PROFABIGHI_CAPITAL Ratio🌟 Overview
The PROFABIGHI_CAPITAL Ratio Tracker is a comprehensive multi-asset performance dashboard designed for cryptocurrency portfolio analysis , evaluating up to 33 altcoins against a customizable benchmark using six key quantitative metrics: alpha for excess returns, beta for relative volatility, Sharpe ratio for overall risk-adjusted performance, Sortino ratio for downside risk focus, omega ratio for probability-weighted gain-loss assessment, and rate of change (ROC) for momentum tracking. It aggregates these metrics into unified composite scores for each asset, enabling traders to rank and compare opportunities through intuitive table-based visualizations , median benchmarking , and top-performer highlights , all while supporting selective metric activation, adjustable parameters, and real-time alerts for systematic decision-making in volatile markets.
⚙️ Metrics Selection
- Toggle for enabling alpha calculations to quantify an asset's unique performance beyond benchmark movements , ideal for identifying true outperformance in diversified portfolios
- Toggle for activating beta measurements to evaluate how closely an asset mirrors benchmark volatility , helping assess diversification benefits or leverage exposure
- Toggle for incorporating Sharpe ratio to measure returns per unit of total risk , providing a standardized benchmark for comparing asset efficiency across varying volatility profiles
- Toggle for including Sortino ratio to emphasize returns adjusted for harmful downside moves only, particularly useful in asymmetric markets like crypto where upside swings are desirable
- Toggle for utilizing omega ratio to analyze the full return distribution by weighting probable gains against losses relative to a target threshold , capturing tail risks and skewness effects
- Toggle for adding rate of change to capture short-term momentum trends , complementing longer-term risk metrics with directional conviction signals
- Modular activation allows traders to tailor the analysis to specific philosophies, such as risk-averse setups focusing on Sortino and omega or momentum-driven approaches emphasizing ROC alongside Sharpe
- Computational efficiency through conditional enabling, ensuring only selected metrics consume resources while maintaining flexibility for evolving market conditions or strategy refinements
🎯 Alpha and Beta Parameters
- Adjustable lookback period for alpha and beta computations, balancing statistical robustness with responsiveness —longer horizons smooth noise for stable estimates, shorter ones highlight recent regime shifts
- Customizable benchmark symbol selection, such as broad market cap indices or sector-specific aggregates , to define the reference for relative performance evaluation and ensure meaningful comparisons
- Alpha derivation as the intercept in a regression of asset returns against benchmark returns , revealing skill-based outperformance after accounting for systematic market exposure
- Beta estimation via covariance divided by benchmark variance , quantifying sensitivity to market moves —values above 1 signal amplified volatility for growth-oriented allocations , below 1 indicate defensive traits
- Shared lookback application across both metrics for consistency, with higher values promoting trend-following reliability and lower values enabling tactical adjustments to intraday or weekly dynamics
- Conditional benchmark data fetching only when alpha or beta is active, optimizing script performance by avoiding unnecessary external data requests in lightweight configurations
- Tooltip-guided parameter explanations emphasizing trade-offs between smoothness and reactivity, aiding users in aligning settings with their timeframe and risk tolerance
- Integration with daily return series for precise regression inputs, ensuring calculations reflect realistic percentage-based movements rather than absolute price changes
⚡ Sharpe Ratio Parameters
- Rolling period for mean return and volatility estimation , where shorter windows capture recent performance spikes for agile monitoring, and longer ones provide trend-stable assessments
- Exponential moving average smoothing length to filter daily fluctuations in raw ratios, reducing visual noise while preserving signals of genuine risk-return shifts
- Daily return computation via price changes divided by prior close , standardizing inputs for cross-asset comparability regardless of nominal price levels
- Mean return via simple moving average over the period, representing average daily excess as the reward component in the risk-adjusted formula
- Standard deviation of returns as the risk denominator , capturing total volatility including both upside and downside deviations for holistic efficiency gauging
- Raw ratio as mean divided by standard deviation , with zero-volatility safeguards to prevent errors during flat periods , defaulting to neutral performance
- Annualization through multiplication by the square root of 365 , converting daily metrics to yearly equivalents for intuitive benchmarking against industry standards
- Smoothed and annualized output for each asset, enabling direct ranking of risk efficiency —higher values highlight superior return generation per volatility unit
🎯 Sortino Ratio Parameters
- Extended lookback for downside deviation accumulation , favoring longer periods for reliable negative return sampling in sporadic drawdown environments
- Annual risk-free rate input as the downside threshold , adjustable to reflect opportunity costs like bond yields or inflation , with zero default treating all losses as harmful
- Smoothing period via EMA to stabilize the ratio against window shifts , mirroring Sharpe approach but tailored to the selective nature of downside focus
- Periodic returns calculated as close-to-prior ratios minus one, ensuring percentage consistency for multi-asset analysis
- Effective period adaptation to available bars, allowing early calculations with shorter windows that expand over time for progressive accuracy
- Downside squared deviations summed only for underperformance instances , divided by period count , then square-rooted for standard deviation equivalent
- Raw ratio as excess mean return over downside deviation , scaled annually via square root scaling , emphasizing protection against capital erosion
- Smoothed final values per asset, rewarding strategies that minimize harmful volatility while ignoring beneficial upside dispersion common in crypto rallies
🔄 Omega Ratio Parameters
- Calculation period for return distribution sampling , longer horizons capturing fuller gain-loss spectra for robust probability weighting
- Target return threshold per period, defining success boundaries —zero treats positives as gains , positives add hurdles for conservative analysis
- EMA smoothing to dampen ratio swings from individual extreme returns entering or exiting the window, maintaining trend clarity
- Periodic returns derived similarly to other ratios, with decimal conversion of target for precise excess/shortfall computations
- Cumulative above-target excesses summed for gains , below-target shortfalls for losses , via explicit loop over historical series
- Raw ratio as gains divided by losses , with zero-loss default to neutral rather than infinity, avoiding misleading perfect-period artifacts
- Smoothed output revealing distributional health —ratios above 1 favor gains , higher values signal skewed positives ideal for tail-risk hedging
- Asset-specific computations highlighting asymmetry , where fat positive tails in crypto assets can elevate omegas despite high total volatility
📈 Rate of Change Parameters
- Period length for percentage momentum measurement , shorter for reactive trend detection , longer for sustained direction confirmation
- Built-in ROC function application to source prices , yielding unbounded percentage shifts —positive for uptrends , negative for downtrends
- Zero default for missing data , treating data gaps as neutral momentum to avoid biasing composite scores
- Complementary role to risk metrics , capturing raw directional strength without normalization, spotlighting acceleration phases
- Direct integration into averages, where high ROC boosts scores in momentum-favoring selections , balanced by volatility adjustments elsewhere
- Simplicity in computation enabling lightweight inclusion , with na handling ensuring seamless array pushes in scoring logic
💼 Assets Configuration
- Number of altcoins to monitor and display, scalable from focused portfolios to broad market scans for comprehensive opportunity hunting
- Top combined assets count for dedicated ranking table , adjustable to highlight elite performers without overwhelming the view
- Individual symbol inputs grouped left and right for organizational clarity , accepting crypto pairs , indices , or custom tickers
- Conditional activation based on total count , loading only selected assets to optimize data requests and calculations
- Default focus on major and mid-cap altcoins , but fully customizable for sector-specific or emerging token universes
- Prefix stripping in displays for clean ticker presentation , enhancing readability in table formats
- Array-based storage of names and scores post-calculation, facilitating sorting , medians , and iterative population
- Integration with security requests for daily closes , ensuring uniform timeframe data across diverse exchanges
🎨 Table Style
- Background color with transparency for semi-opaque overlays , blending professional aesthetics with chart visibility
- Border color for frame delineation , providing subtle separation without distracting from metric focus
- Consistent application across main , median , and top tables , maintaining visual coherence in multi-panel layouts
- Frame width and color for structural emphasis , using dark tones to evoke institutional-grade presentation
- Color functions for score backgrounds — green for above-median outperformance , red for underperformance , gray for invalids
- Emoji integration for intuitive cues — rockets for strong assets , down arrows for laggards , enhancing at-a-glance scanning
📡 Data Fetching and Returns Calculation
- Benchmark close retrieval conditional on alpha or beta needs, using daily timeframe for consistent periodicity
- Parallel asset close fetches via security calls , defaulting to na for inactive symbols to prevent errors
- Returns function standardizing one-period ROC for daily percentage changes , zero-filling na for continuity
- Benchmark returns computed similarly, serving as regression baseline for relative metrics
- Na propagation to individual asset returns , ensuring downstream calculations skip invalid data gracefully
- Daily resolution enforcement across all fetches, aligning with annualization assumptions in ratios
- Efficient conditional logic minimizing API calls , scalable to full 33-asset loads without performance degradation
📈 Alpha Calculation
- Function guarding against na inputs , returning na for insufficient data to flag unreliable estimates
- Mean asset and benchmark returns via SMA over lookback , establishing central tendencies
- Covariance as product mean minus means product , capturing joint variability
- Benchmark variance similarly, ensuring positive denominator for beta
- Beta as cov/var ratio , zero-default for flat benchmarks to avoid divisions
- Alpha as asset mean minus beta times benchmark mean , isolating idiosyncratic performance
- Zero fallback for na alphas , treating computation failures as neutral in composites
- Per-asset execution only when enabled, feeding into scoring arrays for holistic aggregation
📉 Beta Calculation
- Identical input guards and mean computations as alpha , leveraging shared regression framework
- Covariance and variance derivations mirroring alpha prep , focusing solely on slope coefficient
- Beta output as sensitivity measure , with zero handling for degenerate cases
- Na-to-zero conversion for seamless array integration , avoiding score distortions
