Zaktualizowano
Integrated Financial Analysis Pro [MarkitTick]
💡 Institutional-grade financial analysis engine that transforms any TradingView chart into a professional-level quantitative research terminal. Rather than offering a single isolated metric, this tool orchestrates a full spectrum of return, risk, efficiency, and distributional statistics — simultaneously evaluated across five independently configurable time horizons — and renders them through a precision-crafted multi-period analytical dashboard. Designed to the exacting standards of portfolio management desks and quantitative research divisions, it delivers the analytical depth of a dedicated risk management platform directly on the chart, without requiring external software or data exports.
✨ Originality and Utility
● A Unified Quantitative Research Terminal on TradingView
The financial analysis landscape on TradingView is dominated by single-purpose indicators: one tool for Sharpe ratio, another for drawdown, yet another for beta. The Integrated Financial Analysis indicator abandons this fragmented paradigm entirely. It is engineered as a self-contained institutional research engine — one deployment that computes, renders, and cross-references the complete taxonomy of quantitative finance metrics in a single, coherent analytical environment. From raw return attribution through tail-risk quantification to efficiency ratio synthesis, every metric is evaluated in relation to every other, across every configured period, simultaneously.
● Five-Period Comparative Architecture
The defining architectural feature of this indicator is its five-dimensional temporal grid. Users configure five independent lookback periods — expressed in Days, Weeks, Months, or Years — and the engine produces a full metric profile for each without overlap or contamination between windows. This non-overlapping, sequential window design is intentional: it allows a portfolio analyst to observe, in a single glance, how a security's risk-adjusted profile evolves from short-term to long-term horizons, identifying whether outperformance is structurally persistent or episodic. No other publicly available TradingView indicator offers this degree of temporal granularity across such a broad metric set.
● Dual-Benchmark Architecture with Optional Secondary Index
The engine supports a configurable primary benchmark and an optional secondary index, giving institutional users the flexibility to evaluate a security's performance against multiple reference points — such as a broad market index and a sector-specific sub-index — without modifying the script. The active benchmark drives all relative metrics simultaneously: excess return, beta, alpha, tracking error, information ratio, upside and downside capture ratios, and active return are all anchored to the same user-selected reference universe.
● Adaptive Timeframe Intelligence
The indicator detects the active chart timeframe — daily, weekly, or monthly — and automatically calibrates all annualization denominators, period multipliers, and observation thresholds accordingly. The correct number of trading periods per year is derived at runtime, not hardcoded, ensuring that every ratio produced is internally consistent regardless of whether the chart is displaying daily bars, weekly candles, or monthly closes.
🔬 Methodology and Concepts
● Category I — Return and Performance Attribution
Stock Performance & Index Performance
Measures the cumulative percentage gain or loss of both the target security and the benchmark index over each configured period. These are the baseline reference values against which all relative metrics are computed.
Excess Return
Quantifies the differential between the security's total return and the benchmark's total return over the same window. A persistently positive excess return — especially across multiple time horizons simultaneously — is the primary indicator of alpha-generative capability rather than mere beta exposure.
Compound Annual Growth Rate (CAGR)
The geometrically annualized return over each period, normalized to a per-year basis regardless of the actual window length. CAGR eliminates the distortion caused by the arithmetic mean's inability to account for compounding, providing the most accurate measure of the security's long-run growth trajectory.
Regression Alpha (Jensen's Alpha)
The intercept term extracted from the proprietary multivariate regression engine embedded in the indicator's computation library. Alpha represents the portion of the security's return that is attributable neither to broad market exposure (beta) nor to the risk-free rate — it is the pure measure of manager skill or structural edge. The computation enforces a minimum observation threshold (configurable, defaulting to three months of trading periods) to prevent statistically invalid alpha estimates from appearing in the dashboard.
Upside Capture Ratio
Measures how much of the benchmark's positive return periods the security captures on average. A value above 1.0 signifies that the security amplifies bullish benchmark performance, which is desirable when combined with a low Downside Capture Ratio.
Downside Capture Ratio
The complement to Upside Capture — measures the security's average participation in the benchmark's negative return periods. A value below 1.0 signifies meaningful downside protection: the security loses less than the benchmark during market stress.
Composite Capture Ratio
The ratio of Upside Capture to Downside Capture. This single composite statistic encapsulates the asymmetry of the security's return profile: values substantially above 1.0 indicate favorable convexity — the security captures more upside than downside — which is the defining characteristic of superior risk-adjusted performance.
Hit Ratio
The proportion of periods within the selected window in which the security generated a positive return. Unlike CAGR or Sharpe Ratio, the Hit Ratio measures consistency of directionality rather than magnitude-weighted performance. A high Hit Ratio combined with strong Profit Factor identifies securities with both reliable return frequency and favorable win/loss magnitude distribution.
● Category II — Risk and Volatility Metrics
Annualized Standard Deviation
The annualized measure of the dispersion of the security's periodic returns around their mean. This is the denominator in the Sharpe and Treynor ratios and the primary measure of total realized volatility. All annualization is performed using the timeframe-calibrated period count.
Beta (Market Sensitivity)
The slope coefficient from the proprietary regression engine, measuring the sensitivity of the security's excess returns to movements in the benchmark's excess returns. A beta above 1.0 denotes an aggressive security amplifying market moves; below 1.0 denotes defensive behavior.
Downside Beta
A refined version of conventional beta that restricts the regression sample exclusively to periods in which the benchmark registered a negative return. Downside Beta isolates the security's co-movement with the market specifically during adverse conditions — an asymmetric risk measure that conventional beta obscures by averaging across all market regimes.
R-Squared (Coefficient of Determination)
The proportion of the security's return variance explained by the benchmark's movements. A high R-squared validates the interpretive relevance of the regression-derived Beta and Alpha: in a low R-squared environment, beta becomes a poor predictor and Alpha loses much of its statistical meaning.
Tracking Error
The annualized standard deviation of the active return series — the period-by-period difference between the security and the benchmark. Tracking Error is the primary measure of active management deviation and is directly used as the denominator of the Information Ratio.
Average Active Return
The arithmetic mean of the period-by-period excess return of the security over the benchmark, annualized to the configured period basis. Together with Tracking Error, this forms the numerator and denominator of the Information Ratio, and independently signals the consistency of outperformance relative to benchmark.
Value at Risk (VaR)
A statistical threshold measure that estimates the maximum loss the security would be expected to incur over the selected period under normal market conditions, at a specific confidence level. The computation requires a minimum observation threshold (configurable, defaulting to one year of trading periods) to ensure statistical significance of the distributional estimate. Displayed as a percentage of the security's current value. Note that VaR measures expected losses within the normal distribution of market conditions and does not capture tail events.
Conditional Value at Risk (CVaR / Expected Shortfall)
The expected value of losses beyond the VaR threshold — the average loss in worst-case scenarios. CVaR is a coherent risk measure that VaR is not: it satisfies the sub-additivity property required for proper portfolio aggregation. The same minimum observation threshold applied to VaR governs CVaR to maintain distributional reliability.
Downside Deviation
The annualized standard deviation of returns that fall below the user-configured Minimum Acceptable Return (MAR). Unlike total standard deviation, Downside Deviation ignores periods of outperformance relative to the MAR threshold, recognizing that upside volatility is not risk in the economically meaningful sense. This is the denominator of the Sortino Ratio.
Skewness
The third standardized moment of the return distribution, measuring directional asymmetry. Positive skewness indicates a distribution with a longer right tail — infrequent large gains — while negative skewness (common in equity strategies) indicates a distribution with a longer left tail — infrequent but large losses. The computation requires a minimum observation threshold of six months by default to achieve sufficient distributional stability.
Kurtosis
The fourth standardized moment, measuring tail heaviness relative to a normal distribution. Excess kurtosis above 3 (leptokurtosis) indicates fatter tails than assumed by Gaussian models, which implies that extreme events — both gains and losses — occur more frequently than standard risk models predict. This is a critical input for tail risk assessment beyond what VaR and CVaR alone capture.
Maximum Drawdown (MDD)
The largest peak-to-trough decline observed within the selected period. Maximum Drawdown measures the worst historical loss that a fully committed investor would have endured. It is the denominator of the Calmar Ratio and the primary measure of catastrophic risk tolerance.
Drawdown Duration
The length (in trading days) of the longest drawdown episode within the selected window — from the peak at which the drawdown began to the point of maximum loss. A long Drawdown Duration, even if the MDD percentage is moderate, signals persistent capital impairment risk.
Time to Recovery
The number of trading days required to fully recover from the Maximum Drawdown back to the prior peak. An asymmetry between MDD Percentage and Time to Recovery reveals the speed of mean reversion in the security's price discovery process. Prolonged recovery periods reduce the effective compounded return and are particularly destructive to capital allocation efficiency.
● Category III — Efficiency Ratios and Risk-Adjusted Returns
Sharpe Ratio
The excess return per unit of total volatility, annualized. The Sharpe Ratio is the most widely referenced risk-adjusted performance metric in institutional finance. The excess return is computed relative to the user-configured risk-free rate, and the denominator is the total annualized standard deviation of the security's returns. Values above 1.0 are generally considered acceptable; above 2.0, exceptional.
