow.
LIMITATIONS AND REALISTIC EXPECTATIONS
Practical application requires understanding both the indicator's considerable strengths and inherent limitations. COT data inherently lags price action by three days, as Tuesday positions are not published until Friday afternoon. This delay means the indicator cannot catch rapid intraday reversals or respond to surprise news events. Traders using the COT Index for timing entries must accept this latency and focus on swing trading and position trading timeframes where three-day lags matter less than in day trading or scalping.
The weekly publication schedule similarly makes the indicator unsuitable for short-term trading strategies requiring immediate feedback. The COT Index works best for traders operating on weekly or longer timeframes, where positioning shifts measured in weeks and months align with trading horizon.
Extreme COT readings can persist far longer than typical technical indicators suggest, testing the patience and capital reserves of traders attempting to fade them. When crude oil enters a sustained bull market driven by genuine supply disruptions, commercial hedgers may maintain bearish positioning for many months as prices grind higher. A commercial COT Index reading of fifteen indicating extreme bearishness might persist for three months while prices continue rallying before finally reversing. Traders without sufficient capital and risk tolerance to weather such drawdowns will exit prematurely, precisely when the signal is about to work (Irwin and Sanders, 2012).
Position sizing discipline becomes paramount when implementing COT-based strategies. Rather than risking large percentages of capital on individual signals, successful COT traders typically allocate modest position sizes across multiple signals, allowing some to take time to mature while others work more quickly.
The indicator also cannot overcome fundamental regime changes that alter the structural drivers of markets. If gold enters a true secular bull market driven by monetary debasement, commercial hedgers may remain persistently bearish as mining companies sell forward years of production at what they perceive as favorable prices. Their positioning indicates valuation concerns from a production cost perspective, but cannot stop prices from rising if investment demand overwhelms physical supply-demand balance.
Similarly, structural changes in market participation can alter the meaning of positioning extremes. The growth of commodity index investing in the two thousands brought massive passive long-only capital into futures markets, fundamentally changing typical positioning ranges. Traders relying on COT signals without recognizing this regime change would have generated numerous false bearish signals during the commodity supercycle from 2003 to 2008.
The research foundation supporting COT analysis derives primarily from commodity markets where the commercial hedger information advantage is most pronounced. Studies specifically examining financial futures like equity indices and bonds show weaker but still present effects. Traders should calibrate expectations accordingly, recognizing that COT analysis likely works better for crude oil, natural gas, corn, and wheat than for the S&P 500, Treasury bonds, or currency futures.
Another important limitation involves the reporting threshold structure. Not all market participants appear in COT data, only those holding positions above specified minimums. In markets dominated by a few large players, concentration metrics become critical for proper interpretation. A single large trader accounting for thirty percent of commercial positioning might skew the entire category if their individual circumstances are idiosyncratic rather than representative.
GOLD FUTURES DURING A HYPOTHETICAL MARKET CYCLE
Consider a practical example using gold futures during a hypothetical but realistic market scenario that illustrates how the COT Index indicator guides trading decisions through a complete market cycle. Suppose gold has rallied from fifteen hundred to nineteen hundred dollars per ounce over six months, driven by inflation concerns following aggressive monetary expansion, geopolitical uncertainty, and sustained buying by Asian central banks for reserve diversification.
Large speculators, operating primarily trend-following strategies, have accumulated increasingly bullish positions throughout this rally. Their COT Index has climbed progressively from forty-five to eighty-five. The table display shows that large speculators now hold net long positions representing thirty-two percent of total open interest, their highest in four years. Momentum indicators show positive readings, indicating positions are still building though at a decelerating rate. Position velocity has turned negative, suggesting the pace of position building is slowing.
Meanwhile, commercial hedgers have responded to the rally by aggressively selling forward production and inventory. Their COT Index has moved inversely to price, declining from fifty-five to twenty. This bearish commercial positioning represents mining companies locking in forward sales at prices they view as attractive relative to production costs. The table shows commercials now hold net short positions representing twenty-nine percent of total open interest, their most bearish stance in five years. Concentration metrics indicate this positioning is broadly distributed across many commercial entities, suggesting the bearish stance reflects collective industry view rather than idiosyncratic positioning by a single firm.
Small traders, attracted by mainstream financial media coverage of gold's impressive rally, have recently piled into long positions. Their COT Index has jumped from forty-five to seventy-eight as retail investors chase the trend. Television financial networks feature frequent segments on gold with bullish guests. Internet forums and social media show surging retail interest. This retail enthusiasm historically marks late-stage trend development rather than early opportunity.
The COT Index indicator, configured to monitor commercial positioning from a contrarian perspective, displays a clear bearish signal given the extreme commercial short positioning. The table displays multiple confirming metrics: positioning extremity shows commercials at the ninety-sixth percentile of bearishness, market power indicates they control twenty-nine percent of open interest, and sentiment divergence registers sixty-five, indicating massive disagreement between commercial hedgers and large speculators. This divergence, the highest in three years, places the market in the historically high-risk category for reversals.
The interpretation requires nuance and consideration of context beyond just COT data. Commercials are not necessarily predicting an imminent crash. Rather, they are hedging business operations at what they collectively view as favorable price levels. However, the data reveals they have sold unusually large quantities of forward production, suggesting either exceptional production expectations for the year ahead or concern about sustaining current price levels or combination of both. Combined with extreme speculator positioning indicating a crowded long trade, and small trader enthusiasm confirming retail FOMO, the confluence suggests elevated reversal risk even if the precise timing remains uncertain.
A prudent trader analyzing this situation might take several actions based on COT Index signals. Existing long positions could be tightened with closer stop losses. Profit-taking on a portion of long exposure could lock in gains while maintaining some participation. Some traders might initiate modest short positions as portfolio hedges, sizing them appropriately for the inherent uncertainty in timing reversals. Others might simply move to the sidelines, avoiding new long entries until positioning normalizes.
The key lesson from case study analysis is that COT signals provide probabilistic edges rather than deterministic predictions. They work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five percent win rate with proper risk management produces substantial profits over time, yet still means forty-five percent of signals will be premature or wrong. Traders must embrace this probabilistic reality rather than seeking the impossible goal of perfect accuracy.
INTEGRATION WITH TRADING SYSTEMS
Integration with existing trading systems represents a natural and powerful use case for COT analysis, adding a positioning dimension to price-based technical approaches or fundamental analytical frameworks. Few traders rely exclusively on a single indicator or methodology. Rather, they build systems that synthesize multiple information sources, with each component addressing different aspects of market behavior.
Trend followers might use COT extremes as regime filters, modifying position sizing or avoiding new trend entries when positioning reaches levels historically associated with reversals. Consider a classic trend-following system based on moving average crossovers and momentum breakouts. Integration of COT analysis adds nuance. When large speculator positioning exceeds ninety or commercial positioning falls below ten, the regime filter recognizes elevated reversal risk. The system might reduce position sizing by fifty percent for new signals during these high-risk periods (Kaufman, 2013).
Mean reversion traders might require COT signal confluence before fading extended moves. When crude oil becomes technically overbought and large speculators show extreme long positioning above eighty-five, both signals confirm. If only technical indicators show extremes while positioning remains neutral, the potential short signal is rejected, avoiding fades of trends with underlying institutional support (Kaufman, 2013).
Discretionary traders can monitor the indicator as a continuous awareness tool, informing bias and position sizing without dictating mechanical entries and exits. A discretionary trader might notice commercial positioning shifting from neutral to progressively more bullish over several months. This trend informs growing positive bias even without triggering mechanical signals.
Multi-timeframe analysis represents another powerful integration approach. A trader might use daily charts for trade execution and timing while monitoring weekly COT positioning for strategic context. When both timeframes align, highest-probability opportunities emerge.
Portfolio construction for futures traders can incorporate COT signals as an additional selection criterion. Markets showing strong technical setups AND favorable COT positioning receive highest allocations. Markets with strong technicals but neutral or unfavorable positioning receive reduced allocations.
ADVANCED METRICS AND INTERPRETATION
The metrics table transforms simple positioning data into multidimensional market intelligence. Position extremity, calculated as the absolute deviation from the historical mean normalized by standard deviation, helps identify truly unusual readings versus routine fluctuations. A reading above two standard deviations indicates ninety-fifth percentile or higher extremity. Above three standard deviations indicates ninety-ninth percentile or higher, genuinely rare positioning that historically precedes major events with high probability.
Market power, expressed as a percentage of total open interest, reveals whose positioning matters most from a mechanical market impact perspective. Consider two scenarios in gold futures. In scenario one, commercials show a COT Index reading of fifteen while their market power metric shows they hold net shorts representing thirty-five percent of open interest. This is a high-confidence bearish signal. In scenario two, commercials also show a reading of fifteen, but market power shows only eight percent. While positioning is extreme relative to this category's normal range, their limited market share means less mechanical influence on price.
The rate of change and momentum metrics highlight whether positions are accelerating or decelerating, often providing earlier warnings than absolute levels alone. A COT Index reading of seventy-five with rapidly building momentum suggests continued movement toward extremes. Conversely, a reading of eighty-five with decelerating or negative momentum indicates the positioning trend is exhausting.
Position velocity measures the rate of change in positioning changes, effectively a second derivative. When velocity shifts from positive to negative, it indicates that while positioning may still be growing, the pace of growth is slowing. This deceleration often precedes actual reversal in positioning direction by several weeks.
Sentiment divergence calculates the absolute difference between normalized commercial and large speculator index values. When commercials show extreme bearish positioning at twenty while large speculators show extreme bullish positioning at eighty, the divergence reaches sixty, representing near-maximum disagreement. Wang (2003) found that these high-divergence environments frequently preceded increased volatility and reversals. The mechanism is intuitive. Extreme divergence indicates the informed hedgers and momentum-following speculators have positioned opposite each other with conviction. One group will prove correct and profit while the other proves incorrect and suffers losses. The resolution of this disagreement through price movement often involves volatility.
The table also displays concentration metrics when available. High concentration indicates a few dominant players controlling most of the positioning within a category, while low concentration suggests broad-based participation. Broad-based positioning more reliably reflects collective market intelligence and industry consensus. If mining companies globally all independently decide to hedge aggressively at similar price levels, it suggests genuine industry-wide view about price valuations rather than circumstances specific to one firm.
DATA QUALITY AND RELIABILITY
The CFTC has maintained COT reporting in various forms since the nineteen twenties, providing nearly a century of positioning data across multiple market cycles. However, data quality and reporting standards have evolved substantially over this long period. Modern electronic reporting implemented in the late nineteen nineties and early two thousands significantly improved accuracy and timeliness compared to earlier paper-based systems.
Traders should understand that COT reports capture positions as of Tuesday's close each week. Markets remain open three additional days before publication on Friday afternoon, meaning the reported data is three days stale when received. During periods of rapid market movement or major news events, this lag can be significant. The indicator addresses this limitation by including timestamp information and staleness warnings.
The three-day lag creates particular challenges during extreme volatility episodes. Flash crashes, surprise central bank interventions, geopolitical shocks, and other high-impact events can completely transform market positioning within hours. Traders must exercise judgment about whether reported positioning remains relevant given intervening events.
Reporting thresholds also mean that not all market participants appear in disaggregated COT data. Traders holding positions below specified minimums aggregate into the non-reportable or small trader category. This aggregation affects different markets differently. In highly liquid contracts like crude oil with thousands of participants, reportable traders might represent seventy to eighty percent of open interest. In thinly traded contracts with only dozens of active participants, a few large reportable positions might represent ninety-five percent of open interest.
Another data quality consideration involves trader classification into categories. The CFTC assigns traders to commercial or non-commercial categories based on reported business purpose and activities. However, this process is not perfect. Some entities engage in both commercial and speculative activities, creating ambiguity about proper classification. The transition to Disaggregated reports attempted to address some of these ambiguities by creating more granular categories.
COMPARISON WITH ALTERNATIVE APPROACHES
Several alternative approaches to COT analysis exist in the trading community beyond the normalization methodology employed by this indicator. Some analysts focus on absolute position changes week-over-week rather than index-based normalization. This approach calculates the change in net positioning from one week to the next. The emphasis falls on momentum in positioning changes rather than absolute levels relative to history. This method potentially identifies regime shifts earlier but sacrifices cross-market comparability (Briese, 2008).
Other practitioners employ more complex statistical transformations including percentile rankings, z-score standardization, and machine learning classification algorithms. Ruan and Zhang (2018) demonstrated that machine learning models applied to COT data could achieve modest improvements in forecasting accuracy compared to simple threshold-based approaches. However, these gains came at the cost of interpretability and implementation complexity.
The COT Index indicator intentionally employs a relatively straightforward normalization methodology for several important reasons. First, transparency enhances user understanding and trust. Traders can verify calculations manually and develop intuitive feel for what different readings mean. Second, academic research suggests that most of the predictive power in COT data comes from extreme positioning levels rather than subtle patterns requiring complex statistical methods to detect. Third, robust methods that work consistently across many markets and time periods tend to be simpler rather than more complex, reducing the risk of overfitting to historical data. Fourth, the complexity costs of implementation matter for retail traders without programming teams or computational infrastructure.
PSYCHOLOGICAL ASPECTS OF COT TRADING
Trading based on COT data requires psychological fortitude that differs from momentum-based approaches. Contrarian positioning signals inherently mean betting against prevailing market sentiment and recent price action. When commercials reach extreme bearish positioning, prices have typically been rising, sometimes for extended periods. The price chart looks bullish, momentum indicators confirm strength, moving averages align positively. The COT signal says bet against all of this. This psychological difficulty explains why COT analysis remains underutilized relative to trend-following methods.
Human psychology strongly predisposes us toward extrapolation and recency bias. When prices rally for months, our pattern-matching brains naturally expect continued rally. The recent price action dominates our perception, overwhelming rational analysis about positioning extremes and historical probabilities. The COT signal asking us to sell requires overriding these powerful psychological impulses.
The indicator design attempts to support the required psychological discipline through several features. Clear threshold markers and signal states reduce ambiguity about when signals trigger. When the commercial index crosses below twenty, the signal is explicit and unambiguous. The background shifts to red, the signal label displays bearish, and alerts fire. This explicitness helps traders act on signals rather than waiting for additional confirmation that may never arrive.
The metrics table provides analytical justification for contrarian positions, helping traders maintain conviction during inevitable periods of adverse price movement. When a trader enters short positions based on extreme commercial bearish positioning but prices continue rallying for several weeks, doubt naturally emerges. The table display provides reassurance. Commercial positioning remains extremely bearish. Divergence remains high. The positioning thesis remains intact even though price action has not yet confirmed.