- Toggle-based activation per asset, allowing isolated volatility analysis without excess return overhead
- Conceptual role in diversification —low betas signal hedges , high ones amplify market bets
- Lookback sensitivity trade-off : short for tactical betas , long for structural exposures
⚡ Sharpe Ratio Calculation
- Source na guard returning na , preserving data integrity
- Daily returns via change over prior source , avoiding log approximations for arithmetic consistency
- Period SMA for mean reward , stdev for total risk dispersion
- Raw daily ratio with zero-stdev neutral default , preventing infinities
- Nz-EMA smoothing to dampen variability , weighting recent ratios heavily
- Sqrt(365) annualization for yearly comparability , assuming i.i.d. returns
- Zero na fallback , distinguishing errors from flat performance
- Asset-parallel computations , ranking efficiency where high Sharpes indicate optimal risk pricing
🎯 Sortino Ratio Calculation
- Na source guard , with annualization factor predefined for scaling
- Periodic returns and per-period risk-free derivation for threshold alignment
- Effective period min with bar count , enabling progressive buildup
- Loop-summed downside squares only for positive deviations ( underperformance ), averaged and sqrt-ed
- Excess mean over downside dev , scaled annually , zero-dev neutral
- Nz-EMA smoothing for stability , focusing on loss aversion
- Zero na output , emphasizing downside protection in crypto's crash-prone nature
- Longer periods favored for sparse downside events , enhancing estimate reliability
🔄 Omega Ratio Calculation
- Na guard with periodic returns and decimal target setup
- Loop over period accumulating above-target excesses vs. below shortfalls
- Raw ratio as gains/losses , zero-loss neutral to conservatism
- Nz-EMA smoothing , defaulting raw na to zero for continuity
- Distributional insight : >1 favors assets with skewed positives , <1 warns of loss dominance
- Target flexibility —zero for absolute , positive for relative hurdles
- Per-asset loops ensuring full history scan , capturing crypto's lottery-like tails
📈 Rate of Change Calculation
- Simple ta.roc application over period , percentage momentum direct from prices
- Na-to-zero for gaps , neutral in momentum absence
- Unbounded output allowing extreme trend magnitudes , unlike bounded oscillators
- Toggle integration boosting composites in trending selections
- Short-period reactivity for entry timing , complementing ratio stability
🎯 Combined Score Calculation
- Selected metrics count via incremental ifs , normalizing averages
- Last-bar loop over assets , building per-asset score arrays
- Switch-retrieved metric values , na-filtered pushes with valid count tracking
- Average only over valid scores , handling partial data gracefully
- Var assignment to per-asset combined vars , persisting for table use
- Equal-weighting assumption , treating metrics as complementary signals
- Na results when no valids , flagging data-deficient assets
- Holistic aggregation simplifying multi-metric overload into rankable scores
📊 Table Display Functions
- Background color getter : green above median , red below, gray invalid
- Emoji selector : rocket for outperformers , down for underperformers , blank invalid
- Row/column math for three-column layout , maximizing space efficiency
- Prefix-stripped asset names for compact display
- Rounded three-decimal scores or N/A , centered alignment
- Header branding centered, dark background for prominence
- Median table compact right-side , gray neutral for reference
- Top table left-side descending sort via indices array , limited rows
📋 Table Preparation
- Var arrays for names and scores , last-bar conditional pushes
- Conditional per-asset adds based on num_assets , avoiding over-allocation
- Median via array.median , central tendency for relative gauging
- Sort indices descending for top ranking , min with size for bounds
- String concatenation for alerts , newline-separated asset-score pairs
- Once-per-bar alert freq , compiling only non-na for actionable output
- Barstate.islast gating all prep/display , preventing historical repaints
✅ Key Takeaways
- Modular metrics enable tailored risk-return portfolios , from alpha hunts to downside shields
- Composite scores distill complexity into actionable rankings , median-anchored for relativity
- Benchmark-relative analysis uncovers crypto alphas amid market noise
- Table triad — main matrix , median ref , top highlights —delivers scannable insights
- Alerts and custom assets support automated monitoring in dynamic altcoin spaces
- Smoothing and lookbacks balance reactivity with stability for versatile timeframes
- Equal-metric averaging assumes balance , customizable via toggles for bias
Educational
ROC Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The ROC Tracker → PROFABIGHI_CAPITAL indicator measures momentum strength by calculating the Rate of Change (ROC) for up to 33 customizable altcoins over a user-specified period, revealing acceleration or deceleration in price movements. It dynamically generates color-gradient tables displaying individual ROC values, median benchmarks, and ranked top momentum performers with emoji indicators, allowing traders to spot surging assets for timely entries or fading ones for exits in volatile markets.
⚙️ General Settings
– ROC Period : Defines the lookback bars for percentage change computation, where shorter periods (e.g., 5-10) highlight immediate momentum bursts while longer spans (e.g., 20-50) capture sustained trends—key for aligning with trading horizons like scalping or swing setups.
💎 Asset Selection Settings
– Number of Altcoins to Display : Scales the primary table from a streamlined 5-asset view for rapid momentum checks to a full 33-symbol scan for broad-market acceleration profiling—balances detail with computational efficiency.
– Number of Top ROC Assets : Configures the momentum leaderboard to emphasize leading changers, adjustable from 1 for focused highlights to the total count for unbridled ranking—accelerates identification of breakout candidates.
– Asset 1-17 (Left Group) : Curates the main table's left column with essential altcoins, enabling personalization from anchors like ETHUSD to varied inclusions such as XRPUSD—each retrieves daily closes for standalone ROC derivation, with tooltips confirming symbol standards.
– Asset 18-33 (Right Group) : Populates the right column for diversified momentum tracking, incorporating further tokens from LTCUSD to specialized selections like MNTUSD—fosters balanced tri-column flow for lateral dataset review.
– Dynamic Input Rendering : Activates fields proportional to asset tally, veiling extras to sidestep errors and simplify navigation—facilitates effortless escalation from narrow lists to panoramic surveillance.
🎨 Table Style Settings
– Low ROC Color : Sets the gradient's deceleration base (e.g., deep red for negative changes), promptly signaling momentum fades that may prompt profit-taking or avoidance.
– High ROC Color : Anchors the acceleration peak (e.g., vivid green for positive changes), illuminating surging movers ripe for momentum continuation plays.
– Neutral ROC Value : Centers the color pivot at zero change (typically 0.0), modulating from loss to gain hues—adjustment biases toward conservative or aggressive momentum reads.
– ROC Color Range : Governs the transitional breadth around neutral, embracing wide fades for nuanced momentum gradients or narrow contrasts for binary surge/lag demarcation.
– Table Background : Deploys a muted dark semi-transparent canvas for thematic unity and cross-theme visibility, crafting an elegant momentum dashboard.
– Table Border : Enframes with neutral gray for subtle containment, encapsulating data without stylistic diversion.
📡 Data Fetching
– Asset Data Retrieval : Conducts concurrent daily close queries for nominated symbols, interposing NA for gaps to fortify table resilience.
– Return Series Computation : Applies 1-period percentage variances to asset paths, yielding the momentum quanta for period-based change metrics.
– Missing Data Resilience : Implants sentinels (-9999) for voids, rendering as grays to indicate incompleteness without structural breach.
🧮 Calculations
– Periodic Return Generation : Computes rate of change over the specified bars as current divided by prior minus unity, distilling momentum as percentage acceleration.
– Raw ROC Derivation : Directly yields the percentage shift over the lookback, quantifying speed without further averaging for pure velocity insight.
– NA Propagation Handling : Forwards missing values to preserve computational chain integrity, displaying as neutrals in outputs.
📋 Table Display
– Dynamic Layout Optimization : Erects columns (up to 9 for tri-set harmony) and rows attuned to asset volume plus header, assuring pithy utility for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded momenta (3 decimals), and velocity emojis in parsimonious trios for row-thrifty perusal.
– ROC Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate momentum profiling.
– Emoji Velocity Markers : Dispatches rocket for above-median changes (accelerators) and downward arrow for below (decelerators), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal momentum with gradient tint, mooring relative appraisals as a parity linchpin.
– Top ROC Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for surge-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded momenta on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– ROC quantification unveils momentum velocity, spotlighting acceleration for timely pursuits.
– Rolling period with direct computation yields crisp, unaltered speed metrics.
– Profuse symbol pliancy forges bespoke crypto velocity observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten surge/lag discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Omega Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Omega Ratio Tracker → PROFABIGHI_CAPITAL indicator quantifies the probability-weighted gain-to-loss efficiency by computing the Omega ratio for up to 33 customizable altcoins over a rolling lookback period, contrasting cumulative returns above a user-defined target against those below to assess favorable outcomes. It dynamically constructs color-gradient tables featuring individual Omegas, median benchmarks, and ranked top performers with emoji indicators, allowing traders to evaluate assets' upside potential relative to downside risks for informed, asymmetric opportunity selection.
⚙️ General Settings
– Calculation Period (Bars) : Establishes the historical scope for return accumulation and threshold comparisons, where shorter windows spotlight immediate efficiencies amid market swings while extended periods gauge long-term gain/loss asymmetries—pivotal for matching trading cadences like intraday (e.g., 20-50 bars) or swing (e.g., 100+ bars).
– Target Return per Period (%) : Specifies the aspirational return threshold per bar/day, serving as the pivot separating "gains" from "losses" in the ratio—elevated targets demand superior performance for positive Omegas, ideal for high-conviction filters, while modest ones broaden inclusion for diverse scans.
– Smoothing Period (EMA) : Implements exponential moving average on raw ratios to mitigate transients, with low values (e.g., 1-2) retaining volatility for granular views and higher settings (e.g., 4-7) fostering trend persistence for strategic planning.
💎 Asset Selection Settings
– Number of Altcoins to Display : Dictates the primary table's expanse from a targeted 5-asset spotlight for swift evaluations to a maximal 33-symbol expanse for holistic risk-reward profiling—impacts processing demands and dashboard density.
– Number of Top Omega Assets : Tailors the elite leaderboard to showcase premier ratios, variable from 1 for ultra-focused highlights to the aggregate count for unfiltered excellence—expedites prioritization of high-gain/low-loss candidates.
