I have the following database table:
x
Date Return Index
01-01-2020 0.1 Null
01-02-2020 0.2 Null
01-03-2020 0.3 Null
I would like to update the Index value using the following formula:
Index = (Previous_Month_Index * Return) + Previous_Month_Index (Use 100 for Previous_Month_Index for the first month)
Expected Result: (Index to be calculated order by Date asc)
Date Return Index
01-01-2020 0.1 110 -- (100 + 10)
01-02-2020 0.2 132 -- (110 + (110 * 0.20)) = 110 + 22 = 132
01-03-2020 0.3 171.6 -- (132 + (132 * 0.30)) = 132 + 39.6 = 171.6
How can I do this using SQL? I tried the following query but getting an error:
Windowed functions cannot be used in the context of another windowed function or aggregate.
--first, load the sample data to a temp table
select *
into #t
from
(
values
('2020-01-01', 0.10),
('2020-02-01', 0.20),
('2020-03-01', 0.30)
) d ([Date], [Return]);
--next, calculate cumulative product
select *, CumFactor = cast(exp(sum(log(case when ROW_NUMBER() OVER(order by [Date] ASC) = 1 then 100 * [Return] else [Return] end)) over (order by [Date])) as float) from #t;
drop table #t
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Answer
Thinking mathematically, the result that you want is equivalent to this product:
100 * (1 + a1) * (1 + a2) * (1 + a3) * .
where a1, a2, a3 are the values of the column [Return]
.
This product can be obtained by:
100 * EXP(SUM(LOG(1 + [Return])))
and you can do this in sql like this:
SELECT *,
100 * EXP(SUM(LOG(1 + [Return])) OVER (ORDER BY [Date])) [Index]
FROM #t
See the demo.