Alert functionality ensures traders do not miss signals due to inattention while also not requiring constant monitoring that can lead to emotional decision-making. Setting alerts for COT extremes enables a healthier relationship with markets. When meaningful signals occur, alerts notify them. They can then calmly assess the situation and execute planned responses.
However, no indicator design can completely overcome the psychological difficulty of contrarian trading. Some traders simply cannot maintain short positions while prices rally. For these traders, COT analysis might be better employed as an exit signal for long positions rather than an entry signal for shorts.
Ultimately, successful COT trading requires developing comfort with probabilistic thinking rather than certainty-seeking. The signals work over many observations by identifying higher-probability configurations, not by generating perfect calls on individual trades. A fifty-five or sixty percent win rate with proper risk management produces substantial profits over years, yet still means forty to forty-five percent of signals will be premature or wrong. COT analysis provides genuine edge, but edge means probability advantage, not elimination of losing trades.
EDUCATIONAL RESOURCES AND CONTINUOUS LEARNING
The indicator provides extensive built-in educational resources through its documentation, detailed tooltips, and transparent calculations. However, mastering COT analysis requires study beyond any single tool or resource. Several excellent resources provide valuable extensions of the concepts covered in this guide.
Books and practitioner-focused monographs offer accessible entry points. Stephen Briese published The Commitments of Traders Bible in two thousand eight, offering detailed breakdowns of how different markets and trader categories behave (Briese, 2008). Briese's work stands out for its empirical focus and market-specific insights. Jack Schwager includes discussion of COT analysis within the broader context of market behavior in his book Market Sense and Nonsense (Schwager, 2012). Perry Kaufman's Trading Systems and Methods represents perhaps the most rigorous practitioner-focused text on systematic trading approaches including COT analysis (Kaufman, 2013).
Academic journal articles provide the rigorous statistical foundation underlying COT analysis. The Journal of Futures Markets regularly publishes research on positioning data and its predictive properties. Bessembinder and Chan's earlier work on systematic risk, hedging pressure, and risk premiums in futures markets provides theoretical foundation (Bessembinder, 1992). Chang's examination of speculator returns provides historical context (Chang, 1985). Irwin and Sanders provide essential skeptical perspective in their two thousand twelve article (Irwin and Sanders, 2012). Wang's two thousand three article provides one of the most empirical analyses of COT data across multiple commodity markets (Wang, 2003).
Online resources extend beyond academic and book-length treatments. The CFTC website provides free access to current and historical COT reports in multiple formats. The explanatory materials section offers detailed documentation of report construction, category definitions, and historical methodology changes. Traders serious about COT analysis should read these official CFTC documents to understand exactly what they are analyzing.
Commercial COT data services such as Barchart provide enhanced visualization and analysis tools beyond raw CFTC data. TradingView's educational materials, published scripts library, and user community provide additional resources for exploring different approaches to COT analysis.
The key to mastering COT analysis lies not in finding a single definitive source but rather in building understanding through multiple perspectives and information sources. Academic research provides rigorous empirical foundation. Practitioner-focused books offer practical implementation insights. Direct engagement with data through systematic backtesting develops intuition about how positioning dynamics manifest across different market conditions.
SYNTHESIZING KNOWLEDGE INTO PRACTICE
The COT Index indicator represents the synthesis of academic research, trading experience, and software engineering into a practical tool accessible to retail traders equipped with nothing more than a TradingView account and willingness to learn. What once required expensive data subscriptions, custom programming capabilities, statistical software, and institutional resources now appears as a straightforward indicator requiring only basic parameter selection and modest study to understand. This democratization of institutional-grade analysis tools represents a broader trend in financial markets over recent decades.
Yet technology and data access alone provide no edge without understanding and discipline. Markets remain relentlessly efficient at eliminating edges that become too widely known and mechanically exploited. The COT Index indicator succeeds only when users invest time learning the underlying concepts, understand the limitations and probability distributions involved, and integrate signals thoughtfully into trading plans rather than applying them mechanically.
The academic research demonstrates conclusively that institutional positioning contains genuine information about future price movements, particularly at extremes where commercial hedgers are maximally bearish or bullish relative to historical norms. This informational content is neither perfect nor deterministic but rather probabilistic, providing edge over many observations through identification of higher-probability configurations. Bessembinder and Chan's finding that commercial positioning explained modest but significant variance in future returns illustrates this probabilistic nature perfectly (Bessembinder and Chan, 1992). The effect is real and statistically significant, yet it explains perhaps ten to fifteen percent of return variance rather than most variance. Much of price movement remains unpredictable even with positioning intelligence.
The practical implication is that COT analysis works best as one component of a trading system rather than a standalone oracle. It provides the positioning dimension, revealing where the smart money has positioned and where the crowd has followed, but price action analysis provides the timing dimension. Fundamental analysis provides the catalyst dimension. Risk management provides the survival dimension. These components work together synergistically.
The indicator's design philosophy prioritizes transparency and education over black-box complexity, empowering traders to understand exactly what they are analyzing and why. Every calculation is documented and user-adjustable. The threshold markers, background coloring, tables, and clear signal states provide multiple reinforcing channels for conveying the same information.
This educational approach reflects a conviction that sustainable trading success comes from genuine understanding rather than mechanical system-following. Traders who understand why commercial positioning matters, how different trader categories behave, what positioning extremes signify, and where signals fit within probability distributions can adapt when market conditions change. Traders mechanically following black-box signals without comprehension abandon systems after normal losing streaks.
The research foundation supporting COT analysis comes primarily from commodity markets where commercial hedger informational advantages are most pronounced. Agricultural producers hedging crops know more about supply conditions than distant speculators. Energy companies hedging production know more about operating costs than financial traders. Metals miners hedging output know more about ore grades than index funds. Financial futures markets show weaker but still present effects.
The journey from reading this documentation to profitable trading based on COT analysis involves several stages that cannot be rushed. Initial reading and basic understanding represents the first stage. Historical study represents the second stage, reviewing past market cycles to observe how positioning extremes preceded major turning points. Paper trading or small-size real trading represents the third stage to experience the psychological challenges. Refinement based on results and personal psychology represents the fourth stage.
Markets will continue evolving. New participant categories will emerge. Regulatory structures will change. Technology will advance. Yet the fundamental dynamics driving COT analysis, that different market participants have different information, different motivations, and different forecasting abilities that manifest in their positioning, will persist as long as futures markets exist. While specific thresholds or optimal parameters may shift over time, the core logic remains sound and adaptable.
The trader equipped with this indicator, understanding of the theory and evidence behind COT analysis, realistic expectations about probability rather than certainty, discipline to maintain positions through adverse volatility, and patience to allow signals time to develop possesses genuine edge in markets. The edge is not enormous, markets cannot allow large persistent inefficiencies without arbitraging them away, but it is real, measurable, and exploitable by those willing to invest in learning and disciplined application.
REFERENCES
Bessembinder, H. (1992) Systematic risk, hedging pressure, and risk premiums in futures markets, Review of Financial Studies, 5(4), pp. 637-667.
Bessembinder, H. and Chan, K. (1992) The profitability of technical trading rules in the Asian stock markets, Pacific-Basin Finance Journal, 3(2-3), pp. 257-284.
Briese, S. (2008) The Commitments of Traders Bible: How to Profit from Insider Market Intelligence. Hoboken: John Wiley & Sons.
Chang, E.C. (1985) Returns to speculators and the theory of normal backwardation, Journal of Finance, 40(1), pp. 193-208.
Commodity Futures Trading Commission (CFTC) (2009) Explanatory Notes: Disaggregated Commitments of Traders Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Commodity Futures Trading Commission (CFTC) (2020) Commitments of Traders: About the Report. Available at: www.cftc.gov (Accessed: 15 January 2025).
Irwin, S.H. and Sanders, D.R. (2012) Testing the Masters Hypothesis in commodity futures markets, Energy Economics, 34(1), pp. 256-269.
Kaufman, P.J. (2013) Trading Systems and Methods. 5th edn. Hoboken: John Wiley & Sons.
Ruan, Y. and Zhang, Y. (2018) Forecasting commodity futures prices using machine learning: Evidence from the Chinese commodity futures market, Applied Economics Letters, 25(12), pp. 845-849.
Sanders, D.R., Boris, K. and Manfredo, M. (2004) Hedgers, funds, and small speculators in the energy futures markets: an analysis of the CFTC's Commitments of Traders reports, Energy Economics, 26(3), pp. 425-445.
Schwager, J.D. (2012) Market Sense and Nonsense: How the Markets Really Work and How They Don't. Hoboken: John Wiley & Sons.
Tharp, V.K. (2008) Super Trader: Make Consistent Profits in Good and Bad Markets. New York: McGraw-Hill.
Wang, C. (2003) The behavior and performance of major types of futures traders, Journal of Futures Markets, 23(1), pp. 1-31.
Williams, L.R. and Noseworthy, M. (2009) The Right Stock at the Right Time: Prospering in the Coming Good Years. Hoboken: John Wiley & Sons.
FURTHER READING
For traders seeking to deepen their understanding of COT analysis and futures market positioning beyond this documentation, the following resources provide valuable extensions:
Academic Journal Articles:
Fishe, R.P.H. and Smith, A. (2012) Do speculators drive commodity prices away from supply and demand fundamentals?, Journal of Commodity Markets, 1(1), pp. 1-16.
Haigh, M.S., Hranaiova, J. and Overdahl, J.A. (2007) Hedge funds, volatility, and liquidity provision in energy futures markets, Journal of Alternative Investments, 9(4), pp. 10-38.
Kocagil, A.E. (1997) Does futures speculation stabilize spot prices? Evidence from metals markets, Applied Financial Economics, 7(1), pp. 115-125.
Sanders, D.R. and Irwin, S.H. (2011) The impact of index funds in commodity futures markets: A systems approach, Journal of Alternative Investments, 14(1), pp. 40-49.
Books and Practitioner Resources:
Murphy, J.J. (1999) Technical Analysis of the Financial Markets: A Guide to Trading Methods and Applications. New York: New York Institute of Finance.
Pring, M.J. (2002) Technical Analysis Explained: The Investor's Guide to Spotting Investment Trends and Turning Points. 4th edn. New York: McGraw-Hill.
Federal Reserve and Research Institution Publications:
Federal Reserve Banks regularly publish working papers examining commodity markets, futures positioning, and price discovery mechanisms. The Federal Reserve Bank of San Francisco and Federal Reserve Bank of Kansas City maintain active research programs in this area.
Online Resources:
The CFTC website provides free access to current and historical COT reports, explanatory materials, and regulatory documentation.
Barchart offers enhanced COT data visualization and screening tools.
TradingView's community library contains numerous published scripts and educational materials exploring different approaches to positioning analysis.
Trading Lot & Margin Calculator
# 💹 Trading Lot & Margin Calculator - Professional Risk Management Tool
## 🎯 Overview
A comprehensive, all-in-one calculator dashboard that helps traders determine optimal position sizes, calculate margin requirements, and manage risk effectively across multiple asset classes. This indicator displays directly on your chart as a customizable table, providing real-time calculations based on current market prices.
## ✨ Key Features
### 📊 Three Powerful Calculation Modes:
**1. Calculate Lot Size (Risk-Based Position Sizing)**
- Input your risk percentage and stop loss in pips
- Automatically calculates the optimal lot size for your risk tolerance
- Respects margin limitations (configurable margin % cap)
- Ensures positions don't exceed minimum lot size (0.01)
- Perfect for risk management and proper position sizing
**2. Calculate Margin Cost**
- Input desired lot size
- See exactly how much margin is required
- Shows percentage of deposit used
- Displays free margin remaining
- Warns when insufficient funds
**3. Margin to Lots**
- Specify a fixed margin amount you want to use
- Calculator shows how many lots/contracts you can buy
- Ideal for traders with fixed margin budgets
## 🤖 Auto-Detection of Instruments
The calculator **automatically detects** what you're trading and adjusts calculations accordingly:
### ✅ Fully Supported:
- **💱 Forex Pairs** - All majors, minors, exotics (EURUSD, GBPJPY, etc.)
- Standard lot: 100,000 units
- JPY pairs: 0.01 pip size, others: 0.0001
- **🛢️ Commodities** - Gold, Silver, Oil
- XAUUSD (Gold): 100 oz per lot
- XAGUSD (Silver): 5,000 oz per lot
- Oil (WTI/Brent): 1,000 barrels per lot
- **📈 Indices** - US500, NAS100, US30, DAX, etc.
- Correct contract sizes per point
- **📊 Stocks** - All individual stocks
- 1 lot = 1 share
- Direct share calculations
### ⚠️ Known Limitation:
- **₿ Crypto calculations may not work properly** on all crypto pairs. Use manual contract size if needed.
## 📋 Dashboard Information Displayed:
- 🎯 Optimal/Requested Lot Size
- 💰 Margin Required
- 📊 Margin % of Deposit
- 💵 Free Margin Remaining
- 💎 Position Value
- 📈 Pip/Point Value
- ⚠️ Safety Warnings (insufficient funds, high risk, etc.)
- 🔍 Detected Instrument Type
- 📦 Contract Size
## ⚙️ Customizable Settings:
**Account Settings:**
- Account Deposit
- Leverage (1:1 to 1:1000)
- Max Margin % of Deposit (default 5% for safety)
**Risk Management:**
- Risk Percentage (for lot size calculation)
- Stop Loss in Pips
- Lot Amount (for margin cost calculation)
- Margin to Use (for margin-to-lots calculation)
**Display Options:**
- Show/Hide Dashboard
- Position: Top/Middle/Bottom, Left/Right
- Auto-detect instrument ON/OFF
- Manual contract size override
## 🎨 Professional Design
- Clean, modern table interface
- Color-coded warnings (red = danger, yellow = caution, green = safe)
- Large, readable text
- Minimal screen space usage
- Non-intrusive overlay
## 💡 Use Cases:
1. **Day Traders** - Quick position sizing based on account risk
2. **Swing Traders** - Calculate optimal positions for longer-term setups
3. **Risk Managers** - Ensure positions stay within margin limits
4. **Beginners** - Learn proper position sizing and risk management
5. **Multi-Asset Traders** - Seamlessly switch between forex, commodities, indices, and stocks
## ⚠️ Important Notes:
- ✅ Works on all timeframes
- ✅ Updates in real-time with price changes
- ✅ Minimum lot size enforced (0.01)
- ✅ Margin calculations use current chart price
- ⚠️ **Crypto calculations may be inaccurate** - verify with your broker
- 📌 Always verify calculations with your broker's specifications
- 📌 Contract sizes may vary by broker
## 🚀 How to Use:
1. Add indicator to any chart
2. Click settings ⚙️ icon
3. Enter your account details (deposit, leverage)
4. Choose calculation mode
5. Input your parameters
6. View optimal lot size and margin requirements on dashboard
## 📈 Perfect For:
- Forex traders managing multiple currency pairs
- Commodity traders (Gold, Silver, Oil)
- Index traders (S&P 500, NASDAQ, etc.)