– Asset 1-17 (Left Group) : Loads the main table's left column with bedrock altcoins, facilitating bespoke curation from stalwarts like ETHUSD to varied mid-tiers such as XRPUSD—each solicits daily closes for autonomous Omega computation, with tooltips validating symbol protocols.
– Asset 18-33 (Right Group) : Charges the right column for augmented diversification, embracing further tokens from LTCUSD to esoteric picks like MNTUSD—cultivates equilibrated tri-column ergonomics for lateral dataset traversal.
– Dynamic Input Activation : Manifests fields per asset tally, obfuscating redundants to forestall faults and declutter—empowers fluid augmentation from succinct rosters to panoramic oversight sans reconfiguration.
🎨 Table Style Settings
– Low Omega Color : Grounds the gradient's unfavorable terminus (e.g., stark red for ratios below 1.0), instantaneously tagging assets with skewed losses over gains that might erode portfolio viability.
– High Omega Color : Secures the advantageous apex (e.g., radiant green for ratios above 1.0), illuminating prospects with dominant upsides relative to downsides for asymmetric edge hunting.
– Neutral Omega Value : Locates the color fulcrum at equilibrium efficiency (typically 1.0 for balanced outcomes), where ratios modulate from penalty to premium—refinement inclines toward prudent or venturesome outlooks.
– Omega Color Range : Regulates the transitional amplitude encircling neutral, favoring expansive fades for refined gradations or constricted shifts for unequivocal high/low bifurcation.
– Table Background : Imposes a discreet dark semi-opaque substrate for thematic cohesion and theme-agnostic legibility, evoking a refined analytics interface.
– Table Border : Encases perimeters with subdued gray for tacit delineation, encapsulating intelligence without stylistic encumbrance.
📡 Data Fetching
– Asset Data Retrieval : Undertakes simultaneous daily close interrogations for nominated symbols, interposing NA for lacunae to buttress table solidity.
– Return Series Computation : Extracts 1-period percentage variances from asset trajectories, proffering the elemental grist for gain/loss partitioning.
– Void Data Fortification : Implants sentinels (-9999) for lacunae, materializing as grays in renderings to signify incompleteness sans architectural compromise.
🧮 Calculations
– Periodic Return Generation : Forges bar/daily percentage alterations as source divided by antecedent minus unity, underpinning the discrete quanta for target-relative dissection.
– Target Threshold Decimalization : Transmutes percentage input to fractional form, delineating the demarcation betwixt accretive and detractive outcomes.
– Cumulative Gain Accrual : Aggregates excesses above target over the period, encapsulating favorable deviations' aggregate potency.
– Cumulative Loss Accrual : Tallies shortfalls below target, quantifying adverse deviations' collective burden.
– Raw Omega Formulation : Divides gains by losses, yielding the probability-adjusted efficiency quotient—defaults to NA on nil losses for interpretive clarity.
– EMA Transient Suppression : Exponentially averages raw quotients to quell ephemera, engendering interpretable contours over jagged dailies.
– Annualization Omission : Presents periodic ratios without scaling, prioritizing raw bar-level insights for intraday or short-term applicability.
📋 Table Display
– Dynamic Layout Optimization : Assembles columns (apex 9 for tri-set orchestration) and rows calibrated to asset quantum plus header, vouchsafing succinct potency for 1-33 symbols.
– Main Table Architecture : Branded header vaults the apical row, shadowed by asset symbols, rounded quotients (3 decimals), and efficiency emojis in parsimonious trios for row-thrifty perusal.
– Omega Color Continuum : Cartographs values from low (red) via neutral (midpoint) to high (green), with grays for voids—precipitates immediate gain/loss equilibrium profiling.
– Emoji Efficiency Markers : Dispatches rocket for above-median quotients (asymmetric victors) and downward arrow for below (lopsided laggards), infusing expeditious visual discernment.
– Median Table Encapsulation : Terse single-column depiction of pivotal quotient with gradient tint, mooring relative appraisals as a parity linchpin.
– Top Omega Table Hierarchy : Descending stratification in 3-column lattice (symbol, value, emoji) with header branding, converging on paramount assets for gain-dominant dispositions.
– Index-Fueled Ranking : Mobilizes array indices for descending distillation, refabricating sorted arrays while custodians originals for scrupulous median genesis.
🔔 Alerts
– Dynamic Alert Fabrication : Erects newline-segmented compendia of symbols and rounded quotients on the ultimate bar, amputating prefixes for laconic phrasing.
– Once-Per-Bar Dispatch : Ignites alerts at closure with the plenary dataset, harmonizing external adjuncts like dispatches or automata.
– Output Refinement : Distills parseable essence by eliding NAs, honing on operable datum for unencumbered conduit amalgamation.
✅ Key Takeaways
– Gain/loss partitioning via target thresholds unveils asymmetric efficiency beyond traditional metrics.
– Rolling computations with smoothing furnish trend-stable, noise-attenuated efficiency vistas.
– Profuse symbol pliancy forges bespoke crypto observatories from titans to obscurities.
– Gradient lattices with medians and tops hasten low-loss/high-gain discernment through optics.
– Automated alerts encapsulate scans into consumable missives, hastening from scrutiny to stratagem.
Sortino Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sortino Ratio Tracker → PROFABIGHI_CAPITAL indicator assesses downside risk-adjusted performance by computing the Sortino ratio for up to 33 customizable altcoins over a rolling lookback period, focusing solely on negative volatility to penalize harmful deviations while smoothing and annualizing for actionable insights. It dynamically generates color-gradient tables displaying individual Sortinos, median benchmarks, and ranked top performers with emoji indicators, empowering traders to prioritize assets with superior returns relative to their drawdown risks for more resilient portfolio construction.
⚙️ General Settings
– Calculation Period (Days/Bars) : Specifies the historical window for return averaging and downside deviation estimation, where shorter periods emphasize recent efficiency amid volatility spikes while longer horizons evaluate enduring downside protection—vital for aligning with strategies like short-term trading (e.g., 30-60 bars) versus long-term holding (e.g., 90+ bars).
– Annual Risk-Free Rate (%) : Sets the threshold below which returns are considered "downside," typically a conservative benchmark like treasury yields—higher rates raise the bar for positive Sortinos, favoring only truly superior risk-adjusted outcomes.
– Smoothing Period (EMA) : Applies exponential moving average to raw ratios for noise reduction, where minimal smoothing (e.g., 1-3) preserves granularity for active monitoring while higher values (e.g., 5+) yield trend-stable views for strategic overviews.
– Number of Altcoins to Display : Determines the primary table's breadth from a streamlined 5-asset focus for rapid scans to a thorough 33-symbol panorama for exhaustive downside risk profiling—directly affects data processing and visual footprint.
– Number of Top Sortino Assets : Configures the leaderboard to spotlight leading ratios, scalable from 1 for laser-focused highlights to the full asset set for complete efficiency hierarchy—facilitates prioritization of low-downside winners.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Fills the main table's left column with cornerstone altcoins, enabling tailored selection from majors like ETHUSD to diversified options such as XRPUSD—each pulls daily closes for standalone Sortino computation, with tooltips verifying symbol conventions.
– Asset 18-33 (Right Group) : Loads the right column for extended diversification, incorporating further tokens from LTCUSD to specialized choices like MNTUSD—promotes balanced tri-column ergonomics for fluid cross-dataset comparison.
– Dynamic Input Activation : Renders fields conditionally on total assets, hiding extras to avert errors and declutter the interface—supports frictionless growth from compact portfolios to all-encompassing surveillance.
🎨 Table Style Settings
– Low Sortino Color : Establishes the gradient's downside anchor (e.g., intense red for negative ratios), immediately flagging assets with excessive harmful volatility that could undermine portfolio stability.
– High Sortino Color : Pins the excellence terminus (e.g., luminous green for positive ratios), illuminating low-risk/high-return standouts perfect for conservative growth strategies.
– Neutral Sortino Value : Positions the color inflection at breakeven efficiency (typically 0.0), pivoting hues from penalty to premium—tweaking recalibrates toward defensive or opportunistic lenses.
– Sortino Color Range : Modulates the spectrum's transitional span around neutral, opting for broad fades in subtle differentiation or tight contrasts for stark performer/laggard splits.
– Table Background : Instills a understated dark semi-transparent foundation for unified readability across themes, evoking a sleek, professional analytics dashboard.
– Table Border : Circumscribes frames with unobtrusive gray for gentle containment, directing focus to the gradient-infused data without stylistic interference.
📡 Data Fetching
– Asset Data Retrieval : Performs concurrent daily close queries for specified symbols, substituting NA for voids to sustain table robustness.
– Return Series Computation : Extracts 1-period percentage changes from asset series, supplying the granular inputs for mean and downside deviation metrics.
– Missing Data Resilience : Employs sentinels (-9999) for gaps, manifesting as grays in tables to denote incompleteness without layout disruption.
🧮 Calculations
– Periodic Return Generation : Derives daily/bar percentage changes as source over prior close minus one, capturing discrete movements for efficiency evaluation.
– Mean Return Estimation : Averages returns over the rolling period with simple moving average, forging a baseline excess performance metric.
– Downside Deviation Quantification : Sums squared deviations below the risk-free threshold, averaging to measure only harmful volatility—ignores upside for focused risk penalization.
– Raw Sortino Formulation : Divides mean excess return by downside deviation, defaulting to zero on nil volatility for computational safety.
– EMA Noise Attenuation : Exponentially smooths raw ratios to filter transients, yielding interpretable trends over erratic daily swings.
– Annualization Adjustment : Scales smoothed ratios by the square root of 365 (crypto calendar), transforming periodic efficiency into yearly benchmarks for cross-asset comparability.
📋 Table Display
– Dynamic Layout Scaling : Erects columns (maximum 9 for tri-set grouping) and rows attuned to asset quantity plus header, guaranteeing compact utility for 1-33 symbols.
– Main Table Architecture : Branded header traverses the summit row, pursued by asset symbols, rounded ratios (3 decimals), and efficiency emojis in efficient trios for streamlined row navigation.
– Sortino Color Continuum : Maps values from low (red) via neutral (midpoint) to high (green), with grays for voids—enables instantaneous downside efficiency profiling.
