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Forex Tick Data QC (Daily Files): Audit-Grade Validation for Accurate Backtests

Sep 26, 2025 · 5 min read
Forex Tick Data QC (Daily Files): Audit-Grade Validation for Accurate Backtests

Summary

Audit-grade Forex tick data quality checks on daily files: deduplication, strict time ordering, weekend filtering, gap thresholds, spread caps, outlier control, and UTC-aligned outputs for reliable backtests and AI/SMC research.

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Looking for clean, trustworthy Forex tick data delivered as daily files? Our audit-grade Tick Data Quality Control (QC) pipeline validates every day of ticks so your backtests, AI/SMC research, and execution models rely on consistent, UTC-aligned, noise-reduced inputs. We remove duplicates, enforce strict chronological ordering, cap unrealistic spreads, filter weekend ticks, and flag abnormal price jumps—then hand back deterministic, analysis-ready files (CSV/Parquet) with a full QC report.

Why daily files (and QC) matter

  • Stable ingestion pipelines: Daily granularity keeps S3/object-storage prefixes, data lakes, and CI jobs simple and predictable.
  • Deterministic results: Identical inputs → identical outputs. Crucial for auditability, research reproducibility, and model governance.
  • Lower noise, better signals: Deduplication, UTC normalization, and outlier/spread controls reduce backtest drift and label leakage.
  • Partitioning & cost control: Day-by-day files compress well (Parquet) and keep query scopes tight for Python/R/SQL workflows.
  • Multi-source merges: Clean, UTC-aligned ticks simplify venue aggregation and downstream OHLCV bar generation.

What our Tick Data QC does

  • Deduplication & strict ordering: Removes duplicate prints and sorts by timestamp with stable tie-breakers (nanosecond-safe), yielding a canonical tick sequence.
  • Weekend-tick filtering: Excludes off-session/invalid prints that distort indicators and bar builders.
  • Gap detection & quantification: Flags missing intervals, provides per-day gap stats, and highlights material coverage risks.
  • Spread thresholds: Caps unrealistic spreads with symbol-aware policies (e.g., EURUSD vs XAUUSD vs USDJPY) and optional venue conditions.
  • Outlier control: Detects and marks extreme price jumps (configurable z-score/percent) for transparent filtering or review.
  • UTC alignment: Normalizes all timestamps to UTC to avoid DST drift and to enable reproducible intraday research.
  • Integrity artifacts: SHA-256 checksums, per-file manifests, QC summaries, and optional lineage metadata.

Deliverables (US-oriented, research-ready)

  • Validated daily tick files in CSV or Parquet, compressed and partitioned by YYYY/MM/DD.
  • Deterministic M1–D1 bars (optional): Stable OHLCV rules with explicit session filters and reproducible rounding.
  • QC report & manifest: Counts for duplicates removed, weekend ticks filtered, gap statistics, spread-cap hits, and outlier flags, plus checksums.
  • Data dictionary & usage notes: Column definitions, timestamp policy, spread/outlier thresholds, symbol caveats.

Key metrics (example)

Metric Value Notes
Duplicates removed 2,341 Daily sum, per symbol (example)
Weekend ticks filtered 1,109 Example figure
Largest gap 47s 08:12:14 → 08:13:01 UTC (example)
Spread caps applied 0.35% Of ticks (policy-dependent)
Outliers flagged (reviewed) 0.08% Post-review share (example)

Who uses this

  • US prop firms & quant desks: consistent tick streams for intraday alpha, slippage studies, and execution testing.
  • HFT/low-latency researchers: deterministic preprocessing to validate market microstructure hypotheses.
  • AI/SMC modelers: clean tick inputs for LSTM/Transformer pipelines and Smart Money Concepts feature engineering.

Our process

  1. Intake: share raw tick archives or provide S3/HTTPS/SFTP access (we can sign NDAs).
  2. QC policy setup: confirm spread caps, outlier rules, weekend/session policy, and symbol-specific nuances.
  3. Validation run: day-by-day pass with full logs, metrics, and data integrity checks.
  4. Delivery: CSV/Parquet daily files + optional deterministic M1–D1 bars + QC reports + manifests.

Why us

  • Deterministic by design: audit-grade, repeatable outputs suitable for compliance and peer review.
  • Performance-first: optimized pipelines to handle large multi-year archives quickly.
  • Domain focus: Forex-specific details handled correctly (UTC, weekend/session rules, symbol-aware spread logic).

SEO keywords we actually cover

forex tick data quality, tick data validation, daily tick files, forex tick data cleaning, deterministic bar generation, UTC aligned OHLCV, backtesting accuracy, spread thresholds, gap detection, duplicate removal, weekend tick filtering, price outlier control, CSV Parquet forex datasets, quant research data, prop trading tick data, intraday execution testing, AI SMC features, EURUSD GBPUSD USDJPY XAUUSD tick data.

FAQs (for long-tail searches)

Do you support multiple symbols and venues?

Yes—multi-symbol (e.g., EURUSD, GBPUSD, USDJPY, XAUUSD) with symbol-aware spread/outlier policies and optional venue tags for aggregation.

How do you handle DST and time zones?

All timestamps are normalized to UTC; no local/DST ambiguity. This is essential for reproducible intraday research and cross-venue merges.

What’s the difference between raw ticks and deterministic bars?

Ticks are the atomic prints (bid/ask, trade). Deterministic bars apply explicit, documented rules to produce stable OHLCV series (M1–D1) from the validated ticks.

Can I re-run the pipeline and get bit-for-bit identical outputs?

Yes. With unchanged inputs and policies, outputs are deterministic and come with checksums/manifests for audit trails.

How big are the files and how are they delivered?

Daily Parquet partitions are typically much smaller than CSV. Delivery is via S3/HTTPS/SFTP with optional client-side encryption.

Try it with your data

Send a sample day and we’ll return a validated daily file, QC report, and—optionally—deterministic bars. See how cleaner inputs stabilize your backtests and models.

Learn more about Tick Data QC