Historical Time Series API

vaidotas.gulbinas

Hi,

I have troubles getting time series for long period of time.

Let's move to an example. I'm using Python. I have several rics: "XAU=", "EUR=", "GBP=". For these rics, I'd like to get all available historical daily close price. But there are many that I've come into.

• I don't know the beginning date of available data,
• There's a limit of 3,000 datapoints per request,
• Errors when data is not available.

Starting from Point 1: how could I get the very first available date of each ric? (of course I could just check it manually in Eikon, but it could become a problem if I have 200 rics)

Point 2: this is well known problem, so if I haven't set the date, I would receive most recent 3,000 datapoints, or 1,000 for each ric that I'm using in example. What should I do with previous datapoints?

Point 3: I kind of found a way to avoid first two problems by just creating lists of start and end dates, and create timeseries request for each pair of dates. With a help of "for item in list", I could easily get all this data with more requests, if.... there's no error. If no datapoints are available for certain data range, the code stops working. Another thing, if only one of rics data available, it becomes another problem as dataframe that you get has column name "CLOSE" instead of ric (which would be the case if several rics have available data)

So to summarize, what would be the best way to get all available historical daily timeseries for many rics using Python API?

Let me know if something is unclear. Thanks!

chavalit-jintamalit

Hi @vaidotas.gulbinas

You can request the data and check whether it should have more datapoint or not?

The picture above is just an example idea.

Then you can loop the process for the whole RIC list you have.

By the way, requesting a lot of data may be blocked due to API limitation, please refer to https://developers.refinitiv.com/eikon-apis/eikon-data-api/docs?content=49692&type=documentation_item

If this is the case, you may consider subscribing to another product such as Tick History product.