– Emoji Efficiency Markers : Deploys rocket for above-median ratios (superior performers) and downward arrow for below (inferior), infusing swift visual assessment.
– Median Table Encapsulation : Succinct single-column portrayal of central ratio with gradient hue, anchoring relative evaluations as a risk-neutral pivot.
– Top Sortino Table Hierarchy : Descending classification in 3-column matrix (symbol, value, emoji) with header branding, concentrating on elite assets for downside-focused decisions.
– Index-Fueled Ranking : Exploits array indices for descending extraction, reconstructing sorted arrays while preserving originals for exact median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Constructs newline-separated assemblages of symbols and rounded ratios on the terminal bar, excising prefixes for terse formatting.
– Once-Per-Bar Dispatch : Initiates alerts at close with the complete dataset, accommodating external integrations like notifications or automated systems.
– Output Refinement : Curates parseable content by excluding NAs, zeroing in on executable data for streamlined workflow incorporation.
✅ Key Takeaways
– Downside-focused Sortino ratios spotlight assets excelling in returns per harmful volatility unit.
– Rolling computations with smoothing and annualization yield comparable, trend-stable efficiency metrics.
– Vast symbol adaptability crafts bespoke crypto dashboards from majors to alts.
– Gradient tables with medians and tops accelerate low-risk winner identification via visuals.
– Automated alerts consolidate scans into digestible packets, expediting from evaluation to execution.
Sharpe Ratio Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Sharpe Ratio Tracker → PROFABIGHI_CAPITAL indicator evaluates risk-adjusted performance by computing the Sharpe ratio for up to 33 customizable altcoins over a rolling lookback period, smoothing values for stability and annualizing for comparability. It dynamically renders color-gradient tables showcasing individual Sharpe ratios, median benchmarks, and ranked top performers with emoji indicators, enabling traders to identify assets delivering superior returns per unit of volatility for optimized portfolio selection.
⚙️ General Settings
– Sharpe Rolling Period : Adjustable lookback window for return and volatility averaging, where shorter horizons capture recent efficiency while longer spans assess sustained performance stability.
– Smoothing Period : EMA length applied to raw ratios to dampen noise, promoting smoother trends for clearer visual and analytical insights.
– Number of Altcoins to Display : Scales the primary table's capacity from a focused 5-asset scan for quick reviews to a full 33-symbol matrix for comprehensive risk-adjusted screening.
– Number of Top Sharpe Assets : Curates the leaderboard to emphasize leading ratios, tunable from 1 for pinpoint focus to the total count for exhaustive ranking of efficiency standouts.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Populates the main table's left column with foundational altcoins, supporting customization from blue-chips like ETHUSD to diversified selections such as XRPUSD—each input retrieves daily closes for isolated Sharpe derivation, with tooltips ensuring accurate symbol formatting.
– Asset 18-33 (Right Group) : Fills the right column for broader exposure, accommodating additional tokens from LTCUSD to niche assets like MNTUSD—facilitates ergonomic tri-column layout for horizontal scanning across the expanded dataset.
– Dynamic Input Rendering : Conditionally activates fields based on total assets, concealing unused slots to eliminate errors and streamline the interface—allows effortless scaling from compact watchlists to exhaustive monitoring without reconfiguration.
🎨 Table Style Settings
– Low Sharpe Color : Anchors the gradient's underperformance base (e.g., deep red for negative ratios), visually flagging assets with poor efficiency that may drag portfolio returns.
– High Sharpe Color : Establishes the excellence endpoint (e.g., vivid green for positive ratios), spotlighting high-efficiency performers ideal for risk-conscious allocations.
– Neutral Sharpe Value : Centers the color pivot at breakeven efficiency (typically 0.0), where ratios shift from subdued to vibrant hues—calibration tilts toward conservative or aggressive interpretations.
– Sharpe Color Range : Broadens or narrows the transition zone around neutral, yielding gradual blends for nuanced rankings or sharp delineations for clear high/low separation.
– Table Background : Deploys a subtle dark semi-transparent canvas for all views, fostering glare-free readability across themes while delivering a cohesive dashboard appearance.
– Table Border : Frames outlines with neutral gray for understated structure, containing content without diverting from the gradient-centric data narrative.
📡 Data Fetching
– Asset Data Retrieval : Executes parallel daily close requests for designated symbols, gracefully managing empty inputs by inserting NA placeholders to uphold table cohesion.
– Return Series Computation : Derives 1-period percentage changes for each asset, furnishing the discrete inputs for mean and standard deviation estimations.
– Invalid Data Mitigation : Substitutes missing values with sentinels (-9999) for rendering as grays, preserving layout amid incomplete datasets.
🧮 Calculations
– Daily Return Generation : Applies rate of change over one day to each asset's series, yielding percentage shifts as the core for efficiency metrics.
– Mean Return Smoothing : Averages returns over the rolling period via simple moving average, establishing historical performance baselines.
– Standard Deviation Volatility : Computes rolling dispersion of returns, quantifying risk as the denominator for ratio normalization.
– Raw Sharpe Derivation : Divides mean return by standard deviation, handling zero-volatility cases with zero fallback for stability.
– EMA Smoothing Application : Applies exponential moving average to raw ratios, attenuating fluctuations for trend-revealing outputs.
– Annualization Scaling : Multiplies smoothed ratios by the square root of 365, converting daily efficiency to yearly comparability.
📋 Table Display
– Dynamic Layout Optimization : Constructs columns (up to 9 for tri-set configuration) and rows scaled to asset count plus header, ensuring compact efficiency for 1-33 symbols.
– Main Table Framework : Branded header bridges the top row, trailed by asset symbols, rounded ratios (3 decimals), and efficiency emojis in streamlined trios for row-efficient navigation.
– Sharpe Color Continuum : Interpolates from low (red) through neutral (midpoint) to high (green), with grays for invalids—facilitates at-a-glance risk-adjusted profiling.
– Emoji Efficiency Markers : Renders rocket for above-median ratios (strong performers) and downward arrow for below (weak), injecting rapid visual sentiment.
– Median Table Encapsulation : Compact single-column showcase of central ratio with gradient coloring, anchoring relative evaluations as an efficiency fulcrum.
– Top Sharpe Table Hierarchy : Descending rank in 3-column array (symbol, value, emoji) with header branding, zeroing in on superior assets for allocation prioritization.
– Index-Fueled Ranking : Harnesses array indices for descending extraction, rebuilding sorted arrays while safeguarding originals for precise median derivation.
🔔 Alerts
– Dynamic Alert Fabrication : Assembles newline-separated compilations of symbols and rounded ratios on the final bar, purging prefixes for succinct formatting.
– Once-Per-Bar Dispatch : Activates alerts at close with the full dataset, accommodating external integrations like notifications or bots.
– Output Refinement : Curates parseable content by excluding NAs, concentrating on executable data for seamless workflow embedding.
✅ Key Takeaways
– Transforms risk-adjusted efficiency into gradient-scored tables for effortless asset ranking.
– Rolling Sharpe with smoothing and annualization delivers comparable, noise-reduced insights.
– Extensive symbol flexibility supports tailored crypto portfolios from majors to alts.
– Top medians and emojis accelerate outperformance detection with visual punch.
– Automated alerts package complete scans, streamlining from analysis to action.
Beta Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Beta Tracker → PROFABIGHI_CAPITAL indicator quantifies market sensitivity by calculating the beta coefficient for up to 33 customizable altcoins relative to a selected benchmark over a user-defined lookback, revealing how assets amplify or dampen systemic movements. It dynamically renders color-gradient tables with individual betas, median values, and sorted top sensitivities alongside emoji indicators, enabling traders to assess volatility alignment and construct diversified portfolios based on risk exposure profiles.
⚙️ General Settings
– Beta Measurement Length : Establishes the historical horizon for return covariance and variance computations, where shorter spans highlight recent sensitivities while longer periods reveal enduring market correlations—essential for tailoring to trading styles like short-term scalping or long-term holding.
– Benchmark Symbol : Designates the reference index for beta normalization, such as total market cap to evaluate broad exposure or Bitcoin for coin-specific amplification—forms the foundational volatility baseline for all asset comparisons.
– Number of Altcoins to Display : Scales the primary table's capacity from a concise 5-asset focus for quick scans to a robust 33-symbol overview for exhaustive screening, directly influencing data volume and computational efficiency.
– Number of Top Beta Assets : Curates the leaderboard to showcase the most sensitive performers, adjustable from 1 for pinpoint focus to the full asset count for comprehensive ranking—streamlines identification of high-volatility opportunities.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Populates the main table's left column with core altcoins, supporting sequential customization from established leaders like ETHUSD to diversified mid-caps such as XRPUSD—each fetches daily closes for independent beta derivation, with tooltips ensuring proper symbol entry.
– Asset 18-33 (Right Group) : Fills the right column for expanded coverage, accommodating additional tokens from LTCUSD to niche selections like MNTUSD—facilitates balanced tri-column layout for ergonomic horizontal scanning across the dataset.
– Dynamic Input Adaptation : Conditionally renders inputs based on total assets, suppressing unused fields to prevent errors and streamline the interface—allows seamless scaling from minimal watchlists to full-spectrum monitoring without reconfiguration.
🎨 Table Style Settings
– Low Beta Color : Anchors the gradient's defensive endpoint (e.g., muted red for betas below 1.0), visually denoting lower market sensitivity and potential stability in portfolios.
– High Beta Color : Defines the aggressive anchor (e.g., vibrant green for betas above 1.0), spotlighting amplified movers ideal for volatility-seeking strategies.
– Neutral Beta Value : Centers the color transition at market-equivalent sensitivity (typically 1.0), where betas pivot from subdued to heightened hues—calibration shifts emphasis toward conservative or offensive interpretations.
– Beta Color Range : Expands or contracts the spectrum bandwidth around neutral, fostering gradual blends for nuanced rankings or abrupt shifts for clear high/low demarcation.