Sortino Ratio
The excess return per unit of downside deviation, computed against the user-configured Minimum Acceptable Return (MAR) threshold. By penalizing only harmful volatility — returns below the MAR — the Sortino Ratio provides a more economically rational measure of risk-adjusted performance for strategies that exhibit positive skewness or controlled drawdown profiles. The Sortino Ratio consistently produces higher values than Sharpe for strategies with right-skewed return distributions.
Calmar Ratio
The annualized return relative to the Maximum Drawdown. The Calmar Ratio bridges the performance domain and the catastrophic risk domain: it asks, in essence, how much return is generated per unit of worst-case loss endured. It is particularly valued in absolute return and alternative investment contexts where drawdown constraints are binding.
Treynor Ratio
The excess return per unit of systematic risk (beta) rather than total risk. The Treynor Ratio is appropriate for evaluating a security's contribution to a well-diversified portfolio, where idiosyncratic risk is assumed to be diversified away. It is computed from the same regression engine that produces Beta and Alpha.
Information Ratio
The average active return divided by the tracking error. The Information Ratio quantifies the consistency of outperformance relative to the benchmark: a high Information Ratio indicates not merely that the security has outperformed, but that it has done so with predictable, reliable regularity. Values above 0.5 are considered strong; above 1.0, exceptional, in institutional active management benchmarks.
Profit Factor
The ratio of the sum of all positive returns to the absolute sum of all negative returns within the selected period. A Profit Factor above 1.0 indicates that gross gains exceed gross losses; above 2.0 is generally considered robust. Unlike Sharpe Ratio, Profit Factor makes no distributional assumptions and is therefore insensitive to the non-normality that characterizes most financial return series.
🎨 Visual Guide
● Transposed Multi-Period Analytics Table
The on-chart table is rendered in transposed format: metrics are organized as rows along the left column, while the five configured time periods occupy the five data columns to the right. This layout is deliberately chosen for its analytical efficiency — the eye traverses the table horizontally across time horizons for a single metric, and vertically across metrics for a single period, enabling both temporal comparison and cross-metric synthesis without reorganizing the mental model.
Color coding is applied to each cell based on the metric's directional interpretation:
Header rows are color-differentiated by category: Performance and Ratio metrics use a blue header scheme; Risk and Volatility metrics use a purple header scheme, enabling rapid visual triage of the table by analytical domain.
The table is conditional: it renders only when the user has enabled at least one metric in the configuration, and suppresses entirely when Table Display Mode is set to "Hide All."
● Single Active Metric Plot with Dynamic Gradient Cloud
The plotting architecture enforces a single-active-metric principle: only one metric is visualized as the primary oscillator line at any given time, determined by the user's Plot Period configuration and metric selection. This design eliminates chart noise from overlapping oscillator lines and focuses analytical attention on the chosen metric's historical trajectory.
The active metric line is colored dynamically:
A gradient fill cloud occupies the space between the metric line and the zero axis:
A secondary envelope fill between the metric line and its moving average further highlights divergences between the current metric value and its trend baseline.
● Candle Coloring via Normalized Gradient Signal
When candle coloring is enabled and a plot metric is active, the chart's candles are recolored on the overlay pane according to a normalized gradient derived from the active metric's value relative to its own recent bull/bear force range. Candles are mapped on a smooth gradient spectrum from the Bear color (at the extreme negative end) through neutral to the Bull color (at the extreme positive end). This transforms the price candles into a visual heatmap of the current metric's quantitative state, allowing instantaneous assessment of whether the security's risk-adjusted posture is improving or deteriorating on a bar-by-bar basis.
● Moving Average Overlay
A configurable moving average is plotted alongside the active metric. In Auto mode, the MA length is automatically set to the timeframe-calibrated annual period count — one full year of trading bars — providing a natural long-run baseline for any metric. In Manual mode, the user specifies an explicit length. The MA can be applied to any of the 30 available metrics, enabling visual identification of trend inflections in Sortino Ratio, Information Ratio, Excess Return, or any other selected series.
● Zero Reference Line
A zero-axis reference line is rendered with automatic color adaptation based on the chart's background luminosity: dark on light themes, light on dark themes. This ensures legibility across all TradingView chart color schemes without manual adjustment.
📖 How to Use
● Establishing the Analytical Framework
Begin by configuring the Primary Market Index to the most relevant benchmark for the security under analysis. For equities, this is typically the broad market index (e.g., S&P 500, NASDAQ-100) or a sector-specific benchmark. For alternative or cross-asset analysis, the Secondary Index input can be activated to substitute a more precise reference universe. All relative metrics — Alpha, Beta, Tracking Error, Information Ratio, Capture Ratios, and Active Return — will immediately recalibrate to the selected benchmark.
● Configuring the Five Analytical Periods
Set the five period lengths and their unit type (Days, Weeks, Months, or Years) to reflect your investment horizon stack. A typical institutional setup might configure 1Y, 2Y, 3Y, 4Y, and 5Y to assess long-term statistical persistence, or a tactical setup might use shorter windows such as 3M, 6M, 1Y, 2Y, and 3Y to monitor both short-cycle tactical performance and strategic-cycle persistence simultaneously.
● Interpreting the Dashboard Table
Scan horizontally across a single metric row to identify whether performance characteristics are strengthening or weakening across time horizons. A Sortino Ratio that is strong at 1Y but weak at 3Y and 5Y suggests recent tactical outperformance that is not structurally persistent. Conversely, a consistently high Sharpe Ratio across all five periods indicates structurally superior risk-adjusted performance.
Scan vertically down a single period column to assess the holistic risk-adjusted profile for that specific window. A high CAGR with a poor Sortino and a large Maximum Drawdown reveals a volatile, drawdown-prone return stream that misleads when evaluated by raw return alone.
● Using the Plot Period for Temporal Forensics
The Plot Period is independent of the five table periods and can be set to any value within the supported range. Use this to select a specific analytical window for dynamic visualization. Plotting the Sortino Ratio with a 1-year Plot Period while the table displays 1Y through 5Y periods provides simultaneous static (tabular) and dynamic (oscillator) analysis of risk-adjusted efficiency across different temporal regimes.
● Identifying Risk-Adjusted Regime Shifts
The moving average on the active metric plot is the primary tool for regime detection. When the Sortino Ratio oscillator crosses below its annual moving average, it signals a deterioration in downside-adjusted performance relative to the recent trend — a potential early warning of risk regime transition. Combine this with the gradient candle coloring to identify whether the deterioration is occurring gradually or abruptly.
● Setting Academic Observation Thresholds
The three minimum observation settings — for regression-based metrics (Beta, Alpha, R-Squared), for distributional tail risk (VaR, CVaR), and for higher moments (Skewness, Kurtosis) — enforce statistical validity standards. When fewer bars than the configured threshold are available, the corresponding cells display "N/A" rather than producing numerically unreliable estimates. These thresholds should be calibrated to your statistical confidence requirements: increase them for higher-stakes decisions, reduce them for exploratory analysis on shorter datasets.
🎯Performance Metrics Reference Guide
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01 — PERFORMANCE METRICS
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▸ STOCK PERFORMANCE (Holding-Period Return)
Total price return of the instrument over the selected period.
Threshold: <0% [Loss] | 0–10% [Marginal] | 10–20% [Solid] | >20% [Strong]
Recommendation: Meaningless without benchmark context — always read alongside Index Performance.
▸ INDEX PERFORMANCE (Benchmark Holding-Period Return)
Total return of the selected market index over the equivalent period.
Threshold: Serves as the passive baseline — the minimum return justifying active exposure.
Recommendation: Persistent underperformance vs. the index disqualifies the active approach on a risk-adjusted basis.
▸ EXCESS RETURN (Stock Perf − Index Perf)
Arithmetic difference between instrument return and benchmark return over the same period.
Threshold: <0% [Underperforming] | 0–3% [Marginal Edge] | 3–5% [Meaningful] | >5% [Strong Alpha Premium]
Recommendation: Positive, consistent excess return across multiple periods is the primary empirical evidence of skill over passive indexing.
▸ CAGR (Compound Annual Growth Rate)
Geometric mean annualized return, smoothing compounding effects across multi-year periods.
Threshold: <7% [Weak] | 7–12% [Solid] | 12–20% [Strong] | >20% [Exceptional]
Recommendation: Must exceed risk-free rate + benchmark CAGR + inflation premium to justify active risk capital deployment.
▸ HIT RATIO (Win Rate)
Percentage of periods or trades generating a positive return.
Threshold: <45% [Poor] | 45–55% [Marginal] | 55–65% [Good] | >65% [Strong]
Recommendation: Never interpret in isolation — a 45% Hit Ratio with 2.5:1 reward/risk outperforms 65% with 0.8:1; always pair with Profit Factor.
▸ ALPHA (Regression-Based, Annualized)
Intercept of the OLS regression of excess stock returns on excess benchmark returns, annualized via CAPM.
Threshold: <0% [Value Destructive] | 0–2% [Marginal] | 2–5% [Significant] | >5% [Exceptional]
Recommendation: Valid only with ≥60 observations and R² >40% — low-R² Alpha is statistical noise, not skill.
▸ UPSIDE CAPTURE RATIO
Ratio of strategy mean return to benchmark mean return during positive benchmark periods.
Threshold: <80% [Weak] | 80–100% [Below Market] | 100–120% [Good] | >120% [Strong]
Recommendation: Must materially exceed 100% to justify the active risk premium — evaluate asymmetrically against Downside Capture.
▸ DOWNSIDE CAPTURE RATIO
Ratio of strategy mean return to benchmark mean return during negative benchmark periods.
