Risk-Adjusted Performance Rankings | NickJoanRisk-Adjusted Performance Rankings | NickJoan
Core Idea
Risk-Adjusted Performance Rankings is a multi-asset comparison dashboard designed to rank up to 15 symbols by how efficiently they convert recent price movement into risk-adjusted return. Instead of looking only at raw price performance, the indicator evaluates three classic performance measures: Sharpe, Sortino and Omega over a user-defined lookback window and organizes the results into a table.
The script can be used in two ways:
• As a metrics table, where all three risk-adjusted values are shown side by side for each asset.
• As a ranking tool, where the symbols are sorted by Sharpe, Sortino, Omega, or a composite Z-Score score.
Calculation Logic
The indicator works by taking the percentage return of each symbol over the selected period and then building three separate statistics from that same return stream.
1. Return calculation
For each symbol, the script first calculates the one-bar rate of change. This creates a rolling return series that acts as the base input for all three risk-adjusted metrics.
2. Sharpe ratio
The Sharpe calculation measures average return relative to total return volatility.
• The script calculates the mean of returns over the selected lookback.
• It calculates the standard deviation of those returns.
• It divides mean return by standard deviation.
• It then multiplies by the square root of the lookback length to create a rolling-style scaled value.
In practical terms, a higher Sharpe reading means the asset has produced more return for each unit of total volatility.
3. Sortino ratio
The Sortino ratio is similar to Sharpe, but it only penalizes downside volatility.
• The script collects only negative returns from the lookback window.
• It computes the standard deviation of those downside returns.
• It divides mean return by that downside deviation.
• It then scales the result by the square root of the lookback.
This means Sortino rewards assets that may have volatile upside moves but relatively controlled downside behavior.
4. Omega ratio
The Omega calculation compares total gains to total losses over the selected window.
• All positive returns are summed as gains.
• All negative returns are converted to positive values and summed as losses.
• Omega is computed as the ratio of total gains to total losses.
A value above 1 suggests gains outweigh losses, while a value below 1 suggests the opposite.
Ranking Logic
The indicator supports several ranking modes, and each one uses the same asset list but applies a different sort key.
Metrics Table
In Metrics Table mode, the script shows:
• The ticker name.
• Sharpe.
• Sortino.
• Omega.
This mode is the most direct view if you want to inspect each asset’s raw values without sorting.
Sharpe / Sortino / Omega ranking
When one of these modes is selected:
• The table sorts the assets by that chosen metric.
• The highest values appear at the top.
• The table becomes a direct performance leaderboard.
Z-Score ranking
The Z-Score mode is a composite ranking system.
• The script first computes the mean and standard deviation of each metric across all 15 assets.
• It then converts each asset’s Sharpe, Sortino, and Omega into z-scores.
• Those three standardized values are averaged into one composite score.
• Assets are sorted by that final score.
This allows apples-to-apples comparison even when the raw metrics live on different numeric scales.
What the Colors Mean
The script uses color thresholds to make the table easier to read at a glance.
Sharpe colors
Sharpe cells are colored according to the input range defined by:
• Sharpe Min
• Sharpe Max
Values below the minimum are treated as weak.
Values between the lower zone and upper zone are shown as progressively stronger.
Values above the upper threshold are treated as strong.
Sortino colors
Sortino uses the same idea, but with its own range:
• Sortino Min
• Sortino Max
This allows the heatmap to reflect downside-adjusted performance independently from Sharpe.
Omega colors
Omega is especially important because it is naturally centered around 1.0.
• Values below the lower threshold are weak.
• Values between the band limits gradually improve.
• Values above the upper threshold are strong.
Z-Score colors
The Z-Score mode uses a standardized color logic:
• Strongly negative values are weak.
• Slightly negative values are mid-negative.
• Slightly positive values are mid-positive.
• Strongly positive values are strong.
This helps show whether an asset is above or below the group average on a normalized basis.
Table Output
Metrics Table output
In this mode, the table displays:
• Column 1: ticker.
• Column 2: Sharpe.
• Column 3: Sortino.
• Column 4: Omega.
Single-metric ranking output
In Sharpe, Sortino, and Omega modes, the table displays:
• Rank number.
• Ticker.
• Chosen metric.
This keeps the interface minimal while still showing the full ranked order.
Z-Score output
In this mode, the table displays:
• Rank number.
• Ticker.
• Sharpe Z.
• Sortino Z.
• Omega Z.
• Average score.
This view is useful when you want a compact, relative ranking rather than raw values.
Inputs
The indicator has four main input groups.
Calculation
• Period: defines the lookback window used for all metric calculations.