– Table Background : Applies a subtle dark semi-transparent canvas across all views, promoting eye comfort on varied themes while unifying the professional dashboard aesthetic.
– Table Border : Outlines frames with neutral gray for subtle definition, framing content without distracting from the gradient-driven data insights.
📡 Data Fetching
– Benchmark Data Retrieval : Utilizes security requests for daily closing prices from the designated symbol, compiling a consistent series for variance and covariance baselines.
– Asset Data Retrieval : Conducts parallel daily close pulls for chosen symbols, substituting NA for invalid inputs to safeguard computational flow.
– Rate of Change Derivation : Generates 1-period percentage returns for assets and benchmark, providing the discrete inputs for mean estimation and co-movement analysis.
– Invalid Data Safeguarding : Flags missing values with sentinels (-9999) for table rendering as grays, maintaining structural integrity amid data gaps.
🧮 Calculations
– Return Series Generation : Applies rate of change over one day to each asset and benchmark, yielding daily percentage shifts as the raw material for sensitivity metrics.
– Mean Return Smoothing : Averages returns via simple moving over the lookback, establishing historical performance norms for both series.
– Covariance Quantification : Computes the averaged product of asset and benchmark returns minus their means' product, encapsulating directional co-variance.
– Benchmark Variance Measurement : Averages squared deviations of benchmark returns from its mean, capturing the reference's inherent volatility.
– Beta Coefficient Computation : Divides covariance by variance to derive systemic sensitivity, where values above 1.0 indicate amplification and below suggest dampening.
– NA Handling in Metrics : Defaults beta to NA for zero-variance benchmarks, preventing division errors while displaying as neutrals.
📋 Table Display
– Dynamic Layout Scaling : Constructs columns (up to 9 for tri-set grouping) and rows based on asset volume plus header, optimizing density for seamless 1-33 symbol integration.
– Main Table Structuring : Branded header spans the top row, succeeded by asset symbols, rounded betas (3 decimals), and sensitivity emojis in compact trios for efficient row-wise scanning.
– Beta Color Spectrum : Applies gradient mapping from low (red) via neutral (midpoint) to high (green), with grays for invalids—facilitates instantaneous volatility profile assessment.
– Emoji Sensitivity Cues : Deploys rocket for above-median betas (high sensitivity) and downward arrow for below (low sensitivity), infusing quick visual narrative.
– Median Table Compact View : Single-column encapsulation of central beta with gradient hue, anchoring relative evaluations as a market-neutral fulcrum.
– Top Beta Table Ranking : Descending sort in 3-column format (symbol, value, emoji) with header branding, concentrating on amplified assets for volatility-focused decisions.
– Index-Driven Sorting : Leverages array indices for efficient descending extraction, reconstructing views while retaining originals for accurate median computation.
🔔 Alerts
– Dynamic Alert Assembly : Constructs newline-formatted lists of symbols and rounded betas on the final bar, excising prefixes for concise messaging.
– Bar-Close Triggering : Fires alerts once per close with the entire dataset, supporting seamless external tooling or notifications.
– Formatted Output Optimization : Ensures clean, parseable content by omitting NAs, focusing on viable data for integration.
✅ Key Takeaways
– Illuminates asset-market sensitivity through beta coefficients, guiding volatility-aligned portfolio construction.
– Gradient tables with medians and tops transform raw metrics into actionable, scannable intelligence.
– Extensive symbol customization supports bespoke crypto monitoring from majors to alts.
– Emojis and colors add intuitive flair, accelerating relative strength identification.
– Automated alerts distill full scans into digestible updates, bridging analysis to execution.
Alpha Tracker -> PROFABIGHI_CAPITAL🌟 Overview
The Alpha Tracker → PROFABIGHI_CAPITAL is a sophisticated performance analytics tool that computes and visualizes the risk-adjusted excess returns (alpha) of up to 33 customizable altcoins against a user-defined benchmark over a flexible lookback horizon. By leveraging daily return covariance and beta adjustments, it dynamically generates color-gradient tables showcasing individual alphas, median benchmarks, and ranked top performers with intuitive emoji indicators, empowering traders to swiftly pinpoint relative outperformance and inform portfolio rotations or allocation decisions.
⚙️ General Settings
– Alpha Measurement Length : Defines the historical window for return averaging and covariance calculations, where shorter periods emphasize recent momentum while longer horizons capture sustained trends—crucial for aligning with trading horizons like short-term scalping (e.g., 10-20 days) versus long-term positioning (e.g., 50+ days).
– Benchmark Symbol : Serves as the market reference for alpha isolation, typically a broad index like total crypto cap to gauge systemic risk-adjusted gains; selecting alternatives like Bitcoin enables coin-specific outperformance analysis.
– Number of Altcoins to Display : Controls the scale of the main table, from a focused watchlist of 5-10 high-conviction assets to a comprehensive 33-symbol scan for broad-market screening—impacts computational load and visual density.
– Number of Top Alpha Assets : Limits the dedicated leaderboard to the highest alphas, streamlining focus on actionable leaders (e.g., 3-7 for quick scans) while maintaining full data in the primary view for deeper dives.
💎 Asset Selection Settings
– Asset 1-17 (Left Group) : Curates the primary column of the main table with foundational altcoins, allowing sequential customization from blue-chip like ETHUSD to mid-caps like XRPUSD—each input fetches daily closes for independent alpha computation, with tooltips guiding symbol formatting.
– Asset 18-33 (Right Group) : Expands to secondary symbols in the right column, supporting diverse exposure from established tokens like LTCUSD to emerging ones like ONDOUSD—seamless integration ensures balanced left-right distribution for ergonomic table reading.
– Dynamic Input Scaling : Automatically accommodates the total asset count by disabling unused inputs, preventing errors and optimizing data fetches—enables modular expansion from a minimal 5-asset portfolio to full 33 for exhaustive coverage.
🎨 Table Style Settings
– Low Alpha Color : Establishes the gradient's underperformance endpoint (e.g., deep red for negative alphas), visually signaling laggards that may warrant reduction or avoidance in allocations.
– High Alpha Color : Sets the outperformer anchor (e.g., bright green for positive alphas), highlighting assets generating excess returns beyond benchmark expectations.
– Neutral Alpha Value : Anchors the color spectrum's midpoint, where zero or breakeven alphas transition from red to green—fine-tuning shifts the bias toward aggressive or conservative interpretations.
– Alpha Color Range : Widens or narrows the transition bandwidth around neutral, creating smoother blends for subtle rankings or sharper contrasts for binary hot/cold asset identification.
– Table Background : Applies a semi-opaque dark base across all tables, ensuring low-glare readability on both light and dark themes while maintaining professional aesthetics.
– Table Border : Defines frame outlines for structural definition, with gray subtlety preventing visual clutter while framing content effectively.
📡 Data Fetching
– Benchmark Data Retrieval : Employs security requests for daily closes from the chosen symbol, ensuring a stable time series for covariance baseline without intraday noise.
– Asset Data Retrieval : Parallel daily close fetches for selected symbols, gracefully handling invalid inputs by substituting NA values to preserve table stability.
– Rate of Change Computation : Derives 1-period percentage returns for assets and benchmark, forming the raw input for mean and covariance matrices.
– Error Handling for NA Values : Replaces missing data with sentinel placeholders (-9999) in tables, displaying as gray neutrals to flag data gaps without disrupting layout.
🧮 Calculations
– Return Series Generation : Applies rate of change over one day for each asset and benchmark, capturing discrete daily movements essential for alpha's excess return focus.
– Mean Return Averaging : Computes simple moving averages of returns over the lookback, providing smoothed historical performance baselines for both series.
– Covariance Estimation : Averages the product of asset and benchmark returns minus their means' product, quantifying linear co-dependence critical for beta adjustment.
– Benchmark Variance : Averages squared benchmark deviations from its mean, measuring systemic volatility to normalize asset sensitivity.
– Beta Coefficient : Divides covariance by variance to derive market beta, isolating systematic risk before alpha extraction.
– Alpha Derivation : Subtracts beta-adjusted benchmark mean from asset mean, yielding the intercept as true excess return attributable to security-specific factors.
📋 Table Display
– Dynamic Table Dimensions : Auto-scales columns (up to 9 for tri-column layout) and rows based on asset count plus header, optimizing space for 1-33 symbols without overflow.
– Main Table Population : Features a branded header spanning the top, followed by asset symbols, rounded alphas (3 decimals), and performance emojis in balanced trios for scannable rows.
– Alpha Color Gradient : Maps values from low (red) through neutral (midpoint) to high (green), with gray for invalids—enables instant visual ranking across the dataset.
– Emoji Performance Icons : Renders rocket for above-median alphas (outperformers) and downward arrow for below (laggards), adding emotional quick-scan appeal.
– Median Table Summary : Compact single-column view of the central alpha with gradient coloring, serving as a neutral benchmark for relative assessments.
– Top Assets Table : Ranks the highest alphas descending in a 3-column format (symbol, value, emoji), with header branding for focused opportunity highlighting.
– Array-Based Sorting : Generates descending indices from alpha array, reconstructing sorted lists for leaderboard extraction while preserving originals for display.
🔔 Alerts
– Dynamic Alert Construction : Compiles a newline-separated list of symbols and rounded alphas on the last bar, stripping prefixes for clean formatting.
– Once-Per-Bar Frequency : Triggers alerts at close with the complete dataset, facilitating external integrations like notifications or automation.
– Content Customization : Formats messages for readability, excluding NA values to focus on actionable data points.
✅ Key Takeaways
– Streamlines alpha computation across portfolios, transforming complex risk-adjusted metrics into intuitive, gradient-scored tables for rapid insights.
– Benchmark-relative ranking with medians and tops enables proactive asset rotation based on true outperformance.
– Customizable symbols and lookbacks adapt to diverse crypto watches, from majors to niche alts.
– Visual emojis and colors provide at-a-glance sentiment, complementing numerical precision.
– Automated alerts deliver full-dataset updates, bridging analysis to actionable trading decisions.
