Overview search_marketplace queries the QuantX model registry and returns a ranked list of models matching the specified criteria. Use it to discover signals and strategies before subscribing.Auth is not required — this tool is publicly accessible.
Parameters Free-text search query. Supports natural language. Examples: "momentum US equities", "mean reversion crypto", "low volatility factor bonds"
Optional structured filters to narrow results. Filter by strategy category. Accepted values: Value Description "momentum"Trend-following and price momentum "mean_reversion"Statistical arbitrage and reversion "factor"Multi-factor and smart-beta "ml_alpha"ML/DL-generated alpha signals "macro"Macro and regime-based strategies
Filter by asset class: "equities", "fixed_income", "crypto", "commodities", "fx", "multi_asset".
Minimum annualized Sharpe ratio (backtested). Example: 1.5.
Maximum allowable drawdown (absolute value, e.g. 0.20 = 20%).
List of tags to match. Example: ["long-short", "weekly-rebalance"].
Maximum number of results to return. Default: 10. Max: 50.
Ranking criterion. Accepted values: Value Description "relevance"Default — text + semantic match score "sharpe"Backtested Sharpe ratio (descending) "subscribers"Popularity by subscriber count "published_at"Most recently published first
Returns { "total" : 3 , "results" : [ { "model_id" : "qx-mom-us-001" , "name" : "US Large-Cap Momentum" , "author" : "quantspace-research" , "strategy_type" : "momentum" , "asset_class" : "equities" , "sharpe_ratio" : 1.82 , "max_drawdown" : 0.14 , "subscribers" : 412 , "tags" : [ "long-only" , "weekly-rebalance" , "sp500-universe" ], "published_at" : "2025-11-03T10:00:00Z" }, { "model_id" : "qx-mom-global-007" , "name" : "Global Cross-Asset Momentum" , "author" : "alpha-lab" , "strategy_type" : "momentum" , "asset_class" : "multi_asset" , "sharpe_ratio" : 1.61 , "max_drawdown" : 0.18 , "subscribers" : 289 , "tags" : [ "long-short" , "monthly-rebalance" ], "published_at" : "2025-09-15T08:30:00Z" } ] }
Field Description totalTotal number of matching models results[].model_idUnique model identifier — use with get_model, subscribe_to_model, run_signal results[].sharpe_ratioAnnualized Sharpe ratio from backtests results[].max_drawdownMaximum drawdown from backtests results[].subscribersNumber of active subscribers
Example { "query" : "momentum US equities weekly rebalance" , "filters" : { "strategy_type" : "momentum" , "asset_class" : "equities" , "min_sharpe" : 1.5 , "max_drawdown" : 0.20 }, "sort_by" : "sharpe" }
Next Step Pass a model_id from the results to get_modelrun_signal 
