Estimate portfolio diversification benefit

What it's for

Quantifies whether a startup, product, or engineering investment portfolio is truly diversified in bad states—not merely spread across many line items—and shows which exposures dominate the tail.

What you give it

Inputs split into evidence read from your connected systems, calibration your team owns, and numerical controls that affect precision but never the result's meaning.

{
  "holdings": [
    {
      "capital_at_risk": 100,
      "id": "growth-products",
      "return_scenarios": [
        0.3,
        0.1,
        -0.2,
        -0.4
      ]
    },
    {
      "capital_at_risk": 100,
      "id": "infrastructure-savings",
      "return_scenarios": [
        -0.1,
        0.05,
        0.2,
        0.35
      ]
    }
  ],
  "maximum_portfolio_cvar_loss": 10,
  "maximum_single_risk_contribution_share": 1,
  "minimum_downside_diversification_benefit": 10,
  "scenarios": [
    {
      "id": "expansion",
      "probability": 0.25
    },
    {
      "id": "base",
      "probability": 0.25
    },
    {
      "id": "slowdown",
      "probability": 0.25
    },
    {
      "id": "severe-downturn",
      "is_stress": true,
      "probability": 0.25
    }

What you get back

This is the actual output of running the example above — computed by the same function the platform calls, not an illustration.

{
  "assumptions": [
    "Every holding return uses the same coherent joint scenario column and horizon; probabilities, capital, currency, valuation, liquidity, follow-on obligations, and loss sign are comparable, and independently sorted marginal scenarios are prohibited because they manufacture diversification.",
    "Diversification benefit compares portfolio CVaR with the sum of standalone CVaRs under the same probability law; Euler tail contributions reconcile to portfolio CVaR and may be negative for genuine hedges, but neither contribution nor leave-one-out change is causal attribution.",
    "Historical or simulated scenarios must include common shocks, tail dependence, concentration, nonlinear payoffs, dilution, and missing valuations that matter; a high ordinary diversification ratio cannot override weak stress coverage or an explicit risk-concentration gate.",
    "Holdings are aggregate companies, projects, products, services, or asset exposures, never named employees; this result is not investment advice, a valuation, a capital-allocation order, or authorization to buy, sell, fund, or terminate anything."
  ],
  "configuration": {
    "maximum_portfolio_cvar_loss": 10,
    "maximum_single_risk_contribution_share": 1,
    "minimum_downside_diversification_benefit": 10,
    "scenario_alignment_preserved": true,
    "tail_probability": 0.25
  },
  "decision": "portfolio_diversification_clears_governed_risk_gates",
  "holding_diagnostics": [
    {
      "capital_at_risk": 100,
      "expected_pnl": -5,
      "hedges_portfolio_tail": false,
      "holding_id": "growth-products",
      "leave_one_out_portfolio_cvar_change": -5,
      "portfolio_tail_risk_contribution": 40,
      "positive_tail_risk_contribution_share": 1,
      "standalone_cvar_loss": 40,
      "standalone_volatility": 26.9258
    },
    {
      "capital_at_risk": 100,
      "expected_pnl": 12.5,
      "hedges_portfolio_tail": true,
      "holding_id": "infrastructure-savings",
      "leave_one_out_portfolio_cvar_change": -35,
      "portfolio_tail_risk_contribution": -35,
      "positive_tail_risk_contribution_share": 0,
      "standalone_cvar_loss": 10,
      "standalone_volatility": 16.7705
    }
  ],
  "method": "coherent_scenario_cvar_diversification_benefit_v1",
  "scenario_diagnostics": [
    {
      "is_stress": true,
      "portfolio_loss": 5,

How it works

Constrained optimization — Pick the best feasible option under real limits — budget, headcount, dependencies, capacity — rather than ranking a list and hoping it fits.

1. 1 Freeze holdings, capital at risk, valuation horizon, and one aligned joint scenario matrix with common probabilities and stress labels; reject independently sorted or marginal-only forecasts that destroy dependence.
2. 2 Compute holding and portfolio P&L, fractional-tail CVaR, coherent and downside diversification benefit, volatility diversification, and exact Euler contributions using the portfolio's own tail weights.
3. 3 Reconcile contributions to portfolio CVaR, identify true tail hedges and leave-one-out effects, and recommend only when downside benefit, absolute portfolio loss, and positive risk-contribution concentration all clear governed limits.

Before you trust it

Every tool in the catalog ships with the conditions under which its answer is meaningful — and the conditions under which it should abstain instead of guessing.

Calibrating it to your org

Calibration workflow

1. 1 Define the management decision, target outcome, aggregate unit, privacy boundary, cadence, and prediction/intervention horizon for this organization.
2. 2 Build a tenant-scoped historical cohort using only information available before each prediction or decision; preserve zero periods, censoring, assignment probabilities, and unresolved outcomes when the method requires them.
3. 3 Estimate statistical parameters on training history, but obtain costs, utilities, risk tolerance, practical-effect thresholds, capacity, and policy constraints from accountable decision owners.
4. 4 Validate on later time windows or held-out aggregate units at the deployment grain, against a simple baseline and the function-specific validation strategy.
5. 5 Deploy only if the returned decision clears evidence, overlap, calibration, robustness, and guardrail checks; warning, unsupported, schema-gap, and fallback decisions are abstentions.
6. 6 Monitor realized outcomes, data drift, coverage, and decision regret; recalibrate at a governed cadence or after a detected regime/definition change, never merely because a stakeholder dislikes the result.

Call it from your AI

You don't wire up 388 tools in your MCP client. The GitRevio MCP server exposes 18 tools, three of which let an agent search the catalog, read a tool's schema, and run it — so the assistant finds this one on its own.

gitrevio_capabilities_search
  { "q": "measure coherent portfolio diversification by comparing" }
  → finds "estimate_portfolio_diversification_benefit"

gitrevio_capability_describe
  { "capability_id": "estimate_portfolio_diversification_benefit" }
  → returns the input schema and agent guidance shown on this page

gitrevio_capability_run
  { "capability_id": "estimate_portfolio_diversification_benefit", "arguments": { ... } }
  → returns the result shown above

Works in Claude Desktop, Claude Code, Cursor, Cline, Continue.dev, Goose and Aider. See the MCP server.

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