Hi,   Thanks. That solution was based on monthly returns, and now I am looking for based on daily returns in past 12 months.  I can use that code for daily one as well with few adjustments but the processing time increases.   Best,   Cheema     ... View more

Hi Rick,   Thanks for your response. Please find the data given below, basically its its average monthly returns of two portfolios (time-series). In the past, I used to estimate Newey West t-statistics and found online that t-stat using White’s heteroskedasticity-adjusted standard error is similar, but not sure since it provided me the same answer like simple t-stat. Furthermore, is it possible to code it in a way that I can get White’s heteroskedasticity-adjusted for both the portfolios at once instead of running the model for each portfolio seperately? data have; infile cards expandtabs truncover; input date : yymmn6. port1 port2 ; format date yymmn6.; cards; 199501 -12.8774 -15.9533 199502 2.3605 1.2441 199503 11.3115 3.8817 199504 -7.5567 -6.0238 199505 4.861 1.463 199506 -8.4025 -5.5822 199507 7.877 10.0285 199507 3.8999 2.2173 199508 2.8722 5.5666 199508 4.7494 2.9481 199509 -0.1961 -0.967 199509 -0.906 -3.0715 199510 2.2826 1.3475 199510 1.2008 1.9409 199511 -7.8011 -7.7997 199511 -5.1886 -3.1171 199512 -12.0533 -12.5316 199512 -6.8809 -9.8692 199601 -2.6321 -3.3365 199601 -4.6634 -4.5228 199602 3.352 3.9263 199602 3.082 2.4645 199603 0.1532 2.1435 199603 -1.9428 0.0755 199604 27.5239 25.988 199604 34.4729 42.8569 199605 -5.9426 -9.9524 199605 1.3499 -0.6048 199606 21.3006 15.486 199606 18.1896 13.6956 199607 5.852 5.1746 199607 33.8655 42.5136 199608 -3.3695 0.6106 199608 5.7739 -1.5214 199609 5.857 5.1485 199609 6.3112 0.6669 199610 12.395 7.9307 199610 42.0208 51.5401 199611 5.7496 6.882 199611 15.4236 10.3373 199612 -12.608 -10.3824 199612 -21.5054 -29.4552 run; **** proc means for simple t-stat; proc means data=have n mean t probt maxdec=5; var port1 port2; run; **** proc model for White's heteroskedasticity adjusted t-stat of Port1; proc model data=have;ods graphics off; endo port1 ; instruments / intonly; port1=b0; fit port1 / gmm kernel=(bart, 1, 0); run; quit; **** proc model for White's heteroskedasticity adjusted t-stat of Port2; proc model data=have;ods graphics off; endo port2 ; instruments / intonly; port2=b0; fit port2 / gmm kernel=(bart, 1, 0); run; quit;  Thanks for your help.   Regards,   Cheema  ... View more

Thanks a lot Ksharp 🙂 ... View more

Hi Ksharp,   Sorry for not making it clear. Please find the new one with the example and data at the end. Please find the new data. First, I want to find the number of non-missing daily_ret in a month for each stock. If the number of non-missing daily_ret is at least 5, then I want to replace any missing values in that month using market_ret. Finally, I want to estimate compound or cumulative returns in a month using daily_ret. If the number of non-missing daily_ret in a month for a stock is less than 5, then the monthly return for that stock will be set equal to -99.   For example, in the data provided, the monthly return for January 1960 will be set equal to -99 since there are only 3 non-missing values. However, the cumulative (compound) monthly return for the month of February will be 0.016382. First, we will set the missing daily_ret value for 19600226 (26 February 1960) equal to market return of 0.027 and then estimate compound returns as ((1+0.0025)*(1+0.01)*(1-0.0025)*(1+0.027)*(1-0.0101)*(1+0.0076)*(1-0.0176)-1).   Thanks in advance for your help.   data have; input stock date : yymmdd10. daily_ret mkt_ret ; format date yymmdd10.; cards; 10006 19600104 . 0.01 10006 19600104 0.0387 0.011 10006 19600105 0.0223 0.012 10006 19600106 . 0.013 10006 19600107 -0.0146 0.014 10006 19600221 0.0025 0.024 10006 19600222 0.01 0.025 10006 19600225 -0.0025 0.026 10006 19600226 . 0.027 10006 19600227 -0.0101 0.028 10006 19600228 0.0076 0.029 10006 19600229 -0.0176 0.03 ; run;   ... View more

data have; input stock date : yymmdd10. daily_ret mkt_ret ; format date yymmdd10.; cards; 10006 19600104 . 0.01 10006 19600104 0.0387 0.011 10006 19600105 0.0223 0.012 10006 19600106 . 0.013 10006 19600107 -0.0146 0.014 10006 19600221 0.0025 0.024 10006 19600222 0.01 0.025 10006 19600225 -0.0025 0.026 10006 19600226 . 0.027 10006 19600227 -0.0101 0.028 10006 19600228 0.0076 0.029 10006 19600229 -0.0176 0.03 ; run; Please find the new data. First, I want to find the number of non-missing daily_ret in a month for each stock. If the number of non-missing daily_ret is at least 5, then I want to replace any missing values in that month using market_ret. Finally, I want to estimate compound or cumulative returns in a month using daily_ret. If the number of non-missing daily_ret in a month for a stock is less than 5, then the monthly return for that stock will be set equal to -99. For example, in the data provided, the monthly return for January 1960 will be set equal to -99 since there are only 3 non-missing values. However, the cumulative (compound) monthly return for the month of Feburary will be 0.016382. First, we will set the missing daily_ret value for 19600226 (26 February 1960) equal to market return of 0.027 and then estimate compound returns as ((1+0.0025)*(1+0.01)*(1-0.0025)*(1+0.027)*(1-0.0101)*(1+0.0076)*(1-0.0176)-1).   Thanks in advance for your help.    ... View more

Thanks for your reply, I will edit the post and will fix the errors in it. ... View more

Thaks, I checked those posts earlier but it seems a bit different than what I am looking for. I want additional filters while estimating monthly compounding returns using daily returns. For example, I want to estimate monthly returns when there are at least 15 non-missing daily returns available; otherwise, the monthly return will be set equal to -99. Furthermore, I want to set daily returns equal to market returns when the daily return is missing if at least 15 non-missing daily returns are available. Please correct me if I missed something.   Best,   Cheema  ... View more