Threshold: >100% [Amplifies Losses] | 80–100% [Weak Protection] | 60–80% [Good] | <60% [Excellent]
Recommendation: Institutional capital preservation mandates typically require Downside Capture <70% as a hard ceiling.
▸ CAPTURE RATIO (Upside ÷ Downside)
Composite measure of asymmetric market participation.
Threshold: <1.0 [Unfavorable] | 1.0–1.25 [Neutral] | 1.25–1.5 [Good] | >1.5 [Exceptional]
Recommendation: The single most direct quantitative measure of asymmetric skill — target >1.3 as the minimum viable institutional threshold.
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02 — RISK METRICS
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▸ ANNUALIZED STANDARD DEVIATION (Volatility)
Annualized standard deviation of log returns — the canonical measure of total portfolio risk.
Threshold: <10% [Low] | 10–20% [Moderate] | 20–30% [Elevated] | >30% [High]
Recommendation: Any strategy exceeding 25% volatility must generate proportionately superior Sharpe and Sortino ratios to remain institutionally viable.
▸ BETA (Market Sensitivity)
OLS regression slope of excess stock returns on excess benchmark returns.
Threshold: <0 [Inverse] | 0–0.8 [Defensive] | 0.8–1.2 [Market-Equivalent] | >1.2 [Aggressive]
Recommendation: Align Beta with mandate — defensive portfolios target β <0.8; growth mandates accept β >1.2 only when Alpha is simultaneously positive.
▸ DOWNSIDE BETA
Beta estimated exclusively during periods when the benchmark posted negative returns.
Threshold: <0.7 [Strong Protection] | 0.7–1.0 [Moderate] | 1.0–1.2 [Weak] | >1.2 [Amplified Bear Exposure]
Recommendation: Downside Beta must be materially lower than standard Beta — this divergence is the quantitative signature of genuine asymmetric risk management.
▸ R-SQUARED (Coefficient of Determination)
Proportion of the strategy's return variance explained by benchmark movements.
Threshold: <40% [Idiosyncratic] | 40–70% [Moderate] | 70–85% [High Correlation] | >85% [Quasi-Passive]
Recommendation: Active managers should maintain R² <70% to justify fees above a passive ETF; index-replicating vehicles target R² >95%.
▸ TRACKING ERROR
Annualized standard deviation of active returns (strategy minus benchmark).
Threshold: <2% [Quasi-Passive] | 2–6% [Active] | 6–12% [High Conviction] | >12% [Benchmark-Agnostic]
Recommendation: Tracking Error above 10% demands an Information Ratio above 0.75 to remain institutionally defensible.
▸ AVERAGE ACTIVE RETURN (Avg Absolute Active Return)
Mean absolute magnitude of the strategy's deviation from the benchmark each period.
Threshold: Lower = more consistent tracking | Higher = greater active divergence from benchmark.
Recommendation: Its ratio to Tracking Error approximates the Information Ratio — the core efficiency measure of active management.
▸ VAR (Value at Risk — Annualized, 95% Confidence)
Maximum expected loss at a 95% confidence level over the observation period, scaled to annual.
Threshold: <10% [Conservative] | 10–20% [Moderate] | 20–30% [Elevated] | >30% [High Tail Exposure]
Recommendation: |VaR| must not exceed 50–60% of expected CAGR — when |VaR| > CAGR, the risk/return structure is broken.
▸ CVAR (Conditional Value at Risk / Expected Shortfall)
Mean of all losses exceeding the VaR threshold — the true cost of tail events.
Threshold: CVaR/VaR <1.3 [Moderate Tail] | 1.3–1.6 [Elevated] | >1.6 [Fat-Tail Dominated]
Recommendation: Sharp CVaR/VaR divergence invalidates normal-distribution assumptions — mandatory switch to stress-testing frameworks at that point.
▸ DOWNSIDE DEVIATION
Annualized standard deviation of returns falling below the Minimum Acceptable Return (MAR).
Threshold: <5% [Low] | 5–10% [Moderate] | 10–15% [Elevated] | >15% [High]
Recommendation: Reducing Downside Deviation requires eliminating large negative outliers — not suppressing all volatility; it is the Sortino denominator and directly determines ratio quality.
▸ SKEWNESS
Third standardized moment; measures asymmetry of the return distribution.
Threshold: < −1.0 [Severe Crash Risk] | −1.0 to −0.5 [Negative Skew] | −0.5 to +0.5 [Symmetric] | >+0.5 [Favorable]
Recommendation: Negative skew combined with excess kurtosis is the defining statistical signature of blow-up risk — the profile of failed short-volatility and carry strategies.
▸ KURTOSIS
Fourth standardized moment; measures tail weight relative to a normal distribution (baseline = 3).
Threshold: ≈3 [Normal] | 3–5 [Mildly Leptokurtic] | 5–8 [Fat Tails] | >8 [Extreme Tail Risk]
Recommendation: Kurtosis >6 invalidates standard VaR models — fat-tail hedging is mandatory and Gaussian risk estimates must be abandoned entirely.
▸ MAXIMUM DRAWDOWN (MDD)
Largest peak-to-trough percentage decline in the equity curve over the observation period.
Threshold: <10% [Very Low] | 10–20% [Moderate] | 20–35% [Elevated] | >35% [Severe]
Recommendation: Institutional mandates cap MDD at 15–20%; always evaluate alongside Time to Recovery — depth alone is an incomplete risk picture.
▸ DRAWDOWN DURATION
Maximum consecutive number of periods the equity curve remained below its prior peak.
Threshold: <3 months [Fast] | 3–12 months [Acceptable] | 1–3 years [Concerning] | >3 years [Structural Failure]
Recommendation: Duration >12 months combined with MDD >20% is a composite red flag signaling strategy breakdown — not a temporary adverse cycle.
▸ TIME TO RECOVERY (Average)
Mean number of periods required to return to the prior equity peak following a drawdown.
Threshold: <3 months [Excellent] | 3–6 months [Good] | 6–12 months [Acceptable] | >12 months [Concerning]
Recommendation: Average TTR >6 months paired with high MDD signals compounding destruction — capital locked in recovery generates zero excess return.
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03 — ADVANCED RATIOS & EFFICIENCY
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▸ SHARPE RATIO
Annualized excess return above the risk-free rate per unit of total standard deviation.
Threshold: <0 [Destroys Value] | 0–1.0 [Suboptimal] | 1.0–1.5 [Acceptable] | 1.5–2.0 [Good] | >2.0 [Excellent]
Recommendation: Minimum viable institutional threshold is >1.0 sustained; hedge funds typically mandate Sharpe >1.5 for capital allocation approval.
▸ SORTINO RATIO
Annualized excess return per unit of downside deviation below MAR.
Threshold: <0 [Negative Risk-Adjusted] | 0–1.0 [Marginal] | 1.0–2.0 [Good] | 2.0–3.0 [Excellent] | >3.0 [Exceptional]
Recommendation: A well-managed strategy's Sortino should run 30–60% above its own Sharpe — if Sortino ≈ Sharpe, no protective asymmetry exists in the return distribution.
▸ CALMAR RATIO
Annualized CAGR divided by Maximum Drawdown — return per unit of worst-case loss.
Threshold: <0.5 [Poor] | 0.5–1.0 [Acceptable] | 1.0–2.0 [Good] | >2.0 [Excellent]
Recommendation: Minimum viable institutional threshold is 0.5; top systematic funds sustain 1.5–3.0 — particularly decisive for CTA and trend-following mandate compliance.
▸ TREYNOR RATIO
Annualized excess return per unit of systematic risk (Beta).
Threshold: <0 [Negative] | >0 [Positive] — benchmark against the market's own Treynor for meaningful comparison.
Recommendation: Use exclusively for cross-portfolio Beta-exposure comparison — invalid in isolation and unreliable for strategies with R² <40%.
▸ INFORMATION RATIO
Annualized active return divided by Tracking Error — the definitive efficiency measure of active management.
Threshold: <0.25 [Weak] | 0.25–0.5 [Marginal] | 0.5–0.75 [Skilled] | >0.75 [Exceptional]
Recommendation: IR >0.5 sustained over 36+ months is the gold standard for institutional manager retention — always validate across multiple time horizons.
▸ PROFIT FACTOR
Ratio of total gross profit to total gross loss across all periods.
Threshold: <1.0 [Losing System] | 1.0–1.5 [Marginal] | 1.5–2.0 [Good] | 2.0–3.0 [Strong] | >3.0 [Exceptional]
Recommendation: Minimum viable threshold for live capital deployment is >1.5; Profit Factor >3.0 in backtests demands rigorous overfitting scrutiny before allocation.
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04 — RELATIVE STRENGTH (Plot Only)
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▸ RELATIVE STRENGTH
Real-time ratio of instrument price to benchmark price, rebased to 100.
Threshold: >100 Rising [Sustained Outperformance] | >100 Flat [Holding Edge] | <100 Declining [Structural Underperformance]
Recommendation: Trend slope matters more than absolute level — rising Relative Strength during benchmark weakness is the most constructive institutional confirmation signal.
⚙️ Inputs and Settings
● Market Indices
● Risk Parameters
● Period Selection
● Plot Period Selection
● Table Columns Visibility
● 01 — Performance Metrics (Table & Plot)
Each metric in this group exposes two independent toggles — one for the table dashboard and one for the plot oscillator — allowing the user to include a metric in the tabular summary without necessarily activating it as the primary oscillator, and vice versa.