Table
• Display Mode: chooses between Metrics Table, Sharpe, Sortino, Omega, and Z-Score.
• Table Position: controls where the table is placed on the chart.
Color Scale
• Sharpe Min / Max: controls the heatmap thresholds for Sharpe.
• Sortino Min / Max: controls the heatmap thresholds for Sortino.
• Omega Min / Max: controls the heatmap thresholds for Omega.
Colors
• Strong: the strongest positive color.
• Mid +: the intermediate positive color.
• Mid -: the intermediate negative color.
• Weak: the weakest negative color.
Tickers
The script includes 15 symbol inputs, allowing you to compare a basket of assets at once. This makes it suitable for crypto rotation, watchlist comparison, or broad performance ranking across a selected universe.
How to Use It
This indicator is best used as a relative strength and quality filter, not as a standalone entry signal.
Trend selection
Use the ranking table to see which assets are showing the best risk-adjusted behavior over the chosen period.
Rotation analysis
If you track a basket of coins or market leaders, the indicator can help identify which names are improving in risk-adjusted terms and which ones are losing momentum.
Risk control
A raw gain is not always useful if it comes with excessive volatility or poor downside behavior. This script helps highlight assets with better return efficiency, not just bigger movement.
Multi-factor comparison
Because Sharpe, Sortino, and Omega emphasize different aspects of return quality, the script gives a more balanced view than a single metric alone.
Practical Interpretation
Here is a simple way to read the results:
• High Sharpe: efficient return relative to total volatility.
• High Sortino: strong return with less downside volatility.
• High Omega: gains outweigh losses over the lookback window.
• High Z-Score average: strong performance relative to the rest of the selected universe.
If an asset scores well across all three, it usually represents a stronger and more stable candidate than one that only looks good on one metric.
Best Use Cases
Typical uses include:
• Crypto basket comparison.
• Top-asset ranking.
• Risk-adjusted momentum filtering.
• Rotation watchlists.
• Regime-aware asset selection.
It is especially useful when you want to compare many symbols quickly without manually calculating which ones are actually performing best on a quality-adjusted basis.
Notes
The metric table is only as good as the selected lookback period and asset set.
• Shorter periods react faster but can be noisier.
• Longer periods smooth the results but may lag recent shifts.
• The Z-Score mode is relative to the selected group, so its meaning depends on the symbols you include. Indicator
Omega Ratio AnalysisThe Omega ratio was introduced by Keating and Shadwick in 2002 as a superior alternative to the Sharpe ratio.
Sharpe assumes normally distributed returns (ignores fat tails and might be unrealistic sometimes), Omega captures the entire return distribution. This makes it ideal for analyzing crypto, leveraged ETFs, and any assets with asymmetric returns or fat tails (I love fat tails, as part of my investment strategy of course).
Quant funds prefer Omega because it answers:
"How much do I gain above my threshold versus how much do I lose below it?"
This aligns with actual investment goals better than abstract volatility penalties.
THE MATH
Omega ratio is defined as:
Ω(MAR) = (Sum of returns above MAR) / (Sum of returns below MAR)
Where MAR (Minimum Acceptable Return) is your return threshold .
The indicator calculates this using log returns
for better statistical properties:
Log returns: ln(price / previous price)
For time series mode: Loops through lookback period, summing gains above threshold and losses below threshold
For curve mode: Calculates Omega at multiple MAR levels (from 0% to max) to reveal distribution shape
Values above 1.0 indicate gains exceed losses. For example, Ω = 1.5 means $1.50 in gains for every $1.00 in losses relative to your target.
Time Series Mode
Tracks Omega over time using a rolling window (default 252 bars). Shows color-coded performance zones: Excellent (>1.5), Good (>1.0), Caution (>0.7), Poor (<0.7). Set your annual return target and the indicator converts it to per-bar threshold. Monitor whether you're beating your goal over time.
Omega Curve Mode
It plots Omega versus different MAR thresholds to reveal the return distribution shape. A steep declining curve indicates normal distribution with thin tails. A gentle slope indicates fat tails with asymmetric upside. Compare your asset against any benchmark (default QQQ) to see which has better tail performance at different return thresholds.
HOW TO USE
For Long-Term Investors:
Use 252-bar lookback on daily charts (1 year) or use even weekly charts. Set your annual target around 10% (historical market average). If Omega stays above 1.0, you're beating your goal. Check the curve periodically - a gentle slope means the asset has upside potential beyond average returns.
For Comparing Assets:
Plot two assets (like SPY vs TQQQ). If the leveraged version has a gentler curve slope, it captures more explosive upside days. The crossover point shows which MAR threshold favors which asset. Asset above benchmark at high MAR levels = better for aggressive return goals.
