FIRST: This question is NOT a duplicate. I have asked this on here already and it was closed as a duplicate. While it is similar to other threads on stackoverflow, it is actually far more complex. Please read the post before assuming it is a duplicate:
I am trying to calculate variable moving averages crossover with variable dates.
That is: I want to prompt the user for 3 values and 1 option. The input is through a web front end so I can build/edit the query based on input or have multiple queries if needed.
X = 1st moving average term (N day moving average. Any number 1-N)
Y = 2nd moving average term. (N day moving average. Any number 1-N)
Z = Amount of days back from present to search for the occurance of:
option = Over/Under: (> or <. X passing over Y, or X passing Under Y)
X day moving average passing over OR under Y day moving average
within the past Z days.
My database is structured:
tbl_daily_data
id
stock_id
date
adj_close
And:
tbl_stocks
stock_id
symbol
I have a btree index on:
daily_data(stock_id, date, adj_close)
stock_id
I am stuck on this query and having a lot of trouble writing it. If the variables were fixed it would seem trivial but because X, Y, Z are all 100% independent of each other (could look, for example for 5 day moving average within the past 100 days, or 100 day moving average within the past 5) I am having a lot of trouble coding it.
Please help! :(
Edit: I've been told some more context might be helpful?
We are creating an open stock analytic system where users can perform trend analysis. I have a database containing 3500 stocks and their price histories going back to 1970.
This query will be running every day in order to find stocks that match certain criteria for example:
10 day moving average crossing over 20 day moving average within 5 days
20 day crossing UNDER 10 day moving average within 5 days
55 day crossing UNDER 22 day moving average within 100 days
But each user may be interested in a different analysis so I cannot just store the moving average with each row, it must be calculated.