I have below table with columns Position_Date, Deal_Nr and Market Value. Now I want to create a fourth column which calculates the Delta of Market Value between 2 days on every single Deal. For example Deal nr 100, MV 14/9 = 500. MV 13/9 = 600. 500-600 = -100...
I know how to do this if I sum and group on position date but is there a way to calculate the delta isolated on every deal without making case by and putting deal_nr as condition? I have like 100 different deal_nr and new deals will come so I want the query to be static.
Position_date |Deal_Nr| Market Value | Delta Market Value
2016-09-14 | 100 | 500 | -100
2016-09-14 | 101 | 1000 | 200
2016-09-14 | 102 | 120 | -30
2016-09-14 | 103 | 400 | -40
2016-09-13 | 100 | 600 | -300
2016-09-13 | 101 | 800 | 100
2016-09-13 | 102 | 150 | -150
2016-09-13 | 103 | 440 | 240
2016-09-12 | 100 | 900 | N/A
2016-09-12 | 101 | 700 | N/A
2016-09-12 | 102 | 300 | N/A
2016-09-12 | 103 | 200 | N/A
If I were to calculate the aggregated delta, grouped on position date, the following works.
Select
Position_date,
Market_Value,
Delta_MV = sum(Market_value) - (select sum(Market_value) from t1
where position_Date = a.position_date -1
Group by position_date)
from t1 as a
Group by position_date
You should use LEFT JOIN
as the below:
DECLARE @Tbl TABLE (Position_date DATETIME, MarketValue INT, Deal_Nr INT)
INSERT INTO @Tbl
VALUES
('2016-09-14', 500 ,100 ),
('2016-09-14', 1000,101 ),
('2016-09-14', 120 ,102 ),
('2016-09-14', 400 ,103 ),
('2016-09-13', 600 ,100 ),
('2016-09-13', 800 ,101 ),
('2016-09-13', 150 ,102 ),
('2016-09-13', 440 ,103 ),
('2016-09-12', 900 ,100 ),
('2016-09-12', 700 ,101 ),
('2016-09-12', 300 ,102 ),
('2016-09-12', 200 ,103 )
SELECT
A.Position_date,
A.MarketValue,
A.MarketValue - B.MarketValue AS DeltaMarketValue
FROM
@Tbl A LEFT JOIN
@Tbl B ON A.Deal_Nr = B.Deal_Nr AND
A.Position_date <> B.Position_date AND
DATEADD(DAY, -1, A.Position_date) = B.Position_date
Result:
Position_date MarketValue DeltaMarketValue
--------------- ----------- ----------------
2016-09-14 500 -100
2016-09-14 1000 200
2016-09-14 120 -30
2016-09-14 400 -40
2016-09-13 600 -300
2016-09-13 800 100
2016-09-13 150 -150
2016-09-13 440 240
2016-09-12 900 NULL
2016-09-12 700 NULL
2016-09-12 300 NULL
2016-09-12 200 NULL