{
  "id": 118,
  "rank": 329,
  "name": "Return Distribution Trading Robot",
  "aka": [
    "Probabilistic Market-Neutral Trading Robot",
    "Return-Based Trading Strategy"
  ],
  "family": "K",
  "subtype": "K4",
  "one_liner": "Places orders based on the empirical distribution of returns, using probability-weighted volumes.",
  "market_regime": "volatile|any",
  "timeframes": [
    "M5",
    "H1"
  ],
  "symbols": [
    "EURUSD",
    "GBPJPY",
    "EURCHF"
  ],
  "sessions": [
    "any"
  ],
  "indicators": [],
  "entry_long": [
    "BUY LIMIT order placed at return level <= -0.01"
  ],
  "entry_short": [
    "SELL LIMIT order placed at return level >= 0.01"
  ],
  "exit_rules": [
    "Close all positions when total profit >= TotalProfitTarget",
    "Close positions by type when side-specific profit >= BuyProfitTarget or SellProfitTarget"
  ],
  "filters": [
    "none"
  ],
  "stop_loss": "not specified",
  "take_profit": "not specified",
  "position_size": "volume proportional to probability weight",
  "evidence_type": "forward_results",
  "completeness": 50.0,
  "signal_warnings": [
    "TIME-ONLY ENTRY: the entry conditions reference only clock time or session, with no market condition. This opens positions on a schedule."
  ],
  "claim_warnings": null,
  "opacity_warnings": [
    "UNDEFINED ENTRY TERM: the entry conditions are prose naming a concept with no numeric definition, so two readers would implement them differently. Advisory only -- this does not affect the score."
  ],
  "build_warnings": null,
  "canonical": "https://prismaticalgos.com/compendium/algo/118-return-distribution-trading-robot",
  "snapshot": "2026-10-31 15:46 UTC",
  "source_url": "https://www.mql5.com/en/articles/19797",
  "limitations": "These are machine-extracted research records, not verified trading systems. Catalog rank measures specification detail and claimed evidence, not profitability. The catalog extraction pipeline did not independently backtest these records. Its separate selected testing ledger does not validate the wider corpus. Rules, labels and parameters can be incomplete or wrong; consult the original source and its reuse terms."
}