Analysing your portfolio is not about checking whether your stocks went up. A rigorous analysis examines three distinct dimensions: structural health, risk exposure, and behavioural patterns. Each reveals something the others cannot.
KlirInvest organises portfolio intelligence around three scores — each measuring a different dimension of portfolio quality.
Dimension 1: Structure — The Health Score
The Health Score (0–100) evaluates the structural quality of your portfolio. It answers: "Is this portfolio well-constructed?"
What it measures (model portfolio_health_score@2.1.0):
- Volatility — annualised portfolio standard deviation
- Tail risk (CVaR) — Expected Shortfall in the worst 5% of scenarios
- Concentration — largest single-position weight and top-5 weight sum
- Correlation stress — instability of pairwise correlations under stress
- Drawdown — depth of, and proximity to, the maximum drawdown
- Data confidence — data-quality proxy: history depth, outliers, and coverage behind every other component (NOT a market-liquidity measure)
Each component is converted into a convex penalty and combined as "100 − Σ(weight × penalty)".
Related ideas such as sector balance, geographic distribution, and asset-class balance are valuable diversification concepts but are not direct inputs to this score.
Why it matters:
A portfolio can generate strong returns while carrying structural risks that only manifest during drawdowns. The Health Score identifies these risks during calm periods, when adjustments are least costly and least emotionally driven.
Benchmark: Health Scores below 40 typically reflect elevated concentration, correlation stress, or drawdown fragility that becomes most visible when correlations rise and apparent diversification compresses.
Dimension 2: Exposure — The Risk Score
The Risk Score (model `risk_score@3.0.0`) expresses your portfolio's volatility in plain-English bands so it can be compared over time and across portfolios.
What it measures (model risk_score@3.0.0):
- Single scored input: the percentile rank of your portfolio's annualised volatility against an SPY-based historical reference distribution, returned as a 0–100 score.
- Bands: Defensive (0–25), Balanced (26–50), Aggressive (51–75), Speculative (76–100).
- Data-confidence band (displayed alongside, not scored): derived from return-history length and estimated-position-count completeness.
Related risk metrics (shown separately, not inputs to the Risk Score):
CVaR / Expected Shortfall at 95%, maximum drawdown, market beta, and Student-t tail modelling are surfaced next to the Risk Score as diagnostic context. They are not ingredients of the V3 Risk Score formula.
Why it matters:
Most investors have a vague sense of their risk tolerance but no quantified measure of their realised volatility relative to a familiar reference. The Risk Score gives a single comparable number for that one question; the related metrics above provide the rest of the risk picture.
Dimension 3: Behaviour — The Decision Readiness Score
The Decision Readiness Score (DRS) is KlirInvest's most differentiated metric. It evaluates how much analytical context an investor has reviewed before acting — not whether the decision is right, but whether it is informed.
What it measures:
- Information completeness — has the investor reviewed relevant risk metrics before deciding?
- Simulation usage — was the proposed change modelled through a deterministic stress test or a probabilistic Monte Carlo (two distinct engines) before execution?
- Behavioural pattern consistency — does the investor's trading frequency change with market volatility (a signal of emotional decision-making)?
- Checklist completion — has the Before You Trade framework been followed?
Why it matters:
Barber and Odean's seminal research (2000) found that overtrading reduces returns by 6.5% annually. The Decision Readiness Score does not judge decisions — it measures the analytical process that precedes them.
A high DRS does not guarantee good outcomes. Research on investor behaviour suggests that consistently reviewing risk context before acting can reduce avoidable, emotion-driven decisions.
Bringing the Three Dimensions Together
Each score reveals a different vulnerability:
| Score | Reveals | Catches |
|-------|---------|---------|
| Health Score | Structural weakness | Volatility, tail risk, position concentration, correlation stress, drawdown, data confidence |
| Risk Score | Exposure magnitude | Volatility percentile vs. an SPY-based reference distribution |
| Decision Readiness Score | Behavioural vulnerability | Emotional trading, insufficient analysis, pattern inconsistency |
A portfolio can score well on structure (Health Score 80) but poorly on behaviour (DRS 35) — indicating a well-built portfolio managed impulsively. Or it can score well on behaviour (DRS 85) but poorly on risk (Risk Score 30) — indicating a disciplined investor holding excessive exposure.
The three scores together provide a complete picture that no single metric can.
How to Start
- Enter your holdings — ticker symbols and quantities
- Review your three scores — identify which dimension needs attention
- Examine the components — each score breaks down into actionable sub-metrics
- Model changes — use the deterministic Stress Test to size the impact of a single named shock, and the probabilistic Monte Carlo to see the outcome distribution; the two engines answer different questions and should both be consulted before executing
See how your portfolio scores — run your free analysis at [KlirInvest](/free-tools?tab=analysis).