- Stock traders
- Anyone who wants professional risk management
## 🛡️ Risk Management Features:
- Configurable margin % cap prevents over-leveraging
- Risk-based position sizing protects your account
- Warnings for high risk, insufficient funds, margin limitations
- Prevents positions below minimum lot size
---
**Trade smarter, not harder. Calculate before you trade!** 📊💪
---
## Version Notes:
- Pine Script v6
- Overlay mode for chart display
- No external dependencies
- Lightweight and fast
**Disclaimer:** This calculator is for educational and informational purposes only. Always verify calculations with your broker and trade at your own risk. Past performance does not guarantee future results.
---
XAUUSD Family Scalping (5min)🟡 XAUUSD Family Scalping 5-Min — Momentum Precision Indicator
Overview
This indicator is built for XAUUSD (Gold) on the 5-minute timeframe and is designed for short-term momentum scalping.
It helps traders identify early reversal zones, confirm momentum direction, and detect exhaustion points during high-volatility market moves.
Core Concept
The indicator measures momentum strength and price acceleration using a smoothed oscillator.
It features two adjustable thresholds:
Overbought level: 58
Oversold level: -58
When the momentum line crosses above or below these zones, it signals potential trend continuation or reversal opportunities.
Features
Detects short-term momentum shifts on XAUUSD 5M.
Works with EMA-based trend confirmation (optional).
Adaptive smoothing reduces noise and false reversals.
Highlights overbought/oversold areas visually.
Can be combined with price action or other oscillators for confluence.
Usage
Instrument: XAUUSD (Gold)
Best timeframe: 5-minute (scalping setup)
Use case: Detecting momentum exhaustion and reversal entries.
Sessions: London & New York recommended.
Disclaimer
This indicator is for market analysis and educational purposes.
No indicator guarantees profit — use proper risk management and test before live trading.
MarketMonkey-Indicator-Set-1 - GMMA open 🧠 MarketMonkey-Indicator-Set-1 — GMMA Open
GMMA (Guppy Multiple Moving Average) Toolkit for Trend Clarity & Timing
The MarketMonkey GMMA Open indicators brings a clean, high-performance visual of trend strength and direction using multiple exponential moving averages (EMAs) across short- and long-term time frames.
Designed for traders who want to see momentum shifts and market transitions as they happen, this version overlays directly on the price chart for quick and confident reads.
🔍 How It Works
* Short-term EMAs (3–15) track trader sentiment and momentum.
* Long-term EMAs (30–60) show investor trend commitment.
* The indicator dynamically colors the long-term EMAs:
* 🔵 Blue : Upward momentum
* 🔴 Red : Downward momentum
When the short-term group expands above the long-term group, it signals strength and potential continuation. Tightening or compression may warn of pauses or reversals.
💡 Features
* 12 adjustable EMA periods (customize your GMMA spacing)
* Automatic color shifts for trend clarity
* Live price flag for easy reference
* Compact ticker/date display in the top-right corner
* Minimalist, overlay-based design — no clutter, just clarity
📈 Best Used For
* Spotting early trend changes
* Confirming continuation or breakout setups
* Identifying compression zones before reversals
* Overlaying on ASX, S&P, FX, Gold, or Crypto charts
🔔 Part of the MarketMonkey Indicator Set series — tools built for real-world trend recognition and momentum trading.
Relative Momentum Rotation [CHE] Relative Momentum Rotation — Ranks assets by multi-horizon momentum for guided rotational selection with regime overlay
Summary
This indicator evaluates a universe of assets using a blended momentum measure across three time horizons, then ranks them to highlight top performers for potential portfolio rotation. It incorporates a regime filter to contextualize signals, tinting the background to indicate favorable or unfavorable market conditions and labeling transitions for awareness. By focusing on relative strength within a selectable universe, it helps identify leaders without relying on absolute thresholds, reducing noise from isolated trends and promoting disciplined asset switching.
Motivation: Why this design?
Traders often struggle with momentum signals that perform unevenly across market phases, such as overreacting in volatile periods or lagging in steady uptrends, leading to suboptimal rotations in multi-asset portfolios. The core idea of relative momentum rotation addresses this by comparing assets head-to-head within a defined group, blending short- and long-term changes to capture sustained strength while a regime overlay adds a macro layer to avoid fighting broader trends. This setup prioritizes peer-relative outperformance over standalone measures, aiding consistent selection in rotational strategies.
What’s different vs. standard approaches?
- Reference baseline: Traditional rate-of-change indicators track absolute price shifts over a single window, which can generate whipsaws in sideways markets or miss cross-asset opportunities.
- Architecture differences:
- Blends three distinct horizons into one composite score for a fuller momentum picture, rather than isolating one period.
- Applies ranking across a customizable universe (e.g., crypto or tech stocks) to emphasize relatives, not absolutes.
- Integrates a simple regime check via moving average crossover on a reference symbol, gating selections without overcomplicating the core logic.
- Outputs a dynamic table for visual ranking, plus subtle visual cues like background tints, instead of cluttered plots.
- Practical effect: Charts show clearer hierarchy among assets, with regime tints providing at-a-glance context—top ranks stand out more reliably in bull regimes, helping traders focus rotations without constant recalibration.
How it works (technical)
The indicator starts by assembling a list of symbols from the selected universe, including only those marked as active to keep the group focused. For each symbol, it gathers change rates over three specified horizons on a higher timeframe, blends them using user-defined weights (automatically normalized if they do not sum to one), and computes a single composite score. Scores are then ranked to select the top performers up to a set number, forming a rotation candidate list.
To add context, a regime state is determined by comparing the reference symbol's price to its moving average on daily bars—above signals a positive environment, below a negative one, with an option to invert this logic. The current chart's symbol is checked against the top list for inclusion status. All higher-timeframe data pulls are set to avoid lookahead bias, though updates may shift slightly until bars close. Persistent variables track the table state and prior regime to handle redraws efficiently, ensuring the display rebuilds only when the selection count changes.
Parameter Guide
Universe — Switches between predefined crypto or US-tech symbol sets for ranking peers. Default: Crypto. Trade-offs/Tips: Crypto for volatile assets; US-Tech for equities—match to your portfolio to avoid mismatched volatility.
Include Symbol 1–12 — Toggles individual symbols in the universe on or off. Default: Varies (true for top 10, false for extras). Trade-offs/Tips: Start with defaults for a balanced group; disable laggards to sharpen focus, but keep at least 5–8 for robust ranking.
Scoring Timeframe — Sets the aggregation period for momentum changes (e.g., monthly bars). Default: Monthly. Trade-offs/Tips: Monthly for long-term rotation; weekly for faster signals—increases noise if too short.
Weight 12m / 6m / 3m — Adjusts emphasis on long/medium/short horizons in the blend. Default: 0.50 / 0.30 / 0.20. Trade-offs/Tips: Heavier long-term for stability in trends; balance to fit asset class—test sums near 1.0 to avoid auto-normalization surprises.
ROC over MA instead of Close — Uses smoothed averages for change rates to reduce chop. Default: False. Trade-offs/Tips: Enable in noisy markets for fewer false tops; adds slight lag, so monitor for delayed rotations.
Top N to hold — Limits selections to this many highest-ranked assets. Default: 10. Trade-offs/Tips: Lower for concentrated bets (higher risk/reward); higher for diversification—align with your position sizing.
Mark current symbol if in Top N — Highlights if the chart's asset ranks in the selection. Default: True. Trade-offs/Tips: Useful for self-scanning; disable in multi-chart setups to declutter.
Enable Regime Filter — Activates macro overlay using reference symbol. Default: True. Trade-offs/Tips: Core for trend-aware trading; disable for pure momentum plays, but risks counter-trend entries.
Regime Symbol — Chooses the benchmark for regime (e.g., broad index). Default: QQQ. Trade-offs/Tips: Broad market proxy like SPY for equities; swap for BTC in crypto to match universe.
SMA Length (D) — Sets the averaging window for regime comparison. Default: 100. Trade-offs/Tips: Longer for fewer flips (smoother regimes); shorter for quicker detection—default suits daily checks.
Invert (rare) — Flips the regime logic (price above average becomes negative). Default: False. Trade-offs/Tips: Only if your view inverts the benchmark; test thoroughly as it reverses all tints/labels.
Show Ranking Table — Displays the ranked list with scores and regime status. Default: True. Trade-offs/Tips: Essential for selection; position tweaks help on crowded charts.
Table X / Y — Places the table on the chart (e.g., top-right). Default: Right / Top. Trade-offs/Tips: Corner placement avoids price overlap; middle for central focus in reviews.
Dark Theme — Applies inverted colors for visibility. Default: True. Trade-offs/Tips: Matches most TradingView themes; toggle for light backgrounds without losing contrast.
Text Size — Scales table font for readability. Default: Normal. Trade-offs/Tips: Smaller for dense data; larger on big screens—impacts only last-bar render.
Background Tint by Regime — Colors the chart faintly green/red based on state. Default: True. Trade-offs/Tips: Subtle cue for immersion; disable if it distracts from price action.
Label on Regime Flip — Adds text markers at state changes. Default: True. Trade-offs/Tips: Aids journaling flips; space them by disabling in low-vol periods to cut clutter.
Reading & Interpretation
The ranking table lists top assets by position, symbol, percentage score (higher indicates stronger blended momentum), and regime status—green "ON" for favorable, red "OFF" for cautionary. Background shifts to a light teal in positive regimes (suggesting alignment for longs) or pale red in negative ones (hinting at reduced exposure). Flip labels appear as green "Regime ON" above bars or red "Regime OFF" below, marking transitions without ongoing noise. If the current symbol appears in the top rows with a solid score, it signals potential hold or entry priority within rotations.
Practical Workflows & Combinations
- Trend following: Scan the table weekly on monthly charts for top entrants; confirm with higher highs/lows in price structure before rotating in. Use regime tint as a veto—skip buys in red phases.
- Exits/Stops: Rotate out of bottom-half ranks monthly; tighten stops below recent lows during regime flips to protect against reversals. Pair with volatility filters like average true range for dynamic sizing.
- Multi-asset/Multi-TF: Defaults work across crypto/equities on daily+ timeframes; for intraday, shorten scoring to weekly but expect more interim noise. Scale universe size with portfolio count—e.g., top 5 for aggressive crypto rotations.
Behavior, Constraints & Performance
Signals update on bar close to confirm higher-timeframe data, but live bars may preview shifts from security calls, introducing minor repaint until finalized—mitigated by non-lookahead settings, though daily regime checks can lag by one session. Arrays handle up to 12 symbols efficiently, with loops capped at selection size; max bars back at 5000 supports historical depth without overload. Resource use stays low, but dense universes on very long charts may slow initial loads.
Known limits include sensitivity to universe composition (skewed groups amplify biases) and regime lag at sharp market turns, potentially delaying rotations by a period.
Sensible Defaults & Quick Tuning
Defaults assume a 10-asset crypto rotation on monthly scoring with balanced weights and QQQ regime—ideal for intermediate-term equity-like plays. For too-frequent table reshuffles, extend scoring timeframe or weight longer horizons more. If selections feel sluggish, shorten the 3-month weight or enable MA smoothing off. In high-vol environments, raise top N and SMA length for stability; for crypto bursts, drop to weekly scoring and invert regime if using a volatile proxy.
What this indicator is—and isn’t
This is a selection and visualization tool for momentum-based rotations, layering relative ranks and regime context onto charts to inform asset picks. It is not a standalone system—pair it with entry/exit rules, position sizing, and risk limits. Nor is it predictive; it reacts to past changes and may underperform in prolonged ranges or during universe gaps.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Where does it come from, specifically?
The principle of “composite momentum across multiple horizons” is common in TAA/rotation strategies. As a documented example: Keller/Butler use a composite 1/3/6/12-month momentum (“13612W”)—same idea, different windows/weights.
Robot Wealth
A practical vendor example: EPS Momentum calculates an RMR composite as a weighted mix of 12/6/3/1-month ranks (very close to “12/6/3”).
EPS Momentum
Related but not identical: StockCharts’ RRG measures the momentum rotation of relative strength—often mentioned in the same context, but it doesn’t have a fixed “12/6/3” composite.
chartschool.stockcharts.com
How is it typically computed?
ROC_12 + ROC_6 + ROC_3 (often scaled/weighted), then ranked vs. peers; the rotation periodically holds the top ranks in the portfolio. (Variants use different weights or additionally include 1-month—see the sources above.)
robotwealth.com
epsmomentum.com
Relative Valuation OscillatorRelative Valuation Oscillator (RVO) Description
The Valuation_OTC.pine script is a Relative Valuation Oscillator for TradingView that compares the current asset against a reference asset (like Bitcoin, S&P 500, or Gold) to determine if it's relatively overvalued or undervalued.
Key Features:
1. Multiple Calculation Methods:
Simple Ratio - Compares price ratio deviation from average
Percentage Difference - Direct percentage comparison between assets
Ratio Z-Score - Statistical measure (standard deviations from mean)
Rate of Change Comparison - Compares momentum/performance
Normalized Ratio - 0-100 scale centered at zero
2. Customizable Settings:
Reference asset selection (default: BTC/USDT)
Adjustable lookback period (10-500 bars)
Optional smoothing with configurable period
Overbought/oversold level thresholds (default: ±1.5)
3. Trading Signals:
Overvalued - Oscillator above overbought level (red zone)
Undervalued - Oscillator below oversold level (green zone)
Neutral - Between thresholds
Crossover alerts for key levels
Divergence detection (bullish/bearish)
4. Visual Components:
Color-coded oscillator line (green when positive, red when negative)
Optional signal line for additional smoothing
Background shading for valuation zones
Information table showing current metrics and status
Shape markers for crossovers and divergences
5. Alert Conditions:
Overvalued/undervalued alerts
Zero-line crossovers
Divergence signals
This indicator is useful for pairs trading, relative strength analysis, and identifying when an asset is trading at extremes relative to a benchmark asset.
