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  • Plotting variance depending on sector

    Hello,

    I have a panel data set which contains information on firms (given by REITID), the sector (Sectornumber) a firm operates in and I have a log return series of the firms' stockprice (TotalLogReturn). I managed to generate a graph of the variance of the log return series. I did so by calculating the Variance of the TotalLogReturn, by(Date). Now I want to graph the Variance series of the log return depending on the sector the firm operate in; for a total of 13 variance graphs for every sector. But I can't figure out how to do so. I tried xtline Variance i(Sector) t(Date) but It just generates the same Variance graph for every sector. Could you help me?

    Code:
    xtset REITID Date
    sort REITID Date
    
    by REITID: gen TotalLogReturn = log(TotalReturn[_n])-log(TotalReturn[_n-1])
    egen SD = sd(TotalLogReturn), by(Date)
    gen Variance =  SD^2
    
    input float Date byte Sectornumber float(Variance TotalLogReturn)
    171 1          .            .
    172 1  .01271399    .07647028
    173 1 .014478557    .13145871
    174 1 .005462709     .1797182
    175 1  .01207985     .1280671
    176 1 .013802183    .12089758
    177 1 .022718094   -.02627064
    178 1 .004700374    .07014332
    179 1 .004386538      .098901
    180 1 .005752772  -.012686453
    181 1 .007845905    .14680628
    182 1 .006333977  -.035694007
    183 1 .005497316    .10743682
    184 1 .007141759     .1601549
    185 1 .005127982   .004204398
    186 1 .006305829      .074752
    187 1  .01694326  -.018864773
    188 1 .006311047    .04138524
    189 1 .009498115 -.0045783743
    190 1  .01144282    .04413582
    191 1 .015725248   -.05722305
    192 1 .023222476   -.04872722
    193 1 .016055752    -.0510096
    194 1  .06492129    .08726103
    195 1   .1656582    -.5275189
    196 1  .12633483   -.28661945
    197 1  .05336738     .1991516
    198 1  .04322393     .1398275
    199 1 .023571543    .11157066
    200 1  .02383995    .05644141
    201 1  .01842131   -.05937822
    202 1  .10762425    .12065474
    203 1  .02146371   -.04043105
    204 1 .011512837    .03625132
    205 1 .024182616    .07122423
    206 1  .03887922   -.08280947
    207 1 .028643524    .07350249
    208 1   .0820109    .11163995
    209 1  .12951487    .02777962
    210 1  .02036335    .06785064
    211 1  .01993032     .0103463
    212 1 .025130564     .1011951
    213 1  .08419436   -.11554944
    214 1  .06420892 -.0004016963
    215 1  .07555228   .006008491
    216 1   .0840135    .06081253
    217 1    .134007    .06228115
    218 1 .007738933  -.018172609
    219 1  .18569894    .14843237
    220 1  .10825178    .09344856
    221 1  .14502089     -.187984
    222 1 .026267266   .032185115
    223 1   .0886342    .09677877
    224 1   .3085793    .06493157
    225 1  .07441192  .0039215563
    226 1  .07664512    .01992873
    227 1  .01925132    -.1026542
    228 1  .09450532   -.07764153
    229 1 .009929138   -.08239751
    171 2          .            .
    172 2  .01271399   .008298767
    173 2 .014478557   .032523055
    174 2 .005462709     .2086389
    175 2  .01207985   -.10969877
    176 2 .013802183    .10318407
    177 2 .022718094    .29257214
    178 2 .004700374    -.2366491
    179 2 .004386538 -.0024751995
    180 2 .005752772   -.02129074
    181 2 .007845905    .04335041
    182 2 .006333977  -.065104224
    183 2 .005497316   .021753816
    184 2 .007141759  .0037902505
    185 2 .005127982    -.0101394
    186 2 .006305829    .03135045
    187 2  .01694326    -.0224728
    188 2 .006311047 -.0025284954
    189 2 .009498115  -.021753816
    190 2  .01144282  -.016960636
    191 2 .015725248   -.13805278
    192 2 .023222476    .04864619
    193 2 .016055752    -.1982754
    194 2  .06492129   -.20145097
    195 2   .1656582   -1.3009998
    196 2  .12633483     .4123676
    197 2  .05336738    -.3253563
    198 2  .04322393    .54591703
    199 2 .023571543   -.10919936
    200 2  .02383995  -.007722039
    201 2  .01842131     .1901077
    202 2  .10762425   -.01948218
    203 2  .02146371   -.04689976
    204 2 .011512837      .279152
    205 2 .024182616   -.04233433
    206 2  .03887922      -.16411
    207 2 .028643524    -.2042156
    208 2   .0820109    .15191607
    209 2  .12951487   -.07669263
    210 2  .02036335  -.014598786
    211 2  .01993032     -.150481
    
