Moderate Value Screener (NASDAQ + NYSE + TSX v6 FINAL CLEAN)Moderate Value Screener (NASDAQ + NYSE + TSX v6 FINAL CLEAN)
Indikatoren und Strategien
Pump-Smart Shorting StrategyThis strategy is designed for actively hedging long token positions by opening and closing short positions in response to market momentum, specifically after strong upward moves ("pumps"). It incorporates momentum detection, cooldown logic, and avoids shorting during periods of high volatility or when a pump is active. The script includes risk management, visual feedback zones for operational states, and a control panel for real-time diagnostics.
How The Strategy Works
1. Pump Detection
The strategy monitors for strong upward moves using:
- RSI (Relative Strength Index): A value ≥ 70 signals strong buying momentum.
- Volume: If current volume exceeds 1.5× the average, combined with a single-bar price jump > 5%.
- When these pump conditions are met, the strategy blocks shorts and colors the background orange.
2. Pump End and Cooldown
Once pump conditions cease, the strategy enters a cooldown phase:
RSI must drop to ≤ 60.
Either the price momentum slows or volume returns to near average.
Users can set a waiting period (barsWait) after the pump ends before entering shorts.
3. Short Trade Entry
Shorts are opened only if:
- The pump has ended and cooldown conditions are met (shortAfterPump).
- Or a new high is established and no pump is underway (shortOnPeak).
Visual indicators:
Blue arrow for "short after pump".
Red arrow for "short on a new high".
4. No-Short Zones
A red background flag indicates zones where shorting is blocked:
If pump conditions are active.
If market is still cooling down post-pump.
If the cooldown period (barsWait) hasn't elapsed.
5. Position Management & Risk Controls
The script only opens a short if no short is currently active.
Take Profit (green line): Short closes if price falls ~2% below the short entry.
Stop Loss (red line): Short closes if price rises ~6% above the entry.
If a pump is detected while in a short, the position is closed immediately to mitigate risk.
6. Real-Time Visual Feedback
Shapes Above Bars:
Orange circle: pump start
Teal circle: pump end
Blue triangle: short after pump
Red triangle: short on new high
Overlay Lines:
Blue line: active short entry price
Green line: take profit threshold
Red line: stop loss threshold
Background Colors:
Orange: pump zone (no shorts)
Blue: post-pump entry zone
Red: no-short zone (visual block for restricted shorts)
Info Panel (top right): Shows pump status, cooldown, entry opportunities, and whether shorting is blocked.
Customization Parameters
lookbackPeriod: Bars to look back for new highs
minProfitPerc: Take profit percent on shorts
stopLossPerc: Maximum allowed loss percent before stop out
rsiPeriod, rsiHigh, rsiCool: Momentum detection/cooldown tuning
volMult, pctUp: Volume and price jump sensitivity for pump detection
barsWait: Number of bars to wait post-pump before allowing shorts
hedgeTokens: Short position size per entry
Use Cases
Active Hedging: For users managing large, illiquid spot positions who want to systematically hedge risk after large upward moves.
Momentum-Aware Shorting: Ensures shorts are only entered after euphoria cools, tactics for avoiding squeeze/liquidation risk.
Visual Diagnostics: Clear overlays and color codes for trading zones, signal clarity, and operational feedback.
Strategy Logic Summary
Condition Action Visual Feedback
Pump detected Block shorts, close shorts Orange/red background
Pump ended, cooled Enable shorts Blue background, arrow
New high (no pump) Allow short entry Red arrow
Take profit reached Close short Green line
Stop loss reached Close short Red line
Blocked zone No shorts allowed Red background
This script is robust for market environments with frequent volatility spikes, giving traders a clear, rule-based template for short-side risk management.Documentation: Short After Pump Ends Strategy
Purpose: This Pine Script strategy allows you to hedge long token positions by opening shorts after strong price pumps finish and during market consolidations. It is designed to minimize risk from short squeezes and avoid shorting during active pumps.
Key Features:
Pump Detection:
Uses RSI, volume, and single-bar price jump to detect if the market is in an upward pump.
No short positions are opened during these zones. Red background visually highlights these periods.
Orange background highlights active pump zones.
Cooldown Logic:
Shorts are only opened after the pump has ended and the market has cooled down (RSI ≤ 60, volume and momentum returned to normal).
You can set how many bars to wait after the pump ends (barsWait) before shorts can be placed again.
Short Entry Triggers:
Short After Pump: When cooldown completes and no short position is active.
Short on New High: If a new high is formed and no pump is active (optional; keep for more frequent entries).
Risk Management:
Take Profit (TP): Short closes if market falls the specified percentage from entry.
Stop Loss (SL): Short closes if market rises the specified percentage.
If a pump is detected while in a short, the short is closed immediately.
Visuals and Feedback:
Shape markers for pump start/end, short entries (arrows) — without labels for clean visuals.
Colored overlays:
Orange = pump zone (no shorting)
Blue = post-pump short entry zones
Red = no-short zones (blocked periods)
Panel widget displays pump status, cooldown, opportunities, and zone state.
