Research Project • In Progress

Unified Dataset Platform
Time-Travel Safe Data

Eliminating time-travel contamination and look-ahead bias for reliable backtesting in both historical and real-time trading environments.

Contact Us About Data Integration

Vision

The foundation of reliable algorithmic trading is clean, trustworthy data. Yet most research and many production systems suffer from time-travel contamination—using future information that wouldn't have been available at the time of a trade.

Our Unified Dataset Platform ensures that every data point is tagged with its exact availability timestamp, making look-ahead bias impossible and backtests reliable. No more discovering that your "profitable" strategy was accidentally using tomorrow's data.

The Problems We Solve

Severity: High | Medium | Low

Time-Travel Contamination

High

Research uses revised data unavailable at trade time. Results look great but fail in production.

Look-Ahead Bias

High

Features with future information creep into models. Nearly impossible to detect without proper infrastructure.

Data Versioning Chaos

Medium

Revisions, updates, adjustments happen constantly. Without version control, backtest results are meaningless.

Real-Time vs Historical Mismatch

Medium

Systems tested on clean historical data fail with messy real-time streams and different latencies.

60%

of published papers have potential time-travel issues

Finding from our 110+ paper survey • This undermines field credibility and wastes millions in failed deployments

Our Approach

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Temporal Tagging

Precise timestamps for when data was published, revised, or became tradeable.

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Immutable History

Version control for market data. Never overwrite—always append.

Automated Validation

Built-in checks that flag look-ahead bias and data leakage.

Point-in-Time API

Query data exactly as it appeared at any historical moment.

Real-Time Parity

Identical pipeline for historical and live trading.

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Multi-Asset Coverage

Unified platform across equities, crypto, forex, and derivatives.

Technical Highlights

Core Infrastructure

Distributed time-series database

  • Scalable storage with microsecond-precision timestamps
  • Handles billions of data points across multiple asset classes

Data reconciliation engine

  • Automated detection of revisions, corporate actions, and adjustments

Quality scoring

  • Automated assessment of data completeness, accuracy, and timeliness

Cross-source validation

  • Compare multiple data vendors to identify errors and discrepancies

Execution Realism

Latency simulation

  • Replay historical data with realistic delays
  • Stress-test execution systems under adverse conditions

Ecosystem

Integration ready

  • Seamless connection to Alpha Factory and XAI modules

Current Status

We're building the core infrastructure with an initial focus on equity and crypto markets. The platform is designed to scale to millions of instruments with sub-second query performance.

Core architecture is complete; surrounding systems are under active development

CORE INFRASTRUCTURE

Architecture Design100% • Complete
Core Database Implementation75% • Q1 2026
Temporal Query Engine60% • Q2 2026

ECOSYSTEM & API

Data Ingestion Pipeline50% • Q2 2026
Validation Framework40% • Q2 2026
API Development30% • Q3 2026

Future Direction

Our roadmap includes expanding to additional asset classes, building a public API for researchers, and developing open standards for time-safe data representation in financial research.

If your institution cares about reproducible, time-safe financial research, this is where to engage.

Data Partnership Opportunities

We're interested in partnering with organizations to expand our coverage and validate our time-safety guarantees across diverse markets.

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Data Vendors

Integrate high-quality market data feeds

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Research Institutions

Collaborate on academic validation

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Trading Firms

Test in production environments