Download 360 DBN files (36.3 MB) using Rust databento client
- Created data/examples/download_ml_training_data.rs using reqwest + Databento HTTP API - Downloaded 90 days × 4 symbols (ES.FUT, NQ.FUT, ZN.FUT, 6E.FUT) - Files saved to test_data/real/databento/ml_training/ - Total: 360 files, 15 MB compressed DBN format - Used existing Rust pattern from download_nq_fut.rs - API key loaded from .env file - 100% success rate (360/360 files) - Ready for ML training benchmarks Next: Create simplified training benchmark for RTX 3050 Ti GPU measurements
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jgrusewski
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docs/DATA_VALIDATION_GUIDE.md
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docs/DATA_VALIDATION_GUIDE.md
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# DBN Data Quality Validation Guide
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## Overview
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Comprehensive data quality validation tools for DBN (Databento Binary) market data files. These tools ensure data quality before backtesting and catch issues early in the data acquisition pipeline.
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## Features
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- **Multi-file validation** - Validate individual symbols or all symbols at once
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- **Quality scoring (0-100)** - Automated quality assessment with ratings
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- **Anomaly detection** - Automated detection of price spikes, gaps, and corrupted data
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- **Multiple report formats** - Text, JSON, and HTML reports
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- **CI/CD integration** - Exit codes for automated validation pipelines
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- **Pre-commit hooks** - Validate new data before committing
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## Quick Start
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### Validate Single Symbol
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--symbol ES.FUT \
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--format text
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```
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### Validate All Symbols
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--all \
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--format html \
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--output validation_report.html
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```
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### CI/CD Mode (Exit on Failure)
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--all \
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--fail-on-poor-quality \
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--min-quality-score 70
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```
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## Quality Checks
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### Critical Issues (Score -20)
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- **OHLCV Violations** - Invalid price relationships (high < low, etc.)
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- **Negative Prices** - Prices below zero (data corruption)
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- **Out-of-Order Timestamps** - Chronological ordering broken
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### High Severity Issues (Score -10-15)
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- **Duplicate Timestamps** - Multiple bars at same timestamp
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### Medium Severity Issues (Score -5)
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- **Price Spikes (>10%)** - Abnormal price movements
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- **Zero Volumes (>10%)** - Excessive bars with no volume
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### Low Severity Issues (Score -2)
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- **Timestamp Gaps (>5%)** - Missing data periods
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- **Low Completeness (<80%)** - Insufficient data coverage
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## Quality Ratings
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| Score | Rating | Status | Description |
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|-------|--------|--------|-------------|
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| 90-100 | EXCELLENT | ✅ Production Ready | No critical issues, minor anomalies only |
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| 75-89 | GOOD | ✅ Production Ready | Some minor issues, acceptable for production |
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| 60-74 | ACCEPTABLE | ⚠️ Caution | Notable issues, review recommended |
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| 40-59 | POOR | ❌ Not Ready | Significant quality problems |
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| 0-39 | CRITICAL | ❌ Blocked | Critical data corruption, unusable |
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## Report Formats
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### Text Report (Console)
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```
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═══════════════════════════════════════════════════════
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DBN DATA QUALITY VALIDATION REPORT
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═══════════════════════════════════════════════════════
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Timestamp: 2025-10-13T08:31:14.367677223+00:00
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Duration: 3ms
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📊 SUMMARY
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Total Symbols: 1
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Total Files: 1
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Total Bars: 1674
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Overall Quality: 90 (EXCELLENT)
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─────────────────────────────────────────────────────
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SYMBOL: ES.FUT
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─────────────────────────────────────────────────────
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📈 Statistics:
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Bars: 1674
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Price Range: $3604.99 - $5175.00
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Avg Close: $4822.21
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...
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```
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### JSON Report (API Integration)
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```json
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{
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"timestamp": "2025-10-13T08:31:14.367677223+00:00",
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"total_symbols": 1,
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"total_bars": 1674,
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"overall_quality": {
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"score": 90,
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"rating": "EXCELLENT",
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"issues": ["294 duplicate timestamps"],
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"recommendations": ["Remove duplicate bars"]
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},
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"symbols": [...]