Parameters:
lookbackPeriod: Number of bars for new high detection.
minProfitPerc: Take profit percentage for shorts.
stopLossPerc: Max loss percentage before the short is stopped.
rsiPeriod, rsiHigh, rsiCool: Controls for pump/cooldown detection.
volMult, pctUp: Volume and price jump detection for identifying pumps.
barsWait: Wait time after pump ends before shorts are allowed.
hedgeTokens: Number of tokens to use for each short position.
Logic Summary Table:
Market Condition Action Visual Feedback
Pump detected No shorts/open, close shorts Orange/red overlay
Pump ended and cooled Shorts enabled (entry) Blue overlay, no short zone removed
New high while not pumping Shorts enabled (entry) Red arrow
TP or SL hit Short closed Green/red line overlay
Blocked periods No short allowed Red overlay
Usage:
- Deploy this strategy to minimize drawdown from post-pump reversals.
- Identify and avoid risky periods with clear overlays and marker signals.
- Actively hedge positions only when market is not in a strong upward momentum.
Customizable for:
- More conservative/aggressive pump detection (change RSI/volume/price thresholds).
- Adaptable to different token sizes and market environments (modify hedgeTokens, waiting periods, percent thresholds).
FMFM60الوصف بالعربية:
هذا المؤشر متقدم ويعرض اتجاه السوق والترند بشكل واضح، ويحدد مناطق العرض والطلب (Supply & Demand) بالإضافة إلى فجوات القيمة العادلة (FVG). يوفر إشارات شراء وبيع (Call و Put) عند كسر أو اختراق المستويات الهامة. كما يحدد أهدافًا ومستويات دعم ومقاومة رئيسية. المؤشر مناسب لجميع المتداولين الراغبين في تحليل السوق بدقة واتخاذ قرارات تداول مستنيرة.
الوصف بالإنجليزية:
This is an advanced indicator that clearly displays the market direction and trend, and identifies Supply & Demand zones along with Fair Value Gaps (FVG). It provides Buy and Sell signals (Call and Put) when key levels are broken or breached. It also defines targets and major support and resistance levels. The indicator is suitable for all traders who want precise market analysis and informed trading decisions.
Gann-ADeLLaunch the indicator and select an important and influential high and low on the daily time frame. In the information window on the right side of the chart, move the numbers shown in the levels section forward from the second point you selected and draw a vertical line and wait for a reversal on these time frames and enjoy trading.
Don't forget about price action.
ADeL - Fn
Fmfm50الوصف بالعربية:
هذا المؤشر متقدم ويعرض اتجاه السوق والترند بشكل واضح، ويحدد مناطق العرض والطلب (Supply & Demand) بالإضافة إلى فجوات القيمة العادلة (FVG). يوفر إشارات شراء وبيع (Call و Put) عند كسر أو اختراق المستويات الهامة. كما يحدد أهدافًا ومستويات دعم ومقاومة رئيسية. المؤشر مناسب لجميع المتداولين الراغبين في تحليل السوق بدقة واتخاذ قرارات تداول مستنيرة.
الوصف بالإنجليزية:
This is an advanced indicator that clearly displays the market direction and trend, and identifies Supply & Demand zones along with Fair Value Gaps (FVG). It provides Buy and Sell signals (Call and Put) when key levels are broken or breached. It also defines targets and major support and resistance levels. The indicator is suitable for all traders who want precise market analysis and informed trading decisions
ICT Sessions With BOS [TradeWithRon]
WITH BOS
This version includes BOS with filter for each session.
NONE,FVG,CISD Filter preset
you can choose how many BOS per session, style etc.
ICT Sessions and killzones maps three intraday sessions on your chart (Asia, London, NY), tracks each session’s live high/low, draws optional session range boxes, and projects ICT OTE zones in real time—with granular styling, touch/mitigation logic, and alerting.
What it does
*Live Session high/low tracking.
Historical session lines:
When a session ends, its final High/Low are preserved as tracked lines (with optional labels) for a configurable number of recent sessions.
Session boxes (ranges):
Draws a shaded box from session start to end that expands with new highs/lows. Limit how many recent boxes remain on chart.
ICT OTE zones (live):
For the currently active session, projects user-defined Fibonacci OTE levels (e.g., 61.8%, 70.5%, 78.6) between the session’s running high and low. Zones update tick-by-tick and can show labels. You can retain a history of recent sessions’ OTE levels.
snapshot
Break visualization (mitigation):
Optionally color the bar when price breaks a stored session High/Low. You can:
Require a body close through the level (vs. any touch)
Auto-remove the line and/or label on touch/close
Use custom break colors per session and side (high/low)
Timestamps:
Add up to two recurring vertical timestamp markers (e.g., 08:00, 09:30), plus an opening horizontal marker (e.g., 09:30) with label that extends until the next occurrence.
