Arms Index TRIN

Family: Flow surveillance

What it computes

Emits ArmsIndexTrinTick ticks carrying advances, declines, up_volume, down_volume, trin off subscribed-universe option trades.

Available on the live, historical, and replay drives.

Methodology

Arms (1967) Trading Index (advances / declines) / (up_volume / down_volume) across the matched-cohort universe.

See the methodology overview for the citation index.

Inputs

Subscribed-universe option trades.

Key outputs

Advances, declines, up_volume, down_volume, trin. The full field set is in the tick table below.

Output schema (ArmsIndexTrinTick)

The field / type / description table below is regenerated from the ArmsIndexTrinTick Rust source by docs-site/scripts/inject-doc-tables.ts on every npm run docs:build. Do not hand-edit between the sentinels.

Field	Type	Description
date	i32	Trading-session date (YYYYMMDD).
ts_ms	i32	Milliseconds since midnight at emission time.
advances	u32	Symbols whose session balance is currently > 0.
declines	u32	Symbols whose session balance is currently < 0.
up_volume	f64	Cumulative call premium across the advancing cohort (USD).
down_volume	f64	Cumulative put premium across the declining cohort (USD).
trin	f64	Arms TRIN: (advances / declines) / (up_volume / down_volume). NAN when either ratio is undefined; INFINITY when only the volume denominator collapses.

Configuration (ArmsIndexTrinParams)

Regenerated from the ArmsIndexTrinParams Rust source — see the note above.

Field	Type	Description
contracts	SecurityFilter	Contracts the subscription tracks. The institutional idiom is to subscribe by underlying symbol — the engine fans out across the chain and the TRIN aggregates by symbol.
conditions	ConditionPolicy	Trade-condition admission policy.
venues	ExchangeFilter	Exchange / venue admission policy.
min_emit_interval_ms	i32	Minimum interval between universe emissions (milliseconds).

Example

Python

import kairos_thetadata as kt

client = kt.Client.connect(kt.Credentials.from_env())

def on_emission(tick):
    print(tick)

sub = client.live().arms_index_trin([]).for_index("SPX").on_event(on_emission)
sub.wait(timeout_seconds=60.0)

TypeScript

import { Client, Credentials } from "kairos-thetadata";

const client = await Client.connect(Credentials.fromEnv());
await client
  .live()
  .armsIndexTrin([])
  .forIndex("SPX")
  .onEvent((tick) => {
    console.log(tick);
  });

Rust

// Cargo.toml:
//   kairos = "0.1"

use kairos::{Client, ArmsIndexTrinRow};

# fn run() -> Result<(), Box<dyn std::error::Error>> {
let client = Client::connect(("me@example.com", "secret"))?;

let sub = client
    .live()
    .arms_index_trin(["SPX"])
    .on_event(|row: &ArmsIndexTrinRow| {
        println!("trin={} advances={}", row.trin, row.advances)
    })?;
// ... later ...
sub.unsubscribe();
# Ok(())
# }

for_index / for_sector are Python / TypeScript SDK conveniences. On the Rust thin client, pass the constituent universe to the analytic accessor (client.live().<analytic>([...])) — the engine drives the same per-symbol fan-out.