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Random data provider

What it is¶

This provider can quickly create large DataSets with randomized historical data for blind testing purposes.

Hopefully, it will help you fight over-optimization and design better trading systems without curve-fitting.

Creating a random DataSet¶

Creating a new DataSet containing random data is straightforward:


First, you need to specify a prefix which will be used to create required number of random symbols in conjunction with the counter. On the right, there's a preview area. For example, if you enter "TEST" as the prefix and request the provider to create 1000 symbols, it will show that the symbols "TEST0" to "TEST999" are going to be created.

1-minite and Daily data are supported: you can select a data scale from the drop down list. For 1-minute scale, custom market hours can be specified. Finally, the Starting Date field controls how deep your "historical" data will be.

Under the hood¶

Under the hood, the provider implements two different engines of synthetic data creation:

• RandomWalk Generator based on power-law distribution by tmh13. The original ChartScript could be configured for a market bias (i.e. bull, bear or neutral market) whereas the Random provider makes this choice, well, randomly.
• johnjan's simple random data generator described here: Radom Data Adapter and random data.
  

It's impossible to know beforehand which method will be used - method will be picked randomly for each symbol. Furthermore, refreshing a symbol's data doesn't keep the random engine preference.

Like in real life, synthetic prices can not go below zero: when the price gets "close enough", the Random provider will make its best to not allow the market to lose its value, usually by forming a basing period or doing a "V" reversal.

Further reading¶

• A theory of power-law distributions in financial market fluctuations - PDF, 184Kb
  

Known issues¶

• Currently, updating all data by this provider ("Update all data...") has a bug: if you try to update all data when there are several DataSets containing both minute and daily data for new symbols (i.e. the ones having no historical data yet), the operation will not succeed or will deliver data in an incorrect bar scale.
  • Workaround: after creation of Random DataSets containing both minute and daily data, update each DataSet individually to create the historical data. Subsequently you can safely use the "Update all data..." option.
• Bar data editing fails for intraday charts
• Symbols with extra large data (e.g. half a million bars) may have very long loading times
  • Workaround: selecting "All data" will load such files instantly, other data loading ranges aren't recommended.
    

Roadmap¶

• Option: security ceases trading after its price have gotten too close to zero.
• Throw in "black swan" events such as price shocks, complete delisting or trading halts.
• Improve volatility randomization.