Alerts:
Built-in alerts for:
Touch of Session 1/2/3 High/Low (Asia/London/NY)
Touch of OTE levels (per session)
Key inputs:
Time & Limits
Timezone (e.g., GMT-4)
Timeframe limit: hide all drawings on and above a specified TF
Sessions
Session windows (default):
Session 1 (Asia): 18:00–00:00
Session 2 (London): 00:00–06:00
Session 3 (NY): 08:00–12:00
How many to keep (lines/boxes)
Line width, colors, and label suffixes (“High”/“Low”)
Labels: toggle, text (“Asia”, “London”, “NY”), size, and colors
Boxes: toggle per session and background colors
ICT OTE Zones
Toggle per session (Asia/London/NY)
Levels (comma-separated %s, e.g., 61.8,70.5,78.6)
History: number of past sessions to retain
Opacity, line width/style, and label size
Custom label text per session (e.g., “Asia OTE”)
Break/Mitigation Behavior:
Enable Mitigated Candles (bar color on break)
Remove line on touch and/or remove label on touch
Require body close (vs. wick touch)
Custom break colors by session and side
Timestamps
Opening horizontal line (time, style, width, color, label text/size, drawing limit)
Two vertical timestamps (times, style, width, color, drawing limit)
Alerts
Master Enable Alerts
Per-session toggles for High/Low touches
OTE touch alerts
How it works (under the hood)
Detects session state via input.session() windows in the chosen timezone.
Live session High/Low lines and labels update in real time; on session end, final levels are stored with optional labels and tracked length.
OTE zones are live-computed from current session High↔Low and refreshed every bar; a compact rolling history is enforced.
Bar coloring reacts to break events (touch or body-close, per your setting) and uses session-specific colors when enabled.
Timestamp lines/labels are created on each occurrence and trimmed to a drawing limit for performance.
Tips:
To hide session lines but keep boxes, set line color opacity to 0.
Use Timeframe Limit to keep higher-TF charts clean.
Fine-tune OTE Levels and History to balance clarity and performance.
For stricter break logic, enable Require Body Close.
Note: The script reserves high limits for lines/labels/boxes to keep recent context visible while managing cleanup automatically. Adjust “Session Number” and “Number Of Boxes” to suit your workflow.
— © TradeWithRon
PulseGrid Universal Scalper - Adaptive Pulse and Symmetric SpansInstrument agnostic. Works on any symbol and timeframe supported by TradingView.
Message or hit me up in chat for full access .
Purpose and scope
PulseGrid is a short timeframe strategy designed to read intrabar structure and recent path so that entries align with actionable momentum and context. The strategy is private. The description below provides all the information needed to understand how it behaves, how it sizes risk, how to tune it responsibly, and how to evaluate results without making unrealistic claims. The design is instrument agnostic. It runs on any asset class that prints open high low close bars on TradingView. That includes commodities such as Gold and WTI, currencies, crypto, equity indices, and single stocks. Performance will always depend on the symbol’s liquidity, spread, slippage, and session structure, which is why the description focuses on principles and safe parameter ranges instead of hard promises.
What the strategy does at a glance
It builds a composite entry signal named Pulse from five normalized bar features that reflect short term pressure and follow through.
It applies regime guards that keep the strategy inactive when the tape is either too quiet, too bursty, or too directionally random.
It optionally uses a directional filter where a fast and a slow exponential average must agree and their gap must be material relative to recent true range.
When a signal is allowed, risk is sized using symmetric spans that come from nearby untraded price distances above and below the market. The strategy sets a single stop and a single take profit from those spans.
Lines for entry, stop, and take profit are drawn on the chart. A compact on chart table shows trade counts, win rate, average R per trade, and profit factor for all trades, longs only, and shorts only.
This combination yields entries that are reactive but not chaotic, and risk lines that respect the market’s recent path instead of generic pip or point targets.
Why the design is original and useful
The core originality is the union of a composite entry that adapts to volatility and a geometry based risk model. The entry uses five different viewpoints on the same bar space instead of relying on a single technical indicator. The risk model uses spans that come from actual untraded distance rather than fixed multipliers of a generic volatility measure. The result is a framework that is simple to read on a chart and simple to evaluate, yet it avoids the traps of curve fitting to one symbol or one month of data. Because everything is normalized locally, the same logic translates across asset classes with only modest tuning.
The Pulse composite in detail
Pulse is a weighted blend of the following normalized features.
Impulse imbalance. The script sums upward and downward impulses over a short window. An upward impulse is the extension of highs relative to the prior bar. A downward impulse is the extension of lows relative to the prior bar. The net imbalance, scaled by the local range, captures whether extension pressure is building or fading.
Wick and close location. Inside each bar, the distance between the close and the extremes carries information about rejection or acceptance. A bar that closes near the high with relatively heavier lower wick suggests upward acceptance. A bar that closes near the low with heavier upper wick suggests downward acceptance. A weight controls the contribution of wick skew versus close location so that users can favor reversal or momentum behaviour.
Shock touches. Within the recent range window, touches that occur very near the top decile or bottom decile are marked. A short sliding window counts recent shocks. Frequent top shocks in a rising context suggest supply tests. Frequent bottom shocks in a declining context suggest demand tests. The count is normalized by window length.
Breakout ledger. The script compares current extremes to lagged extremes and keeps a simple count of recent upside and downside breakouts. The difference behaves as a short term polarity meter.
Curvature. A simple second difference in closing price acts as a curvature term. It is normalized by the recent maximum of absolute one bar returns so that the value remains bounded and comparable to other terms.
