{
  "id": 11540,
  "rank": 2326,
  "name": "Sharpe-ratio-based risk-return strategy",
  "aka": [
    "risk-return trading strategy",
    "dynamic Sharpe-ratio-based trading strategy"
  ],
  "family": "I",
  "subtype": "I4",
  "one_liner": "Selects stocks based on recent risk-adjusted performance and dynamically rebalances the portfolio.",
  "market_regime": "any",
  "timeframes": [
    "null"
  ],
  "symbols": [
    "null"
  ],
  "sessions": [
    "null"
  ],
  "indicators": [
    {
      "name": "rolling returns",
      "params": {
        "period": 30
      },
      "applied_to": "close"
    },
    {
      "name": "rolling volatility",
      "params": {
        "period": 30
      },
      "applied_to": "close"
    }
  ],
  "entry_long": [
    "null"
  ],
  "entry_short": [
    "null"
  ],
  "exit_rules": [
    "null"
  ],
  "filters": [
    "transaction costs 0.1%",
    "slippage 0.2%"
  ],
  "stop_loss": "total portfolio value falls below 70% of initial capital",
  "take_profit": "null",
  "position_size": "allocated according to relative Sharpe ratios",
  "evidence_type": "backtest_shown",
  "completeness": 50.0,
  "signal_warnings": null,
  "claim_warnings": [
    "UNSIZED CLAIM: performance figures are published with no trade count, so the sample behind them cannot be judged.",
    "UNDATED CLAIM: performance figures are published with no test period, so they cannot be checked or reproduced."
  ],
  "opacity_warnings": null,
  "build_warnings": null,
  "canonical": "https://prismaticalgos.com/compendium/algo/11540-sharpe-ratio-based-risk-return-strategy",
  "snapshot": "2026-10-31 15:46 UTC",
  "source_url": "https://github.com/kexintao01-netizen/Risk-Return-Trading-Strategy-with-Python-Backtesting",
  "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."
}