● 02 — Risk Metrics (Table & Plot)
● 03 — Advanced Ratios (Table & Plot)
● 04 — Misc Controls
● Moving Average
● Color Settings
● Hide or Show
● Academic Standards
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Return Decomposition and Attribution Theory
The foundational architecture of this indicator is grounded in the Brinson-Hood-Beebower return attribution framework and its extensions. Returns are decomposed into systematic components (benchmark-attributable) and idiosyncratic components (security-specific), with the regression engine serving as the primary instrument of decomposition. The excess return series — the foundation of all risk-adjusted ratio computation — is constructed relative to the user-configured risk-free rate, consistent with Capital Market Theory's excess return formulation. All return series are derived from a continuous compounding framework, which provides additivity across periods and eliminates the geometric-vs-arithmetic mean distortion inherent in simple return aggregation across multi-period windows.
● Modern Portfolio Theory and CAPM Integration
The regression engine is calibrated to the Capital Asset Pricing Model (CAPM) framework: security excess returns are regressed against benchmark excess returns, yielding the systematic risk coefficient (Beta), the idiosyncratic return premium (Alpha), and the explanatory power of the model (R-Squared). Jensen's Alpha, as computed here, is the annualized constant term of this regression — the theoretically risk-adjusted measure of return that cannot be explained by market exposure alone. Downside Beta extends this framework into the Post-Modern Portfolio Theory (PMPT) domain by restricting the regression to the subset of periods where the benchmark's return is negative, isolating the security's co-movement with market stress rather than averaging it with benign periods.
● Downside Risk Paradigm and Post-Modern Portfolio Theory
The Sortino Ratio, Downside Deviation, CVaR, and Maximum Drawdown metrics collectively implement the Post-Modern Portfolio Theory framework developed by Rom and Ferguson (1994) as a systematic critique of the Markowitz mean-variance model. The core principle is that risk is not symmetric: investors do not uniformly penalize upside and downside volatility. By constructing a partial lower-moment framework — measuring only the variance of returns below the MAR threshold — these metrics align the mathematical definition of risk with its behavioral economic reality. The Sortino Ratio's use of semi-deviation rather than total standard deviation as the denominator directly embeds this asymmetric preference structure into the efficiency metric.
● Tail Risk and Extreme Value Theory
The VaR and CVaR computations address the empirically documented inadequacy of Gaussian return models. Financial return distributions exhibit persistent leptokurtosis — fat tails — and negative skewness, a combination that causes Gaussian VaR to systematically underestimate the probability and magnitude of extreme losses. CVaR (also known as Expected Shortfall) is a coherent risk measure in the sense defined by Artzner, Delbaen, Eber, and Heath (1999): it satisfies monotonicity, sub-additivity, homogeneity, and translational invariance. The sub-additivity property is particularly critical: it ensures that the combined CVaR of a portfolio is always less than or equal to the sum of the individual CVaRs, making CVaR compatible with portfolio aggregation arithmetic that VaR violates. The minimum observation thresholds enforced for these metrics reflect their well-known sensitivity to sample size: both VaR and CVaR require sufficient distributional sampling to produce statistically stable confidence interval estimates.
● Information Ratio and Active Management Efficiency
The Information Ratio, as deployed here, follows the Grinold and Kahn formulation from "Active Portfolio Management" (2000): annualized active return divided by annualized tracking error. This ratio encapsulates the fundamental law of active management in a single statistic. Grinold's Fundamental Law states that the Information Ratio of a strategy is approximately equal to the information coefficient (IC — the per-period predictive skill) multiplied by the square root of the breadth (number of independent bets). A strategy with broad diversification but modest per-bet skill can achieve the same Information Ratio as a concentrated strategy with high per-bet skill. The indicator exposes both the numerator (Average Active Return) and denominator (Tracking Error) as independent metrics, enabling the user to decompose the IR into its constituent drivers.
● Capture Ratio Asymmetry and Convexity Measurement
The Upside and Downside Capture Ratios implement a conditional performance attribution that partitions the benchmark's return history into two exclusive regimes: periods of positive benchmark return and periods of negative benchmark return. The security's average return in each regime, normalized by the benchmark's average return in the same regime, produces the two capture statistics. Their ratio — the Composite Capture Ratio — is a direct measure of the convexity of the return relationship between the security and the benchmark. A ratio substantially above 1.0 indicates that the payoff profile is convex — the security behaves like a long option on the benchmark — which is the behavioral signature of strategies that exhibit positive tail dependency in bull markets and negative tail dependency in bear markets.
● Profit Factor and Distribution-Free Performance Assessment
The Profit Factor is the sole metric in the indicator's suite that makes no parametric distributional assumption. It is computed directly from the empirical return series as the ratio of gross positive returns to the absolute value of gross negative returns. This distribution-free characteristic is particularly valuable when Kurtosis is elevated: in leptokurtic environments, parametric measures like Sharpe Ratio are biased by the fat-tail contamination of the standard deviation estimate. The Profit Factor remains unaffected by distributional shape, making it a robust complement to parametric ratio metrics in any fat-tailed return environment.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
✨ Originality and Utility
● A Unified Quantitative Research Terminal on TradingView
The financial analysis landscape on TradingView is dominated by single-purpose indicators: one tool for Sharpe ratio, another for drawdown, yet another for beta. The Integrated Financial Analysis indicator abandons this fragmented paradigm entirely. It is engineered as a self-contained institutional research engine — one deployment that computes, renders, and cross-references the complete taxonomy of quantitative finance metrics in a single, coherent analytical environment. From raw return attribution through tail-risk quantification to efficiency ratio synthesis, every metric is evaluated in relation to every other, across every configured period, simultaneously.
● Five-Period Comparative Architecture
The defining architectural feature of this indicator is its five-dimensional temporal grid. Users configure five independent lookback periods — expressed in Days, Weeks, Months, or Years — and the engine produces a full metric profile for each without overlap or contamination between windows. This non-overlapping, sequential window design is intentional: it allows a portfolio analyst to observe, in a single glance, how a security's risk-adjusted profile evolves from short-term to long-term horizons, identifying whether outperformance is structurally persistent or episodic. No other publicly available TradingView indicator offers this degree of temporal granularity across such a broad metric set.
● Dual-Benchmark Architecture with Optional Secondary Index
The engine supports a configurable primary benchmark and an optional secondary index, giving institutional users the flexibility to evaluate a security's performance against multiple reference points — such as a broad market index and a sector-specific sub-index — without modifying the script. The active benchmark drives all relative metrics simultaneously: excess return, beta, alpha, tracking error, information ratio, upside and downside capture ratios, and active return are all anchored to the same user-selected reference universe.
● Adaptive Timeframe Intelligence
The indicator detects the active chart timeframe — daily, weekly, or monthly — and automatically calibrates all annualization denominators, period multipliers, and observation thresholds accordingly. The correct number of trading periods per year is derived at runtime, not hardcoded, ensuring that every ratio produced is internally consistent regardless of whether the chart is displaying daily bars, weekly candles, or monthly closes.
🔬 Methodology and Concepts
● Category I — Return and Performance Attribution
Stock Performance & Index Performance
Measures the cumulative percentage gain or loss of both the target security and the benchmark index over each configured period. These are the baseline reference values against which all relative metrics are computed.
Excess Return
Quantifies the differential between the security's total return and the benchmark's total return over the same window. A persistently positive excess return — especially across multiple time horizons simultaneously — is the primary indicator of alpha-generative capability rather than mere beta exposure.
Compound Annual Growth Rate (CAGR)
The geometrically annualized return over each period, normalized to a per-year basis regardless of the actual window length. CAGR eliminates the distortion caused by the arithmetic mean's inability to account for compounding, providing the most accurate measure of the security's long-run growth trajectory.
Regression Alpha (Jensen's Alpha)
The intercept term extracted from the proprietary multivariate regression engine embedded in the indicator's computation library. Alpha represents the portion of the security's return that is attributable neither to broad market exposure (beta) nor to the risk-free rate — it is the pure measure of manager skill or structural edge. The computation enforces a minimum observation threshold (configurable, defaulting to three months of trading periods) to prevent statistically invalid alpha estimates from appearing in the dashboard.
Upside Capture Ratio
Measures how much of the benchmark's positive return periods the security captures on average. A value above 1.0 signifies that the security amplifies bullish benchmark performance, which is desirable when combined with a low Downside Capture Ratio.
Downside Capture Ratio
The complement to Upside Capture — measures the security's average participation in the benchmark's negative return periods. A value below 1.0 signifies meaningful downside protection: the security loses less than the benchmark during market stress.
Composite Capture Ratio
The ratio of Upside Capture to Downside Capture. This single composite statistic encapsulates the asymmetry of the security's return profile: values substantially above 1.0 indicate favorable convexity — the security captures more upside than downside — which is the defining characteristic of superior risk-adjusted performance.
Hit Ratio
The proportion of periods within the selected window in which the security generated a positive return. Unlike CAGR or Sharpe Ratio, the Hit Ratio measures consistency of directionality rather than magnitude-weighted performance. A high Hit Ratio combined with strong Profit Factor identifies securities with both reliable return frequency and favorable win/loss magnitude distribution.
● Category II — Risk and Volatility Metrics
Annualized Standard Deviation
The annualized measure of the dispersion of the security's periodic returns around their mean. This is the denominator in the Sharpe and Treynor ratios and the primary measure of total realized volatility. All annualization is performed using the timeframe-calibrated period count.
