Tick Index

Family: Flow surveillance

What it computes

Emits TickIndexTick ticks carrying tick_index, uptick_symbols, downtick_symbols, unchanged_symbols off subscribed-universe stock trades.

Available on the live, historical, and replay drives.

Methodology

NYSE TICK-style universe-wide signed-tick aggregator over per-symbol Lee-Ready (1991) last-tick directions.

See the methodology overview for the citation index.

Inputs

Subscribed-universe stock trades.

Key outputs

Tick_index, uptick_symbols, downtick_symbols, unchanged_symbols. The full field set is in the tick table below.

Output schema (TickIndexTick)

The field / type / description table below is regenerated from the TickIndexTick 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.
tick_index	i32	Universe-wide signed-tick sum: Σ last_direction_i.
uptick_symbols	u32	Count of symbols currently sitting on an uptick (last_direction = +1).
downtick_symbols	u32	Count of symbols currently sitting on a downtick (last_direction = −1).
unchanged_symbols	u32	Count of symbols whose last classification is unresolved (last_direction = 0).

Configuration (TickIndexParams)

Regenerated from the TickIndexParams 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 stock tape and the tick index 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().tick_index([]).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()
  .tickIndex([])
  .forIndex("SPX")
  .onEvent((tick) => {
    console.log(tick);
  });

Rust

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

use kairos::{Client, TickIndexRow};

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

let sub = client
    .live()
    .tick_index(["SPX"])
    .on_event(|row: &TickIndexRow| println!("tick_index={} upticks={}", row.tick_index, row.uptick_symbols))?;
// ... 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.