run_trading_job

Overview

run_trading_job runs a VectorBT backtest from portfolio weights (Portfolio.from_orders, TargetPercent) and returns performance metrics (return, Sharpe, drawdown, …). Usually the last step of the core path after run_po_job.

Parameters

string

required

Blob storage URL pointing to a portfolio_optimization_*.json file.This is the output_url returned by run_po_job. The blob must contain Weights (and prices). Signal-based Entries / Exits are not used.

object

required

Trading and backtesting configuration.

Show config fields

object

required

Backtest execution settings.

Show Trading params fields

number

Initial portfolio cash in USD. Default: 1000000.

string

Pandas frequency for the backtest. Use "D" (daily). Default: "D".

integer

Round-trip transaction cost in integer basis points (bps), not a fraction. Example: 5 = 5 bps = 0.05%. Default: 0.

integer

Slippage in integer basis points. Example: 2 = 2 bps. Default: 0.

number

Annual risk-free rate used for Sharpe/Sortino. Default: 0.02.

object

Optional window for the backtest itself.

Show Backtest params fields

string

YYYY-MM-DD. The backtest starts on the next business day after this date. Omit it to start from the first date in the portfolio weights.

string

YYYY-MM-DD. The backtest ends on this date. Omit it to use all available data.

Leave Backtest params out and the backtest simply follows the prices and weights that portfolio optimization produced. Set it when you want to cut the window further — for example to test a specific period without rerunning the optimization.

Returns

{
  "status": "Succeeded",
  "output_url": "https://stqsnpprod.blob.core.windows.net/data/trading_report_b1218bfd0544.json",
  "output_name": "trading_report_b1218bfd0544.json",
  "execution_name": "trading-worker-abc123xyz"
}

Field	Description
`status`	Job terminal status (`Succeeded`)
`output_url`	Full HTTPS URL to the backtest results blob
`output_name`	Blob filename
`execution_name`	Job execution ID for audit/debugging

The trading_report_*.json blob contains VectorBT performance metrics: total return, Sharpe ratio, max drawdown, win rate, and related statistics.

Example

{
  "input_url": "https://stqsnpprod.blob.core.windows.net/data/portfolio_optimization_35c1b5239d23.json",
  "config": {
    "Trading params": {
      "initial_capital$": 1000000,
      "frequency": "D",
      "trade_comission": 5,
      "slippage_bps": 2,
      "risk_free_rate": 0.02
    }
  }
}

Next Step

This is the last step of the core pipeline. Download the blob from output_url to inspect the results. You can also run optional analytics from portfolio_optimization_*.json (or, for some tools, from data_extractor_*.json with optional weights):

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