{
  "slug": "equal-weight",
  "title": "Equal-weight allocation",
  "topic": "allocation",
  "summary": "A transparent baseline that assigns identical capital weights to a declared number of assets.",
  "version": "1.0.0",
  "published": "2026-10-16",
  "status": "Educational reference",
  "formula": "w_i = 1 / N",
  "inputs": [
    [
      "assets",
      "Integer, 2 through 50",
      "Number of distinct included assets"
    ]
  ],
  "method": [
    "The rule contains no return estimates. That makes its arithmetic easy to inspect, but the universe is still a substantive choice. Four assets receive one quarter each; splitting one economic exposure into two tickers would change the resulting economic allocation.",
    "The output is a target vector, not a trade list. To implement it, first map the ordered assets, identify drifted holdings and decide when and how to rebalance. The turnover reference can measure an already aligned before-and-after comparison."
  ],
  "limits": [
    "Equal capital does not imply equal contribution to volatility or equal exposure to common factors. The card deliberately does not infer missing assets, cash, leverage, execution prices or costs. A passing arithmetic test says nothing about the merits of the chosen universe."
  ],
  "checks": [
    "Every weight is nonnegative; weights sum to one within floating-point tolerance.",
    "Two, four and fifty assets; fractional, missing and oversized counts rejected."
  ],
  "related": [
    "equal-weight-universe",
    "choosing-a-reference-model"
  ],
  "sources": [
    {
      "title": "MOSEK: portfolio variance and allocation constraints",
      "url": "https://docs.mosek.com/portfolio-cookbook/markowitz.html"
    }
  ],
  "example": {
    "assets": 4
  },
  "frozen_result": {
    "schema_version": 1,
    "model_id": "equal-weight",
    "model_version": "1.0.0",
    "engine_version": "1.0.0",
    "published_at": "2026-10-16",
    "scope": "Synthetic educational reference calculation. Not a fitted investment strategy, forecast, provider model or client return.",
    "inputs": {
      "assets": 4
    },
    "outputs": {
      "weights": [
        0.25,
        0.25,
        0.25,
        0.25
      ],
      "weight_sum": 1
    },
    "notes": [
      "No expected returns or covariance inputs. Rebalancing costs and universe selection are outside the rule."
    ]
  }
}