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}
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```
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### HTML Report (Dashboard)
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Interactive HTML dashboard with:
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- Color-coded quality scores
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- Expandable anomaly details
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- Symbol-level drill-down
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- Export-ready format
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## CI/CD Integration
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### Shell Script (Recommended)
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```bash
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./scripts/validate_data_quality.sh \
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--all \
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--min-quality 70 \
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--output validation_reports
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```
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**Exit Codes:**
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- `0` - All validations passed
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- `1` - Quality check failed
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- `2` - Validation error (no data, missing files)
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### GitHub Actions
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Workflow automatically triggers on:
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- Push to `test_data/**/*.dbn`
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- Pull requests with DBN files
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- Daily at 2 AM UTC (data degradation check)
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- Manual workflow dispatch
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```yaml
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# .github/workflows/data-quality-validation.yml
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name: DBN Data Quality Validation
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on:
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push:
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paths: ['test_data/**/*.dbn']
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pull_request:
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paths: ['test_data/**/*.dbn']
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schedule:
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- cron: '0 2 * * *'
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```
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### Pre-commit Hook
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```bash
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# Install pre-commit hook
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ln -sf ../../.githooks/pre-commit-data-validation .git/hooks/pre-commit
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# Or configure git hooks path
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git config core.hooksPath .githooks
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```
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The hook automatically:
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1. Detects changed `.dbn` files
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2. Validates affected symbols
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3. Blocks commit if quality < 60
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**Skip hook (emergency only):**
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```bash
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git commit --no-verify
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```
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## CLI Reference
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### Options
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| Option | Description | Default |
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|--------|-------------|---------|
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| `--symbol <SYMBOL>` | Validate specific symbol | - |
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| `--all` | Validate all symbols | false |
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| `--format <FORMAT>` | Output format: text, json, html | text |
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| `--output <FILE>` | Output file path | stdout |
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| `--fail-on-poor-quality` | Exit 1 if quality fails | false |
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| `--min-quality-score <N>` | Minimum score (0-100) | 70 |
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| `--verbose` | Enable verbose output | false |
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| `--data-dir <PATH>` | Test data directory | test_data/real/databento |
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### Examples
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**Quick validation:**
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- --symbol ES.FUT
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```
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**Full validation with HTML report:**
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--all \
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--format html \
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--output reports/validation_$(date +%Y%m%d).html
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```
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**Strict CI/CD mode:**
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```bash
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--all \
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--min-quality-score 80 \
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--fail-on-poor-quality
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```
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**Validate specific date range (via script):**
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```bash
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# Validate symbol with custom data directory
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cargo run -p backtesting_service --bin validate_dbn_data -- \
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--symbol ES.FUT \
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--data-dir test_data/real/databento/2024-01
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```
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## Anomaly Types
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### Price Spikes
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**Detection:** >10% price change between consecutive bars
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**Example:**
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```
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[MEDIUM] Price Spike at bar 145: 12.34% price change ($4800.00 -> $5392.00)
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```
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**Causes:**
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- Flash crash events
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- Data encoding errors
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- Market microstructure noise
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### Timestamp Gaps
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**Detection:** >2 minutes between consecutive 1-minute bars
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**Example:**
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```
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[LOW] Large Gap at bar 250: 3600 seconds (60 minutes)
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```
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**Causes:**
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- Market close/open transitions (expected)
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- Trading halts
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- Data acquisition interruptions
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### OHLCV Violations
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**Detection:** Invalid price relationships
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**Example:**
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```
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[HIGH] OHLCV Violation at bar 42: O=4822.50 H=4820.00 L=4825.00 C=4823.00
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```
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**Causes:**
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- Data corruption
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- Encoding errors
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- Incorrect parsing
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### Duplicate Timestamps
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**Detection:** Multiple bars at same timestamp
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**Example:**
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```
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[MEDIUM] Duplicate Timestamp at bar 99: Duplicate timestamp found
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```
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**Causes:**
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- Data source overlaps
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- Incorrect data merging
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- Replay buffer issues
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## Troubleshooting
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### No DBN Files Found
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**Error:**
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```
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No DBN files found in: test_data/real/databento
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```
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**Solutions:**
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1. Check data directory path: `--data-dir <path>`
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2. Verify files exist: `ls test_data/real/databento/*.dbn`
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3. Check file permissions
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### Invalid DBN Header
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**Error:**
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```
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Failed to create DBN decoder for file: ES.FUT_ohlcv-1m_2024-01-02.dbn
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Caused by: decoding error: invalid DBN header
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```
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**Solutions:**
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1. Verify file is valid DBN format: `file <filename>.dbn`
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2. Re-download corrupted file
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3. Check DBN version compatibility
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### Quality Score Below Threshold
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**Error:**
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```
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❌ VALIDATION FAILED: Quality score 65 < minimum 70
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```
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**Solutions:**
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1. Review validation report for specific issues
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2. Fix data quality problems (deduplicate, correct timestamps)
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3. Lower threshold if issues are acceptable: `--min-quality-score 60`
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## Performance
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### Benchmarks
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| Symbol | Files | Bars | Load Time | Validation Time | Total |
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|--------|-------|------|-----------|-----------------|-------|
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| ES.FUT | 1 | 1,674 | 1.3ms | 1.7ms | 3ms |
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| ESH4 | 3 | 5,022 | 3.9ms | 5.1ms | 9ms |
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| NQ.FUT | 1 | 1,674 | 1.2ms | 1.6ms | 2.8ms |
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| All | 6 | 8,370 | 6.4ms | 8.4ms | 14.8ms |
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**Target:** <10ms per file (ACHIEVED ✅)
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### Optimization Tips
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1. **Use `--release` mode** for production validation (25x faster)
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2. **Validate specific symbols** during development
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3. **Cache validation reports** in CI/CD pipelines
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4. **Parallel validation** for large symbol sets (future enhancement)
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## Best Practices
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### Development
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1. **Validate before backtesting** - Catch data issues early
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2. **Review anomalies** - Understand data quality characteristics
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3. **Track quality scores** - Monitor data degradation over time
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### Production
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1. **CI/CD integration** - Block bad data from merging
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2. **Automated monitoring** - Daily validation checks
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3. **Quality thresholds** - Enforce minimum standards (>70)
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4. **Alert on failures** - Notify team of quality issues
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### Data Acquisition
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1. **Pre-commit validation** - Check new data before commit
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2. **Multi-file validation** - Ensure consistency across dates
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3. **Cross-symbol validation** - Check price correlations (future)
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4. **Incremental validation** - Only validate changed files
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## Future Enhancements
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- [ ] Cross-symbol correlation analysis
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- [ ] Time alignment validation across symbols
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- [ ] Statistical anomaly detection (ML-based)
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- [ ] Historical quality tracking (trends)
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- [ ] Parallel validation for large datasets
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- [ ] WebAssembly build for browser validation
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- [ ] Real-time validation during data streaming
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- [ ] Automated data repair suggestions
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## Support
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**Issues:** Report validation bugs or feature requests via GitHub Issues
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**Documentation:** See `TESTING_PLAN.md` for backtesting strategy
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**Examples:** See `services/backtesting_service/examples/` for usage patterns
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---
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**Last Updated:** 2025-10-13
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**Tool Version:** 1.0.0
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**Status:** Production Ready ✅
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