I have data in the format below with fiscal year start month and fiscal year end month.Using the daily observation for each calendar year, I want to find the average returns for each year such that it will end in the month of fiscal year end and not the end of month for calendar year which is Dec as firms have different fiscal year end.
Thus the average ret for firm A in 1991 will start from the seventh month of 1990 and end on the 6month of 1991 or using firm B the average ret in 1991 will start from the 11 month of 1990 and end on the 10month of 1991.
How do I solve this problem?.Thanks in advance for the assistance.
Compname Date Ret Fiscal year end month
A 1/01/1990 1.5 6
A 2/01/1990 1.6 6
A 3/01/1990 1.7 6
A 4/01/1990 1.8 6
.
.
.
.
A 31/12/2016 1.8 6
B 1/01/1990 2.5 10
B 2/01/1990 2.6 10
B 3/01/1990 2.7 10
B 4/01/1990 2.8 10
.
.
B 31/12/2016 2.5 10
You can do this by adding months and extracting the year. Here is a method using proc sql:
proc sql;
select compname, year(intnx('month', date, 12 - fy_end_month)) as fyyyy, avg(ret)
from t
group by compname, year(intnx('month', date, 12 - fy_end_month));
Related
I am new to Power BI.I have one year filter (Range filter) and one week number filter (Range filter). I want to calculate values such that when i select year 2021 to 2022 and week number 42 to 10 it will first show data for 42th weeks to 52th weeks for year 2021 and for 1st week to 10 th weeks for year 2022.
I have two tables in PowerBI, one modified date and one fact for customer scores. The relationship will be using the "Month Num" column. Score assessments take place every June, so I would like to be able to have the scores for 12 months (June 1 to June 30) averaged. Then I will just have a card comparing the Previous year score and Current year score. Is there a way to do this dynamically, so I do not have to change the year in the function every new year? I know using the AVERAGE function will be nested into the function somehow, but I am getting confused not using a calendar year and not seasoned enough to use Time Intelligence functions yet.
Customer Score Table
Month
Month Num
Year
Score
Customer #
June
6
2020
94.9
11111
July
7
2020
97
11111
months
continue
2020
100
June
6
2021
89
22222
July
7
2021
91
22222
months
continue
2021
100
June
6
2022
93
33333
July
7
2022
94
33333
Date Table
Month
Month Num
Month Initial
january
1
J
feb
2
F
march
3
M
other
months
continued
Quick question. I'm working with code that produces a spreadsheet that contains the information like the following:
year business sales profit
2001 a 5 3
2002 a 6 4
2003 a 4 2
2001 b 2 1
2002 b 6 3
2003 b 7 5
How can I get Stata to total sales and profits across years?
Thanks
Try
collapse (sum) sales profit, by(year)
or, if you want to retain your original data,
bysort year: egen tot_sales = total(sales)
egen stands for extended generate, a very useful command.
I have the following goal regarding my data structure
group; month; year; next_year
1; February; 2014; 0
1; March; 2006; 0
1; November; 2013; 1
2; January; 2014; 0
3; January; 2004; 0
I do have group, month and year, however the column next_year needs to be generated from the first three: For each observation, I want to check if there is another observation within the same group that has a date-value which falls into the period of next year. If so, I want to set the value of next_year to 1, otherwise to 0 (see example).
I started by converting the date into a format that Stata can interpret - using ym(month, year) - such that I can make comparisons. However, I am not sure how to iterate over all observations within the group in order to determine if that is the case or not.
I would know how to do it in e.g. Java, but I don't for Stata. I suppose I should not start with loops as there are probably some implemented commands for such problems.
If you want to check if there is a following observation within the next 12 months, you can try:
clear
set more off
*----- example data -----
input group str8 month year
1 March 2006
1 March 2013
1 November 2013
1 January 2013
2 January 2014
3 January 2004
end
*----- what you want -----
gen dat = monthly(month + string(year), "MY")
format dat %tm
bysort group (dat): gen next = dat[_n+1] - dat <= 12
list, sepby(group)
Make sure you understand the difference between Nick's code and mine. They work under different assumptions. You can check the differences running both pieces of code with the data I have provided (originally Nick's but with one observation deleted to get the point across; by chance, if you use Nick's data without the modification, the results will be the same).
