Market Tide

Family: Flow surveillance

What it computes

Emits MarketTideTick ticks carrying net_prem, net_call, net_put, advancing_count, declining_count off subscribed-universe option trades.

Available on the live, historical, and replay drives.

Methodology

Universe-wide aggregate tape-aggregator (SpotGamma Market Tide, FlowAlgo Tape, CBOE OMON Composite).

See the methodology overview for the citation index.

Inputs

Subscribed-universe option trades.

Key outputs

Net_prem, net_call, net_put, advancing_count, declining_count. The full field set is in the tick table below.

Output schema (MarketTideTick)

The field / type / description table below is regenerated from the MarketTideTick 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.
net_prem	f64	Universe-wide Σ(call_prem) − Σ(put_prem) (USD).
net_call	f64	Universe-wide cumulative call-side premium (USD).
net_put	f64	Universe-wide cumulative put-side premium (USD).
advancing_count	u32	Symbols whose per-symbol balance is currently > 0.
declining_count	u32	Symbols whose per-symbol balance is currently < 0.

Configuration (MarketTideParams)

Regenerated from the MarketTideParams 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 tide 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().market_tide([]).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()
  .marketTide([])
  .forIndex("SPX")
  .onEvent((tick) => {
    console.log(tick);
  });

Rust

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

use kairos::{Client, MarketTideRow};

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

let sub = client
    .live()
    .market_tide(["SPX"])
    .on_event(|row: &MarketTideRow| println!("net_prem={}", row.net_prem))?;

// ... later, to stop delivery ...
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.