Institutional crypto data research
The evidence layer
for crypto markets.
Microstructure research for desks that underwrite digital-asset risk with evidence, not narrative.
- Focus
- Order-book microstructure
- Instruments
- Spot · Perpetuals · Options
- Standard
- Versioned & reproducible
02clocks
Exchange and receive time stored for every event
05stages
From raw venue feed to delivered, defended dataset
04domains
Research coverage areas that institutions underwrite
100%
Of releases versioned with lineage and QA scorecards
Markets
Live market
terminal.
Streaming prices, full-depth order books, and executed trades for the three most liquid crypto assets, sourced directly from Kraken’s public market data feed.
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- 24h VWAP
- —
- 24h volume
- —
- 24h range
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- High vs low, intraday
- Top-10 imbalance
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Market data: Kraken public WebSocket v2 & REST API. Charting by TradingView Lightweight Charts™. Informational only, not investment advice.
Global markets
Markets never close. Neither does the evidence.
24 / 7 / 365
Crypto markets never close. Our capture and QA run continuously.
Event-level
Every book update and trade stored with exchange and receive time.
Reproducible
Each published figure traceable from raw venue event to result.
Research & insights
Research that
moves desks.
Research notes, explainers, and methodology papers on the structure of digital-asset markets, with figures computed from live market data.
View all research
Data products
Institutional
data catalog.
Versioned datasets with lineage, QA scorecards, and documentation attached to every release. Hover a dataset to preview a sample.
| Dataset | Description | Granularity | Delivery | Tier | Action |
|---|---|---|---|---|---|
| LT.L2Normalized order books | Full-depth L2 snapshots and incremental updates, reconciled to one venue ontology. | Event-level | ParquetS3SFTP | Enterprise | Request more sample |
| LT.TRDTrades & aggressor flags | Every print with inferred aggressor side, outlier triage, and dual timestamps. | Tick | ParquetREST | Professional | Request more sample |
| LT.BAROHLCV bars | Consistent bars built from validated trades, not venue-reported candles. | 1s – 1d | CSVParquetREST | Research | Request more sample |
| LT.LIQLiquidity & slippage metrics | Depth at basis-point bands, spread distributions, and modelled impact curves. | 1 min | ParquetREST | Professional | Request more sample |
| LT.DRVFunding & basis surfaces | Perpetual funding, dated-futures basis, and open-interest context across venues. | 1 min / 8 h | ParquetS3 | Enterprise | Request more sample |
| LT.QAFeed quality diagnostics | Sequence gaps, clock skew envelopes, and per-release QA scorecards. | Per release | ScorecardParquet | Included | Request more sample |
Access & pricing
Start free. Scale when your research does.
Research
Analysts, students, and early-stage funds
Free
No card required · free forever
- OHLCV bars and reference data
- Research notes library
- Live market terminal
- Quarterly methodology updates
Professional
Quant teams and discretionary desks
$29/ month
Billed monthly · or $264/year (save 24%)
- Everything in Research
- Tick trades with aggressor flags
- Liquidity & slippage metrics
- REST API access with history
- Analyst support on methodology
Enterprise
Market makers, exchanges, and allocators
$49/ month
Billed monthly · or $447/year (save 24%)
- Everything in Professional
- Full-depth normalized order books
- Funding & basis surfaces
- Bulk delivery to S3 or SFTP
- Priority research desk access
Prices in USD, excluding applicable taxes. Cancel anytime.
Research coverage
Where we apply pressure.
Coverage is organized around the questions institutions actually underwrite, not vanity dashboards. Each domain maps to schemas, QA gates, and research notes with explicit assumptions.
Order-book dynamics
L1/L2Depth imbalance, queue dynamics, quote lifetime, and replenishment behavior across continuous and event clocks.
- Top-of-book resilience
- Hidden liquidity proxies
- Cross-venue depth alignment
Trade & mark quality
TRDPrint classification, aggressor inference, and mark integrity under fragmented matching and delayed settlement semantics.
- Aggressive vs passive flow
- Mark staleness bounds
- Outlier trade triage
Latency topology
LATReceive-path characterization, venue-relative delay surfaces, and reconstruction confidence under clock drift.