Stock Fundamental Overlay [DarwinDarma]Stock Fundamental Overlay
Stock Fundamental Overlay is a comprehensive valuation indicator that displays multiple fundamental analysis metrics directly on your price chart.
Key Features:
• Graham Number - Benjamin Graham's intrinsic value formula
• Book Value Per Share (BVPS) - Net asset value baseline
• DCF Valuation - Discounted Cash Flow analysis (non-financial stocks)
• DDM Valuation - Dividend Discount Model (dividend-paying stocks)
• Visual Value Zones - Color-coded undervalued/overvalued regions
• Real-time Fundamental Table - Live metrics and valuations
• Price vs Graham Comparison - Quick valuation assessment
• Built-in Alerts - Notification when price crosses key levels
Valuation Models:
• Graham Number: √(22.5 × EPS × BVPS)
• DCF: Customizable discount rate, growth rate, and forecast period
• DDM: Gordon Growth Model for dividend analysis
Visual Elements:
• Plot lines for BVPS, Graham Number, and DCF values
• Shaded value zone between BVPS and Graham Number
• Background coloring: Deep value (below BVPS), Undervalued (below Graham), Overvalued (>1.5x Graham)
• Dynamic table showing all metrics with theme-aware text colors
Special Handling:
• Financial sector detection - DCF disabled for banks/financials where FCF metrics are distorted
• Automatic light/dark theme adaptation
• TTM (Trailing Twelve Months) data for current metrics
How to Use - Value Investing Approach:
1. Identifying Undervalued Stocks:
• Look for price trading BELOW the Graham Number (green zone) - potential value opportunity
• Deep value: Price below BVPS indicates trading below net asset value
• Check "Price vs Graham" % in table - negative values suggest undervaluation
• Compare multiple models: When price is below Graham, DCF, and BVPS simultaneously, stronger buy signal
2. Margin of Safety:
• Benjamin Graham recommended buying at 2/3 of intrinsic value (33% margin of safety)
• Monitor the gap between current price and valuation lines
• Larger gaps = greater margin of safety = lower downside risk
• Use the shaded "Value Zone" as your target buying range
3. Setting Alerts:
• "Price Below Graham Number" - Notifies when stock enters value territory
• "Price Below Book Value" - Extreme value alert for deep value hunters
• "Price Below DCF Value" - Cash flow-based value signal
• Set alerts on watchlist stocks to catch value opportunities
4. Customizing for Your Strategy:
• Conservative investors: Use lower growth rates (3-4%) and higher discount rates (12-15%)
• Growth-value investors: Adjust growth rate (6-8%) for quality compounders
• Dividend investors: Focus on DDM value and Div/Share metrics
• Adjust forecast years based on business predictability (stable = 10 years, cyclical = 5 years)
5. Red Flags to Avoid:
• Negative EPS or FCF (red values in table) - proceed with caution
• Financial sector stocks - Use DDM and Graham, ignore DCF
• Price far above Graham (>1.5x) with red background = overvalued territory
• No fundamental data = "N/A" in table - stock may lack reporting or be too small
• Stock persistently below BVPS for extended periods - potential value trap or business in distress
• Price significantly above ALL models (BVPS, Graham, DCF) - sentiment-driven, lacks intrinsic value foundation (fragile)
⚠️ Important Value Investing Warnings:
• Value Trap Alert: A stock staying below BVPS for months/years may signal fundamental deterioration, asset impairments, or dying industry - not just "cheap." Investigate WHY it's cheap before buying
• Sentiment Bubble Risk: When price trades far above BVPS, Graham Number, AND DCF simultaneously, the stock has no intrinsic value basis. Examples: commodity stocks during boom cycles (gold miners in gold rallies), meme stocks, hype-driven sectors. These are highly fragile and vulnerable to mean reversion
• Cyclical Trap: Commodity/cyclical stocks can appear "cheap" at peak earnings (low P/E, high FCF) but are actually expensive. Normalize earnings across the cycle before valuing
• Quality Matters: Some excellent businesses (asset-light, high ROIC) naturally trade above book value. Don't avoid quality - adjust expectations for business model
6. Monitoring Positions:
• Watch for price approaching or exceeding Graham Number - consider taking profits
• Track EPS and FCF trends quarter-to-quarter in the table
• If fundamentals deteriorate (falling BVPS, negative FCF), reassess thesis
• Use background colors for quick visual check: green = hold/buy, red = overvalued
Perfect for:
Value investors seeking multi-model fundamental analysis, long-term investors comparing intrinsic value to market price, dividend investors evaluating yield stocks, and fundamental traders looking for entry/exit signals.
Note: Only works with stocks that have financial data available. Not applicable to crypto, forex, or futures. This indicator provides analysis tools; always conduct thorough research and due diligence before investing.
SMA+デマンド・オファーゾーン最強版（仮）This indicator is designed to help traders visually identify both trend direction and potential reversal zones in one glance.
📊 Key Features:
• Displays 4 SMAs (9 / 20 / 75 / 200) simultaneously
• Automatically detects and plots Demand Zones (green) and Supply Zones (red) based on recent swing highs and lows
• Shows ▲ Golden Cross and ▼ Dead Cross markers when SMA 9 crosses SMA 20
• Built-in alert conditions for SMA crossovers and zone breakouts
💡 How to Use:
Use SMA direction and alignment to confirm the trend, and watch for Supply/Demand zones and cross signals as potential reversal or breakout setups.
Perfect for spotting pullbacks and identifying confluence zones between trend and structure.
⚙️ Customization:
• Adjustable SMA lengths, colors, and line widths
• Modify pivot length to fine-tune zone sensitivity
✅ Built with Pine Script v5
✅ Works on FX, Stocks, Crypto, and Indices
Author’s Note:
I created this indicator to combine trend-following tools with supply-demand logic in a clean and intuitive way.
Even beginners can easily visualize where reactions or breakouts are likely to happen.
If you find this script helpful, please give it a ❤️ and follow for more updates!
Trend Alignment TableThe Trend Alignment Table is a clean, visual tool designed to quickly assess trend direction and alignment across multiple moving averages — without cluttering your chart.
Instead of plotting moving average lines, this indicator displays a compact on-chart table showing each selected MA and its corresponding trend status using color-coded circles.
🧩 How It Works
Each circle represents the relationship between price and its corresponding moving average (MA):
Price vs. MA MA Direction Circle Color Meaning
Above Rising 🟢 Green Bullish continuation
Above Falling 🟡 Yellow Weakening bullishness
Below Falling 🔴 Red Bearish continuation
Below Rising 🟡 Yellow Weakening bearishness
⚙️ Features
Up to 4 customizable moving averages
Type: SMA, EMA, SMMA (RMA), WMA, VWMA
Source: Any price source (close, open, etc.)
Length: Fully adjustable
Dynamic color-coded circles (green, yellow, red by default — fully customizable)
User-selectable table position (top-left, top-right, bottom-left, bottom-right)
Clean visual layout for quick multi-timeframe trend confirmation
📊 Use Cases
Instantly identify trend alignment across short-, medium-, and long-term averages
Confirm trend strength or weakening momentum
Combine with other indicators or strategies for confirmation signals
🧠 Default Settings
MA Type Length Color
MA #1 SMA 5 Green
MA #2 SMA 20 Gold
MA #3 SMA 50 Orange
MA #4 SMA 150 Red
🧰 Created for traders who value clarity.
Whether you trade trends, reversals, or momentum shifts, the Trend Alignment Table gives you a concise, at-a-glance view of the market’s directional structure.
CHOCH + FVG Signals [30m Optimized]CHOCH + FVG Signals
🎯 What It Does:
This script automatically scans your chart for high-probability Smart Money Concepts (SMC) setups based on two key institutional trading principles:
Change of Character (CHOCH) – A shift in market structure signaling potential reversal
Fair Value Gap (FVG) – An imbalance zone where price moved too fast, often acting as support/resistance
When both conditions align, the script plots clear Buy (▲) and Sell (▼) signals directly on your chart — ideal for intraday trading on the 30-minute timeframe (but works on any timeframe).
✅ Key Features:
🔹 Visual Fair Value Gaps
Green shaded zones = Bullish FVGs (potential support)
Red shaded zones = Bearish FVGs (potential resistance)
Toggle on/off in settings
🔹 Smart CHOCH Detection
Detects breaks of recent swing highs/lows with proper context
Avoids false signals by confirming prior price structure
🔹 Clear Trade Signals
Green ▲ below bar = Buy signal (Bullish CHOCH + FVG confluence)
Red ▼ above bar = Sell signal (Bearish CHOCH + FVG confluence)
🔹 Customizable Filters
Option to require FVG for a signal (recommended for higher accuracy)
Adjust sensitivity via swing detection settings (default optimized for 30m)
🔹 Alert-Ready
Built-in alert conditions for instant notifications on TradingView mobile/desktop
⚙️ How to Use:
Apply to a 30-minute chart (e.g., EURUSD, Gold, NAS100, BTC)
Wait for at least 50–100 bars to load (so swing points appear)
Look for:
A green triangle (▲) → consider long entry near FVG support
A red triangle (▼) → consider short entry near FVG resistance
Confirm with price action: Wait for a strong candle close or rejection at the FVG zone
Use stop-loss below/above the FVG and target recent liquidity pools
💡 Pro Tip: Best used during high-volume sessions (e.g., London Open 7–10 AM UTC, NY Open 12:30–3:30 PM UTC).
🛠️ Settings (Inputs):
Show Fair Value Gaps
✅ Enabled
Visualize FVG zones
Max FVG History
100 bars
Prevent chart clutter
Require FVG for Signal?
✅ Enabled
Higher-quality setups (disable to test CHOCH-only)
⚠️ Important Notes:
This is a signal generator, not financial advice. Always manage risk.
Works best in trending or breaking markets — avoid during low-volatility ranges.
FVGs may get filled (tested) before price continues — patience improves results.
Backtest on historical data before live trading.
📣 Ideal For:
Retail traders learning Smart Money Concepts (SMC)
Price action traders seeking institutional-level confluence
Intraday scalpers & swing traders on 30m–1H timeframes
Risk-On / Risk-Off CompositeReal-time Risk-On / Risk-Off Composite from your four ratios:
SPY / TLT (equities vs long bonds)
HYG / LQD (high-yield vs IG credit)
HG / GOLD (copper vs gold)
BTC / GOLD (speculative vs defensive)
It:
normalizes each ratio with a z-score (so they’re comparable),
lets you weight them,
plots a composite line + histogram (up = risk-on, down = risk-off),
shows a small heat-table for each sub-signal,
and includes alert conditions for Risk-On / Risk-Off flips.
Multi-Timeframe EMA Trend Dashboard with Volume and RSI Filters═══════════════════════════════════════════════════════════
MULTI-TIMEFRAME EMA TREND DASHBOARD
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OVERVIEW
This indicator provides a comprehensive view of trend direction across multiple timeframes using the classic EMA 20/50 crossover methodology, enhanced with volume confirmation and RSI filtering. It aggregates trend information from six timeframes into a single dashboard for efficient market analysis.
The indicator is designed for educational purposes and to assist traders in identifying potential trend alignments across different time horizons.
