Synthetic Time Series
Generator Engine
Generate hundreds of realistic synthetic data series for stress-testing your strategies, training ML models, and exploring tail risk — without overfitting to a single asset's history.
The Problem: History is a single sample path
Relying solely on historical data for backtesting leads to overfitting. You are optimizing for a specific sequence of events that will never happen again in the exact same way.
Data Scarcity
Financial history is limited. You run out of out-of-sample data quickly, making it hard to validate complex models.
Lack of Extremes
Black swan events are rare. Your strategy might never have seen a 1987 crash or 2020 pandemic in its training data.
Overfitting
Strategies often learn noise instead of signal. Synthetic data helps separate robust logic from historical quirks.
Why use Synthetic Data?
- Validate strategy robustness across thousands of alternative market scenarios.
- Train Reinforcement Learning agents on unlimited unique episodes.
- Stress test portfolios against regime changes and volatility shocks.
- Estimate tail risk (VaR, CVaR) with higher confidence.
Production Ready
The Neural Engine is fully operational and available for immediate deployment. Stop backtesting on limited historical data and start validating your edge on infinite scenarios.
Get Your License
Join now to receive pricing details and access the Neural Engine.