Accurate and precise market data for AI-driven financial models
Use case for machine learning
Your challenge
The success of ML models heavily relies on the quality and accessibility of historical financial data.
The success of trading algorithms depends first and foremost on overcoming data challenges. Machine learning requires clean, normalized historical data showing relationships across assets, exchanges, and time periods. Data flaws like survivorship bias or inconsistent taxonomies produce misleading predictions. The advantage in today's algorithmic markets goes to models supported by reliable data infrastructure.
Developer challenges:
Poor data quality leading to unreliable models
Survivorship bias
Inconsistent data formats
Temporal mismatches
Incomplete features
Limited historical data for rare events
What you can achieve with FinFeedAPI
Products used
Complete, Unfiltered Market Data
- Get access to 100% of exchange-distributed messages without gaps
- Eliminate selection bias through comprehensive data inclusion
- See all market events including halts, auctions, and system-wide actions
Nanosecond-Precision Timestamps
- Sequence events for cause-effect analysis
- Measure latency precisely for execution modeling
- Analyze price reaction to various order sizes and types
- Develop optimal execution strategies based on historical market impact
Feature Engineering from Raw Data
- Extract meaningful features from complete order flow
- Enable custom technical indicators based on full market depth
- Get data for derived signals from administrative messages and event sequences
Price Movement Prediction
- Train models on complete order book states to predict short-term price movements
- Develop pattern recognition algorithms based on unfiltered market events
- Identify predictive signals from trade condition flags and execution properties
Anomaly Detection and Risk Management
- Train models to identify unusual market conditions or potential risks
- Develop early warning systems for liquidity crises or volatility events
- Create classification models for different market regime states