The Undesirables

Predict the future market value of any collectible trading card using stochastic finance Monte Carlo simulations. Supports GBM and Merton Jump-Diffusion stochastic models with Poisson-driven jumps. Returns full forecast percentiles (5th through 95th), model parameters, VaR/CVaR risk metrics, and confidence intervals. Covers Pokémon, Magic, Yu-Gi-Oh, sports cards, and any tokenized real-world asset.

Daily TCGCSV market data snapshot with top movers, price changes, and volume trends across all 13 supported TCG games.

Trending Cards Feed: returns the top trading cards by market activity (30-day sales volume, views, price velocity). Covers all 25 supported TCG games. Useful for autonomous buy/sell agents tracking market momentum and identifying emerging opportunities.

Historical Token Simulator: Fetches OHLC (Open, High, Low, Close) token data from CoinGecko and applies Merton Jump-Diffusion Monte Carlo simulation to project future trajectories.

Fetch real-time NFT collection floor prices via Alchemy and run Merton Jump-Diffusion Monte Carlo simulations for institutional-grade price forecasting. Supports any ERC-721 or ERC-1155 contract on Ethereum mainnet. Returns current floor, historical volatility, drift parameters, and forecast percentiles.

Grade any physical Pokémon, Magic: The Gathering, Yu-Gi-Oh, or Digimon trading card using a 3-stage AI pipeline: (1) Qwen Vision LLM analyzes corners, edges, and surface defects, (2) OpenCV measures exact centering ratios programmatically, (3) BGS professional capping algorithm adjusts the final grade. Returns PSA/Beckett-calibrated subgrades and an overall condition score. Accepts card image URLs or base64.

Grade-or-Not Decision Engine: answers 'will grading this trading card make me money?' by combining AI grade prediction with PSA fee schedules, shipping costs, and graded market values to calculate expected ROI. Returns a clear GO/NO-GO verdict with best-case, predicted, and worst-case profit scenarios.

Detect mispriced weather derivatives on Kalshi by comparing live National Weather Service forecast data against current contract pricing. Finds statistical edges in temperature, precipitation, and wind speed markets.

Find guaranteed-profit basket arbitrage in prediction markets by aggregating all NO outcomes. When the total cost of buying every NO contract is less than the guaranteed payout, the yield is risk-free.

Batch Card Triage (GET variant): pass comma-separated card image URLs as the image_urls query param and get a profit-ranked grading triage. Each card is AI-graded then scored by expected ROI from professional grading, ranked highest-profit first. Identical to the POST endpoint — this GET form exists so the CDP Bazaar can index it.

Optimize a trading card portfolio using Markowitz mean-variance analysis with Merton Jump-Diffusion Monte Carlo simulations. 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.

Scan for cross-platform prediction market arbitrage opportunities between Polymarket and Kalshi using Gen3 Neuro-Symbolic NLI matching. Identifies price discrepancies where the same event is priced differently across platforms, creating risk-free edge.