Pulse is smoothed over a fraction of the main signal length. Smoothing removes impulse spikes without destroying the quick reaction that scalpers need. The absolute value of smoothed Pulse can be used with an adaptive gate so that only the top percentile of energy for the recent environment is eligible for entries. A small floor prevents accidental entries during very quiet periods.
Regime guards that keep the strategy selective
Three guards must all pass before any entry can occur.
Auction Balance Factor. This is the proportion of closes that land inside a mid band of the prior bar’s high to low range. High values indicate balanced chop where breakouts tend to fail. Low values indicate directional conditions. The strategy requires ABF to sit below a user chosen maximum.
Dispersion via a Gini style measure on absolute returns. Very low dispersion means bars are small and uniform. Very high dispersion means a few outsized bars dominate and slippage risk can be elevated. The strategy allows the user to require the dispersion measure to remain inside a band that reflects healthy activity.
Binary entropy of direction. Over the core window, the proportion of up closes is used to compute a simple entropy. Values near one indicate coin flip behaviour. Values near zero indicate one sided sequences. The guard requires entropy below a ceiling so that random directionality does not produce noise entries.
An optional directional filter asks that a fast and a slow exponential average agree on direction and that their gap, when divided by an average true range, exceed a threshold. This filter can be enabled on symbols that trend cleanly and disabled when the composite entry is already selective enough.
Risk sizing with symmetric spans
Instead of fixed points or a pure ATR multiplier, the strategy sizes stops and targets from a pair of spans. The upward span reflects recent untraded distance above the market. The downward span reflects recent untraded distance below the market. Each span is floored by a fallback that comes from the maximum of a short simple range average and a standard average true range. A tick based floor prevents microscopic stops on instruments with high tick precision. An asymmetry cap prevents one span from becoming many times larger than the other. For long entries the stop is a multiple of the downward span and the target is a multiple of the upward span. For short entries the stop is a multiple of the upward span and the target is a multiple of the downward span. This creates a risk box that is symmetric by construction yet adaptive to recent voids and gaps.
Execution, ties, and housekeeping
Entries evaluate at bar close. Exits are tested from the next bar forward. If both stop and target are hit within the same bar, the outcome can be resolved in a consistent way that favors the stop or the target according to a single user setting. A short cooldown in bars prevents flip flops. Users can restrict entries to specific sessions such as London and New York. The chart renders entry, stop, and target lines for each trade so that every action is visible. The table in the top right shows trade counts, take profit and stop counts, win rate, average R per trade, and profit factor for the whole set and by direction.
Defaults and responsible backtesting
The default properties in the script use a realistic initial capital and commission value. Users should also set slippage in the strategy properties to reflect their broker and symbol. Small timeframe trading is sensitive to friction and the strategy description does not claim immunity to that reality. The strategy is intended to be tested on a dataset that produces a meaningful sample of trades. A sample in the range of a hundred trades or more is preferred because variance in short samples can be large. On thin symbols or periods with little regular trading, users should either change timeframe, change sessions, or use more selective thresholds so that the sample contains only liquid scenarios.
Universal usage across markets
The strategy is universal by design. It will run and produce lines on any open high low close series on TradingView. The composite entry is made of normalized parts. The regime guards use proportions and bounded measures. The spans use untraded distance and range floors measured in the local price scale. This allows the same logic to function on a currency pair, a commodity, an index future, a stock, or a crypto pair. What changes is calibration.
A safe approach for universal use is as follows.
Start with the default signal length and wick weight.
If the chart prints many weak signals, enable the directional filter and raise the normalized gap threshold slightly.
If the chart is too quiet, lower the adaptive percentile or, with adaptive off, lower the fixed pulse threshold by a small amount.
If stops are too tight in quiet regimes, raise the fallback span multiplier or raise the minimum tick floor in ticks.
If you observe long one sided days, lower the maximum entropy slightly so that entries only occur when directionality is genuine rather than alternating.
Because the logic is bounded and local, these simple steps carry over across symbols. That is why the strategy can be used literally on any asset that you can load on a TradingView chart. The code does not depend on a specific tick size or a specific exchange calendar. It will still remain true that symbols with higher spread or fewer regular trading hours demand stricter thresholds and larger floors.
Suggested parameter ranges for common cases
These ranges are guidelines for one to five minute bars. They are not promises of performance. They reflect the balance between having enough signals to learn from and keeping noise controlled.
Signal length between 18 and 34 for liquid commodities and large capitalization equities.
Wick weight between 0.30 and 0.50 depending on whether you want reversal recognition or close momentum.
Adaptive gate percentile between 85 and 93 when adaptive is enabled. Fixed threshold between 0.10 and 0.18 when adaptive is disabled. Use a non zero floor so very quiet periods still require some energy.
Auction Balance Factor maximum near 0.70 for symbols with clear session bursts. Slightly higher if you prefer to include more balanced prints.
Dispersion band with a lower bound near 0.18 and an upper bound near 0.68 for most session instruments. Tighten the band if you want to skip very bursty days or very flat days.
Entropy maximum near 0.90 so coin flip phases are filtered. Lower the ceiling slightly if the symbol whipsaws frequently.
Stop multiplier near one and take profit multiplier between two and three for a single target approach. Larger target multipliers reduce hit rate and lengthen holding time.