For Regime Detection:
Use shorter periods (60-90 bars) for curve calculation. When curves become steeper, returns are normalizing and momentum may be fading. When curves flatten or become more convex, fat tails are developing (bullish regime forming).
APPLICATIONS
Asset Selection: Screen for asymmetric opportunities by comparing curve shapes. Gentle slopes indicate lottery-ticket upside potential.
Leverage Analysis: Quantify whether leveraged ETFs justify the volatility by comparing curves at high MAR levels. If 3x ETF curve significantly above 1x at MAR = 2%, leverage premium exists.
Risk Assessment: Steep curves = predictable, capped returns. Gentle curves = volatile but moonshot potential. Choose based on your risk tolerance and return goals.
Performance vs Benchmark: Compare your holdings against sector ETFs or market indices. If your curve is below benchmark at your target MAR, you're not getting paid for the extra risk.
PRACTICAL TIPS
Curve Period: Use 60-90 bars to see asymmetry during volatile markets. Longer periods (252-1000 bars) average out cycles and produce linear curves.
MAR Increments: Keep at 50 for smooth curves. Only lower for performance reasons.
Multi-Symbol Analysis: Compare growth stocks vs QQQ, value vs SPY, crypto vs BTC, or leveraged vs unleveraged to quantify relative risk-reward.
Reading the X-Axis: MAR shows per-bar percentage. On daily charts, 0.5% MAR means "only days with +0.5%+ returns count as wins." On monthly charts, 3% MAR means "only months with +3%+ returns count as wins."
My indicator is perfect for quant investors who want institutional-grade risk analysis. Goes beyond simple volatility metrics to reveal the true shape of return distributions.
PRACTICAL EXAMPLE:
This chart compares SPY versus TQQQ (3x leveraged Nasdaq ETF) on monthly bars over 252 months (21 years), spanning the 2008 crisis, 2020 crash, and multiple market cycles.
Both start at Omega = 1.50 (identical overall risk-adjusted returns), but the curve shapes reveal how those returns were achieved:
SPY (in cyan): Steep drop from 1.5 to near zero by MAR = 1.7% per month. Returns cluster tightly around average - predictable but limited upside.
TQQQ (in red): Gradual slope maintaining Omega = 0.35 even at MAR = 8.7% per month. Shows fat right tail with many explosive +20-40% months that SPY never sees.
Key insight is: For aggressive goals (20-30% annual), SPY's Omega drops to 0.5 (losses dominate) while TQQQ stays above 1.0 (gains exceed losses). TQQQ offers better odds at high return targets, but requires surviving -60 to -90% bear market drawdowns.
This demonstrates how curves reveal distribution characteristics that price charts or Sharpe ratios miss - specifically the asymmetric upside advantage of leveraged products for long-term holders with high risk tolerance.
Let me know if you have questions or suggestions:
- Henrique Centieiro
Indicator
Aggregated Scores Oscillator [Alpha Extract]A sophisticated risk-adjusted performance measurement system that combines Omega Ratio and Sortino Ratio methodologies to create a comprehensive market assessment oscillator. Utilizing advanced statistical band calculations with expanding and rolling window analysis, this indicator delivers institutional-grade overbought/oversold detection based on risk-adjusted returns rather than traditional price movements. The system's dual-ratio aggregation approach provides superior signal accuracy by incorporating both upside potential and downside risk metrics with dynamic threshold adaptation for varying market conditions.
🔶 Advanced Statistical Framework
Implements dual statistical methodologies using expanding and rolling window calculations to create adaptive threshold bands that evolve with market conditions. The system calculates cumulative statistics alongside rolling averages to provide both historical context and current market regime sensitivity with configurable window parameters for optimal performance across timeframes.
🔶 Dual Ratio Integration System
Combines Omega Ratio analysis measuring excess returns versus deficit returns with Sortino Ratio calculations focusing on downside deviation for comprehensive risk-adjusted performance assessment. The system applies configurable smoothing to both ratios before aggregation, ensuring stable signal generation while maintaining sensitivity to regime changes.
