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.

On the usual no-ML path you do not pass a separate testing-end date here — the backtest follows the prices/weights from portfolio optimization (sample start → end, with the first covariance_window days used as PO warmup upstream).

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
    }
  }
}

Resources

Resource	Value
Container Apps Job	`trading-worker`
Container name	`trading-worker`
Env vars injected	`INPUT_URL`, `CONFIG`
Output blob prefix	`trading_report_`

Next Steps

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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