These are safe starting points across commodities, currencies, indices, equities, and crypto. From there, small increments are preferred over dramatic changes.
How to evaluate responsibly
A clean chart and a direct test process help avoid confusion. Use standard candles for signals and exits. If you use a non standard chart type such as Heikin Ashi or Renko, do so only for visualization and not for the strategy’s signal computation, as those chart types can produce unrealistic fills. Turn off other indicators on the published chart unless they are needed to demonstrate a specific property of this strategy. When you post results or discuss outcomes, include the symbol, timeframe, commission and slippage settings, and the session settings used. This makes the context clear and avoids misleading readers.
When you look at results, consider the following.
The distribution of R per trade. A positive average R with a moderate profit factor suggests that exits are sized appropriately for the symbol.
The balance between long and short sides. The HUD table separates the two so you can see if one side carries the edge for that symbol.
The sensitivity to the tie preference. If many bars hit both stop and take profit, the market is chopping inside the risk box and you may need larger floors or stricter regime guards.
The session effect. Session hours matter for many instruments. Align your session filter with where liquidity and volatility concentrate.
Known limitations and honest warnings
PulseGrid is not a guarantee of future profit. It is a systematic way to read short term structure and to size risk in a way that reflects recent path. It assumes that the data feed reflects the exchange reality. It assumes that slippage and spread are non zero and uses explicit commission and user provided slippage to approximate that. It does not place multiple targets. It does not trail stops. It is not a high frequency system and does not attempt to model queue priority or microsecond fills. On illiquid symbols or very short timeframes outside regular hours, signals will be less reliable. Users are responsible for choosing realistic settings and for evaluating whether the symbol’s conditions are suitable.
First use checklist
Load the symbol and timeframe you care about.
If the instrument has clear sessions, turn on the session filter and select realistic London and New York hours or other sessions relevant to the instrument.
Set commission and slippage in the strategy properties to values that match your broker or exchange.
Run the strategy with defaults. Look at the HUD summary and the lines.
Decide whether to enable the directional filter. If you see frequent reversals around the entry line, enable it and raise the normalized gap threshold slightly.
Adjust the adaptive gate. If the chart floods, raise the percentile. If the chart starves, lower it or use a slightly lower fixed threshold.
Adjust the fallback span multiplier and tick floor so that stops are never microscopic.
Review per session performance. If one session underperforms, restrict entries to the better one.
This simple process takes minutes and transfers to any other symbol.
Why this script is private
The source remains private so that the underlying method and its implementation details are not copied or republished. The description here is complete and self contained so that users can understand the purpose, originality, usage, and limitations without needing to inspect the source. Privacy does not change the strategy’s on chart behavior. It only protects the specific coding details.
Guarantee and compliance statements
This description does not contain advertising, solicitations, links, or contact information. It does not make performance promises. It explains how the script is original and how it works. It also warns about limitations and the need for realistic assumptions. The strategy is not investment advice and is not created only for qualified investors. It can be tested and used for educational and research purposes. Users should read TradingView’s documentation on script properties and backtesting. Users should avoid non standard chart types for signal computation because those produce unrealistic results. Users should select realistic account sizes and friction settings. Users should not post claims without showing the settings used.
Closing summary
PulseGrid is a compact framework for short timeframe trading that combines a composite entry built from multiple normalized bar features with a symmetric span model for risk. The entry adapts to volatility. The regime guards keep the strategy inactive when the tape is either too quiet or too erratic. The risk geometry respects recent untraded spans instead of arbitrary distances. The entire design is instrument agnostic. It will run on any symbol that TradingView supports and it will behave consistently across asset classes with modest tuning. Use it with a clean chart, realistic friction, and enough trades to make your evaluation meaningful. Use sessions if the instrument concentrates activity in specific hours. Adjust one control at a time and prefer small increments. The goal is not to find a magic parameter. The goal is to maintain a stable rule set that reads market structure in a way you can trust and audit.
The Eligible Asset Power Table -> PROFABIGHI_CAPITAL🌟 Overview
The Eligible Asset Power Table is a multi-asset screening dashboard that assesses cryptocurrency portfolios across multiple momentum, risk, and relative metrics to generate eligibility scores. It combines RSI variants, rate of change layers, Sharpe ratios, momentum RSI, price delta analysis, and beta exposure to rank assets, helping traders identify high-conviction opportunities through dual-mode scoring and visual tables.
