dynamics / white-paper

1. Abstract

Dynamics is a framework for observing motion within data ecosystems. It models equilibrium, inertia, and drift across market-like streams, deriving interpretable matrices and auxiliary signals that describe change as a first-class object.

The system organizes measurements into composable layers — matrices (state), strategy_aux (intent), and mea_aux (observation) — unified by a routing core and a disciplined data schema.

Tagline: “Measure motion, then design with it.”

2. Core Framework

  • Matrices: tabular fields of relations (benchmark, delta) over a selected coin universe, exposed via /api/matrices/latest.
  • strategy_aux: persistence of hypotheses, playbooks, tiers, flags, and shift stamps.
  • mea_aux: measurements and checkpoints, retrospective fetch, autosave hooks.
  • Routing “Golgi”: an index that maps features to locations and associates functional enzymes (wires) to routes.

Endpoint Example

ts
// GET /api/matrices/latest
{
  "ok": true,
  "coins": ["BTC","ETH","BNB","SOL","ADA","USDT","XRP","XPL"],
  "symbols": ["BTCUSDT","ETHUSDT","BNBUSDT","SOLUSDT","ADAUSDT","USDTUSDT","XRPUSDT","XPLUSDT"],
  "window": "30m",
  "ts": 1759196895525,
  "matrices": {
    "benchmark": { "ts": 1759196895525, "values": { "BTC": {"BTC":1, "ETH":0.98, "...":"..." } } },
    "delta":     { "ts": 1759196895525, "values": { "BTC": {"BTC":0, "ETH":-0.012, "...":"..." } } }
  }
}

Client Hook Sketch

ts
// useLatestMatrices.ts
import { useEffect, useState } from "react";

export function useLatestMatrices(coinUniverse: string[]) {
  const [data, setData] = useState<any>(null);
  const [loading, setLoading] = useState(true);
  useEffect(() => {
    const params = new URLSearchParams({ coins: coinUniverse.join(",") });
    fetch("/api/matrices/latest?" + params.toString())
      .then(r => r.json())
      .then(setData)
      .finally(() => setLoading(false));
  }, [coinUniverse]);
  return { data, loading };
}

3. Gravitational Model (IdHR)

The gravitational mode projects price-action into an elliptic space built over segmented ranges (IdHR). Densities become potential wells; transitions become inertial vectors (vInner, vOuter).

Elliptic density sketch

density levels (IdHR ellipses)vector drift (vInner -> vOuter)

Mathematical Note

tex
\textbf{Inertia: } \mathbf{I} = \sum_{b \in B} w_b\, (\mathbf{c}_b - \bar{\mathbf{c}}) \\
\textbf{Delta: } \Delta_{i,j} = \frac{P_i}{P_j} - 1 \\
\textbf{Benchmark: } \beta_i = \mathrm{median}_{j \in U} \left( \frac{P_i}{P_j} \right)

Interpretation

  • Ellipses ≈ constant density levels across IdHR bins.
  • Vector tails start at current centroid; heads point to drift.
  • Neutral cells appear yellow in heatmaps; freeze flags in purple.

4. System Schema & Pipelines

Schemas separate concerns while staying query-friendly (PostgreSQL): public, strategy_aux, mea_aux.

DDL Sketch

sql
-- schema: strategy_aux
create table if not exists strategy_aux.shift_flags (
  id bigserial primary key,
  symbol text not null,
  tier text not null,
  shift_ts timestamptz not null default now(),
  swap_tag text,
  meta jsonb default '{}'
);

-- schema: mea_aux
create table if not exists mea_aux.checkpoints (
  id bigserial primary key,
  scope text not null,        -- e.g. "matrices/latest"
  coins text[] not null,
  payload jsonb not null,
  created_at timestamptz not null default now()
);

Autosave & Retrospective

  • Autosave on material changes in matrices window.
  • Retrospective fetch for backfills / regression runs.
  • Hooks: beforePersist, afterPersist, onShift.

5. Methodology & Experimentation

  1. Observation: capture states into matrices.
  2. Calibration: tune tiers, thresholds, epsilon for shift detection.
  3. Validation: backtest with retrospective fetch; store checkpoints.
  4. Iteration: promote “lab” artifacts into main routes after scrutiny.

Shift Detection (pseudo)

ts
const SHIFT_EPS = 0.015; // 1.5%
function detectShift(prev: number, curr: number) {
  const d = (curr - prev) / Math.max(Math.abs(prev), 1e-9);
  return Math.abs(d) >= SHIFT_EPS ? { ok: true, delta: d } : { ok: false, delta: d };
}

Benchmark / Delta Notes

md
- Benchmark uses robust center (median) across the selected universe U.
- Delta is relational (pairwise), enabling heatmaps w/ neutral bands.
- Persistence ensures reproducibility of visual states.

6. Epilogue & Vision

Dynamics evolves toward a living atlas of motion — interfaces that don’t just display markets, but converse with them. Upcoming: interactive matrix, strategy notebooks, and cross-project bridges (Haus, Harues, Rep.Isl).

Roadmap seeds: interactive heatmaps, autosave w/ diffs, tier visualizers.