- Feed continuity maps
- Skew envelopes
- Gap attribution
Structural risk signals
RSKRegime-aware liquidity fragility, basis stress, and funding/inventory feedback loops that matter to risk desks.
- Liquidity cliffs
- Basis dislocation
- Inventory feedback
Research pipeline
From feed to
defended feature.
The pipeline is the product. We do not hand over unexplained columns. We hand over a reproducible path from venue event to analytical object, with failure modes labeled rather than hidden.
dataset: l2.btc_perp.v3
lineage:
venues: [binance, bybit, okx]
clocks: [exchange_ts, recv_ts]
qa:
gap_rate: monitored
crossed_book: blocked
confidence: surfaced
delivery: parquet + research note- 01
Ingest
Venue feeds captured with dual clocks, sequence metadata, and instrument identity preserved before any normalization.
- 02
Normalize
Tick rules, symbol maps, and book event semantics reconciled into a venue ontology designed for cross-market research.
- 03
Validate
Integrity gates for crossed books, stale quotes, sequence breaks, and anomalous depth before any feature generation.
- 04
Reconstruct
Order-book state rebuilt with explicit confidence bounds. Event time and receive time are separate research axes.
- 05
Deliver
Versioned datasets and notes shipped with lineage, transforms, and QA summaries desks can defend under scrutiny.
Technology
Methodology
over mythology.
Four controls we apply before any signal is considered institutional-ready. Select a layer to inspect how it works.
Layer 01 / 04
Normalized venue ontology
Unified schemas across spot, perpetual, and options venues—timestamps, tick rules, and instrument identity treated as research objects.
- 1Canonical instrument IDs across venues and contract generations
- 2Explicit tick-size and lot-size versioning by calendar epoch
- 3Book event taxonomy that survives venue-specific quirks
instrument: symbol: BTC-USDT-PERP venue: bybit tick: 0.10 epoch: 2024-05-01 map_id: lt.inst.btc_perp.042
Who we serve
Built for institutional mandates.
- Independence
- Methods and conclusions are set by the research desk, not by the venues we measure.
- Transparency
- Methods, assumptions, and known limits published with every release.
- Reproducibility
- Every figure traceable from raw venue event to published number.
Hedge funds & prop desks
Alpha research on clean, reproducible microstructure data with defensible lineage.
Market makers
Venue-level liquidity, latency, and adverse-selection analytics for quoting decisions.
Asset managers & allocators
Execution cost benchmarks and liquidity risk evidence for digital-asset mandates.
Exchanges & infrastructure
Independent market-quality measurement across competing venues.
Risk & compliance
Surveillance-grade trade and book records with documented integrity checks.
Academic research
Versioned datasets and methodology papers suitable for peer-reviewed work.
Who we are
Ladder Trader makes fragmented crypto venues measurable with the rigor of traditional electronic markets, so allocators can reason about liquidity, latency, and structural risk without opaque intermediaries.
Vision
Become the research substrate institutions trust when the question is not “what happened on crypto Twitter,” but “what did the book actually do.”
Mission
Deliver datasets, notes, and analytical frameworks that convert raw market microstructure into decision-ready signal for desks, funds, market makers, and builders.
Built for the questions institutions actually underwrite.
Primary facts first
Venue events, book state, and execution marks precede interpretation. Narrative is a derivative product, never the input.
Reproducibility as product
Every transform is versioned, deterministic, and auditable. If a desk cannot replay the path from raw feed to feature, it is not research-grade.
Uncertainty made explicit
Clock skew, sequence gaps, and reconstruction confidence are surfaced as first-class fields, not smoothed away for convenience.
Horizon over hype
We optimize for compounding institutional trust: coverage that deepens, schemas that stabilize, and methods that survive regime change.
Contact
Engage the research desk.
Tell us the mandate, venues, horizon, and constraints. We reply with coverage fit, a recommended pathway, and what we can (and cannot) defend methodologically.
- 01
Research brief
Scoped note on a venue, instrument class, or microstructure question—assumptions and limits included.
- 02
Dataset pilot
Time-bounded sample of a versioned book or trade dataset with QA scorecard and lineage attached.
- 03
Desk partnership
Ongoing coverage, custom transforms, and methodology review for teams integrating Ladder Trader into production research.