Synthetic Data
Synthetic data sets, created to represent similarities to crucial information of the actual data, are useful means to get access to additional data. Synthetic data does not represent actual events in the real world, but has been artificially created using real data. It contains the same statistical properties, which indicates that performing an analysis on the synthetic data would give similar results to performing the analysis on the real data.
What is Synthetic Data?
How can Synthetic Data be used?
In financial markets, using synthetic data can be helpful for building models to enhance trading decisions and for testing software and machine learning algorithms. Another benefit is to use synthetic data to expand small datasets in order to provide robustness. This approach helps mitigate overfitting risks and allows for extensive testing across various market regimes, ensuring more robust and reliable trading systems.
Our services
What can we offer you?
We can create high level synthetic financial timeseries data, tailored for a specific market and timeframe. For example, 15-minute data of the S&P 500 index.
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Reach out to us if you have any more questions or have specific needs. We're here to help!