// Omega Ratio Calculation
Excess_Return = sum((Daily_Return > Target_Return ? Daily_Return - Target_Return : 0), Period)
Deficit_Return = sum((Daily_Return < Target_Return ? Target_Return - Daily_Return : 0), Period)
Omega_Ratio = Deficit_Return ≠ 0 ? (Excess_Return / Deficit_Return) : na
// Sortino Ratio Framework
Downside_Deviation = sqrt(sum((Daily_Return < Target_Return ? (Daily_Return - Target_Return)² : 0), Period) / Period)
Sortino_Ratio = (Mean_Return / Downside_Deviation) * sqrt(Annualization_Factor)
// Aggregated Score
Aggregated_Score = SMA(Omega_Ratio, Omega_SMA) + SMA(Sortino_Ratio, Sortino_SMA)
🔶 Dynamic Band Calculation Engine
Features sophisticated threshold determination using both expanding historical statistics and rolling window analysis to create adaptive overbought/oversold levels. The system incorporates configurable multipliers and sensitivity adjustments to optimize signal timing across varying market volatility conditions with automatic band convergence logic.
🔶 Signal Generation Framework
Generates overbought conditions when aggregated score exceeds adjusted upper threshold and oversold conditions below lower threshold, with neutral zone identification for range-bound markets. The system provides clear binary signal states with background zone highlighting and dynamic oscillator coloring for intuitive market condition assessment.
🔶 Enhanced Visual Architecture
Provides modern dark theme visualization with neon color scheme, dynamic oscillator line coloring based on signal states, and gradient band fills for comprehensive market condition visualization. The system includes zero-line reference, statistical band plots, and background zone highlighting with configurable transparency levels.
snapshot
🔶 Risk-Adjusted Performance Analysis
Utilizes target return parameters for customizable risk assessment baselines, enabling traders to evaluate performance relative to specific return objectives. The system's focus on downside deviation through Sortino analysis provides superior risk-adjusted signals compared to traditional volatility-based oscillators that treat upside and downside movements equally.
🔶 Multi-Timeframe Adaptability
Features configurable calculation periods and rolling windows to optimize performance across various timeframes from intraday to long-term analysis. The system's statistical foundation ensures consistent signal quality regardless of timeframe selection while maintaining sensitivity to market regime changes through adaptive band calculations.
🔶 Performance Optimization Framework
Implements efficient statistical calculations with optimized variable management and configurable smoothing parameters to balance responsiveness with signal stability. The system includes automatic band adjustment mechanisms and rolling window management for consistent performance across extended analysis periods.
This indicator delivers sophisticated risk-adjusted market analysis by combining proven statistical ratios in a unified oscillator framework. Unlike traditional overbought/oversold indicators that rely solely on price movements, the ASO incorporates risk-adjusted performance metrics to identify genuine market extremes based on return quality rather than price volatility alone. The system's adaptive statistical bands and dual-ratio methodology provide institutional-grade signal accuracy suitable for systematic trading approaches across cryptocurrency, forex, and equity markets with comprehensive visual feedback and configurable risk parameters for optimal strategy integration. Indicator
Dynamic Risk-Adjusted Performance Ratios with TableWith this indicator, you have everything you need to monitor and compare the Sharpe ratio, Sortino ratio, and Omega ratio across multiple assets—all in one place. This tool is designed to help save time and improve efficiency by letting you track up to 15 assets simultaneously in a fully customizable table. You can adjust the lookback period to fit your trading strategy and get a clearer picture of how your assets perform over time. Instead of switching between charts, this indicator puts all the critical information you need at your fingertips.
Sharpe Ratio -
Helps evaluate the overall efficiency of investments by comparing the average return to the total risk (measured by the standard deviation of all returns). Essentially, it tells you how much excess return you’re getting for each unit of risk you’re taking. A higher Sharpe ratio means you’re getting better risk-adjusted performance—something you’ll want to aim for in your portfolio.
Sortino Ratio -
Goes a step further by focusing only on downside risk—because let’s face it, no one worries about positive volatility. This ratio is calculated by dividing the average return by the standard deviation of only the negative returns. Perfect for those concerned about avoiding losses rather than chasing extreme gains. It gives you a sharper view of how well your assets are performing relative to the risks you’re trying to avoid.
Omega Ratio -
Offers a unique perspective by comparing the sum of positive returns to the absolute sum of negative returns. It’s a straightforward way to see if your wins outweigh your losses. A higher Omega ratio means your positive returns significantly exceed the downside, which is exactly what you want when building a strong, reliable portfolio.
This indicator is perfect for traders who want to streamline their decision-making process and gain an edge. Bringing together these three critical ratios into a single user-defined table makes it easy to compare and rank assets at a glance. Whether optimizing a portfolio or looking for the best opportunities, this tool helps you stay ahead by focusing on risk-adjusted returns. The customizable lookback period lets you tailor the analysis to fit your unique trading approach, giving you insights that align with your goals. If you’re serious about making data-driven decisions and improving your trading outcomes, this indicator is a game-changer for your toolkit.
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