UK Recessions (1956–2023) This is a basic script that shows the UK recession periods with the dates pulled from the Wikipedia page on the UK Recession if you wish to check the reasons behind.
It will not show any future recessions however it may be updated.
SSMT [TakingProphets]SSMT (Sequential SMT) — multi-cycle intermarket divergence with quarter-based timing
Purpose
Informational overlay that detects intermarket SMT divergences between the chart symbol and a user-selected correlated symbol. It does not generate buy/sell signals and is not financial advice. Use it to structure analysis and alerts, not to automate trades.
What it does
Scans for SMT on five coordinated cycles: Micro, 90-Minute, Daily (Q1–Q4), Weekly, Monthly.
Draws anchored lines and labels where divergences occur and keeps them after the period ends so you can use historical SMTs as context.
Offers per-cycle alerts (high-side/bearish, low-side/bullish).
Optional session/quarter boxes for timing context.
Time base uses America/New_York to align with common session conventions (with a 17:00–18:00 ET pause guard for CME instruments).
Why these modules belong together (more than a mashup)
All cycles share a single time-partitioning framework (quarters/sessions → day → week → month). That common clock means:
Comparability: divergences on Micro/90m/D/W/M are directly comparable because they’re computed with the same boundaries for both instruments.
Sequencing: higher-cycle context can gate lower-cycle events (e.g., a Daily Q3 divergence framing how you treat a Micro divergence).
Persistence: drawings retain the cycle identity (e.g., , ) so prior signals remain interpretable as the market progresses.
This is a coherent engine—not separate indicators pasted together—because detection, labeling, alerts, and persistence are all driven by the same quarter/period state machine.
How it works (high-level mechanics)
Time partitioning
Daily quarters (ET):
Q1: 18:00–00:00
Q2: 00:00–06:00
Q3: 06:00–12:00
Q4: 12:00–18:00
90-Minute cycle: four 90-minute blocks inside the active session.
Micro cycle: finer 20–22 minute blocks inside the session for granular timing.
Weekly/Monthly: tracked by calendar periods (Mon–Fri, and calendar month).
Pause guard: 17:00–18:00 ET to avoid false transitions during CME’s daily maintenance window.
State tracking (per cycle)
Tracks previous vs. current highs/lows for the chart symbol and the correlated symbol (fetched at the same timeframe).
Maintains cycle IDs (e.g., year*100 + weekofyear for weekly) so drawings remain tied to the originating period.
Divergence condition (SMT)
High-side (bearish): one instrument makes a higher high vs. its previous period while the other does not.
Low-side (bullish): one instrument makes a lower low vs. its previous period while the other does not.
When detected, the script plots a labeled span/line (e.g., SSMT w/ES) and records it for persistence.
Alerts
Two per cycle: High-side (bearish) and Low-side (bullish).
Fire on the bar where the condition first becomes true.
Inputs & customization
Correlated symbol (default can be an index future).
Cycle toggles: Micro, 90m, Daily (Q1–Q4), Weekly, Monthly.
Styling: line color/width, label text/size.
Session/quarter boxes: on/off.
Alerts: per-cycle SMT events on/off.
How to use
Add the indicator to your chart (e.g., NQ, ES) and select a correlated symbol.
Turn on the cycles you want to monitor; optionally enable quarter/session boxes.
Interpret SMTs by side:
High-side (bearish): chart makes HH, correlated does not.
Low-side (bullish): chart makes LL, correlated does not.
Set alerts for the cycles that matter to your workflow.
Combine with your higher-timeframe narrative and risk rules.
Repainting, timing, and limitations
Uses higher-timeframe data without look-ahead; values can update intrabar until the period closes.
SMTs may form and resolve within a period; conservative users may wait for period close.
Assumes America/New_York timing; very thin markets may yield fewer or noisier signals.
SMT quality depends on the benchmark you select; correlations vary across regimes.
Educational tool only. No performance claims; not a signal generator.
Originality & scope (for protected/invite-only publications)
A multi-cycle SMT engine built on a shared quarter/period state machine (Micro → 90m → Daily Q1–Q4 → Weekly → Monthly).
Quarter-aware persistence keeps divergence drawings tied to their source cycle for durable context.
CME pause handling and stable calendar IDs make detections consistent across sessions and rollovers.
Implements SMT through extremum sequencing and cross-instrument comparison rather than wrapping generic divergence indicators.
CRT [TakingProphets]CRT (Candle Range Theory) — HTF context overlay with alerts
Purpose
Informational overlay to structure higher-timeframe (HTF) context. It does not generate buy/sell signals and is not financial advice. Use it to organize analysis and alerts—not to automate trades.
What it does
Projects HTF candles (1m → 1M) on any lower timeframe so the big picture stays on the chart.
Detects CRT transitions on the HTF (bullish/bearish “failed continuation” pattern).
Evaluates SMT divergence vs. a user-selected correlated instrument on the same HTF (historical & real-time).
Extends live HTF Open/High/Low/Close as developing reference levels.
Concepts (what it looks for)
Candle Range Theory (CRT) — a 3-bar HTF pattern where candle 2 fails to continue candle 1’s move:
Bearish CRT: candle 2 trades above candle 1’s high but closes back inside candle 1’s range and does not break its low.
Bullish CRT: candle 2 trades below candle 1’s low but closes back inside candle 1’s range and does not break its high.
SMT divergence (intermarket) — compares HTF swing extremes between the chart symbol and a correlated symbol:
Bearish SMT: one makes a higher high while the other does not.
Bullish SMT: one makes a lower low while the other does not.
Checked in two modes: historical (between the two last closed HTF bars) and real-time (last closed vs. current forming HTF bar).
How the elements work together (integration, not a mashup)
All modules share one HTF time base, so annotations describe the same segment of price action. The overlay produces an explicit context state by sequencing the modules in this order:
HTF Projection → Structural Frame
The last three HTF candles are drawn (bodies+wicks). This creates the “canvas” the rest of the logic references (ranges, highs/lows, and time boundaries).
CRT Test → Directional Bias Candidate
The script evaluates the 3-bar CRT conditions on those exact HTF candles (not lower-TF approximations).
If conditions are forming on the current HTF bar, status is CRT Forming.
If they complete on the close, status becomes CRT Confirmed (Bullish/Bearish).
SMT Check → Confirmation/Stress-Test on the Same HTF
Using the same HTF window, the tool compares swing progress with the correlated symbol.
Historical SMT comments on whether the prior HTF segment’s push had intermarket agreement.
Real-time SMT comments on the current forming push.
This lets you confirm a CRT bias (e.g., Bearish CRT + Bearish SMT) or challenge it (e.g., Bullish CRT but Bearish SMT).
Live HTF OHLC → Actionable Reference Levels
The current HTF Open/High/Low/Close are extended as levels. These are the decision rails you’ll typically use to judge follow-through, failure, mitigation, or targets in the same CRT/SMT context.
Resulting context states (what you’ll see in alerts/labels):
Neutral (no CRT; SMT may still inform context).
CRT Forming (monitor): HTF push is underway; watch real-time SMT into HTF High/Low/Close projections.
CRT Confirmed (bias): HTF failure pattern locked; use projections as reference for continuation/invalidations.
CRT + SMT Aligned (confluence): CRT direction agrees with SMT; strongest context.
CRT vs. SMT Mixed (caution): bias exists but intermarket is disagreeing; treat levels as potential fade zones.
Why this is not a mashup
Every module is computed and plotted in the same HTF coordinate system, so signals are about one thing: the current HTF segment.
CRT provides the bias hypothesis, SMT provides a cross-market test of that hypothesis in the same window, and live OHLC projections supply the exact levels used to act on or fade that hypothesis.
Alerts are tied to state transitions (e.g., CRT forming → confirmed; SMT flip), not to unrelated features.
Mechanics (high-level)
HTF Projection: pulls HTF OHLC/time for the last three HTF bars and renders body boxes + wicks; optional time labels adapt to intraday vs D/W/M.
CRT Labels: when the three-bar conditions are met, prints BULLISH CRT or BEARISH CRT on the HTF stack.
SMT Lines: draws labeled diagonals across the relevant HTF pair for historical and real-time checks using your correlated symbol.
Live Levels: extends the current HTF Open/High/Low/Close horizontally; anchors are deterministic (Open = first bar, High/Low = first occurrence, Close = current bar).
Inputs & customization
HTF timeframe: 1m–1M.
Display: candle width/opacity, borders/wicks, time labels (12h/24h).
SMT: enable/disable, correlated symbol, line style/width, optional labels.
Projections: enable/disable, left extension (bars), per-level styling and price labels.
Alerts: switches for CRT, SMT-historical, SMT-real-time.
Alerts (workflow prompts)
Bullish/Bearish CRT detected on the selected HTF.
Bullish/Bearish SMT (historical) between the two last closed HTF bars.
Bullish/Bearish SMT (real-time) between the last closed and current forming HTF bar.
Suggested text includes the HTF and current context state so you know if CRT and SMT are aligned or mixed.
Example use
Bearish scenario: A Bearish CRT confirms on the 4H; soon after, real-time SMT (bearish) appears while price probes the projected 4H High. Context = CRT + SMT Aligned → treat the projected Open/Close as near-term objectives.
Mixed scenario: A Bullish CRT forms on 1H, but historical SMT (bearish) printed in the prior segment. Context = Mixed → continue to monitor real-time SMT and projected Low for possible invalidation.
Notes & limitations
HTF values are provisional until the HTF bar closes; labels/lines can update while forming.
SMT depends on the correlated symbol you select; relationships vary by market/regime.
Session gaps/illiquid hours can distort extremes and time labels.
Educational tool: no performance claims, no entry/exit signals.
Originality & scope (for protected/invite-only publications)
A unified HTF projection → CRT test → SMT check → live level pipeline that yields explicit context states instead of separate, unrelated overlays.
Formal CRT detection performed on actual HTF bars (not lower-TF approximations).
Dual-mode SMT tied to the same HTF windows (historical + real-time), plotted as labeled span lines.
Deterministic OHLC projection (first-occurrence anchoring) to align decisions with the identified context.