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FEATURES
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MULTI-TIMEFRAME ANALYSIS
• Monitors 6 timeframes simultaneously: 1m, 5m, 15m, 1H, 4H, 1D
• Each timeframe analyzed independently using request.security()
• Non-repainting implementation with proper lookahead settings
• Calculates overall trend strength as percentage of bullish timeframes
EMA CROSSOVER SYSTEM
• Fast EMA (default: 20) and Slow EMA (default: 50)
• Bullish: Fast EMA > Slow EMA
• Bearish: Fast EMA < Slow EMA
• Neutral: Fast EMA = Slow EMA (rare condition)
• Visual EMA plots with optional fill area
VOLUME CONFIRMATION
• Optional volume filter for crossover signals
• Compares current volume against moving average (default: 20-period SMA)
• Categorizes volume as: High (>1.5x average), Normal (>average), Low (70), oversold (<30), and neutral zones
• Used in quality score calculation
• Optional display toggle
SUPPORT & RESISTANCE DETECTION
• Automatic detection using highest/lowest over lookback period (default: 50 bars)
• Plots resistance (red), support (green), and mid-level (gray)
• Step-line style for clear visualization
• Optional display toggle
QUALITY SCORING SYSTEM
• Rates trade setups from 1-5 stars
• Considers: MTF alignment, volume confirmation, RSI positioning
• 5 stars: 4+ timeframes aligned + volume confirmed + RSI 50-70
• 4 stars: 4+ timeframes aligned + volume confirmed
• 3 stars: 3+ timeframes aligned
• 2 stars: Exactly 3 timeframes aligned
• 1 star: Other conditions
VISUAL DASHBOARD
• Clean table display (position customizable)
• Color-coded trend indicators (green/red/yellow)
• Extended statistics panel (toggleable)
• Shows: Trends, Strength, Quality, RSI, Volume, Price Distance
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TECHNICAL SPECIFICATIONS
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CALCULATIONS
Trend Determination per Timeframe:
• request.security() fetches EMA values with gaps=off, lookahead=off
• Compares Fast EMA vs Slow EMA
• Returns: 1 (bullish), -1 (bearish), 0 (neutral)
Trend Strength:
• Counts number of bullish timeframes
• Formula: (bullish_count / 6) × 100
• Range: 0% (all bearish) to 100% (all bullish)
Price Distance from EMA:
• Formula: ((close - EMA) / EMA) × 100
• Positive: Price above EMA
• Negative: Price below EMA
• Warning when absolute distance > 5%
ANTI-REPAINTING MEASURES
• All request.security() calls use lookahead=barmerge.lookahead_off
• Dashboard updates only on barstate.islast
• Historical bars remain unchanged
• Crossover signals finalize on bar close
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USAGE GUIDE
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INTERPRETING THE DASHBOARD
Timeframe Rows:
• Each row shows individual timeframe trend status
• Look for alignment (multiple timeframes same direction)
• Higher timeframes generally more significant
Strength Indicator:
• >66.67%: Strong bullish (4+ timeframes bullish)
• 33.33-66.67%: Mixed/choppy conditions
• <33.33%: Strong bearish (4+ timeframes bearish)
Quality Score:
• Higher stars = better confluence of factors
• 5-star setups have strongest multi-factor confirmation
• Lower scores may indicate weaker or conflicting signals
SUGGESTED APPLICATIONS
Trend Confirmation:
• Check if multiple timeframes confirm current chart trend
• Higher agreement = stronger trend confidence
• Use for position sizing decisions
Entry Timing:
• Wait for EMA crossover on chart timeframe
• Confirm with higher timeframe alignment
• Volume above average preferred
• RSI not in extreme zones
Divergence Detection:
• When lower timeframes diverge from higher
• May indicate trend exhaustion or reversal
• Requires additional confirmation
CUSTOMIZATION
EMA Settings:
• Adjust Fast/Slow lengths for different sensitivities
• Shorter periods = more responsive, more signals
• Longer periods = smoother, fewer signals
• Common alternatives: 10/30, 12/26, 50/200
Volume Filter:
• Enable for higher-quality signals (fewer false positives)
• Disable in always-liquid markets or for more signals
• Adjust MA length based on typical volume patterns
Display Options:
• Toggle EMAs, S/R levels, extended stats as needed
• Choose dashboard position to avoid chart overlap
• Adjust colors for visibility preferences
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ALERTS
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AVAILABLE ALERT CONDITIONS
1. Bullish EMA Cross (Volume Confirmed)
2. Bearish EMA Cross (Volume Confirmed)
3. Strong Bullish Alignment (4+ timeframes)
4. Strong Bearish Alignment (4+ timeframes)
5. Trend Strength Increasing (>16.67% jump)
6. Trend Strength Decreasing (>16.67% drop)
7. Excellent Trade Setup (5-star rating)
Alert messages use standard placeholders:
• {{ticker}} - Symbol name
• {{close}} - Current close price
• {{time}} - Bar timestamp
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LIMITATIONS & CONSIDERATIONS
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KNOWN LIMITATIONS
• Lower timeframe data may not be available on all symbols
• 1-minute data typically limited to recent history
• request.security() subject to TradingView data limits
• Dashboard requires screen space (may overlap on small screens)
• More complex calculations may affect load time on slower devices
NOT SUITABLE FOR
• Highly volatile/illiquid instruments (many false signals)
• News-driven markets during announcements
• Automated trading without additional filters
• Markets where EMA strategies don't perform well
DOES NOT PROVIDE
• Exact entry/exit prices
• Stop-loss or take-profit levels
• Position sizing recommendations
• Guaranteed profit signals
• Market predictions
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BEST PRACTICES
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RECOMMENDED USAGE
✓ Combine with price action analysis
✓ Use appropriate risk management
✓ Backtest on historical data before live use
✓ Adjust settings for specific market characteristics
✓ Wait for higher-quality setups in important trades
✓ Consider overall market context and fundamentals
NOT RECOMMENDED
✗ Using as standalone trading system without confirmation
✗ Trading every signal without discretion
✗ Ignoring risk management principles
✗ Trading without understanding the methodology
✗ Applying to unsuitable markets/timeframes
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EDUCATIONAL BACKGROUND
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EMA CROSSOVER STRATEGY
The Exponential Moving Average crossover is a classical trend-following technique:
• Golden Cross: Fast EMA crosses above Slow EMA (bullish signal)
• Death Cross: Fast EMA crosses below Slow EMA (bearish signal)
• Widely used since the 1970s in various markets
• More responsive than SMA due to exponential weighting
MULTI-TIMEFRAME ANALYSIS
Analyzing multiple timeframes helps traders:
• Identify alignment between short and long-term trends
• Reduce false signals from single-timeframe noise
• Understand market context across different horizons
• Make informed decisions about trade duration
VOLUME ANALYSIS
Volume confirmation adds reliability:
• High volume suggests institutional participation
• Low volume signals may indicate false breakouts
• Volume precedes price in many market theories
• Helps distinguish genuine moves from noise
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TECHNICAL IMPLEMENTATION
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CODE STRUCTURE
• Organized in clear sections with proper commenting
• Uses explicit type declarations (int, float, bool, color, string)
• Constants defined at top (BULLISH=1, BEARISH=-1, etc.)
• Functions documented with @function, @param, @returns
• Follows PineCoders naming conventions (camelCase variables)
PERFORMANCE OPTIMIZATION
• var keyword for table (created once, not every bar)
• Calculations cached where possible
• Dashboard updates only on last bar
• Minimal redundant security() calls
SECURITY IMPLEMENTATION
• Proper gaps and lookahead parameters
• No future data leakage
• Signals finalize on bar close
• Historical bars remain static
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VERSION INFORMATION
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Current Version: 2.0
Pine Script Version: 5
Last Updated: 2024
Developed by: Zakaria Safri
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SETTINGS REFERENCE
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EMA SETTINGS
• Fast EMA Length: 1-500 (default: 20)
• Slow EMA Length: 1-500 (default: 50)
VOLUME & MOMENTUM
• Use Volume Confirmation: true/false (default: true)
• Volume MA Length: 1-500 (default: 20)
• Show RSI Levels: true/false (default: true)
• RSI Length: 1-500 (default: 14)
PRICE ACTION FEATURES
• Show Price Distance: true/false (default: true)
• Show Key Levels: true/false (default: true)
• S/R Lookback Period: 10-500 (default: 50)
DISPLAY SETTINGS
• Show EMAs on Chart: true/false (default: true)
• Fast EMA Color: customizable (default: cyan)
• Slow EMA Color: customizable (default: orange)
• EMA Line Width: 1-5 (default: 2)
• Show Fill Between EMAs: true/false (default: true)
• Show Crossover Signals: true/false (default: true)
DASHBOARD SETTINGS
• Position: Top Left/Right, Bottom Left/Right
• Show Extended Statistics: true/false (default: true)
ALERT SETTINGS
• Alert on Multi-TF Alignment: true/false (default: true)
• Alert on Trend Strength Change: true/false (default: true)
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RISK DISCLAIMER
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This indicator is provided for educational and informational purposes only. It should not be considered financial advice or a recommendation to buy or sell any security.
IMPORTANT NOTICES:
• Past performance does not indicate future results
• All trading involves risk of capital loss
• No indicator guarantees profitable trades
• Always conduct independent research and analysis
• Use proper risk management and position sizing
• Consult a qualified financial advisor before trading
• The developer assumes no liability for trading losses
By using this indicator, you acknowledge that you understand these risks and accept full responsibility for your trading decisions.
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SUPPORT & CONTRIBUTIONS
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FEEDBACK WELCOME
• Constructive comments appreciated
• Bug reports help improve the indicator
• Feature suggestions considered for future versions
• Share your experience to help other users
OPEN SOURCE
This code is published as open source for the TradingView community to:
• Learn from the implementation
• Modify for personal use
• Understand multi-timeframe analysis techniques
If you find this indicator useful, please consider:
• Leaving a thoughtful review
• Sharing with other traders who might benefit
• Following for future updates and releases
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ADDITIONAL RESOURCES
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RECOMMENDED READING
• TradingView Pine Script documentation
• PineCoders community resources
• Technical analysis textbooks on moving averages
• Multi-timeframe trading strategy guides
• Risk management principles
RELATED CONCEPTS
• Trend following strategies
• Moving average convergence/divergence
• Multiple timeframe analysis
• Volume-price relationships
• Momentum indicators
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Thank you for using this indicator. Trade responsibly and continue learning!
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HermesHERMES STRATEGY - TRADINGVIEW DESCRIPTION
OVERVIEW
Hermes is an adaptive trend-following strategy that uses dual ALMA (Arnaud Legoux Moving Average) filters to identify high-quality entry and exit points. It's designed for swing and position traders who want smooth, low-lag signals with minimal whipsaws.
Unlike traditional moving averages that operate on price, Hermes analyzes price returns (percentage changes) to create signals that work consistently across any asset class and price range.
HOW IT WORKS
DUAL ALMA SYSTEM
The strategy uses two ALMA lines applied to price returns:
• Fast ALMA (Blue Line): Short-term trend signal (default: 80 periods)
• Slow ALMA (Black Line): Long-term baseline trend (default: 250 periods)
ALMA is superior to simple or exponential moving averages because it provides:
• Smoother curves with less noise
• Significantly reduced lag
• Natural resistance to outliers and flash crashes
TRADING LOGIC
BUY SIGNAL:
• Fast ALMA crosses above Slow ALMA (bullish regime)
• Price makes new N-bar high (momentum confirmation)
• Optional: Price above 200 EMA (macro trend filter)
• Optional: ALMA lines sufficiently separated (strength filter)
SELL SIGNAL:
• Fast ALMA crosses below Slow ALMA (bearish regime)
• Optional: Price makes new N-bar low (momentum confirmation)
The strategy stays in position during the entire bullish regime, allowing you to ride trends for weeks or months.
VISUAL INDICATORS
LINES:
• Blue Line: Fast ALMA (short-term signal)
• Black Line: Slow ALMA (long-term baseline)
TRADE MARKERS:
• Green Triangle Up: Buy executed
• Red Triangle Down: Sell executed
• Orange "M": Buy blocked by momentum filter
• Purple "W": Buy blocked by weak crossover strength
KEY PARAMETERS
ALMA SETTINGS:
• Short Period (default: 30) - Fast signal responsiveness
• Long Period (default: 250) - Baseline stability
• ALMA Offset (default: 0.90) - Balance between lag and smoothness
• ALMA Sigma (default: 7.5) - Gaussian curve width
ENTRY/EXIT FILTERS:
• Buy Lookback (default: 7) - Bars for momentum confirmation (required)
• Sell Lookback (default: 0) - Exit momentum bars (0 = disabled for faster exits)
• Min Crossover Strength (default: 0.0) - Required ALMA separation (0 = disabled)
• Use Macro Filter (default: true) - Only enter above 200 EMA
BEST PRACTICES
RECOMMENDED ASSETS - Works well on:
• Cryptocurrencies (Bitcoin, Ethereum, etc.)
• Major indices (S&P 500, Nasdaq)
• Large-cap stocks
• Commodities (Gold, Oil)
RECOMMENDED TIMEFRAMES:
• Daily: Primary timeframe for swing trading
• 4-Hour: More active trading (increase trade frequency)
• Weekly: Long-term position trading
PARAMETER TUNING:
• More trades: Lower Short Period (60-80)
• Fewer trades: Raise Short Period (100-120)
• Faster exits: Set Sell Lookback = 0
• Safer entries: Enable Macro Filter (Use Macro Filter = true)
STRATEGY ADVANTAGES
1. Low Lag - ALMA provides faster signals than traditional moving averages
2. Smooth Signals - Minimal whipsaws compared to crossover strategies
3. Asset Agnostic - Same parameters work across different markets
4. Trend Capture - Stays positioned during entire bullish regimes
5. Risk Management - Multiple filters prevent poor entries
6. Visual Clarity - Easy to interpret regime and filter states
WHEN TO USE HERMES
BEST FOR:
• Trending markets (crypto bull runs, equity uptrends)
• Swing trading (hold days to weeks)
• Position trading (hold weeks to months)
• Clear trend identification
• Risk-managed exposure
NOT SUITABLE FOR:
• Ranging/sideways markets
• Scalping or day trading
• High-frequency trading
• Mean reversion strategies
RISK DISCLAIMER
This indicator is for educational purposes only. Past performance does not guarantee future results. Always use proper position sizing and risk management. Test thoroughly on historical data before live trading.
CREDITS
Inspired by Giovanni Santostasi's Power Law Volatility Indicator, generalized for universal application across all assets using adaptive ALMA filtering.
Strategy by Hermes Trading Systems
QUICK START
1. Add indicator to chart
2. Use on daily timeframe for best results
3. Look for green buy signals when blue line crosses above black line
4. Exit on red sell signals when blue line crosses below black line
5. Adjust parameters based on your trading style:
• Conservative: Enable Macro Filter, increase Buy Lookback to 10
• Aggressive: Disable Macro Filter, lower Short Period to 60
• Default settings work well for most assets
ZS Game Changer Pump & Dump DetectorZS GAME CHANGER PUMP AND DUMP DETECTOR - TOP 2 MOMENTUM TRACKER
Created by Zakaria Safri
An intelligent indicator specifically designed to identify and highlight the two most significant pump and dump candles within your selected lookback period. Perfect for traders who want to focus on the game-changing moves that truly matter in volatile markets like cryptocurrency, stocks, and forex.
CORE FEATURES
AUTOMATIC GAME CHANGER DETECTION
The indicator continuously scans your specified lookback period and automatically identifies the top 2 strongest pump candles and top 2 strongest dump candles. These game-changing candles are highlighted with distinctive gold labels and horizontal reference lines, making them instantly visible on your chart. Unlike other indicators that show every small move, this focuses exclusively on the market-moving moments that define trends and create opportunities.
INTELLIGENT PUMP AND DUMP CLASSIFICATION
Uses advanced percentage-based calculations to classify candles as pumps when price surges significantly upward and dumps when price plunges sharply downward. The detection system accounts for candle body size, wick proportions, and volume confirmation to ensure only legitimate momentum moves trigger signals. Customizable thresholds allow adaptation to any market volatility profile from calm stocks to wild altcoins.
ADVANCED WICK EXCLUSION FILTER
Eliminates false signals caused by candles with large wicks and small bodies. This filter focuses analysis exclusively on candles with substantial body sizes that indicate genuine directional conviction rather than temporary spikes followed by rejection. The body to candle ratio is fully adjustable to match your preferred signal quality standards.
VOLUME CONFIRMATION SYSTEM
Optional volume filter ensures detected pumps and dumps are backed by real market participation. The indicator compares current volume against a moving average and only triggers signals when volume exceeds your specified multiplier threshold. This eliminates low-volume noise and focuses on moves supported by institutional or crowd participation.
RALLY SEQUENCE DETECTION
Identifies and highlights consecutive sequences of pump or dump candles with colored background overlays. Green background indicates sustained buying pressure across multiple candles while red background shows sustained selling pressure. The rally detection system includes an optional one-miss allowance that prevents the sequence from breaking due to a single neutral candle.
HORIZONTAL REFERENCE LINES
Draws dashed lines from each game changer candle extending to the current bar, providing constant visual reference to the most significant support and resistance levels created by extreme momentum. The top game changer gets a thick dashed line while the second gets a dotted line for easy differentiation. Labels on the right side display the exact percentage move.
