fintech-algorithms
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Minimum-Volatility Index

Install and import#

bash
npm install fintech-algorithms
ts
import { calculate } from "fintech-algorithms/index-and-benchmark-engineering/alternative-weighting/minimum-volatility-index";

Signature#

calculate(data)

Solves for the weights that minimise portfolio variance for a given covariance matrix. The result is only as good as the covariance estimate, which is the part that is hard — not the optimisation.

Parameters#

NameTypeNotes
data{ ids: string[]; covariance: number[][] }covariance must be square, symmetric and positive semi-definite. A matrix estimated from fewer observations than assets will not be, and no optimiser can rescue it.

Returns#

{ ids, weights, variance, volatility }

The minimising weights and the portfolio variance and volatility they achieve.

Errors#

  • When the covariance matrix is not square or not symmetric — throws

Complexity: time O(n³), space O(n²).

Worked example#

verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.

Input#

data
{
  "ids": ["A", "B", "C"],
  "covariance": [
    [0.04, 0.006, 0.004],
    [0.006, 0.0225, 0.003],
    [0.004, 0.003, 0.01]
  ]
}

Call#

calculate(data)

Returns#

object with 4 fields: ids, weights, variance, volatility

{
  "ids": ["A", "B", "C"],
  "weights": [0.093023, 0.232558, 0.674419],
  "variance": 0.007814,
  "volatility": 0.088397
}

Diagrams#

Minimum-Volatility Index — article hero
Minimum-Volatility Index — failure guard
Minimum-Volatility Index — worked example

Calculation flow#

Minimum-Volatility Index calculation flow
flowchart LR
    A["Point-in-time inputs"] --> B["Validate units and timing"]
    B --> C{"Contract feasible?"}
    C -->|No| D["Reject with reason"]
    C -->|Yes| E["Calculate Minimum-Volatility Index"]
    E --> F["Recompute invariants"]
    F --> G{"Checks pass?"}
    G -->|No| D
    G -->|Yes| H["Publish audited output"]
Minimum-Volatility Index methodology state
stateDiagram-v2
    [*] --> FrozenInputs
    FrozenInputs --> Validated: contract passes
    FrozenInputs --> Rejected: missing or infeasible
    Validated --> Calculated: apply named rule
    Calculated --> Audited: invariants pass
    Calculated --> Rejected: invariant fails
    Audited --> Published: version and timestamp recorded
    Published --> Revised: approved correction
    Revised --> FrozenInputs: rebuild from retained source state

How it works#

This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.

Read the article →

References#

The rest of the Alternative Weighting family#