⚙️ General Settings
- Evaluation mode toggle between aggressive averaging for nuanced scoring or conservative consensus requiring all conditions met for full eligibility
- Number of assets to screen, adjustable up to the platform's data fetch limits for focused or comprehensive portfolio reviews
- Count of top-ranked assets for a dedicated summary table, customizable to highlight leading candidates without overwhelming the display
📊 Indicator Parameters - RSI#1
- Source price selection for RSI input, allowing adaptation to closes, highs, or other series for tailored momentum sensitivity
- Period length for the shorter RSI variant, tuning detection of near-term overbought or oversold zones
- Primary smoothing moving average type, from basic to advanced options like hull or variable index for refined signal clarity
- Length for the first smoothing layer, balancing lag and responsiveness in volatile conditions
- Secondary smoothing moving average type, enabling dual-layer processing or crossover comparisons for added confirmation
- Length for the second smoothing layer, providing deeper trend stability
- Toggle for second MA comparison mode, shifting from fixed thresholds to dynamic relative movements
- Volatility lookback for adaptive smoothing when using variable index methods, responding to market dispersion
📊 Indicator Parameters - RSI#2
- Period length for the medium-term RSI variant, capturing sustained momentum beyond immediate fluctuations
- Primary smoothing moving average type applied to the longer RSI, consistent with RSI#1 for uniform processing
- Length for the first RSI#2 smoothing, optimizing for intermediate trend persistence
- Secondary smoothing moving average type, supporting layered refinement or bullish/bearish crossovers
- Length for the second RSI#2 smoothing, enhancing equilibrium zone reliability
- Toggle for second MA comparison, favoring motion-based conditions over static levels
- Volatility lookback specific to RSI#2's adaptive smoothing, scaling to regime changes
📈 Indicator Parameters - ROC#1
- Period length for the shortest rate of change, emphasizing immediate price acceleration for quick trend shifts
📈 Indicator Parameters - ROC#2
- Period length for the medium rate of change, evaluating ongoing momentum to validate directional strength
📈 Indicator Parameters - ROC#3
- Period length for the longest rate of change, assessing extended trends to confirm multi-period alignment
⚡ Indicator Parameters - Sharpe Ratio
- Lookback period for return averaging and volatility measurement, defining the window for efficiency snapshots
- Smoothing period on raw ratios, applying exponential decay to highlight persistent risk-reward patterns
- Buy threshold for positive conditions, establishing the minimum efficiency level for asset qualification
- Sell threshold for negative flags in averaging mode, pinpointing low-efficiency underperformers
🎯 Momentum RSI Parameters
- Momentum input period, deriving price changes to feed into RSI for velocity-driven insights
- RSI period on the momentum series, normalizing changes into overbought/oversold signals
- Primary smoothing moving average type on momentum RSI, selectable for signal purification
- Length for the first momentum RSI smoothing, aligning lag with trading horizons
- Secondary smoothing moving average type, facilitating comparative layers for crossover setups
- Length for the second momentum RSI smoothing, adding baseline robustness
- Toggle for second MA comparison, prioritizing relative dynamics over absolute readings
- Volatility lookback for momentum RSI's adaptive smoothing, attuning to velocity dispersion
📊 Indicator Parameters - Price Delta RSI
- Condition type between raw delta or RSI-transformed, choosing direct flow analysis or oscillator normalization
- Period for price delta calculation, quantifying net changes to reveal underlying pressure
- RSI period applied to delta, smoothing flow into bounded momentum readings
- Primary smoothing type for delta RSI, from averages to hull for delta refinement
- Length for the first delta RSI smoothing, tuning to flow trends in ranging or trending phases
- Secondary smoothing type, enabling dual-MA for enhanced crossover precision
- Length for the second delta RSI smoothing, bolstering signal stability
- Toggle for second MA comparison on delta RSI, emphasizing motion over static hurdles
- Volatility lookback for delta RSI's adaptive smoothing, adapting to flow-specific variability
📉 Beta Parameters
- Benchmark symbol choice, such as market indices, to gauge asset sensitivity against broader movements
- Lookback period for beta estimation, ensuring sufficient data for covariance while staying current
💼 Assets Configuration
- Sequential symbol inputs for up to 39 assets, supporting diverse crypto pairs across exchanges
- Conditional data loading by count, activating fetches only for selected instruments to conserve resources
- Prefix handling for clean display, stripping exchange details for ticker focus
- Broad compatibility for majors, mid-caps, or niche tokens, enabling sector or theme-based scans
🔧 Helper Functions
- Versatile moving average applicator, supporting multiple types including exponential variants and volatility-adjusted for flexible smoothing
- Sharpe ratio engine, annualizing mean returns over volatility with optional decay for trend focus
- Beta regressor, pulling benchmark data to compute relative risk via return covariances
- Layered ROC calculators, delivering percentage changes across horizons for momentum stacking
📊 Indicator Calculations
- Dual RSI systems with multi-MA options, scoring on optimal ranges or crossover confirmations for balanced strength
- Triple ROC cascade from acute to chronic, binary scoring on positivity to align short, medium, and long trends
- Sharpe derivation prioritizing excess efficiency, with thresholds gating high-reward low-risk assets
- Momentum RSI fusing velocity into RSI, smoothed for level or motion-based bullish filters
- Price delta probing net flow, raw or RSI-normalized, with adaptive layers for directional purity