You are correct in avoiding an explicit loop. This kind of problem is soluble using by:.
I modified your example to have two observations for one group in one year.
clear
input group str8 month year
1 February 2014
1 March 2006
1 March 2013
1 November 2013
2 January 2014
3 January 2004
end
bysort group (year) : gen next_year = year[_n+1] == year + 1
bysort group year (next_year) : replace next_year = next_year[_N]
list, sepby(group)
+------------------------------------+
| group month year next_y~r |
|------------------------------------|
1. | 1 March 2006 0 |
2. | 1 November 2013 1 |
3. | 1 March 2013 1 |
4. | 1 February 2014 0 |
|------------------------------------|
5. | 2 January 2014 0 |
|------------------------------------|
6. | 3 January 2004 0 |
+------------------------------------+
Getting an explicit sort order is essential. Within group, we look ahead to see if the next year is the current year plus 1, assigning 1 if true and 0 if false. That will at most be true for the last observation for a given group and year. If there is more than one observation for each group and year, any occurrence of 1 must be spread to all such observations.
For a tutorial on by:, see Speaking Stata: How to move step by: step.
The assumption here is that you mean in the next calendar year, not in the next 12 months. Making your dates into Stata monthly dates will be needed for most other problems, but doesn't make this one easier. Here is one way to do that in your situation, assuming that month is string and year is numeric:
gen mdate = monthly(month + string(year), "MY")
format mdate %tm
I am using Stata and I have 6 years of daily returns for stocks that individuals hold in their portfolios. I would like to aggregate the daily returns to monthly portfolio returns. In some instances, the individual may hold more than one stock in the portfolio. I am struggling with writing the code to do this.
For a visual, my data looks like this:
I would like the results to look like this:
Where individual 2's portfolio return for the month of December 1996 is calculated as: 0.3 * 0.0031 + 0.7 * 0.0076 = 0.00625.
I have tried the collapse command such as
collapse Return, by (ID Year Month)
but this does not provide the same return that I calculated out in Excel.
I am able to make a weighted portfolio return for all the days using
bysort ID year month: egen wt_return = stock_weight * monthly_return
But this gives me daily returns. My trouble is then aggregating them into one return for the corresponding month.
As for the specifics, I would like to calculate the monthly portfolio return as the product of 1 + the weighted daily returns. As a last resort, the mean return for the month could work.
You don't show monthly portfolio return for person 2 in 1991. Your initial example data doesn't show stock weights but the desired example
data does. Your variable Monthly Return is not reproducible. You should take time to verify your question is clear when posting.
It's supposed be clear to the public who will read it, not only to you.
I didn't bother checking if your computations are correct but below is what I
understand you want. The procedure is simply to compute a weighted return and then
add them up by person year month groups. (I assume the stock weights apply to stocks on a daily basis, which is what your example data implies.)
clear all
set more off
input ///
perid year month day str3 stockid return stockw
1 1991 1 1 "ABC" .01 1
1 1991 1 2 "ABC" .02 1
1 1991 1 3 "ABC" -.01 1
1 1991 1 31 "ABC" .004 1
1 1996 12 31 "ABC" .002 1
2 1991 1 1 "ABC" .01 .3
2 1991 1 2 "ABC" .02 .3
2 1996 12 31 "ABC" .004 .3
2 1991 1 1 "XYZ" .001 .7
2 1991 1 2 "XYZ" .004 .7
2 1996 12 31 "XYZ" .021 .7
end
* create weighted return
gen returnw = return * stockw
sort perid year month day
list, sepby(perid year month day)
* sum weighted returns by person, year, month
collapse (sum) returnw, by (perid year month)
list, sepby(perid)
If you want collapse to sum, then you must indicate it with the (sum) (although I'm not clear if this is what you want). By default, it computes the mean. Read help collapse thouroughly.