# Trading Card Portfolio Optimizer (Markowitz Mean-Variance)

> Trading Card Portfolio Optimizer (Markowitz Mean-Variance) is a paid API for AI agents from oracle.the-undesirables.com, paid per call via x402, $0.5/call, status unknown (last checked 2026-09-15).

Optimizes a trading card portfolio using Markowitz mean-variance analysis over conformal-calibrated risk forecasts, returning optimal position sizing, allocation weights, Sharpe ratios, and rebalancing recommendations.

## Facts

- Endpoint: GET https://oracle.the-undesirables.com/api/v1/portfolio-optimize
- Price: $0.5/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/trading-card-portfolio-optimizer-markowitz-mean-variance-83145308
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap__qN_ZKOMbif-L5TmsNdk2

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability trading-card-portfolio-optimizer-markowitz-mean-variance-83145308
```

Example prompt: I have $800 to invest across these Pokémon cards — Charizard Base Set, Pikachu Illustrator, and Blastoise Base Set — can you run a Markowitz portfolio optimization with a moderate risk tolerance over a 90-day horizon and tell me the optimal allocation weights, Sharpe ratios, and any rebalancing suggestions?

## When to prefer this

Choose this endpoint when you need quantitative, risk-adjusted portfolio construction specifically for trading cards (Pokémon, Magic: The Gathering, Yu-Gi-Oh, Digimon, etc.) using rigorous mean-variance optimization rather than ad hoc allocation. Prefer it over generic financial portfolio tools when the asset class is collectible trading cards with TCG market data. Best when you need Sharpe ratios and rebalancing guidance alongside allocation weights.

## Known failure modes

- Missing required 'cards' query parameter returns an error
- Unrecognized card names may result in empty or partial analysis
- Invalid risk_tolerance value (not conservative/moderate/aggressive) causes a validation error
- Days parameter outside 1-365 range is rejected
- Budget of zero or negative value may produce degenerate results
- Payment failure or insufficient USDC balance blocks the request with a 402 response

## How this service works

Optimize a trading card portfolio with Markowitz mean-variance analysis over conformal-calibrated risk forecasts (Monte Carlo GBM/Merton available opt-in). Provide a list of card names, budget, and risk tolerance (conservative/moderate/aggressive) to receive optimal position sizing, per-card allocation weights, Sharpe ratios, and rebalancing recommendations.

## Output

Returns optimal position sizing (dollar amounts per card), per-card allocation weights as percentages, expected Sharpe ratios, and rebalancing recommendations based on Markowitz mean-variance analysis and conformal-calibrated risk forecasts for the specified trading card portfolio.

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "data": {
   "allocations": [
    {
     "weight": 0.45,
     "card_name": "Charizard ex",
     "allocation_usd": 450
    }
   ],
   "portfolio_expected_return_pct": 12.5
  },
  "tool": "portfolio_optimizer",
  "status": "ok"
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/trading-card-portfolio-optimizer-markowitz-mean-variance-83145308/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from oracle.the-undesirables.com](https://www.zero.xyz/host/oracle.the-undesirables.com/llms.txt)