[Suggestion] Synthetic series for first "games" and / or testing

A great repo and paper: [https://github.com/golsun/deep-RL-trading](https://github.com/golsun/deep-RL-trading)

This could be useful for FinRL maybe as helper / environment function. Training first on rather simple idealized synthetic prices before feeding real data might be beneficial to learn the agent the "basics". Also it's great for testing.

- Sine wave
- Trend curves
- Random walk
- Different types of autocorrelation
- Adding different degrees of noise/trend
- Reoccurring patterns
(Source: [https://youtu.be/c0gpgCyjTM8?t=1372](https://youtu.be/c0gpgCyjTM8?t=1372))

There are existing libraries / examples available like
- [https://github.com/Nike-Inc/timeseries-generator](https://github.com/Nike-Inc/timeseries-generator)
- [https://github.com/TimeSynth/TimeSynth](https://github.com/TimeSynth/TimeSynth)
- [https://github.com/stefan-jansen/synthetic-data-for-finance](https://github.com/stefan-jansen/synthetic-data-for-finance)
- [https://towardsdatascience.com/time-series-analysis-creating-synthetic-datasets-cf008208e014](https://towardsdatascience.com/time-series-analysis-creating-synthetic-datasets-cf008208e014)