COMPREHENSIVE STATISTICS DASHBOARD
Real-time information panel showing current market status as pumping, dumping, or neutral along with the current candle percentage change. Displays the exact percentage values for top pump number 1, top pump number 2, top dump number 1, and top dump number 2. Shows running totals of all pumps and dumps detected since chart load. Tracks consecutive candle counts during active rally sequences.
TESTING AND VERIFICATION MODE
Built-in debug mode displays percentage change directly on each qualifying pump and dump candle, allowing instant verification that calculations are accurate. Shows which filters are currently active with a simple code in the dashboard. Helps traders understand exactly why certain candles qualified as game changers.
HOW THE GAME CHANGER DETECTION WORKS
SCANNING ALGORITHM
Every bar close, the indicator scans backward through your specified lookback period examining every candle's percentage change from its previous close. For bullish moves, it identifies the two candles with the largest positive percentage change that meet your threshold requirements. For bearish moves, it identifies the two candles with the largest negative percentage change meeting threshold requirements.
RANKING SYSTEM
Candles are ranked purely by their percentage move magnitude. The number 1 game changer is always the single strongest move in the lookback period. The number 2 game changer is the second strongest move. Rankings update dynamically as new candles form and old candles exit the lookback window.
VISUAL IDENTIFICATION
Game changer number 1 for both pumps and dumps receives a large gold label reading GAME CHANGER NUMBER 1 with zero transparency for maximum visibility. Game changer number 2 receives a slightly smaller gold label with partial transparency. The candle bars themselves are colored in gold instead of the standard green or red. Horizontal lines extend from the game changer price level to current bar.
FILTER APPLICATION
Only candles that pass your configured filters qualify for game changer consideration. If wick exclusion is enabled, candles with large wicks and small bodies are ignored. If volume confirmation is enabled, only candles with above-average volume qualify. This ensures game changers represent legitimate market moves rather than aberrations.
PRACTICAL APPLICATIONS
FOR CRYPTOCURRENCY TRADERS
Crypto markets experience extreme volatility with occasional massive pump and dump candles that define entire trends. This indicator instantly identifies which candles represent true market structure shifts versus normal noise. Use the game changer levels as key support and resistance for entries, exits, and stop placement. The top pump often marks the local high to watch for breakouts while the top dump marks the local low for reversal trades.
FOR DAY TRADERS
Intraday charts contain hundreds of candles but only a few truly matter for the session outcome. Game changer detection filters out 98 percent of candles to show you the 2 percent that drove the actual price movement. Enter trades on the side of the strongest recent game changer. Use game changer levels as magnet prices where algorithmic trading often returns.
FOR SWING TRADERS
On daily and four-hour timeframes, game changers represent major institutional activity or news-driven moves. The top dump often marks capitulation selling that creates reversal opportunities. The top pump often marks FOMO buying that creates resistance levels. Swing traders can build positions knowing these levels will be defended or tested multiple times.
FOR VOLATILITY ANALYSIS
Understanding which candles created the most volatility helps assess market risk. Multiple game changers clustered together indicate unstable choppy conditions. Game changers separated by many neutral candles indicate trending stable conditions. Use this context to adjust position sizing and stop distances appropriately.
FOR SUPPORT AND RESISTANCE TRADING
Game changer candles create the strongest support and resistance levels because they represent prices where massive volume transacted in short time periods. These levels have higher probability of holding on retest compared to arbitrary moving averages or pivot points. Trade bounces off game changer levels or breakouts through them.
RECOMMENDED SETTINGS BY MARKET
CRYPTOCURRENCY 15-MINUTE TO 1-HOUR CHARTS
Candle Size Threshold: 2.0 percent
Body to Candle Ratio: 0.5
Volume Multiplier: 1.5 times average
Game Changer Lookback: 100 bars
Extreme Threshold: 3.5 percent
Enable Wick Filter: Yes
Enable Volume Confirmation: Yes
Minimum Rally Candles: 3
STOCKS DAILY CHARTS
Candle Size Threshold: 1.0 percent
Body to Candle Ratio: 0.6
Volume Multiplier: 2.0 times average
Game Changer Lookback: 50 bars
Extreme Threshold: 2.5 percent
Enable Wick Filter: Yes
Enable Volume Confirmation: Yes
Minimum Rally Candles: 2
FOREX 1-HOUR TO 4-HOUR CHARTS
Candle Size Threshold: 0.5 percent
Body to Candle Ratio: 0.5
Volume Multiplier: Not applicable
Game Changer Lookback: 80 bars
Extreme Threshold: 1.0 percent
Enable Wick Filter: Yes
Enable Volume Confirmation: No
Minimum Rally Candles: 3
SCALPING 1-MINUTE TO 5-MINUTE CHARTS
Candle Size Threshold: 0.8 percent
Body to Candle Ratio: 0.4
Volume Multiplier: 1.2 times average
Game Changer Lookback: 50 bars
Extreme Threshold: 1.5 percent
Enable Wick Filter: No
Enable Volume Confirmation: Yes
Minimum Rally Candles: 2
WHAT IS INCLUDED
Automatic identification of top 2 pump candles
Automatic identification of top 2 dump candles
Gold colored game changer labels with size differentiation
Gold colored candle bars for game changers
Horizontal reference lines from game changers to current price
Regular pump and dump detection with green and red candles
Rally sequence detection with background highlighting
Extreme move detection and labeling system
Real-time statistics dashboard with all key metrics
Percentage change debug mode for verification
Volume confirmation filter with adjustable multiplier
Wick exclusion filter with adjustable body ratio
Customizable lookback period from 20 to 500 bars
Consecutive candle counter for rally tracking
Alert system for game changers, pumps, dumps, and rallies
Works on all timeframes from 1 minute to monthly
Compatible with stocks, forex, cryptocurrency, and futures
UNDERSTANDING GAME CHANGERS
WHAT MAKES A CANDLE A GAME CHANGER
A game changer is not just a large move but the largest move within context. In a volatile crypto market, a 5 percent pump might not rank in the top 2. In a stable stock, a 2 percent pump could be the number 1 game changer. The indicator adapts to your specific instrument and timeframe to find what truly matters in that context.
WHY FOCUS ON TOP 2 ONLY
Markets are driven by a small number of significant moves rather than the average of all moves. By focusing exclusively on the top 2 in each direction, traders can ignore noise and concentrate on the price levels that actually matter for support, resistance, and momentum. This creates clarity in decision making.
GAME CHANGERS AS MARKET STRUCTURE
The top pump often marks the recent high that bulls must break to continue uptrend. The top dump often marks the recent low that bears must break to continue downtrend. These become the key levels around which all other price action rotates. Understanding this structure is essential for profitable trading.
GAME CHANGERS AS SENTIMENT INDICATORS
Consecutive pump game changers signal strong bullish sentiment and FOMO conditions. Consecutive dump game changers signal fear and capitulation. Alternating pump and dump game changers signal indecision and range conditions. Read the pattern of game changers to gauge market psychology.
VERIFICATION AND TESTING
HOW TO VERIFY ACCURACY
Enable Show Debug Info on Chart in the Testing and Debug settings group. This displays the percentage change calculation directly on every qualifying pump and dump candle. Manually verify by calculating open minus close divided by close multiplied by 100. The debug percentage should match your manual calculation exactly.
HOW TO TEST FILTERS
Toggle wick exclusion filter on and off while watching how many candles qualify. With filter on, candles with long wicks and small bodies should disappear. Toggle volume confirmation on and off to see how low-volume candles get excluded. Adjust the thresholds and watch the real-time impact on signal count.
HOW TO VERIFY GAME CHANGERS
Look at your chart and visually identify which candle had the biggest green body in the lookback period. The game changer number 1 pump label should be on that exact candle. Repeat for the biggest red candle to verify game changer number 1 dump. The rankings should match your visual assessment.
LOOKBACK PERIOD EFFECTS
Decrease the lookback period to 20 bars and watch game changers update to only recent moves. Increase to 500 bars and watch game changers potentially change to older historic moves. The optimal lookback balances recency with significance. Too short misses important levels, too long includes irrelevant history.
DASHBOARD INFORMATION GUIDE
STATUS ROW
Shows PUMPING when current candle qualifies as a pump, DUMPING when current candle qualifies as a dump, or NEUTRAL when current candle does not meet threshold requirements. This updates in real-time on every bar close.
CURRENT CHANGE ROW
Displays the percentage change of the current candle from its previous close. Positive percentages indicate bullish candle, negative indicate bearish candle. This number may or may not meet your threshold to qualify as pump or dump.
TOP PUMP NUMBER 1
The highest positive percentage change found in your lookback period. This candle is marked with the large gold GAME CHANGER NUMBER 1 label below it. Shows N/A if no pumps exist in the lookback period.
TOP PUMP NUMBER 2
The second highest positive percentage change found in your lookback period. Marked with smaller gold GAME CHANGER NUMBER 2 label. Shows N/A if only one or zero pumps exist.
TOP DUMP NUMBER 1
The highest negative percentage change magnitude found in your lookback period. This candle is marked with the large gold GAME CHANGER NUMBER 1 label above it. Shows N/A if no dumps exist.
TOP DUMP NUMBER 2
The second highest negative percentage change magnitude found in your lookback period. Marked with smaller gold GAME CHANGER NUMBER 2 label. Shows N/A if only one or zero dumps exist.
TOTAL PUMPS
Running count of all pump candles detected since you loaded the indicator on this chart. This number continuously increases as new qualifying pumps form. Resets when you reload the chart.
TOTAL DUMPS
Running count of all dump candles detected since chart load. Increases as new qualifying dumps form and resets on chart reload.
CONSECUTIVE
Shows the current count of consecutive pump or dump candles during an active rally. Displays 3 UP during a 3-candle pump rally or 5 DN during a 5-candle dump rally. Shows 0 when no rally is active.
ALERT SYSTEM
GAME CHANGER DETECTED ALERT
Triggers whenever the current candle becomes one of the top 2 pumps or top 2 dumps. This is the highest priority alert indicating a market-moving event just occurred. Use this alert for immediate notification of significant opportunities.
PUMP DETECTED ALERT
Triggers on every candle that qualifies as a pump according to your threshold and filter settings. This includes regular pumps and extreme pumps but excludes game changers which have their separate alert. Use for general upward momentum monitoring.
DUMP DETECTED ALERT
Triggers on every candle that qualifies as a dump according to your settings. Includes regular and extreme dumps but excludes game changers. Use for general downward momentum monitoring.
PUMP RALLY STARTED ALERT
Triggers when consecutive pump candles reach your minimum rally threshold. Indicates the beginning of a sustained upward movement sequence. Use to catch trends early.
DUMP RALLY STARTED ALERT
Triggers when consecutive dump candles reach your minimum rally threshold. Indicates the beginning of a sustained downward movement sequence. Use for trend following or reversal timing.
ALERT MESSAGE FORMAT
All alerts include the ticker symbol and current price using TradingView placeholders. Messages are descriptive and specify which type of signal triggered. Alerts work with TradingView notification system including email, SMS, webhook, and app notifications.
TECHNICAL SPECIFICATIONS
CALCULATION METHODOLOGY
Percentage change calculated as current close minus previous close divided by previous close multiplied by 100. Body ratio calculated as absolute value of close minus open divided by high minus low. Volume elevation calculated as current volume divided by 20-period simple moving average of volume. Game changer ranking uses absolute value comparison across entire lookback array.
PERFORMANCE CHARACTERISTICS
Lightweight calculations optimized for speed on all timeframes. No repainting of signals ensuring all triggers are final on bar close. Variables properly scoped with var keyword for memory efficiency. Maximum bars back set to 500 to prevent excessive historical loading. Updates in real-time on every bar close without lag.
COMPATIBILITY
Works on all TradingView plans including free, pro, and premium. Compatible with stocks, forex, cryptocurrency, futures, indices, and commodities. Functions correctly on all timeframes from 1 second to monthly. No external data requests ensuring fast loading. Overlay true setting places directly on price chart.
RISK DISCLAIMER
This indicator is a technical analysis tool for identifying momentum and should not be used as the sole basis for trading decisions. Game changer levels can be broken during strong trends and are not guaranteed support or resistance. Pump and dump detection does not predict future price direction. Always use proper risk management with stop losses on every trade. Combine this indicator with other forms of analysis including fundamentals, market context, and risk assessment. Practice on demo accounts before live trading. Past performance of game changer signals does not guarantee future results. Trading carries substantial risk of loss and is not suitable for all investors. The creator is not responsible for trading losses incurred while using this tool.
SUPPORT AND UPDATES
Regular updates based on user feedback and market evolution. Built following PineCoders industry standards and best practices for code quality. Clean well-documented code structure for transparency and auditability. Optimized performance across all timeframes and instruments. Active development with continuous improvements and feature additions.
WHY CHOOSE ZS GAME CHANGER PUMP AND DUMP DETECTOR
Focuses on what matters by highlighting only the top 2 moves in each direction instead of cluttering your chart with every small fluctuation. Saves time by automatically identifying the most significant candles rather than requiring manual scanning. Provides clarity through visual gold labels and reference lines that make game changers unmistakable. Adapts to any market with customizable thresholds for volatility and volume. Eliminates noise with advanced wick and volume filters ensuring signal quality. Offers verification through debug mode proving calculations are accurate and trustworthy. Includes comprehensive statistics showing exact percentages and counts. Works everywhere across all markets, timeframes, and instruments without modification.
Transform your chart analysis by focusing exclusively on the game-changing moments that define trends and create opportunities.
Version 1.1 | Created by Zakaria Safri | Pine Script Version 5 | PineCoders Compliant
ZS Master Vision Pro - Advanced Multi-Timeframe Trading SystemZS MASTER VISION PRO - PROFESSIONAL TRADING SUITE
Created by Zakaria Safri
A comprehensive, all-in-one trading system combining multiple proven technical analysis methods into a single, powerful indicator. Designed for traders who demand precision, clarity, and actionable signals across all timeframes.
KEY FEATURES
CORE TREND ALGORITHM
Adaptive ATR-based trend detection with dynamic support and resistance zones. Features Type A and Type B signal modes for different trading styles, strong signal detection in key reversal zones, and optional EMA source smoothing for noise reduction.
MULTI-LAYER EMA CLOUD SYSTEM
Five customizable EMA cloud layers for multi-timeframe analysis with theme-adaptive color coding across five professional themes. Optional line display for detailed MA tracking with configurable periods from scalping to position trading.
WAVE TREND OSCILLATOR
Advanced momentum oscillator with channel-based calculations featuring smart reversal detection at extreme overbought and oversold levels. Includes directional strength confirmation and customizable sensitivity with adjustable reaction periods.