- Beta isolating systematic exposure, supplementing scores with market-context relativity
🎯 Asset Metrics Calculation
- Parallel per-asset pipeline fetching and computing metrics, unpacking into arrays for centralized handling
- Binary condition evaluation per indicator: thresholds, crossovers, or signs, feeding into mode-specific aggregation
- Eight-metric blend: RSIs, ROCs, Sharpe, momentum RSI, delta, averaged aggressively or unanimous conservatively
- Beta as orthogonal factor, weighting top ranks without score dilution
- Neutral na defaults, preserving evaluations amid data gaps
📦 Data Storage Arrays
- Fixed-size arrays for names, metrics, conditions, and flags, indexed by asset order for efficient access
- Segregated storage for raw values, binaries, and composites, supporting sorting and retrieval
- Scalable to max assets, minimizing overhead in partial loads
📊 Data Retrieval for All Assets
- Conditional security pulls aligned to chart timeframe, ensuring consistent multi-symbol data
- Metrics function per instrument, distributing results to arrays for unified processing
- Benchmark-embedded beta calls, avoiding extra fetches
- Last-bar gating for snapshot accuracy, sidestepping repaints
📊 Main Table for All Assets
- Centered wide-format table listing assets leftward with metric columns spanning conditions and beta
- Headers labeling RSI layers, ROC trio, Sharpe, momentum, delta, beta, and final score for metric traceability
- Green/red cell text for met/failed conditions, white neutrals, with score highlighting above midpoint
- Ticker truncation for compactness, transparent overlay for pane integration
🏆 Top Assets Table
- Left-aligned rankings by score-beta composite, descending to prioritize leaders
- Compact four-column view: ticker, score, beta, Sharpe with threshold colors for efficiency triage
- Temporary key sorting, row clearing for updates, limited to user count
- Visual cues mirroring main table, flagging high-Sharpe standouts
✅ Key Takeaways
- Fuses diverse metrics into probabilistic or strict eligibility for alpha hunting across assets
- Dual modes adapt screening from flexible averages to rigorous confluences
- Custom periods and smoothings tune to timeframes, from scalps to positions
- Dual tables balance detail with digestible summaries for rapid insights
- Beta adds relativity, elevating resilient picks in correlated markets
- Efficient array handling scales screening without lag, quota-aware
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
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.
HPAS – Historical Price Action StatisticsHPAS – Historical Price Action Statistics (v7)
A data-driven overview of weekday behavior: price, volatility, and volume.
1) OVERVIEW
HPAS analyzes how each weekday behaves across your selected history. It aggregates daily returns, intraday ranges, and volumes into a compact heatmap table and optionally plots daily range bands (historical & today) on the chart.
Note: All weekday statistics are calculated using UTC-based daily candles for consistent results across markets (especially 24/7 assets like crypto).
The goal is context and probabilities — not signals.
2) HOW IT WORKS
Collects daily bar stats: % gain/loss (close vs open), intraday range ((High−Low) ÷ Open × 100), and contracts (volume).
Groups data by weekday (Sun–Sat) and computes: win/loss frequencies, average and max moves, average intraday ranges, and average volume.
Note: “Weekday” refers to the calendar day in UTC time . This ensures consistency across all assets and exchanges, particularly for 24/7 markets like crypto.
Compares average weekday volume to the current 20-day average (% of 20D).
Displays results in a color-shaded table; optionally draws historical daily range bands plus today’s projection with optional smoothing.
3) INCLUDED FEATURES
Core metrics
Total → Gain / Loss (% of Days): How often the day closes above/below open.
Closing → Avg / Max: Average and largest daily % moves up/down.
Intrabar (optional) → Avg / Max: Typical and extreme intraday % ranges.
Contracts → Avg (K): Average daily volume (shown in thousands).
Contracts → %20D: Weekday’s average volume as % of the current 20-day average.
Visualization & UX
Heatmap coloring: lower values appear darker; higher values lighter.
Current weekday highlight with a left-side triangle.
Tooltips on headers explain what/why/how.
Dark/Light theme support; Colorblind-safe palette toggle (Okabe–Ito).
Projection Bands
Plots historical daily range bands and today’s projected band.
Optional smoothing (SMA) for cleaner band movement.
Band Smoothing Explained: Applies a simple moving average over recent projection values to reduce sudden jumps in the upper/lower bands.
Higher values make the range lines steadier but slower to react; lower values show more real-time variability.
4) USAGE TIPS
Context, not prediction: Use stats to frame expectations, not to force trades.
Cycle awareness: Compare long vs short date windows; behavior can shift across regimes.
Volume tells a story: Elevated %20D can hint at increased participation or attention on certain weekdays.
Targets & risk: Range bands provide realistic context for sizing stops/targets.
Accessibility: Enable Colorblind-safe mode if red/green contrast is hard to read.
5) INTERPRETATION GUIDE
% Gain / % Loss — Frequency of up/down closes. Higher % Gain suggests a bullish weekday bias.
Avg Gain / Avg Loss — Mean daily % move on green/red days. Gauges typical magnitude.
Max Gain / Max Loss — Largest observed daily % change. Sets an upper bound of past extremes.
Hi-Lo Avg / Max — Typical and extreme intraday % ranges. Context for expected volatility.
Contracts Avg (K) — Average daily volume in thousands. Participation proxy.
%20D — Volume vs current 20-day average. 100% = typical, >100% = above-normal, <100% = lighter-than-normal.
6) CREDITS
Inspired by the HPAS concept popularized by Krown Trading and The Caretaker.
Rebuilt and extended for clarity, accessibility, and practical context.
