Question

我想用TSQL通过LIFO（后进先出）方法进行计算。

使用LIFO方法将要求您通过出售最后一笔交易来计算利润/亏损。

示例如何运作：

交易于3月1日结束，我们以5美元购买10只股票
交易于3月2日结束，我们以每股6美元买入15只股票
交易于3月3日结束，我们以4美元买入5只股票
交易于3月4日结束，我们以每股7美元卖出17只股票

到第四次交易时，我们现在已经从3月3日以4美元的价格卖出5只股票，从2月3日以6美元的价格卖出12只股票。

所以现在我们留下了以下内容：从3月1日的交易中获得10股5美元 3月2日（17-5-15 = -3）交易中每股6美元的3只股票。

有13只股票的平均价格为（10 * 5 + 3 * 6）/ 13 = 5.23076923

这是测试数据生成脚本：

use TestTask
go
IF OBJECT_ID('testtable','U')IS NOT NULL
        DROP TABLE testtable
go
create table testtable
(
stockid int not null,
dealid int identity (1,1) not null,
dealtype char(1) not null,
stockdate datetime not null,
stockamount int not null,
priceperstock int not null
)
insert into testtable(stockid,dealtype,stockdate,stockamount,priceperstock)
VALUES
    (111,'B','01.03.2016',10,5),
    (111,'B','02.03.2016',15,6),
    (111,'B','03.03.2016',5,4),
    (111,'S','04.03.2016',17,7)

我想计算财务状况和许多其他参数，这些参数会让我知道剩下多少股票的价格。到目前为止我已经达到了这个目标：

select
stockid,
dealid,
dealtype,
stockdate,
priceperstock,
case dealtype
    when 'B' then stockamount
    when 'S' then -stockamount
end as stockamount,
sum(
        case dealtype
            when 'B' then stockamount
            when 'S' then -stockamount
        end
    ) over (partition by 
        stockid order by dealid ROWS UNBOUNDED PRECEDING)
         as poistion
from testtable

输出：

stockid dealid  dealtype       stockdate           priceperstock    stockamount    poistion
    111       1       B       2016-01-03 00:00:00.000      5             10             10
    111       2       B       2016-02-03 00:00:00.000      6             15             25
    111       3       B       2016-03-03 00:00:00.000      4             5              30
    111       4       S       2016-04-03 00:00:00.000      7            -17             13

期望的输出：

stockid dealid  dealtype       stockdate           priceperstock    stockamount    poistion    stocksleft
    111       1       B       2016-01-03 00:00:00.000      5             10             10      10
    111       2       B       2016-02-03 00:00:00.000      6             15             25      3
    111       3       B       2016-03-03 00:00:00.000      4             5              30      0
    111       4       S       2016-04-03 00:00:00.000      7            -17             13      0

最好的方法是什么？

Answer 1

由于您的示例非常狭窄，因此很难将防弹解决方案整合在一起。但这应该让你开始走上正确的轨道，或者至少是一条轨道。它使用一种反向运行总计，然后从库存量中减去。使用您的数据集进行少量更改：

create table #testtable
(
stockid int not null,
dealid int identity (1,1) not null,
dealtype char(1) not null,
stockdate datetime not null,
stockamount int not null,
priceperstock int not null
)
 insert into #testtable(stockid,dealtype,stockdate,stockamount,priceperstock)
    VALUES
        (111,'B','01.03.2016',10,5),
        (111,'B','02.03.2016',15,6),
        (111,'B','03.03.2016',5,4),
        (111,'S','04.03.2016',-17,7) --signed int

----Add this to see another level 
 --insert into #testtable(stockid,dealtype,stockdate,stockamount,priceperstock)
 --   VALUES
 --       (111,'S','05.03.2016',-12,5)
    ;WITH CTE
    AS (
        SELECT stockid
            , dealid
            , dealtype
            , stockdate
            , priceperstock
            , stockamount
            , sum(stockamount) OVER (
                ORDER BY dealid DESC
                ) AS runningtotal
            , sum(stockamount) OVER (
            ORDER BY dealid) AS position
        FROM #testtable
        )
    SELECT stockid
        , dealid
        , dealtype
        , stockdate
        , priceperstock
        , stockamount
        --, runningtotal
        , position
        , CASE 
            WHEN dealtype = 'S' 
                THEN 0
            WHEN stockamount > runningtotal AND runningtotal < 0
                THEN 0
            WHEN stockamount > runningtotal AND runningtotal >= 0
                THEN runningtotal
            WHEN stockamount < runningtotal
                THEN stockamount
            END AS StockRemaining
    FROM cte
    ORDER BY dealid

Answer 2

我怀疑你可能想要交换你的购买和销售，所以当我认为另一个答案是一个很好的起点时，它不会完全处理整个场景。

基本上我认为你必须用某种迭代机制来处理这个问题。我尝试用递归来做，但不幸的是，分析函数不能正确地使用该方法。所以我回到临时表并循环。

create table #R (
    lvl int not null, stockId int not null, dealId int not null,
    stockDate datetime not null, stockAmount int not null, pricePerStock int not null,
    stockRemaining int not null, amountDeducted int not null
);

insert into #R (
    lvl, stockId, dealId, stockDate, stockAmount,
    pricePerStock, stockRemaining, amountDeducted
)
select 0, stockId, dealId, stockDate, stockAmount, pricePerStock, stockAmount, 0
from <T> where dealtype = 'B' /* <--- your table is <T> */

declare @lvl int = 0;
declare @rowCount int = 1;
while @rowCount > 0
begin
    set @lvl = @lvl + 1;
    with sells as (
        select stockId, dealId as saleId,
            row_number() over (order by dealId) as sellNum, stockAmount as sellAmount
        from <T> where dealType = 'S'
    )
    update #R
    set stockRemaining = (
        select stockRemaining
        from (
            select dealId,
                case
                    when r.stockRemaining + s.sellAmount
                          < sum(stockRemaining) over (order by dealId desc)
                        then r.stockRemaining
                    when sum(stockRemaining) over (order by dealId desc)
                          < s.sellAmount
                        then 0
                    else sum(stockRemaining) over (order by dealId desc)
                          - s.sellAmount
                end as stockremaining
            from sells s inner join #R r
                on r.stockId = s.stockId and r.dealId < s.saleId
            where s.stockId = #R.stockId and s.sellNum = @lvl
        ) data
        where dealId = #R.dealId
    )
    where dealId < (select saleId from sells where sellNum = @lvl);
    set @rowCount = @@rowCount;
end

我已将其删除以便发布。在这里查看它的更多输出以更好地遵循逻辑：http://rextester.com/WPLKLJ95730

使用LIFO方法通过TSQL计算结果

2 个答案: