Hi @shreyanshu_pare,
I'm afraid the query will probably not produce the results you expect. The reason is, that the first .es() query is split on the ExchangeName field while the second is not. I don't see a way to correctly use split .plus() at the same time here.
Instead I would suggest to create an index pattern with a scripted field that calculates the average for each document using (doc['BidPrice'].value + doc['AskPrice'].value) / 2 and visualize that in the Visualize app using the average of the scripted field as a metric aggregation (y-axis) and a date histogram and a terms filter as the bucket aggregations (x-axis).