I am getting unexpected results (and not prepared to declare 'bugs')  regarding dates and open and close prices that I am hoping someone can help explain. So I created a research notebook below to demonstrate most of my issues by pulling some historical data for EURUSD, and using 2 Indicators, ATR and PSAR with a timeframe to fall over the end of year holiday season. 


What I noticed was that the historical pricing data and the indicators' dates don't "match" or "align" as you would expect. To visually demonstrate this, I joined the dataframes and highlighted where historical data had dates the indicators didn't have, and vice versa. This clearly happens on holidays and weekends, which is good to some extent, because I can just drop them. However, this leaves a lot of questions that give me pause as to their accuracy or more likely to "how I am doing it."

My questions:

  1. Why don't they both have the same 'dates' of data? 
  2. Why do the indicators HAVE data for historical dates with NO data? 
  3. Why do the indicators have NO data for historical dates WITH data? 
  4. What is qb.SetTimeZone() supposed to affect?
  5. Why does qb.History() return something called a "remapper" versus the dataframe the qb.Indicator() returns? (reviewing the PandasData.cs from GitHub didn't reveal much, but that probably speaks to my level of coding.) 
  1. Why isn't the open price price exactly the same as the close price from the previous day? 
  2. Is it a new 'tick'? Hence the typically very small difference?
Lastly, I am very new to Python (couple of months) so be gentle if it is a total newb mistake #StillLearning