Beta (Market Sensitivity)
The slope coefficient from the proprietary regression engine, measuring the sensitivity of the security's excess returns to movements in the benchmark's excess returns. A beta above 1.0 denotes an aggressive security amplifying market moves; below 1.0 denotes defensive behavior.
Downside Beta
A refined version of conventional beta that restricts the regression sample exclusively to periods in which the benchmark registered a negative return. Downside Beta isolates the security's co-movement with the market specifically during adverse conditions — an asymmetric risk measure that conventional beta obscures by averaging across all market regimes.
R-Squared (Coefficient of Determination)
The proportion of the security's return variance explained by the benchmark's movements. A high R-squared validates the interpretive relevance of the regression-derived Beta and Alpha: in a low R-squared environment, beta becomes a poor predictor and Alpha loses much of its statistical meaning.
Tracking Error
The annualized standard deviation of the active return series — the period-by-period difference between the security and the benchmark. Tracking Error is the primary measure of active management deviation and is directly used as the denominator of the Information Ratio.
Average Active Return
The arithmetic mean of the period-by-period excess return of the security over the benchmark, annualized to the configured period basis. Together with Tracking Error, this forms the numerator and denominator of the Information Ratio, and independently signals the consistency of outperformance relative to benchmark.
Value at Risk (VaR)
A statistical threshold measure that estimates the maximum loss the security would be expected to incur over the selected period under normal market conditions, at a specific confidence level. The computation requires a minimum observation threshold (configurable, defaulting to one year of trading periods) to ensure statistical significance of the distributional estimate. Displayed as a percentage of the security's current value. Note that VaR measures expected losses within the normal distribution of market conditions and does not capture tail events.
Conditional Value at Risk (CVaR / Expected Shortfall)
The expected value of losses beyond the VaR threshold — the average loss in worst-case scenarios. CVaR is a coherent risk measure that VaR is not: it satisfies the sub-additivity property required for proper portfolio aggregation. The same minimum observation threshold applied to VaR governs CVaR to maintain distributional reliability.
Downside Deviation
The annualized standard deviation of returns that fall below the user-configured Minimum Acceptable Return (MAR). Unlike total standard deviation, Downside Deviation ignores periods of outperformance relative to the MAR threshold, recognizing that upside volatility is not risk in the economically meaningful sense. This is the denominator of the Sortino Ratio.
Skewness
The third standardized moment of the return distribution, measuring directional asymmetry. Positive skewness indicates a distribution with a longer right tail — infrequent large gains — while negative skewness (common in equity strategies) indicates a distribution with a longer left tail — infrequent but large losses. The computation requires a minimum observation threshold of six months by default to achieve sufficient distributional stability.
Kurtosis
The fourth standardized moment, measuring tail heaviness relative to a normal distribution. Excess kurtosis above 3 (leptokurtosis) indicates fatter tails than assumed by Gaussian models, which implies that extreme events — both gains and losses — occur more frequently than standard risk models predict. This is a critical input for tail risk assessment beyond what VaR and CVaR alone capture.
Maximum Drawdown (MDD)
The largest peak-to-trough decline observed within the selected period. Maximum Drawdown measures the worst historical loss that a fully committed investor would have endured. It is the denominator of the Calmar Ratio and the primary measure of catastrophic risk tolerance.
Drawdown Duration
The length (in trading days) of the longest drawdown episode within the selected window — from the peak at which the drawdown began to the point of maximum loss. A long Drawdown Duration, even if the MDD percentage is moderate, signals persistent capital impairment risk.
Time to Recovery
The number of trading days required to fully recover from the Maximum Drawdown back to the prior peak. An asymmetry between MDD Percentage and Time to Recovery reveals the speed of mean reversion in the security's price discovery process. Prolonged recovery periods reduce the effective compounded return and are particularly destructive to capital allocation efficiency.
● Category III — Efficiency Ratios and Risk-Adjusted Returns
Sharpe Ratio
The excess return per unit of total volatility, annualized. The Sharpe Ratio is the most widely referenced risk-adjusted performance metric in institutional finance. The excess return is computed relative to the user-configured risk-free rate, and the denominator is the total annualized standard deviation of the security's returns. Values above 1.0 are generally considered acceptable; above 2.0, exceptional.
Sortino Ratio
The excess return per unit of downside deviation, computed against the user-configured Minimum Acceptable Return (MAR) threshold. By penalizing only harmful volatility — returns below the MAR — the Sortino Ratio provides a more economically rational measure of risk-adjusted performance for strategies that exhibit positive skewness or controlled drawdown profiles. The Sortino Ratio consistently produces higher values than Sharpe for strategies with right-skewed return distributions.
Calmar Ratio
The annualized return relative to the Maximum Drawdown. The Calmar Ratio bridges the performance domain and the catastrophic risk domain: it asks, in essence, how much return is generated per unit of worst-case loss endured. It is particularly valued in absolute return and alternative investment contexts where drawdown constraints are binding.
Treynor Ratio
The excess return per unit of systematic risk (beta) rather than total risk. The Treynor Ratio is appropriate for evaluating a security's contribution to a well-diversified portfolio, where idiosyncratic risk is assumed to be diversified away. It is computed from the same regression engine that produces Beta and Alpha.
Information Ratio
The average active return divided by the tracking error. The Information Ratio quantifies the consistency of outperformance relative to the benchmark: a high Information Ratio indicates not merely that the security has outperformed, but that it has done so with predictable, reliable regularity. Values above 0.5 are considered strong; above 1.0, exceptional, in institutional active management benchmarks.
Profit Factor
The ratio of the sum of all positive returns to the absolute sum of all negative returns within the selected period. A Profit Factor above 1.0 indicates that gross gains exceed gross losses; above 2.0 is generally considered robust. Unlike Sharpe Ratio, Profit Factor makes no distributional assumptions and is therefore insensitive to the non-normality that characterizes most financial return series.
🎨 Visual Guide
● Transposed Multi-Period Analytics Table
The on-chart table is rendered in transposed format: metrics are organized as rows along the left column, while the five configured time periods occupy the five data columns to the right. This layout is deliberately chosen for its analytical efficiency — the eye traverses the table horizontally across time horizons for a single metric, and vertically across metrics for a single period, enabling both temporal comparison and cross-metric synthesis without reorganizing the mental model.
Color coding is applied to each cell based on the metric's directional interpretation:
- Green cells indicate values reflecting favorable conditions for that metric (e.g., positive Excess Return, Sortino above zero, Capture Ratio above 1.0).
- Red cells indicate unfavorable values.
- White cells indicate metrics that are directionally neutral (e.g., raw Drawdown Duration, Standard Deviation, Tracking Error) where color coding would impose a misleading directional judgment.
Header rows are color-differentiated by category: Performance and Ratio metrics use a blue header scheme; Risk and Volatility metrics use a purple header scheme, enabling rapid visual triage of the table by analytical domain.
The table is conditional: it renders only when the user has enabled at least one metric in the configuration, and suppresses entirely when Table Display Mode is set to "Hide All."
● Single Active Metric Plot with Dynamic Gradient Cloud
The plotting architecture enforces a single-active-metric principle: only one metric is visualized as the primary oscillator line at any given time, determined by the user's Plot Period configuration and metric selection. This design eliminates chart noise from overlapping oscillator lines and focuses analytical attention on the chosen metric's historical trajectory.
The active metric line is colored dynamically:
- Bull color (configurable, default cyan-blue) for positive values — indicating favorable performance, efficiency, or positive excess return depending on the active metric.
- Bear color (configurable, default red) for negative values.
A gradient fill cloud occupies the space between the metric line and the zero axis:
- Bull cloud: A gradient from vivid at the peak to transparent at zero, rendering the magnitude of positive performance as a visual intensity gradient.
- Bear cloud: A symmetric gradient below zero, signaling the depth of underperformance or negative efficiency.
A secondary envelope fill between the metric line and its moving average further highlights divergences between the current metric value and its trend baseline.
● Candle Coloring via Normalized Gradient Signal
When candle coloring is enabled and a plot metric is active, the chart's candles are recolored on the overlay pane according to a normalized gradient derived from the active metric's value relative to its own recent bull/bear force range. Candles are mapped on a smooth gradient spectrum from the Bear color (at the extreme negative end) through neutral to the Bull color (at the extreme positive end). This transforms the price candles into a visual heatmap of the current metric's quantitative state, allowing instantaneous assessment of whether the security's risk-adjusted posture is improving or deteriorating on a bar-by-bar basis.
● Moving Average Overlay
A configurable moving average is plotted alongside the active metric. In Auto mode, the MA length is automatically set to the timeframe-calibrated annual period count — one full year of trading bars — providing a natural long-run baseline for any metric. In Manual mode, the user specifies an explicit length. The MA can be applied to any of the 30 available metrics, enabling visual identification of trend inflections in Sortino Ratio, Information Ratio, Excess Return, or any other selected series.
● Zero Reference Line
A zero-axis reference line is rendered with automatic color adaptation based on the chart's background luminosity: dark on light themes, light on dark themes. This ensures legibility across all TradingView chart color schemes without manual adjustment.