Attribution: CRT/SMT concepts inspired by ICT. Design, implementation, and alert framework by TakingProphets.
Prophet Model [TakingProphets]The Prophet Model — context pipeline (HTF PDA → Sweep → CISD → EPE) with dynamic risk
Purpose
Informational overlay for organizing institutional context in real time. It does not issue buy/sell signals and is not financial advice. Use it to structure analysis and checklist-driven execution—not to automate decisions.
What it does (modules at a glance)
Projects HTF PD Arrays (FVGs) onto your current chart and maintains only the nearest active array.
Validates directional bias using Candle Range Theory (CRT) on the same HTF.
Tracks Liquidity Sweeps (BSL/SSL) on HTF-aware pivots.
Confirms Change in State of Delivery (CISD) via displacement after a sweep.
Optionally refines entries with EPE when a local (internal) imbalance forms right after CISD.
Derives dynamic TP/BE/SL from measured displacement and recent extremes (not fixed distances).
Keeps a rules checklist (PDA tap → CRT → Sweep → CISD) and a relationships table (common HTF↔LTF pairings) to enforce process.
How it works (integration, not a mashup)
The modules are sequenced on one HTF time base so each step gates the next:
HTF PD Arrays (context zone). The model identifies valid HTF FVGs, filters tiny/weekend gaps, removes arrays that are invalidated by clean trades-through, and persists only the nearest PDA. This focuses attention on the institutional zone most likely to matter now.
CRT (directional gating). CRT on the same HTF establishes a provisional bias. No entries are implied; CRT simply permits or forbids the following steps. If CRT disagrees with the PDA context, the checklist remains incomplete.
Liquidity Sweep (event). The model tracks HTF-aware BSL/SSL pivots. A sweep only “counts” if it occurs in relation to the active PDA (tap/engagement). This prevents generic swing-high/low tags from triggering downstream logic.
CISD (confirmation). After a qualified sweep, the tool looks for displacement through the sequence open (the open of the impulsive leg beginning at or immediately after the sweep). Crossing that threshold confirms CISD, which marks a structural delivery shift consistent with the CRT bias.
EPE (refinement, optional). Immediately following CISD, the model scans for a fresh internal imbalance. If found quickly, it promotes that price area as the Easiest Point of Entry (EPE) and relabels the reference. If not, the CISD level remains primary.
Dynamic risk levels. TP/BE/SL are derived from the measured displacement around the CISD leg (e.g., BE ≈ 1× leg, TP ≈ 2.25× stretch; SL aligned to nearby structural extremes rather than a fixed pip offset). Levels update with structure and can display prices.
By chaining PDA → CRT → Sweep → CISD → (EPE) → Risk on a single HTF backbone, the tool creates a coherent workflow where later signals simply do not appear without earlier context. That’s why this is not a bundle of independent features: each module’s output is another module’s input.
Concepts & operational rules (high level)
HTF PD Arrays (FVGs)
Uses a standard three-candle gap definition on the chosen HTF, with filters for weekend/tiny gaps.
Inverse mitigation: if price trades cleanly through an array, the box is removed and internal state resets.
Nearest-PDA persistence: when multiple arrays exist, only the closest remains visible to reduce clutter.
Optional right-extension draws lingering influence X bars forward.
Candle Range Theory (CRT)
Bullish CRT: candle 2 wicks below candle 1’s low but closes back inside candle 1’s range, without taking its high.
Bearish CRT: candle 2 wicks above candle 1’s high but closes back inside candle 1’s range, without taking its low.
Role: bias validation paired to CISD when alignments match the active PDA.
Liquidity Sweeps (BSL/SSL)
Tracks candidate HTF pivots as buy-/sell-side liquidity.
A sweep registers when price takes a tracked pivot in the vicinity of the active PDA.
CISD (Change in State of Delivery)
Finds the sequence open for the impulsive leg that begins at/after the sweep.
Bearish path (after BSL sweep): CISD when close < sequence-open.
Bullish path (after SSL sweep): CISD when close > sequence-open.
On confirmation, the model plots a CISD line, checks the box in the Strategy Checklist, and triggers risk calc.
EPE (Easiest Point of Entry)
Within a short window after CISD, scans for a local imbalance; if present, promotes that level as EPE.
If no imbalance forms, CISD remains the operative reference.
Dynamic TP / BE / SL
Built from the measured leg around CISD (not fixed pip steps).
Approximate geometry: BE ≈ 1× leg, TP ≈ 2.25× leg; SL respects nearby structural extremes.
Labels and price markers are optional.
Architecture notes
Maps the current chart to a higher timeframe (e.g., 15s→M5, M1→M15, M5→H1, M15→H4, H1→D, H4→W, D→M).
Retrieves HTF OHLC/time with no lookahead so structures update intrabar until the HTF bar closes.
Periodic cleanup clears obsolete lines/labels/boxes to keep charts responsive.
Inputs (summary)
FVGs/PD Arrays: show/hide, colors, borders, label size, right-extension, nearest-only toggle.
CRT: enable/disable, label style.
Sweeps/CISD/EPE: enable/disable, line/label styles, EPE window.
Risk Levels (TP/BE/SL): enable each, price labels on/off, colors.
Tables/Checklist: strategy checklist on/off; relationships table (common HTF↔LTF pairings); text sizes and header colors.
Alerts (optional)
You may add alertconditions aligned with these events in your own workspace:
HTF PDA tap (bullish/bearish box)
CRT detected (bullish/bearish)
CISD confirmed (bullish/bearish)
EPE set/updated
Example messages:
“Prophet: CISD confirmed on {{ticker}} / {{interval}}”
“Prophet: EPE refined at {{close}} ({{time}})”
Notes & limitations
HTF values are provisional until the HTF bar closes; labels/levels can update while forming.
CISD/EPE are live conditions; they can form and later invalidate within the same HTF bar.
Liquidity relationships vary by market/regime; thin sessions and large gaps can affect clarity.
Educational tool only. No performance claims; no trade signals.
Originality & scope (for protected/invite-only publications)
A single HTF-synchronized engine sequences PDA → CRT → Sweep → CISD → (EPE) and withholds later steps unless prerequisites are met.
Nearest-PDA persistence and inverse-mitigation enforce focus on the most relevant institutional zone.
Displacement-based risk math ties TP/BE/SL to structure instead of static offsets.
Checklist + relationships table promote consistent, rules-first behavior and reduce discretionary drift.
Attribution: Concepts inspired by ICT (PD arrays/FVGs, CRT, sweeps, displacement, refined entries). Design, integration logic, and risk framework by TakingProphets.
HTF Candles [TakingProphets]HTF Candles — higher-timeframe structure, SMT divergence, and live OHLC projections
Purpose
Informational overlay to keep higher-timeframe (HTF) context visible on a lower-timeframe chart. It does not generate buy/sell signals and is not financial advice. Use it to structure analysis and alerts, not to automate trading.
What it does
HTF candle visualization (up to 10 candles, optional right-side offset) with bodies, wicks, and time labels.
SMT divergence checks on the chosen HTF—both historical (last two completed HTF bars) and real-time (last closed vs. current forming bar) vs. a user-selected correlated symbol (default can be an index future).
Live HTF OHLC projections: forward-extending Open / High / Low / Close from the current HTF bar with optional price labels and styling.
HTF close timer (optional) to show when the active HTF candle ends.
Why these modules belong together (more than a mashup)
This overlay uses one HTF time base to align three lenses of the same context:
Candle projection provides the structural frame (ranges and bodies of true HTF bars).
SMT divergence provides intermarket confirmation/invalidations on that same HTF, so the divergence you see is directly comparable to the projected candles.
Live OHLC projections turn the current HTF bar’s evolving state into concrete reference levels for intraday decisions.
Because all three share the same HTF clock and data source, alerts and drawings change together when the HTF state actually changes. The intent is a coherent workflow tool where each module gates the others (structure → confirmation → actionable references), rather than separate indicators merely co-plotted.
How it works (high-level)
Timeframe mapping & data
You choose an HTF (1m–1M). The script retrieves HTF OHLC/time without look-ahead. Objects update intrabar until the HTF bar closes.
Candle rendering
Up to 10 recent HTF candles are drawn as body boxes with wicks.
A horizontal offset/spacing option places the stack right of the current price for clarity.
Visuals (colors, transparency, borders, wick width, label size/format 12h/24h) are configurable.
SMT divergence (historical & real-time)
Compares HTF highs/lows of your chart vs. a correlated symbol using the same HTF.
Bearish SMT (high-side): one makes a higher high while the other does not.
Bullish SMT (low-side): one makes a lower low while the other does not.
Historical mode compares HTF → HTF ; real-time mode compares HTF → HTF as the current HTF bar forms.
Optional lines/labels mark where the divergence is detected.
Live OHLC projections
Extends the current HTF Open / High / Low / Close forward as horizontal lines.
Anchors: Open = first bar of the HTF period; High/Low = first occurrence of each extreme inside the period; Close = current bar.
Each level has independent toggles for price labels, style, and width.
Alerts (workflow prompts)
Bullish SMT, Bearish SMT, Bullish Real-time SMT, Bearish Real-time SMT.
Fire on the bar where the condition first becomes true.
Inputs & customization
Timeframe: select HTF (1m–1M).
Display: number of candles (1–10), right-offset, candle width, transparency, time labels on/off (12h/24h), label size, HTF close timer on/off.
Visuals: bullish/bearish body colors, border color, wick color.
SMT: enable/disable, correlated symbol, line style/width, labels on/off, alerts on/off.
Projections: enable/disable, per-level toggles (Open/High/Low/Close), color/style/width, optional price labels.
Notes & limitations
HTF values are provisional until the HTF bar closes; lines/labels can update during formation.
SMT usefulness depends on the correlated symbol you select; relationships vary by market/regime.
Session gaps/low liquidity can affect extremes and time labels.
Educational tool only. No performance claims and no trade signals.
