[Suggestion] Include timestamp / DatetimeIndex for plotting

After some more exploring, one thing I realized is, that plotting (with pyfolio / quantstats) to evaluate the results is harder than it needs to be. Currently we have no timestamps easily available which are needed for direct plotting or using the above libraries.

The Demo_FinRL_Meta_Integrate_Trends_data_to_DOW_Jones.ipynb is a good example.
It is done there, but with a (hacky) workaround using a Custom_DataProcessor / the yahoofinance dataframe timestamps.

A solution I could think of would be adding 3 functions to the env that return equal weight portfolio returns, buy-and-hold returns and the agent-returns including the timestamps. A pd.Series with DateTimeindex could work.

This would also be a good preparation for more advanced reward functions like (differential / deflated) sharpe, comparing to buy-and-hold etc. that rely on a return series.

What do you think?