📖 How to Use
● Establishing the Analytical Framework
Begin by configuring the Primary Market Index to the most relevant benchmark for the security under analysis. For equities, this is typically the broad market index (e.g., S&P 500, NASDAQ-100) or a sector-specific benchmark. For alternative or cross-asset analysis, the Secondary Index input can be activated to substitute a more precise reference universe. All relative metrics — Alpha, Beta, Tracking Error, Information Ratio, Capture Ratios, and Active Return — will immediately recalibrate to the selected benchmark.
● Configuring the Five Analytical Periods
Set the five period lengths and their unit type (Days, Weeks, Months, or Years) to reflect your investment horizon stack. A typical institutional setup might configure 1Y, 2Y, 3Y, 4Y, and 5Y to assess long-term statistical persistence, or a tactical setup might use shorter windows such as 3M, 6M, 1Y, 2Y, and 3Y to monitor both short-cycle tactical performance and strategic-cycle persistence simultaneously.
● Interpreting the Dashboard Table
Scan horizontally across a single metric row to identify whether performance characteristics are strengthening or weakening across time horizons. A Sortino Ratio that is strong at 1Y but weak at 3Y and 5Y suggests recent tactical outperformance that is not structurally persistent. Conversely, a consistently high Sharpe Ratio across all five periods indicates structurally superior risk-adjusted performance.
Scan vertically down a single period column to assess the holistic risk-adjusted profile for that specific window. A high CAGR with a poor Sortino and a large Maximum Drawdown reveals a volatile, drawdown-prone return stream that misleads when evaluated by raw return alone.
● Using the Plot Period for Temporal Forensics
The Plot Period is independent of the five table periods and can be set to any value within the supported range. Use this to select a specific analytical window for dynamic visualization. Plotting the Sortino Ratio with a 1-year Plot Period while the table displays 1Y through 5Y periods provides simultaneous static (tabular) and dynamic (oscillator) analysis of risk-adjusted efficiency across different temporal regimes.
● Identifying Risk-Adjusted Regime Shifts
The moving average on the active metric plot is the primary tool for regime detection. When the Sortino Ratio oscillator crosses below its annual moving average, it signals a deterioration in downside-adjusted performance relative to the recent trend — a potential early warning of risk regime transition. Combine this with the gradient candle coloring to identify whether the deterioration is occurring gradually or abruptly.
● Setting Academic Observation Thresholds
The three minimum observation settings — for regression-based metrics (Beta, Alpha, R-Squared), for distributional tail risk (VaR, CVaR), and for higher moments (Skewness, Kurtosis) — enforce statistical validity standards. When fewer bars than the configured threshold are available, the corresponding cells display "N/A" rather than producing numerically unreliable estimates. These thresholds should be calibrated to your statistical confidence requirements: increase them for higher-stakes decisions, reduce them for exploratory analysis on shorter datasets.
🎯Performance Metrics Reference Guide
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01 — PERFORMANCE METRICS
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▸ STOCK PERFORMANCE (Holding-Period Return)
Total price return of the instrument over the selected period.
Threshold: <0% [Loss] | 0–10% [Marginal] | 10–20% [Solid] | >20% [Strong]
Recommendation: Meaningless without benchmark context — always read alongside Index Performance.
▸ INDEX PERFORMANCE (Benchmark Holding-Period Return)
Total return of the selected market index over the equivalent period.
Threshold: Serves as the passive baseline — the minimum return justifying active exposure.
Recommendation: Persistent underperformance vs. the index disqualifies the active approach on a risk-adjusted basis.
▸ EXCESS RETURN (Stock Perf − Index Perf)
Arithmetic difference between instrument return and benchmark return over the same period.
Threshold: <0% [Underperforming] | 0–3% [Marginal Edge] | 3–5% [Meaningful] | >5% [Strong Alpha Premium]
Recommendation: Positive, consistent excess return across multiple periods is the primary empirical evidence of skill over passive indexing.
▸ CAGR (Compound Annual Growth Rate)
Geometric mean annualized return, smoothing compounding effects across multi-year periods.
Threshold: <7% [Weak] | 7–12% [Solid] | 12–20% [Strong] | >20% [Exceptional]
Recommendation: Must exceed risk-free rate + benchmark CAGR + inflation premium to justify active risk capital deployment.
▸ HIT RATIO (Win Rate)
Percentage of periods or trades generating a positive return.
Threshold: <45% [Poor] | 45–55% [Marginal] | 55–65% [Good] | >65% [Strong]
Recommendation: Never interpret in isolation — a 45% Hit Ratio with 2.5:1 reward/risk outperforms 65% with 0.8:1; always pair with Profit Factor.
▸ ALPHA (Regression-Based, Annualized)
Intercept of the OLS regression of excess stock returns on excess benchmark returns, annualized via CAPM.
Threshold: <0% [Value Destructive] | 0–2% [Marginal] | 2–5% [Significant] | >5% [Exceptional]
Recommendation: Valid only with ≥60 observations and R² >40% — low-R² Alpha is statistical noise, not skill.
▸ UPSIDE CAPTURE RATIO
Ratio of strategy mean return to benchmark mean return during positive benchmark periods.
Threshold: <80% [Weak] | 80–100% [Below Market] | 100–120% [Good] | >120% [Strong]
Recommendation: Must materially exceed 100% to justify the active risk premium — evaluate asymmetrically against Downside Capture.
▸ DOWNSIDE CAPTURE RATIO
Ratio of strategy mean return to benchmark mean return during negative benchmark periods.
Threshold: >100% [Amplifies Losses] | 80–100% [Weak Protection] | 60–80% [Good] | <60% [Excellent]
Recommendation: Institutional capital preservation mandates typically require Downside Capture <70% as a hard ceiling.
▸ CAPTURE RATIO (Upside ÷ Downside)
Composite measure of asymmetric market participation.
Threshold: <1.0 [Unfavorable] | 1.0–1.25 [Neutral] | 1.25–1.5 [Good] | >1.5 [Exceptional]
Recommendation: The single most direct quantitative measure of asymmetric skill — target >1.3 as the minimum viable institutional threshold.
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02 — RISK METRICS
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▸ ANNUALIZED STANDARD DEVIATION (Volatility)
Annualized standard deviation of log returns — the canonical measure of total portfolio risk.
Threshold: <10% [Low] | 10–20% [Moderate] | 20–30% [Elevated] | >30% [High]
Recommendation: Any strategy exceeding 25% volatility must generate proportionately superior Sharpe and Sortino ratios to remain institutionally viable.
▸ BETA (Market Sensitivity)
OLS regression slope of excess stock returns on excess benchmark returns.
Threshold: <0 [Inverse] | 0–0.8 [Defensive] | 0.8–1.2 [Market-Equivalent] | >1.2 [Aggressive]
Recommendation: Align Beta with mandate — defensive portfolios target β <0.8; growth mandates accept β >1.2 only when Alpha is simultaneously positive.
▸ DOWNSIDE BETA
Beta estimated exclusively during periods when the benchmark posted negative returns.
Threshold: <0.7 [Strong Protection] | 0.7–1.0 [Moderate] | 1.0–1.2 [Weak] | >1.2 [Amplified Bear Exposure]
Recommendation: Downside Beta must be materially lower than standard Beta — this divergence is the quantitative signature of genuine asymmetric risk management.
▸ R-SQUARED (Coefficient of Determination)
Proportion of the strategy's return variance explained by benchmark movements.
Threshold: <40% [Idiosyncratic] | 40–70% [Moderate] | 70–85% [High Correlation] | >85% [Quasi-Passive]
Recommendation: Active managers should maintain R² <70% to justify fees above a passive ETF; index-replicating vehicles target R² >95%.
▸ TRACKING ERROR
Annualized standard deviation of active returns (strategy minus benchmark).
Threshold: <2% [Quasi-Passive] | 2–6% [Active] | 6–12% [High Conviction] | >12% [Benchmark-Agnostic]
Recommendation: Tracking Error above 10% demands an Information Ratio above 0.75 to remain institutionally defensible.
▸ AVERAGE ACTIVE RETURN (Avg Absolute Active Return)
Mean absolute magnitude of the strategy's deviation from the benchmark each period.
Threshold: Lower = more consistent tracking | Higher = greater active divergence from benchmark.
Recommendation: Its ratio to Tracking Error approximates the Information Ratio — the core efficiency measure of active management.
▸ VAR (Value at Risk — Annualized, 95% Confidence)
Maximum expected loss at a 95% confidence level over the observation period, scaled to annual.
Threshold: <10% [Conservative] | 10–20% [Moderate] | 20–30% [Elevated] | >30% [High Tail Exposure]
Recommendation: |VaR| must not exceed 50–60% of expected CAGR — when |VaR| > CAGR, the risk/return structure is broken.
▸ CVAR (Conditional Value at Risk / Expected Shortfall)
Mean of all losses exceeding the VaR threshold — the true cost of tail events.
Threshold: CVaR/VaR <1.3 [Moderate Tail] | 1.3–1.6 [Elevated] | >1.6 [Fat-Tail Dominated]
Recommendation: Sharp CVaR/VaR divergence invalidates normal-distribution assumptions — mandatory switch to stress-testing frameworks at that point.
▸ DOWNSIDE DEVIATION
Annualized standard deviation of returns falling below the Minimum Acceptable Return (MAR).
Threshold: <5% [Low] | 5–10% [Moderate] | 10–15% [Elevated] | >15% [High]
Recommendation: Reducing Downside Deviation requires eliminating large negative outliers — not suppressing all volatility; it is the Sortino denominator and directly determines ratio quality.
