Quant Metrics

quant_metrics is a fixed object of nine risk and performance numbers for one trader. Request it when grade is not enough and you must compare skill or copyability.

Request the object

quant_metrics is an expanded field. It appears on GET /api/v1/trader/{address} and POST /api/v1/traders/batch.

curl -H "Authorization: Bearer $OXINSIDER_API_KEY" \
  "https://api.0xinsider.com/api/v1/trader/swisstony?expand=quant_metrics"

curl -H "Authorization: Bearer $OXINSIDER_API_KEY" \
  -X POST "https://api.0xinsider.com/api/v1/traders/batch" \
  -H "Content-Type: application/json" \
  -d '{"traders": ["swisstony", "0x204f72f35326db932158cba6adff0b9a1da95e14"], "expand": ["quant_metrics"]}'

The object is present only when a computed row under six hours old exists.
A row six hours old or older is omitted. Treat an absent object as not computed.
When the object is present, all nine keys are present. Each value is a number or null.
null means insufficient trade history. Do not convert it to 0.

Read the two headline scores

Both scores run from 0 to 100. Higher is better.

smart_score measures skill against every other trader, risk-adjusted.
copy_score measures how safe the trader is to follow.

smart_score = clamp(0, 100,
    30 * sharpe_percentile / 100
  + 20 * pf_percentile / 100
  + 20 * consistency_percentile / 100
  + 10 * min(1, return_on_capital / 2)
  + 10 * equity_smoothness
  + 10 * (1 - min(1, asset_concentration)))

copy_score starts from the same base and subtracts penalties, then clamps to 0 to 100:

Penalty	Condition
-20	Fewer than 50 markets traded
-15	Positions are highly concentrated
-15	Position size exceeds about 2x Kelly
-10	Worst single-trade loss exceeds 30 percent
-10	Edge is inconsistent

A trader can have a high smart_score and a lower copy_score. Compare skill with smart_score. Choose traders to follow with copy_score.

Read the component metrics

These values are absolute, not ranks.

Field	Meaning
`sharpe_30d`	Sharpe ratio over the last 30 days. Higher is better. A small sample can produce a large magnitude.
`sharpe_7d`	Sharpe ratio over the last 7 days.
`profit_factor`	Gross profit divided by gross loss. Above 1 is profitable. Capped at 1000 when losses are near zero.
`edge_consistency`	Stability of the edge over time, 0 to 1. Higher is more consistent.

Read the percentile ranks

These values place the trader against all traders, 0 to 100.

Field	Meaning
`sharpe_percentile`	Percentile of the Sharpe ratio
`pf_percentile`	Percentile of the profit factor
`consistency_percentile`	Percentile of edge consistency

A percentile moves when the population moves, even if the trader does not trade.

Read the response

{
  "object": "trader",
  "data": {
    "id": "trd_0x204f72f35326db932158cba6adff0b9a1da95e14",
    "username": "swisstony",
    "grade": "S",
    "quant_metrics": {
      "smart_score": 84.2,
      "copy_score": 74.2,
      "sharpe_30d": 2.13,
      "sharpe_7d": 3.44,
      "profit_factor": 4.1,
      "edge_consistency": 0.62,
      "sharpe_percentile": 97.4,
      "pf_percentile": 88.9,
      "consistency_percentile": 91.0
    }
  }
}

Signal scoring names every score the API exposes.
Grades explains the S to F letter above these metrics.
Trust metadata reports the provenance of quant_metrics with expand=trust.

Getting Started

Guides

Concepts

Request the object

Read the two headline scores

Read the component metrics

Read the percentile ranks

Read the response

​Request the object

​Read the two headline scores

​Read the component metrics

​Read the percentile ranks

​Read the response

​Related

Request the object

Read the two headline scores

Read the component metrics

Read the percentile ranks

Read the response

Related