Version: v7 (October 2025)
License: Educational, non-commercial use
Key Inputs (snippet)
// Projection Bands
grpBands = “Projection Bands”
showBands = input.bool(true, “Show daily range bands (historical & today)”, group=grpBands)
smoothLen = input.int(1, “Band smoothing (days)”, minval=1, maxval=20, group=grpBands)
VAH Entry / VAL Exit (Xauusd) by TheMarketVengeanceThis strategy replicates a simplified intraday Market Profile/TPO approach for assets such as XAUUSD on key auction levels and volume dynamics to identify high-probability breakouts and exits.
Value Area Calculation: Each new day, the script accumulates all price and volume data to approximate the previous day’s Volume Weighted Average Price (VWAP, used here as Point of Control or POC). The Value Area High (VAH) and Value Area Low (VAL) are estimated as one standard deviation above and below this daily VWAP, representing the core 70% trading range where the majority of volume transacted.
Entry and Exit Logic: A long trade is triggered when price breaks out above yesterday’s VAH (plus a user-defined buffer) on above-average volume—this confirms momentum outside the fair value range. Exits occur if price falls below VAL, suggesting rejection of higher prices and a shift in auction direction.
Volume Confirmation: Entry signals require volume to be above the moving average, ensuring participation and validation of breakouts.
Intraday Plotting: The strategy plots the previous VAH, VAL, POC, and trigger/entry levels throughout the day for clear, visual reference.
Risk Management: The “pips” buffer input allows traders to fine-tune sensitivity for different markets ( 10pips for gold). Multiple entries are prevented until a new breakout opportunity emerges on the next session.
Only for XAUUSD.
Disclaimer:
This strategy is provided for educational purposes only. It is important to thoroughly review and backtest the strategy under your specific trading conditions before using it with real capital. The author and publisher are not responsible for any trading losses incurred.
Heikin Ashi Signal [Eig] (Widget Compatible)This indicator draws Buy and Sell signals on the current candlestick, based on a complete reversal pattern of the previous three Heikin Ashi (HA) candlesticks:
🟢 Buy Entry (Reversal to Long):
A buy entry signal when the trend changes from bearish (downtrend) to bullish (uptrend).
Pattern: 2 Red HA Bars → followed by 1 Green HA Bar
🔴 Sell Entry (Reversal to Short / Exit Long):
A sell entry/reversal signal when the trend changes from bullish (uptrend) to bearish (downtrend).
Pattern: 2 Green HA Bars → followed by 1 Red HA Bar
💡 How to Use
This indicator is suitable for use as a confirmation tool:
Entry/Exit: Use the triangle signals (Buy/Sell) as entry/exit points.
(Widget Compatible)
Custom TPO Approximation by TheMartketVengeanceThis strategy replicates a simplified intraday Market Profile/TPO approach for assets such as XAUUSD, FX, or stocks, focusing on key auction levels and volume dynamics to identify high-probability breakouts and exits.
Value Area Calculation: Each new day, the script accumulates all price and volume data to approximate the previous day’s Volume Weighted Average Price (VWAP, used here as Point of Control or POC). The Value Area High (VAH) and Value Area Low (VAL) are estimated as one standard deviation above and below this daily VWAP, representing the core 70% trading range where the majority of volume transacted.
Entry and Exit Logic: A long trade is triggered when price breaks out above yesterday’s VAH (plus a user-defined buffer) on above-average volume—this confirms momentum outside the fair value range. Exits occur if price falls below VAL, suggesting rejection of higher prices and a shift in auction direction.
Volume Confirmation: Entry signals require volume to be above the moving average, ensuring participation and validation of breakouts.
Intraday Plotting: The strategy plots the previous VAH, VAL, POC, and trigger/entry levels throughout the day for clear, visual reference.
Risk Management: The “pips” buffer input allows traders to fine-tune sensitivity for different markets (such as 0.0001 for FX or 1 for gold). Multiple entries are prevented until a new breakout opportunity emerges on the next session.
This method enables traders to systemize breakout trades with solid context from auction market theory, volume confirmation, and precise intraday tracking.
ttr双模式移动止盈止损策略V1该策略通过趋势判断当前所处的周期以及波动，开仓逻辑为小仓位大杠杠，在波动中进行移动的止盈止损。The strategy judges the current cycle and volatility through trends, with an opening logic of "small position size and high leverage", and implements dynamic take-profit and stop-loss amid volatility
Heikin Ashi Signal [Eig] (Widget Compatible)This indicator draws Buy and Sell signals on the current candlestick, based on a complete reversal pattern of the previous three Heikin Ashi (HA) candlesticks:
🟢 Buy Entry (Reversal to Long):
A buy entry signal when the trend changes from bearish (downtrend) to bullish (uptrend).
Pattern: 2 Red HA Bars → followed by 1 Green HA Bar
🔴 Sell Entry (Reversal to Short / Exit Long):
A sell entry/reversal signal when the trend changes from bullish (uptrend) to bearish (downtrend).
Pattern: 2 Green HA Bars → followed by 1 Red HA Bar
💡 How to Use
This indicator is suitable for use as a confirmation tool:
Entry/Exit: Use the triangle signals (Buy/Sell) as entry/exit points.
Adaptive Support Resistance LineBuy until price remains above the green support line. Sell until price remains below the red resistance line. The signal is adaptive to volatility and trend to minimize trades. Relevant for securities from different asset classes across different holding periods (few ticks to few months). Inspired by Geometric Brownian Motion.