▸ SKEWNESS
Third standardized moment; measures asymmetry of the return distribution.
Threshold: < −1.0 [Severe Crash Risk] | −1.0 to −0.5 [Negative Skew] | −0.5 to +0.5 [Symmetric] | >+0.5 [Favorable]
Recommendation: Negative skew combined with excess kurtosis is the defining statistical signature of blow-up risk — the profile of failed short-volatility and carry strategies.
▸ KURTOSIS
Fourth standardized moment; measures tail weight relative to a normal distribution (baseline = 3).
Threshold: ≈3 [Normal] | 3–5 [Mildly Leptokurtic] | 5–8 [Fat Tails] | >8 [Extreme Tail Risk]
Recommendation: Kurtosis >6 invalidates standard VaR models — fat-tail hedging is mandatory and Gaussian risk estimates must be abandoned entirely.
▸ MAXIMUM DRAWDOWN (MDD)
Largest peak-to-trough percentage decline in the equity curve over the observation period.
Threshold: <10% [Very Low] | 10–20% [Moderate] | 20–35% [Elevated] | >35% [Severe]
Recommendation: Institutional mandates cap MDD at 15–20%; always evaluate alongside Time to Recovery — depth alone is an incomplete risk picture.
▸ DRAWDOWN DURATION
Maximum consecutive number of periods the equity curve remained below its prior peak.
Threshold: <3 months [Fast] | 3–12 months [Acceptable] | 1–3 years [Concerning] | >3 years [Structural Failure]
Recommendation: Duration >12 months combined with MDD >20% is a composite red flag signaling strategy breakdown — not a temporary adverse cycle.
▸ TIME TO RECOVERY (Average)
Mean number of periods required to return to the prior equity peak following a drawdown.
Threshold: <3 months [Excellent] | 3–6 months [Good] | 6–12 months [Acceptable] | >12 months [Concerning]
Recommendation: Average TTR >6 months paired with high MDD signals compounding destruction — capital locked in recovery generates zero excess return.
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03 — ADVANCED RATIOS & EFFICIENCY
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▸ SHARPE RATIO
Annualized excess return above the risk-free rate per unit of total standard deviation.
Threshold: <0 [Destroys Value] | 0–1.0 [Suboptimal] | 1.0–1.5 [Acceptable] | 1.5–2.0 [Good] | >2.0 [Excellent]
Recommendation: Minimum viable institutional threshold is >1.0 sustained; hedge funds typically mandate Sharpe >1.5 for capital allocation approval.
▸ SORTINO RATIO
Annualized excess return per unit of downside deviation below MAR.
Threshold: <0 [Negative Risk-Adjusted] | 0–1.0 [Marginal] | 1.0–2.0 [Good] | 2.0–3.0 [Excellent] | >3.0 [Exceptional]
Recommendation: A well-managed strategy's Sortino should run 30–60% above its own Sharpe — if Sortino ≈ Sharpe, no protective asymmetry exists in the return distribution.
▸ CALMAR RATIO
Annualized CAGR divided by Maximum Drawdown — return per unit of worst-case loss.
Threshold: <0.5 [Poor] | 0.5–1.0 [Acceptable] | 1.0–2.0 [Good] | >2.0 [Excellent]
Recommendation: Minimum viable institutional threshold is 0.5; top systematic funds sustain 1.5–3.0 — particularly decisive for CTA and trend-following mandate compliance.
▸ TREYNOR RATIO
Annualized excess return per unit of systematic risk (Beta).
Threshold: <0 [Negative] | >0 [Positive] — benchmark against the market's own Treynor for meaningful comparison.
Recommendation: Use exclusively for cross-portfolio Beta-exposure comparison — invalid in isolation and unreliable for strategies with R² <40%.
▸ INFORMATION RATIO
Annualized active return divided by Tracking Error — the definitive efficiency measure of active management.
Threshold: <0.25 [Weak] | 0.25–0.5 [Marginal] | 0.5–0.75 [Skilled] | >0.75 [Exceptional]
Recommendation: IR >0.5 sustained over 36+ months is the gold standard for institutional manager retention — always validate across multiple time horizons.
▸ PROFIT FACTOR
Ratio of total gross profit to total gross loss across all periods.
Threshold: <1.0 [Losing System] | 1.0–1.5 [Marginal] | 1.5–2.0 [Good] | 2.0–3.0 [Strong] | >3.0 [Exceptional]
Recommendation: Minimum viable threshold for live capital deployment is >1.5; Profit Factor >3.0 in backtests demands rigorous overfitting scrutiny before allocation.
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04 — RELATIVE STRENGTH (Plot Only)
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▸ RELATIVE STRENGTH
Real-time ratio of instrument price to benchmark price, rebased to 100.
Threshold: >100 Rising [Sustained Outperformance] | >100 Flat [Holding Edge] | <100 Declining [Structural Underperformance]
Recommendation: Trend slope matters more than absolute level — rising Relative Strength during benchmark weakness is the most constructive institutional confirmation signal.
⚙️ Inputs and Settings
● Market Indices
- Primary Market Index: The benchmark symbol used as the reference universe for all relative metrics. Accepts any TradingView-accessible symbol.
- Secondary Index (Optional): An alternative benchmark that replaces the primary when "Use Secondary Index" is enabled. Useful for sector-relative or custom benchmark analysis.
- Use Secondary Index: Toggles the active benchmark between Primary and Secondary.
● Risk Parameters
- Risk-Free Rate (Annual %): The annualized risk-free rate used to compute excess returns over the risk-free asset. Applied in Sharpe, Treynor, Jensen's Alpha, and related ratio computations. Expressed as a percentage (e.g., 5.0 for 5%). Default: 0.
- Minimum Acceptable Return (MAR) for Sortino (%): The threshold return below which returns are classified as downside losses for the purposes of Downside Deviation and Sortino Ratio computation. Default: 0.
● Period Selection
- Period Type: Unit of the five analytical periods. Options: Days, Weeks, Months, Years.
- Period 1 through Period 5: Integer values defining each of the five analytical windows. All five periods are evaluated in parallel and displayed as five independent columns in the dashboard table.
● Plot Period Selection
- Plot Period Type: Unit of the plot period, independent from the table period type.
- Plot Period Value: Integer value defining the lookback window for the dynamic metric oscillator and its associated moving average.
● Table Columns Visibility
- Table Display Mode: Master control with three options — Show All forces all metric columns visible regardless of individual toggles; Hide All suppresses the entire table entirely; Custom respects individual per-metric visibility toggles, enabling a tailored dashboard.
● 01 — Performance Metrics (Table & Plot)
Each metric in this group exposes two independent toggles — one for the table dashboard and one for the plot oscillator — allowing the user to include a metric in the tabular summary without necessarily activating it as the primary oscillator, and vice versa.
- Stock Performance, Index Performance, Excess Return, CAGR, Capture Ratio, Hit Ratio, Alpha (Regression), Upside Capture, Downside Capture.
● 02 — Risk Metrics (Table & Plot)
- Annualized Standard Deviation, Beta (Regression), Downside Beta, R-Squared, Tracking Error, Average Active Return, VaR, CVaR, Downside Deviation, Skewness, Kurtosis, Max Drawdown, Drawdown Duration, Time to Recovery.
● 03 — Advanced Ratios (Table & Plot)
- Sharpe Ratio, Sortino Ratio, Calmar Ratio, Treynor Ratio, Information Ratio, Profit Factor.
● 04 — Misc Controls
- Relative Strength (Plot): Activates a ratio-based relative strength oscillator comparing the security's price to the benchmark's price, normalized to a percentage scale. This does not appear in the table; it is a plot-only metric for visual trend comparison.
● Moving Average
- Auto-Show MA for Visible Plots: When enabled, automatically renders the annual moving average for whichever metric is currently active in the oscillator pane.
- Show Moving Average: Master toggle for the MA line.
- MA Source: In manual mode, specifies which of the 30 available metrics the MA is computed over. Supports all metrics from both table and plot categories.
- Auto MA Length / Manual Length: Toggles between the timeframe-calibrated annual period count (auto) and a user-specified integer length (manual).
● Color Settings
- Bull Color: The color applied to positive metric values, the bull-side gradient cloud, and candles during positive signal regimes. Default: cyan-blue.
- Bear Color: The color applied to negative metric values, the bear-side gradient cloud, and candles during negative signal regimes. Default: red.
- MA Line Color: The color of the moving average line and its envelope fill. Default: amber.
● Hide or Show
- Show Zero Line: Toggles the zero-axis reference line on the oscillator pane.
- Show Analysis Table: Master toggle for the entire on-chart metric dashboard.
- Show Gradient Cloud: Toggles the graduated fill between the metric line and zero, and the MA envelope fill.
- Color Candles: Toggles gradient candle coloring on the price overlay pane.
● Academic Standards
- Min Obs for Beta/Alpha (3 Months): Minimum bar count required for regression-derived metrics (Beta, Alpha, R-Squared, Treynor) to produce a valid output. Default: 60 bars.
- Min Obs for VaR/CVaR (1 Year): Minimum bar count required for tail risk metrics. Default: 252 bars.