DIVERGENCE SCANNER
Detects four types of divergence automatically:
- Regular Bullish: Price making lower lows while oscillator making higher lows
- Regular Bearish: Price making higher highs while oscillator making lower highs
- Hidden Bullish: Trend continuation signals in uptrends
- Hidden Bearish: Trend continuation signals in downtrends
Automatic fractal-based detection with clear visual labels on chart.
MARKET BIAS INDICATOR
Heikin Ashi-based trend strength analysis with real-time bias calculation showing Bullish or Bearish combined with Strong or Weak conditions. Smoothed for cleaner signals and perfect for trend confirmation.
MOMENTUM SYSTEM
Proprietary momentum calculation using adaptive smoothing with growing and falling state detection. Normalized values for consistent interpretation and responsive to rapid market changes.
DYNAMIC SUPPORT AND RESISTANCE
Automatic pivot-based support and resistance level detection with adjustable left and right bar lookback. Non-repainting levels with visual clarity through color-coded lines.
LIVE INFORMATION DASHBOARD
Real-time market analysis panel displaying current trend direction, market bias based on Heikin Ashi, Wave Trend status and value, and momentum trend with state. Customizable display options with theme-adaptive colors.
VISUAL CUSTOMIZATION
FIVE PROFESSIONAL COLOR THEMES:
Pro - Modern green and red color scheme (default)
Classic - Traditional teal and red combination
Cyberpunk - Neon cyan and magenta contrast
Ocean - Blue and orange contrast
Sunset - Gold and red warmth
SIGNAL STYLES:
Labels with emoji indicators (BUY with rocket, SELL with bear, STRONG with lightning)
Arrows for clean minimal appearance
Triangles for classic approach
DISPLAY OPTIONS:
Color-coded candles following trend direction
Trend background highlighting for instant trend recognition
Optional EMA line display for detailed analysis
Adjustable transparency levels for personal preference
SMART ALERTS
Pre-configured alert conditions for all major signals:
Buy signals for standard entry opportunities
Sell signals for standard exit or short opportunities
Strong buy signals for high-confidence long entries
Strong sell signals for high-confidence short entries
Bullish divergence detection alerts
Bearish divergence detection alerts
Alert messages automatically include ticker symbol, current price, and specific signal type for quick decision making.
HOW TO USE
FOR TREND TRADERS:
Enable EMA Clouds with focus on Cloud 5 featuring 50 and 200 period moving averages. Wait for trend background color change to confirm direction. Enter on STRONG signals aligned with higher timeframe trend direction. Use support and resistance levels for strategic exits.
FOR SWING TRADERS:
Enable Wave Trend Oscillator information display. Look for oversold and overbought reversal setups. Confirm potential reversals with divergence scanner. Enter on smart reversal signals with proper risk management.
FOR SCALPERS:
Use Type B signal mode for more frequent trading signals. Enable Cloud 1 with 5 and 13 periods for quick trend confirmation. Focus on momentum growing and falling states for entry timing. Take quick entries on regular buy and sell signals.
FOR POSITION TRADERS:
Use Type A mode with higher ATR multiplier set to 3.0 or above. Enable only Cloud 5 with 50 and 200 periods for major trend confirmation. Only take STRONG signals for highest probability setups. Hold positions through minor pullbacks and noise.
RECOMMENDED SETTINGS
STOCKS ON DAILY TIMEFRAME:
Trend Period: 180
ATR Period: 155
ATR Multiplier: 2.1
Signal Mode: Type A
FOREX ON HOURLY AND 4-HOUR TIMEFRAMES:
Trend Period: 150
ATR Period: 120
ATR Multiplier: 2.5
Signal Mode: Type A
CRYPTOCURRENCY ON 15-MINUTE AND 1-HOUR TIMEFRAMES:
Trend Period: 100
ATR Period: 80
ATR Multiplier: 3.0
Signal Mode: Type B
SCALPING ON 1-MINUTE AND 5-MINUTE TIMEFRAMES:
Trend Period: 50
ATR Period: 40
ATR Multiplier: 2.0
Signal Mode: Type B
WHAT IS INCLUDED
Trend Analysis using ATR-based adaptive algorithm
Five EMA Cloud Layers for multi-timeframe confluence
Wave Trend Oscillator for momentum and reversal detection
Divergence Scanner detecting four types of divergence
Market Bias using Heikin Ashi-based trend strength
Momentum System with advanced momentum tracking
Support and Resistance Levels with automatic pivot detection
Live Dashboard showing real-time market analysis
Smart Alerts featuring six pre-configured alert types
Five Color Themes offering professional visual options
TECHNICAL DETAILS
CALCULATION METHODS:
Average True Range (ATR) for volatility adaptation
Exponential Moving Average (EMA) and Simple Moving Average (SMA) for trend smoothing
Wave Trend channel oscillator for momentum analysis
Fractal-based divergence detection algorithm
Heikin Ashi transformation for bias calculation
Logarithmic momentum calculation for precision
PERFORMANCE CHARACTERISTICS:
Optimized for maximum speed and efficiency
No repainting signals ensuring reliability
Works on all timeframes from 1 minute to monthly
Compatible with all instruments including stocks, forex, crypto, and futures
RISK DISCLAIMER
This indicator is a technical analysis tool and should not be used as the sole basis for trading decisions. Always use proper risk management and never risk more than you can afford to lose. Combine with other analysis methods and practice on demo accounts first. Past performance does not guarantee future results. Trading carries substantial risk and is not suitable for all investors.
SUPPORT AND UPDATES
Regular updates and continuous improvements
Based on proven technical analysis principles
Developed following Pine Coders best practices and standards
Clean, well-documented, and optimized code structure
WHY CHOOSE ZS MASTER VISION PRO
All-in-one solution eliminating the need for multiple indicators
Highly customizable to adapt to your specific trading style
Professional grade analysis with institutional-quality standards
Clean interface that is not cluttered or confusing
Works everywhere across all markets and all timeframes
Smart signals filtered for quality over quantity
Beautiful design featuring five professional color themes
Active development with regular improvements and updates
Transform your trading with ZS Master Vision Pro today.
Version 2.0 | Created by Zakaria Safri | Pine Script Version 5
Elite_Pro_SignalsA sophisticated trading indicator that combines 8 powerful technical factors into a single confidence score to identify high-probability reversal signals.
8-Factor Confidence Scoring - Weighted analysis of multiple technical aspects
Smart Trend Alignment - Multi-timeframe EMA convergence
Advanced Pattern Recognition - Pin Bars, Engulfing, Inside Bars, Hammer/Shooting Star
Supply/Demand Zones - Automatic key level detection
Support/Resistance Confluence - Price action at significant levels
⚡ Smart Filters
Market Regime Detection - Avoid choppy/low-volatility conditions
Volume Confirmation - Ensure institutional participation
Liquidity Sweep Validation - Smart money movement detection
Candle Quality Filter - Eliminate false signals from tiny candles
🔧 How It Works
Confidence Scoring System (0-100%)
text
Wick Strength (30%) + Trend Alignment (25%) + Pattern Recognition (15%) +
Supply/Demand Zones (12%) + Support/Resistance (10%) + RSI Momentum (5%) +
Volume & Liquidity (5%)
Signal Generation
🟢 BUY Signals - Bullish rejection + Uptrend + High confidence
🔴 SELL Signals - Bearish rejection + Downtrend + High confidence
🎨 Visual Features
Clear Buy/Sell Arrows - Easy-to-spot signals
Confidence Background - Color-coded confidence levels
Info Table - Real-time metrics and analysis
Multi-Timeframe EMAs - Trend direction visualization
Professional Alerts - Real-time notifications
⚙️ Customization
Confidence Weights
Adjust the importance of each factor to match your trading style
Strategy Parameters
EMA periods (Fast: 20, Slow: 50)
RSI levels (Oversold: 25, Overbought: 80)
Minimum confidence threshold (70% recommended)
Advanced Filters
Volume multiplier settings
Liquidity sweep sensitivity
Market regime filters
Zone detection parameters
📈 Recommended Usage
Timeframes
Primary: 5-minute to 1-hour charts
Best Results: 15-minute with 1-hour trend alignment
Markets
Forex Pairs (EURUSD, GBPUSD, XAUUSD)
Indices (US30, NAS100, DE40)
Commodities (Gold, Oil)
Trading Sessions
London & New York overlap (Highest volatility)
Avoid Asian session (Low signal quality)
🔍 Signal Interpretation
High-Confidence Signals (80%+)
Strong trend alignment
Clear rejection patterns
Volume confirmation
Multiple confluence factors
Medium-Confidence Signals (60-80%)
Good setup but missing 1-2 factors
Requires additional confirmation
Low-Confidence Signals (<60%)
Avoid trading
Wait for better setups
Elite_Pro SignalsTrial version to get the signals. used various indicators including candle pattern. Works on 5 min candle but checks multi time frames to see if it is inline with 15 min and 1 hr. Best works on Gold and Indices.
多周期趋势动量面板加强版（Multi-Timeframe Trend Momentum Panel - User Guide）多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)(english explanation follows.)
📖 指标功能详解 (精简版):
🎯 核心功能:
1. 多周期趋势分析 同时监控8个时间周期(1m/5m/15m/1H/4H/D/W/M)
2. 4维度投票系统 MA趋势+RSI动量+MACD+布林带综合判断
3. 全球交易时段 可视化亚洲/伦敦/纽约交易时间
4. 趋势强度评分 0100%量化市场力量
5. 智能警报 强势多空信号自动推送
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📚 重要名词解释:
🔵 趋势状态 (MA均线分析):
名词 含义 信号强度
强势多头 快MA远高于慢MA(差值≥0.35%) ⭐⭐⭐⭐⭐ 做多
多头倾向 快MA略高于慢MA(差值<0.35%) ⭐⭐⭐ 谨慎做多
震荡 快慢MA缠绕,无明确方向 ⚠️ 观望
空头倾向 快MA略低于慢MA ⭐⭐⭐ 谨慎做空
强势空头 快MA远低于慢MA ⭐⭐⭐⭐⭐ 做空
简单理解: 快MA就像短跑运动员(反应快),慢MA是长跑运动员(稳定)。短跑远超长跑=强势多头,反之=强势空头。
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🟠 动量状态 (RSI力度分析):
名词 含义 操作建议
动量上攻↗ RSI>60且快速上升 强烈买入信号
动量高位 RSI>60但上升变慢 警惕回调,可减仓
动量中性 RSI在4060之间,平稳 等待方向明确
动量低位 RSI<40但下跌变慢 警惕反弹,可止盈
动量下压↘ RSI<40且快速下降 强烈卖出信号
简单理解: RSI就像汽车速度表。"动量上攻"=油门踩到底加速,"动量高位"=已经很快但不再加速了。
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🟣 辅助信号:
MACD:
• MACD多头 = 柱状图>0 = 买方力量强
• MACD空头 = 柱状图<0 = 卖方力量强
布林带(BB):
• BB超买 = 价格在布林带上轨附近 = 可能回调
• BB超卖 = 价格在布林带下轨附近 = 可能反弹
• BB中轨 = 价格在中间位置 = 平衡状态
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💡 快速上手 3步看懂面板:
第1步: 看"综合结论标签" (K线上方)
• 绿色"多头占优" → 可以做多
• 红色"空头占优" → 可以做空
• 橙色"震荡/均衡" → 观望
第2步: 看"票数 多/空" (面板最下方)
• 多头票数远大于空头 (差距>2) → 趋势强
• 票数接近 (差距<1) → 震荡市
第3步: 看"趋势强度" (综合标签中)
• 强度>70% → 强势趋势,可重仓
• 强度5070% → 中等趋势,正常仓位
• 强度<50% → 弱势,轻仓或观望
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🎨 时段背景色含义:
• 紫色背景 = 亚洲时段 (东京交易时间) 波动较小
• 橙色背景 = 伦敦时段 (欧洲交易时间) 波动增大
• 蓝色背景 = 纽约凌晨 美盘准备阶段
• 红色背景 = 纽约关键5分钟 (09:3009:35) ⚠️ 最重要! 市场最活跃,趋势易形成
• 绿色背景 = 纽约上午后段 延续早盘趋势
交易建议: 重点关注红色关键时段,这5分钟往往决定全天方向!
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⚙️ 三大市场推荐设置
🥇 黄金: Hull MA 12/EMA 34, 阈值0.250.35%
₿ 比特币: EMA 21/EMA 55, 阈值0.801.20%
💎 以太坊: TEMA 21/EMA 55, 阈值0.600.80%
参数优化建议
黄金 (XAUUSD)
快速MA: Hull MA 12 (超灵敏捕捉黄金快速波动)
慢速MA: EMA 34 (斐波那契数列)
RSI周期: 9 (加快反应)
强趋势阈值: 0.25%
周期: 5, 15, 60, 240, 1440
比特币 (BTCUSD)
快速MA: EMA 21
慢速MA: EMA 55
RSI周期: 14
强趋势阈值: 0.8% (波动大,阈值需提高)
周期: 15, 60, 240, D, W
外汇 EUR/USD
快速MA: TEMA 10 (快速响应)
慢速MA: T3 30, 因子0.7 (平滑噪音)
RSI周期: 14
强趋势阈值: 0.08% (外汇波动小)
周期: 5, 15, 60, 240, 1440
📖 Indicator Function Details (Concise Version):
🎯 Core Functions:
1. MultiTimeframe Trend Analysis Monitors 8 timeframes simultaneously (1m/5m/15m/1H/4H/D/W/M)
2. 4Dimensional Voting System Comprehensive judgment based on MA trend + RSI momentum + MACD + Bollinger Bands
3. Global Trading Sessions Visualizes Asia/London/New York trading hours
4. Trend Strength Score Quantifies market strength from 0100%
5. Smart Alerts Automatically pushes strong bullish/bearish signals
📚 Key Term Explanations:
🔵 Trend Status (MA Analysis):
| Term | Meaning | Signal Strength |
| | | |
| Strong Bull | Fast MA significantly > Slow MA (Diff ≥0.35%) | ⭐⭐⭐⭐⭐ Long |
| Bullish Bias | Fast MA slightly > Slow MA (Diff <0.35%) | ⭐⭐⭐ Caution Long |
| Ranging | MAs intertwined, no clear direction | ⚠️ Wait & See |
| Bearish Bias | Fast MA slightly < Slow MA | ⭐⭐⭐ Caution Short |
| Strong Bear | Fast MA significantly < Slow MA | ⭐⭐⭐⭐⭐ Short |
Simple Understanding: Fast MA = sprinter (fast reaction), Slow MA = longdistance runner (stable). Sprinter far ahead = Strong Bull, opposite = Strong Bear.