Originality & scope (for protected/invite-only publications)
A single HTF-synchronized engine: candle projection, dual-mode SMT, and live OHLC projections all computed from the same HTF series to ensure consistent timing and interpretation.
Real-time SMT explicitly ties the developing HTF bar to the prior closed bar, reducing ambiguity vs. generic divergence checks.
Projection anchoring (first-occurrence rules for H/L, period start for Open, current bar for Close) provides deterministic, reproducible reference levels.
ZLSMA_CEThis indicator combines the power of Chandelier Exit and Zero Lag LSMA (ZLSMA) to provide cleaner trend reversals and early entry alerts.
The Chandelier Exit acts as a dynamic stop-loss and trend tracker based on ATR, while ZLSMA smooths price movement with minimal lag — helping traders identify trend continuation or reversals more accurately.
When combined, this system provides visual and alert-based Buy/Sell signals that can be used for both swing and intraday strategies.
ZarzaZarza All-in-One Indicator for God’s Kingdom
“But remember the Lord your God, for it is He who gives you the power to get wealth, that He may establish His covenant.” — Deuteronomy 8:18
The Zarza All-in-One Indicator is more than a trading tool — it’s a divinely inspired system designed to help Kingdom traders operate with clarity, discipline, and spiritual alignment in the markets.
Built to detect momentum shifts, liquidity zones, reversals, and smart-money movements, this indicator brings together the best of technical precision and prophetic purpose.
This isn’t just about charts — it’s about stewardship.
Every trade is an act of faith and discernment, partnering with Heaven’s wisdom to prepare for the great wealth transfer that will fund God’s Kingdom projects and reach souls across the nations.
Rupeebees Active Option Levels V4This indicator helps you understand the nature of Active options in relationship each other and helps you to predict market trend .
Rupeebees Option OHLC Levels This indicator works with the principle that Option premium calculation can help you to understand the supply and demand in a trend direction.
Rupeebees Option OHLC Levels This Indicator will help you to understand market direction and demand and supply in the active options.All the details are only made with the option premium calculation.
EMA (5, 10, 20, 50, 100, 150, 200)+VWAP+BBEMA Cluster + VWAP + Bollinger Bands + Alerts + Visual Signals (Fixed)
AO Divergence RCT PRO//@description=This indicator, AO Divergence Pro, is a powerful tool designed to automatically identify and plot both classic and hidden divergences on the Awesome Oscillator (AO). Divergences occur when the price action and the oscillator move in opposite directions, often signaling a potential shift in market momentum.
//
// --- Key Features ---
// 1. Regular (Classic) Divergence Detection: This feature identifies potential trend reversals.
// - A **Bullish Regular Divergence** (labeled 'R') is found when the price makes a lower low, but the AO makes a higher low. This suggests that downward momentum is weakening and a reversal to the upside may be imminent.
// - A **Bearish Regular Divergence** (labeled 'R') is found when the price makes a higher high, but the AO makes a lower high. This suggests that upward momentum is fading and a reversal to the downside may be coming.
//
// 2. Hidden Divergence Detection: This feature identifies potential trend continuations.
// - A **Bullish Hidden Divergence** (labeled 'H') is found when the price makes a higher low, but the AO makes a lower low. This often occurs during a pullback in an uptrend, suggesting the trend is likely to resume.
// - A **Bearish Hidden Divergence** (labeled 'H') is found when the price makes a lower high, but the AO makes a higher high. This often occurs during a rally in a downtrend, suggesting the downtrend is likely to continue.
//
// 3. Full Customization: The indicator allows you to toggle the display of each type of divergence (Bullish/Bearish, Regular/Hidden) independently. You can also adjust the pivot detection sensitivity and the time range between divergences to filter signals according to your trading style.
//
// --- How to Use ---
// 1. **Identify Reversals:** Look for the 'R' labels on the chart. A bullish 'R' in a downtrend is a strong signal to consider a long position. A bearish 'R' in an uptrend is a signal to consider a short position.
// 2. **Confirm Continuations:** Look for the 'H' labels. A bullish 'H' during an uptrend pullback can be a good opportunity to add to your position. A bearish 'H' during a downtrend rally can be a signal to enter a short trade.
// 3. **Filter Signals:** Use the settings panel to control the number of signals. For example, increasing the "Min Bars Between" will show fewer, but potentially more reliable, divergences.
//
// --- Attribution ---
// Created by Carlos Mauricio Vizcarra.
//
// --- Disclaimer ---
// This script is for informational and educational purposes only. It is not financial advice. Past performance is not indicative of future results.
KP_EMA_Cross_signal KP_EMA_Cross_signal : This signal removes a lot of false signals and will help in day trading.
Quarter Levels — Auto Recentering NQ onlyQuarter Levels — Auto Recentering (PERMANENT) + Big Offset Labels
What it is
This tool paints true horizontal key levels that traders naturally anchor to: the 00 / 25 / 50 / 75 quarter levels (black), the 35 / 65 / 90 reaction levels (red), and the 10 / 80 sweep/edge levels (purple).
Lines are infinite horizontals and the grid auto-recenters ±200 points around current price each new bar. Labels on the right show the last two digits (e.g., 25, 35, 50, 65, 75, 80, 90), so you instantly know which level you’re at.
Why it helps
Markets often “snap” to simple numbers. These levels create a clean scaffold for intraday structure, pullbacks, and rotations—without clutter or lagging math.
Color Legend
Black — 00 / 25 / 50 / 75:
Core quarter levels. Expect frequent pauses, re-tests, and rotations.
Use: default S/R map; bias for mean-reversion inside ranges.
Red — 35 / 65 / 90:
“Continuation / reaction” levels. Price often accelerates through these once momentum takes.
Use: breakout guides and precise take-profit targets.
Purple — 10 / 80:
Sweep / edge levels. Price often wicks into these and rejects.
Use: fade the last push, or confirm a sweep before a reversal.
How it works
The script draws the levels as extend.both horizontals (not derived from candle points).
Every new bar, it rebuilds the grid around close ± 200 pts (editable in code: RANGE_POINTS).
Prices are snapped to tick (syminfo.mintick) so lines lock to the Y-axis.
Labels show only the offset (two-digit number) to keep the chart clean.
Setup & Customization
No inputs required.
If you want tweaks, open the code and edit at the top:
RANGE_POINTS – widen/narrow the vertical coverage.
LABEL_OFFSET – push labels further to the right.
LABEL_SIZE – size.small / normal / large.
Color & width constants (per group).
Practical Use (playbook)
Use this grid as a price map, not a signal generator. Combine it with your execution tools.
1) In Range Conditions
Fade to Black: When price rotates inside a range, look for exhaustion into black levels (00/25/50/75).
Plan: wait for rejection (wick + failed follow-through), enter back toward the mid/next quarter. Stop just beyond the level; first target the next red or black.
Purple Sweeps: Watch quick spikes into 10/80 that immediately fail.
Plan: fade the sweep with tight risk; scale out at 25/75; hold a runner to 50.
2) In Trend / Momentum
Red Rails (35/65/90): When momentum is strong, price often steps through red levels cleanly.
Plan: use them as continuation targets or trail anchors. If pullback holds above a prior red level, consider continuation with stop below that level.
Quarter-to-Quarter Ladders: In clean trends, expect quarter-to-quarter traversals (00→25→50→75→00…).
Plan: add on pullbacks to 25 or 50 with trend confirmation (e.g., 9/21 EMA stack or anchored VWAP hold).
3) Confluence (AI-logic suggestions)
Pair the grid with any two of:
VWAP / Anchored VWAP: Rejections at a quarter level + VWAP = higher quality entry.
EMAs (9/21/50/200): Use as directional filter. Only take longs at quarters when fast EMAs > slow EMAs.
Liquidity cues: Prior high/low, session O/H/L, or liquidity pools aligning with a quarter level.
Orderflow / footprint: Aggressive delta through a red level? Expect follow-through to the next black or red.
Volatility (ATR): If ATR expands, lean more on red levels (continuations). In compression, lean more on black and purple (fades).
Risk & Management Tips
Stops: Just beyond the level you’re trading against. Let the level “be wrong” to prove you wrong.
Targets: Next red or black line. Scale at the first, hold a small runner to the next.
Session awareness: Levels interact differently in Asia/EU/US. In US RTH, expect sharper responses at red and purple.
Timeframes: Works across all. Intraday (1–15m) for entries; 1h/4h daily for context.
Do not chase: If you miss the touch, wait for the next level; the map is dense by design.
Limitations
This indicator does not generate buy/sell signals; it supplies a stable structure.
In runaway trends, price can cut through multiple lines—use trend filters and risk caps.
Auto-recentering means the visible band travels with price; if you need static levels far away, increase RANGE_POINTS.
Troubleshooting
No labels? Make sure max_labels_count isn’t hit and SHOW_LABELS = true.
Labels too close to price? Increase LABEL_OFFSET.
Too many lines? Reduce RANGE_POINTS or hide a color group in code.
Credits / License
Created by: TRC — The Refuge Camp
License: Free to use on TradingView with attribution.
If you fork or embed, please credit “TRC — The Refuge Camp” and link back to the original post/profile.
Quick Start (TL;DR)
Add the script.
Trade the map:
Fade purple/black in ranges.
Target red/black in trends.
Combine with VWAP/EMAs or your orderflow tool for confirmation.
Respect stops just beyond the level; scale at the next line.
Happy trading, and welcome to the Quarter-Level grid.
Liquidity Sweeps 2nd attemptLiquidity Sweeps 2nd attempt
The Liquidity Sweeps indicator detects the presence of liquidity sweeps on the user's chart, while also providing potential areas of support/resistance or entry when Liquidity levels are taken.
In the event of a Liquidity Sweep a Sweep Area is created which may provide further areas of interest.
KCP FRAMA Trend [Dr.K.C.PRAKASH]KCP FRAMA Trend
An adaptive trend indicator based on the Fractal Adaptive Moving Average (FRAMA).
It identifies breakout zones with clear BUY (green) and SELL (red) signals, colors candles by trend direction, and includes real-time alert conditions for precise trade entries and exits.