- Min Obs for Skew/Kurt (6 Months): Minimum bar count required for higher distributional moment metrics. Default: 126 bars.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
● Return Decomposition and Attribution Theory
The foundational architecture of this indicator is grounded in the Brinson-Hood-Beebower return attribution framework and its extensions. Returns are decomposed into systematic components (benchmark-attributable) and idiosyncratic components (security-specific), with the regression engine serving as the primary instrument of decomposition. The excess return series — the foundation of all risk-adjusted ratio computation — is constructed relative to the user-configured risk-free rate, consistent with Capital Market Theory's excess return formulation. All return series are derived from a continuous compounding framework, which provides additivity across periods and eliminates the geometric-vs-arithmetic mean distortion inherent in simple return aggregation across multi-period windows.
● Modern Portfolio Theory and CAPM Integration
The regression engine is calibrated to the Capital Asset Pricing Model (CAPM) framework: security excess returns are regressed against benchmark excess returns, yielding the systematic risk coefficient (Beta), the idiosyncratic return premium (Alpha), and the explanatory power of the model (R-Squared). Jensen's Alpha, as computed here, is the annualized constant term of this regression — the theoretically risk-adjusted measure of return that cannot be explained by market exposure alone. Downside Beta extends this framework into the Post-Modern Portfolio Theory (PMPT) domain by restricting the regression to the subset of periods where the benchmark's return is negative, isolating the security's co-movement with market stress rather than averaging it with benign periods.
● Downside Risk Paradigm and Post-Modern Portfolio Theory
The Sortino Ratio, Downside Deviation, CVaR, and Maximum Drawdown metrics collectively implement the Post-Modern Portfolio Theory framework developed by Rom and Ferguson (1994) as a systematic critique of the Markowitz mean-variance model. The core principle is that risk is not symmetric: investors do not uniformly penalize upside and downside volatility. By constructing a partial lower-moment framework — measuring only the variance of returns below the MAR threshold — these metrics align the mathematical definition of risk with its behavioral economic reality. The Sortino Ratio's use of semi-deviation rather than total standard deviation as the denominator directly embeds this asymmetric preference structure into the efficiency metric.
● Tail Risk and Extreme Value Theory
The VaR and CVaR computations address the empirically documented inadequacy of Gaussian return models. Financial return distributions exhibit persistent leptokurtosis — fat tails — and negative skewness, a combination that causes Gaussian VaR to systematically underestimate the probability and magnitude of extreme losses. CVaR (also known as Expected Shortfall) is a coherent risk measure in the sense defined by Artzner, Delbaen, Eber, and Heath (1999): it satisfies monotonicity, sub-additivity, homogeneity, and translational invariance. The sub-additivity property is particularly critical: it ensures that the combined CVaR of a portfolio is always less than or equal to the sum of the individual CVaRs, making CVaR compatible with portfolio aggregation arithmetic that VaR violates. The minimum observation thresholds enforced for these metrics reflect their well-known sensitivity to sample size: both VaR and CVaR require sufficient distributional sampling to produce statistically stable confidence interval estimates.
● Information Ratio and Active Management Efficiency
The Information Ratio, as deployed here, follows the Grinold and Kahn formulation from "Active Portfolio Management" (2000): annualized active return divided by annualized tracking error. This ratio encapsulates the fundamental law of active management in a single statistic. Grinold's Fundamental Law states that the Information Ratio of a strategy is approximately equal to the information coefficient (IC — the per-period predictive skill) multiplied by the square root of the breadth (number of independent bets). A strategy with broad diversification but modest per-bet skill can achieve the same Information Ratio as a concentrated strategy with high per-bet skill. The indicator exposes both the numerator (Average Active Return) and denominator (Tracking Error) as independent metrics, enabling the user to decompose the IR into its constituent drivers.
● Capture Ratio Asymmetry and Convexity Measurement
The Upside and Downside Capture Ratios implement a conditional performance attribution that partitions the benchmark's return history into two exclusive regimes: periods of positive benchmark return and periods of negative benchmark return. The security's average return in each regime, normalized by the benchmark's average return in the same regime, produces the two capture statistics. Their ratio — the Composite Capture Ratio — is a direct measure of the convexity of the return relationship between the security and the benchmark. A ratio substantially above 1.0 indicates that the payoff profile is convex — the security behaves like a long option on the benchmark — which is the behavioral signature of strategies that exhibit positive tail dependency in bull markets and negative tail dependency in bear markets.
● Profit Factor and Distribution-Free Performance Assessment
The Profit Factor is the sole metric in the indicator's suite that makes no parametric distributional assumption. It is computed directly from the empirical return series as the ratio of gross positive returns to the absolute value of gross negative returns. This distribution-free characteristic is particularly valuable when Kurtosis is elevated: in leptokurtic environments, parametric measures like Sharpe Ratio are biased by the fat-tail contamination of the standard deviation estimate. The Profit Factor remains unaffected by distributional shape, making it a robust complement to parametric ratio metrics in any fat-tailed return environment.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Informacje o Wersji
Optimizing indicator performance and execution speedInformacje o Wersji
Version Update SummaryNew Feature: Full Color Customization Suite
- Every major visual element on the chart and dashboard can now be recolored to match personal chart themes or brand palettes.
- Previously fixed colors are now fully user-adjustable, giving traders control over how the indicator looks against light or dark backgrounds and custom chart setups.
- New customizable elements include: bullish and bearish metric colors, the moving average line color, the zero-line color for both light and dark backgrounds, the active-metric name label (background, text, and empty state), the performance and risk section header colors, the default table row background, table text color, and the positive, negative, and neutral value colors used throughout the dashboard.
How to Use: Full Color Customization Suite
- Bullish and bearish colors continue to represent the same underlying signal direction as before — only their exact shade is now adjustable, so the color a trader sees still communicates whether the active metric is trending favorably or unfavorably.
- The moving average line color helps distinguish the trend baseline from the raw metric line at a glance.
- The zero-line color separates positive readings above it from negative readings below, and now automatically adapts more clearly depending on chart background choice.
- Table header colors continue to group metrics visually by category, while positive, negative, and neutral value colors keep indicating whether a given cell reading is favorable, unfavorable, or neutral relative to its metric.
Enhancement: Streamlined Input Panel Organization
- The settings panel has been reorganized into clearer, icon-labeled sections for Display, Market Indices, Risk Parameters, Academic Standards, Period Selection, Plot Period Selection, Table Columns Visibility, Moving Average, and Colors, making it faster to locate and adjust specific settings.
- Section names are more concise, reducing clutter for traders navigating a large number of configurable metrics.
Refinement: Consolidated Color Controls
- All color-related settings are now grouped together in a single dedicated section rather than scattered across display and table settings, making theme adjustments faster and more intuitive.
Informacje o Wersji
Timeframe & Chart Compatibility SafeguardsThe indicator now actively detects chart types and timeframes that would produce unreliable statistics, and clearly communicates this instead of silently showing incorrect numbers.
- On non-time-based chart types (such as Renko, Kagi, Point & Figure, Range, or Line Break), the script halts and displays a message explaining that these chart types are not supported because their bars are not evenly spaced in time.
- On sub-daily timeframes, an on-chart message advises switching to a Daily timeframe or higher for correct results.
- If the selected Period settings request lookback windows too large for the current timeframe, a message identifies the issue and suggests a suitable Period Type to switch to.
How to Use: If any of these messages appear on your chart, they indicate the current chart setup cannot produce reliable analysis. Follow the on-screen guidance (switch timeframe, chart type, or adjust Period Type) to restore normal operation.
Period Column Labels Now Show Full Ranges
The performance table's column headers have been upgraded from a single number to a clear start-to-end range for each period bucket.
- Example: a column that previously read simply "3M" (for Period 3) now reads the cumulative range it actually covers, such as "1-3M," making it immediately clear which stretch of time each column represents relative to the others.
How to Use: Read each column header as the exact span of time that column's statistics summarize, rather than assuming it starts from the present bar alone.
Refinements
- Improved accuracy of annualized statistics for markets that trade around the clock (such as crypto) and for charts using non-standard timeframe multipliers.
- More reliable benchmark comparison when the chart symbol and benchmark symbol reference the same underlying market under different tickers.
- Improved compatibility with Heikin Ashi charts so performance and return calculations reflect the correct underlying price data.
- Drawdown Duration and Time to Recovery labels now show a suffix matching your chart's timeframe (Daily, Weekly, Monthly, or bar-based) instead of always showing a daily suffix.
- Improved table text readability and color contrast when using a light chart background theme.
- General input safeguards added to prevent invalid entries for Risk-Free Rate, MAR, and Period values.
- Under-the-hood calculation and rendering refinements for improved stability and consistency across symbols and timeframes.
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💡 Proprietary indicators. Original research. Built by analysts who trade.
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👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
👑 Premium: markittick.com
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.
Dostępne w Płatnej Przestrzeni
Ten wskaźnik jest dostępny wyłącznie dla subskrybentów MarkitTick. Dołącz, aby uzyskać dostęp do tego oraz innych skryptów autorstwa MarkitTick.
💡 Proprietary indicators. Original research. Built by analysts who trade.
📢 Free Telegram: t.me/MarkitTick_Updates
👑 Premium: markittick.com
📢 Free Telegram: t.me/MarkitTick_Updates
👑 Premium: markittick.com
Wyłączenie odpowiedzialności
Informacje i publikacje nie stanowią i nie powinny być traktowane jako porady finansowe, inwestycyjne, tradingowe ani jakiekolwiek inne rekomendacje dostarczane lub zatwierdzone przez TradingView. Więcej informacji znajduje się w Warunkach użytkowania.