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.