Tick-level
Every book event in the window, per symbol
The microstructure of every tick we capture.
AXIOMA Analytics reads the production aggregate DOM feed and turns it into tick-level analytics. For any instrument on the desk it shows how price moved, how liquidity was posted and taken, how spreads behaved and how volatile the tape was — computed from every quote update in the window, not from a daily close.
9 classes
FX, metals, energy, indices, crypto, bonds, futures
10 blocks
Summary, OHLCV, liquidity, distribution, behaviour
Every 45 min
Pipeline writes fresh tick metrics on this cadence
How it works
AXIOMA is not a price display. It is an analytics engine that reads the raw feed the trading pipeline already writes, classifies each instrument by its own asset class, and computes a full microstructure report on demand.
1. Read the feed
Every aggregate DOM row for the selected symbol and window is loaded — best bid, best ask, resting sizes on each side, the pipeline's own imbalance and the derived mid. One-sided and crossed books are dropped so no panel is drawn from a quote that cannot exist.
2. Classify
Instruments are grouped by asset class using the pipeline's own classification chain, subdivided for FX, with a fallback to the symbol signals so nothing silently disappears from the picker.
3. Compute & chart
The analytics layer resamples bars, builds the order-flow, spread, depth, volume-profile, distribution, price-change and return-behaviour series, and streams them to the browser as clean JSON.
What it measures
Ten analytic blocks, all computed from the tick window you select. Change the symbol, timeframe, rolling window or look-back and every panel recomputes together.
Summary & OHLCV
- ticks, open/high/low/close, net change
- realised and annualised volatility, spread statistics
- ticks per minute and tick inter-arrival
- resampled bars from 1 s to 1 d with VWAP, per-bar spread and tick count
Order flow & spread
- order-flow imbalance (signed volume by tick direction)
- bid-ask spread evolution in basis points
- large trades and their one-tick market impact
Liquidity
- volume-at-price profile with POC and the 70% value area
- high-volume nodes
- book depth: resting size per side and depth imbalance
- activity by hour of day (display time zone)
Distribution & risk
- return histogram, skew and excess kurtosis
- Jarque-Bera normality test and bullish ratio
- price change from a fixed reference point, with the window's high and low
Price behaviour
- autocorrelation of returns
- efficiency ratio and Hurst exponent
- variance ratios
- rolling volatility, rolling spread and cumulative return
Coverage & calendar
- instrument coverage per asset class
- a data calendar sizing each day by tick count
- the latest-tick timestamp and freshness, so a stale window is obvious
Where the numbers come from
Two production sources on the analytics estate, and nothing else. There is no synthetic or demo data, and the storage internals are never sent to the browser.
The rows
Per-tick order-book metrics from the production eventhouse: one derived row per symbol and tick — top-of-book quotes, aggregate resting size and the spread/imbalance measures — computed from a full order-book reconstruction, not sampled as point-in-time snapshots.
The instruments
The instrument dimension supplies tickers, descriptions and the asset-class chain, so the UI shows XAUUSD, EURUSD or BTCUSD rather than raw numeric ids.
Freshness
The pipeline writes derived tick metrics on a fixed cadence. Every screen states when the newest tick landed and when the next refresh is due, so you always know how current the view is.
Explore it yourself
Pick an asset class, choose a symbol, set the window and read the panels. The dashboard runs live against the production feed.