🟠 Momentum Status (RSI Analysis):
| Term | Meaning | Trading Suggestion |
| | | |
| Momentum Up ↗ | RSI >60 & rising rapidly | Strong Buy Signal |
| Momentum High | RSI >60 but rising slower | Watch for pullback, consider reducing position |
| Momentum Neutral | RSI between 4060, stable | Wait for clearer direction |
| Momentum Low | RSI <40 but falling slower | Watch for rebound, consider taking profit |
| Momentum Down ↘ | RSI <40 & falling rapidly | Strong Sell Signal |
Simple Understanding: RSI = car speedometer. "Momentum Up" = full throttle acceleration, "Momentum High" = already fast but not accelerating further.
🟣 Auxiliary Signals:
MACD:
MACD Bullish = Histogram >0 = Strong buyer power
MACD Bearish = Histogram <0 = Strong seller power
Bollinger Bands (BB):
BB Overbought = Price near upper band = Possible pullback
BB Oversold = Price near lower band = Possible rebound
BB Middle = Price near middle band = Balanced state
💡 Quick Start 3 Steps to Understand the Panel:
Step 1: Check "Composite Conclusion Label" (Above the chart)
Green "Bulls Favored" → Consider Long
Red "Bears Favored" → Consider Short
Orange "Ranging/Balanced" → Wait & See
Step 2: Check "Votes Bull/Bear" (Bottom of the panel)
Bull votes significantly > Bear votes (Difference >2) → Strong Trend
Votes close (Difference <1) → Ranging Market
Step 3: Check "Trend Strength" (In the composite label)
Strength >70% → Strong Trend, consider heavier position
Strength 5070% → Moderate Trend, normal position size
Strength <50% → Weak Trend, light position or wait & see
🎨 Trading Session Background Color Meanings:
Purple = Asian Session (Tokyo hours) Lower volatility
Orange = London Session (European hours) Increased volatility
Blue = NY Early Morning US session preparation phase
Red = NY Critical 5 Minutes (09:3009:35) ⚠️ Most Important! Market most active, trends easily form
Green = NY Late Morning Continuation of early session trend
Trading Tip: Focus on the red critical period; these 5 minutes often determine the day's direction!
⚙️ Recommended Settings for Three Major Markets
🥇 Gold (XAUUSD):
Fast MA: Hull MA 12 (Highly sensitive for gold's fast moves)
Slow MA: EMA 34 (Fibonacci number)
RSI Period: 9 (Faster reaction)
Strong Trend Threshold: 0.25%
Timeframes: 5, 15, 60, 240, 1440
₿ Bitcoin (BTCUSD):
Fast MA: EMA 21
Slow MA: EMA 55
RSI Period: 14
Strong Trend Threshold: 0.8% (High volatility, requires higher threshold)
Timeframes: 15, 60, 240, D, W
💎 Ethereum (ETHUSD):
Fast MA: TEMA 21
Slow MA: EMA 55
RSI Period: 14
Strong Trend Threshold: 0.600.80%
Timeframes: 15, 60, 240, D, W
💱 Forex EUR/USD:
Fast MA: TEMA 10 (Fast response)
Slow MA: T3 30, Factor 0.7 (Smooths noise)
RSI Period: 14
Strong Trend Threshold: 0.08% (Forex has low volatility)
Timeframes: 5, 15, 60, 240, 1440
多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)多周期趋势动量面板(Multi-Timeframe Trend Momentum Panel - User Guide)(english explanation follows.)
📖 指标功能详解 (精简版):
🎯 核心功能:
1. 多周期趋势分析 同时监控8个时间周期(1m/5m/15m/1H/4H/D/W/M)
2. 4维度投票系统 MA趋势+RSI动量+MACD+布林带综合判断
3. 全球交易时段 可视化亚洲/伦敦/纽约交易时间
4. 趋势强度评分 0100%量化市场力量
5. 智能警报 强势多空信号自动推送
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📚 重要名词解释:
🔵 趋势状态 (MA均线分析):
名词 含义 信号强度
强势多头 快MA远高于慢MA(差值≥0.35%) ⭐⭐⭐⭐⭐ 做多
多头倾向 快MA略高于慢MA(差值<0.35%) ⭐⭐⭐ 谨慎做多
震荡 快慢MA缠绕,无明确方向 ⚠️ 观望
空头倾向 快MA略低于慢MA ⭐⭐⭐ 谨慎做空
强势空头 快MA远低于慢MA ⭐⭐⭐⭐⭐ 做空
简单理解: 快MA就像短跑运动员(反应快),慢MA是长跑运动员(稳定)。短跑远超长跑=强势多头,反之=强势空头。
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🟠 动量状态 (RSI力度分析):
名词 含义 操作建议
动量上攻↗ RSI>60且快速上升 强烈买入信号
动量高位 RSI>60但上升变慢 警惕回调,可减仓
动量中性 RSI在4060之间,平稳 等待方向明确
动量低位 RSI<40但下跌变慢 警惕反弹,可止盈
动量下压↘ RSI<40且快速下降 强烈卖出信号
简单理解: RSI就像汽车速度表。"动量上攻"=油门踩到底加速,"动量高位"=已经很快但不再加速了。
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🟣 辅助信号:
MACD:
• MACD多头 = 柱状图>0 = 买方力量强
• MACD空头 = 柱状图<0 = 卖方力量强
布林带(BB):
• BB超买 = 价格在布林带上轨附近 = 可能回调
• BB超卖 = 价格在布林带下轨附近 = 可能反弹
• BB中轨 = 价格在中间位置 = 平衡状态
________________________________________
💡 快速上手 3步看懂面板:
第1步: 看"综合结论标签" (K线上方)
• 绿色"多头占优" → 可以做多
• 红色"空头占优" → 可以做空
• 橙色"震荡/均衡" → 观望
第2步: 看"票数 多/空" (面板最下方)
• 多头票数远大于空头 (差距>2) → 趋势强
• 票数接近 (差距<1) → 震荡市
第3步: 看"趋势强度" (综合标签中)
• 强度>70% → 强势趋势,可重仓
• 强度5070% → 中等趋势,正常仓位
• 强度<50% → 弱势,轻仓或观望
________________________________________
🎨 时段背景色含义:
• 紫色背景 = 亚洲时段 (东京交易时间) 波动较小
• 橙色背景 = 伦敦时段 (欧洲交易时间) 波动增大
• 蓝色背景 = 纽约凌晨 美盘准备阶段
• 红色背景 = 纽约关键5分钟 (09:3009:35) ⚠️ 最重要! 市场最活跃,趋势易形成
• 绿色背景 = 纽约上午后段 延续早盘趋势
交易建议: 重点关注红色关键时段,这5分钟往往决定全天方向!
________________________________________
⚙️ 三大市场推荐设置
🥇 黄金: Hull MA 12/EMA 34, 阈值0.250.35%
₿ 比特币: EMA 21/EMA 55, 阈值0.801.20%
💎 以太坊: TEMA 21/EMA 55, 阈值0.600.80%
参数优化建议
黄金 (XAUUSD)
快速MA: Hull MA 12 (超灵敏捕捉黄金快速波动)
慢速MA: EMA 34 (斐波那契数列)
RSI周期: 9 (加快反应)
强趋势阈值: 0.25%
周期: 5, 15, 60, 240, 1440
比特币 (BTCUSD)
快速MA: EMA 21
慢速MA: EMA 55
RSI周期: 14
强趋势阈值: 0.8% (波动大,阈值需提高)
周期: 15, 60, 240, D, W
外汇 EUR/USD
快速MA: TEMA 10 (快速响应)
慢速MA: T3 30, 因子0.7 (平滑噪音)
RSI周期: 14
强趋势阈值: 0.08% (外汇波动小)
周期: 5, 15, 60, 240, 1440
📖 Indicator Function Details (Concise Version):
🎯 Core Functions:
1. MultiTimeframe Trend Analysis Monitors 8 timeframes simultaneously (1m/5m/15m/1H/4H/D/W/M)
2. 4Dimensional Voting System Comprehensive judgment based on MA trend + RSI momentum + MACD + Bollinger Bands
3. Global Trading Sessions Visualizes Asia/London/New York trading hours
4. Trend Strength Score Quantifies market strength from 0100%
5. Smart Alerts Automatically pushes strong bullish/bearish signals
📚 Key Term Explanations:
🔵 Trend Status (MA Analysis):
| Term | Meaning | Signal Strength |
| | | |
| Strong Bull | Fast MA significantly > Slow MA (Diff ≥0.35%) | ⭐⭐⭐⭐⭐ Long |
| Bullish Bias | Fast MA slightly > Slow MA (Diff <0.35%) | ⭐⭐⭐ Caution Long |
| Ranging | MAs intertwined, no clear direction | ⚠️ Wait & See |
| Bearish Bias | Fast MA slightly < Slow MA | ⭐⭐⭐ Caution Short |
| Strong Bear | Fast MA significantly < Slow MA | ⭐⭐⭐⭐⭐ Short |
Simple Understanding: Fast MA = sprinter (fast reaction), Slow MA = longdistance runner (stable). Sprinter far ahead = Strong Bull, opposite = Strong Bear.
🟠 Momentum Status (RSI Analysis):
| Term | Meaning | Trading Suggestion |
| | | |
| Momentum Up ↗ | RSI >60 & rising rapidly | Strong Buy Signal |
| Momentum High | RSI >60 but rising slower | Watch for pullback, consider reducing position |
| Momentum Neutral | RSI between 4060, stable | Wait for clearer direction |
| Momentum Low | RSI <40 but falling slower | Watch for rebound, consider taking profit |
| Momentum Down ↘ | RSI <40 & falling rapidly | Strong Sell Signal |
Simple Understanding: RSI = car speedometer. "Momentum Up" = full throttle acceleration, "Momentum High" = already fast but not accelerating further.
🟣 Auxiliary Signals:
MACD:
MACD Bullish = Histogram >0 = Strong buyer power
MACD Bearish = Histogram <0 = Strong seller power
Bollinger Bands (BB):
BB Overbought = Price near upper band = Possible pullback
BB Oversold = Price near lower band = Possible rebound
BB Middle = Price near middle band = Balanced state
💡 Quick Start 3 Steps to Understand the Panel:
Step 1: Check "Composite Conclusion Label" (Above the chart)
Green "Bulls Favored" → Consider Long
Red "Bears Favored" → Consider Short
Orange "Ranging/Balanced" → Wait & See
Step 2: Check "Votes Bull/Bear" (Bottom of the panel)
Bull votes significantly > Bear votes (Difference >2) → Strong Trend
Votes close (Difference <1) → Ranging Market
Step 3: Check "Trend Strength" (In the composite label)
Strength >70% → Strong Trend, consider heavier position
Strength 5070% → Moderate Trend, normal position size
Strength <50% → Weak Trend, light position or wait & see
🎨 Trading Session Background Color Meanings:
Purple = Asian Session (Tokyo hours) Lower volatility
Orange = London Session (European hours) Increased volatility
Blue = NY Early Morning US session preparation phase
Red = NY Critical 5 Minutes (09:3009:35) ⚠️ Most Important! Market most active, trends easily form
Green = NY Late Morning Continuation of early session trend
Trading Tip: Focus on the red critical period; these 5 minutes often determine the day's direction!
⚙️ Recommended Settings for Three Major Markets
🥇 Gold (XAUUSD):
Fast MA: Hull MA 12 (Highly sensitive for gold's fast moves)
Slow MA: EMA 34 (Fibonacci number)
RSI Period: 9 (Faster reaction)
Strong Trend Threshold: 0.25%
Timeframes: 5, 15, 60, 240, 1440
₿ Bitcoin (BTCUSD):
Fast MA: EMA 21
Slow MA: EMA 55
RSI Period: 14
Strong Trend Threshold: 0.8% (High volatility, requires higher threshold)
Timeframes: 15, 60, 240, D, W
💎 Ethereum (ETHUSD):
Fast MA: TEMA 21
Slow MA: EMA 55
RSI Period: 14
Strong Trend Threshold: 0.600.80%
Timeframes: 15, 60, 240, D, W
💱 Forex EUR/USD:
Fast MA: TEMA 10 (Fast response)
Slow MA: T3 30, Factor 0.7 (Smooths noise)
RSI Period: 14
Strong Trend Threshold: 0.08% (Forex has low volatility)
Timeframes: 5, 15, 60, 240, 1440
G_GMMA• Comprehensive GMMA Visualization: It plots six fast EMAs and six slow EMAs, clearly distinguishing short term and long term trends. The indicator fills the space between the fastest and slowest EMAs in each group, turning the moving averages into easily identifiable ribbons rather than a mass of overlapping lines.
• Customizable Appearance: Users can adjust the colors of the fast and slow EMA lines, the fill colors of each ribbon, and the overall line thickness. This makes it easy to tailor the chart to personal preferences or trading templates.
• Dynamic Background Shading: The script can shade the chart’s background depending on whether the fast ribbon is above or below the slow ribbon, giving a quick visual cue for trend direction (uptrend vs. downtrend).
• Touch Alert System: Up to three different EMA lengths can be monitored for “touch” events. When price touches a selected EMA (e.g., 20 , 50 or 200 period EMA), the indicator triggers an alert condition and plots a small circle on the chart at the contact point. This helps traders catch precise entry or exit signals without staring at the screen.
• Flexible Input: Both fast and slow EMA lengths, colors, and alert parameters are user adjustable from the indicator’s settings. This allows the same script to be used on different instruments (e.g., Gold, forex pairs) and time frames by simply changing the period values.
• Trend Sensitive Support/Resistance: By treating the slow EMA ribbon as a dynamic support/resistance zone, the indicator helps traders identify where price is likely to stall or reverse. Combining this with the touch alerts makes it well suited for scalping or intraday trades.
Europe Session LinesThis simple script marks the start of the European trading sessions:
08:00 a.m. London trading session
09:00 a.m. Frankfurt trading session
The settings of the lines can be changed. (thickness, colour, type).
It can be used on Futures and CFDs for example for FDAX, FTSE100 but also for GOLD, Silver and EURO- and GBP based FX pairs as supply or demand zone with the change of character trading setup.