    end
    format %tq Date

  • #2
    I think you want
    Code:
    xtset Sectornumber Date
    xtline Variance
    That works with the data you show.

    Comment


    • #3
      I tried that, but sadly it doesn't work. When I use the Variance as the only variable in xtline, stata tells me that I have too few variables specified.
      Maybe I should have been more clear regarding setting up the panel data, so this is all I got to make it work:

      Code:
      clear all
      
      import excel "Panel Data.xlsx", sheet("Panel Data") firstrow
      
      format Date %td
      gen QDate = qofd(Date)
      format QDate %tq
      drop Date
      rename QDate Date
      format Date %tq
      
      sort REITID Date
      label variable Date "Date"
      xtset REITID Date
      sort REITID Date
      
      *Generating and labeling Average: Leverage, Return, Log Return, Variance, Total Assets/TD/TE/TL/MarketCap.
      gen TotalLeverage = TotalDebt/TotalAssets
      gen TotalReturn = Dividend + Price
      by REITID: gen TotalLogReturn = log(TotalReturn[_n])-log(TotalReturn[_n-1])
      
      egen SD = sd(TotalLogReturn), by(Date)
      gen Variance =  SD^2
      
      xtline Variance

      Comment


      • #4
        I don't understand. When I run
        Code:
        clear
        input float Date byte Sectornumber float(Variance TotalLogReturn)
        171 1          .            .
        172 1  .01271399    .07647028
        173 1 .014478557    .13145871
        174 1 .005462709     .1797182
        175 1  .01207985     .1280671
        176 1 .013802183    .12089758
        177 1 .022718094   -.02627064
        178 1 .004700374    .07014332
        179 1 .004386538      .098901
        180 1 .005752772  -.012686453
        181 1 .007845905    .14680628
        182 1 .006333977  -.035694007
        183 1 .005497316    .10743682
        184 1 .007141759     .1601549
        185 1 .005127982   .004204398
        186 1 .006305829      .074752
        187 1  .01694326  -.018864773
        188 1 .006311047    .04138524
        189 1 .009498115 -.0045783743
        190 1  .01144282    .04413582
        191 1 .015725248   -.05722305
        192 1 .023222476   -.04872722
        193 1 .016055752    -.0510096
        194 1  .06492129    .08726103
        195 1   .1656582    -.5275189
        196 1  .12633483   -.28661945
        197 1  .05336738     .1991516
        198 1  .04322393     .1398275
        199 1 .023571543    .11157066
        200 1  .02383995    .05644141
        201 1  .01842131   -.05937822
        202 1  .10762425    .12065474
        203 1  .02146371   -.04043105
        204 1 .011512837    .03625132
        205 1 .024182616    .07122423
        206 1  .03887922   -.08280947
        207 1 .028643524    .07350249
        208 1   .0820109    .11163995
        209 1  .12951487    .02777962
        210 1  .02036335    .06785064
        211 1  .01993032     .0103463
        212 1 .025130564     .1011951
        213 1  .08419436   -.11554944
        214 1  .06420892 -.0004016963
        215 1  .07555228   .006008491
        216 1   .0840135    .06081253
        217 1    .134007    .06228115
        218 1 .007738933  -.018172609
        219 1  .18569894    .14843237
        220 1  .10825178    .09344856
        221 1  .14502089     -.187984
        222 1 .026267266   .032185115
        223 1   .0886342    .09677877
        224 1   .3085793    .06493157
        225 1  .07441192  .0039215563
        226 1  .07664512    .01992873
        227 1  .01925132    -.1026542
        228 1  .09450532   -.07764153
        229 1 .009929138   -.08239751
        171 2          .            .
        172 2  .01271399   .008298767
        173 2 .014478557   .032523055
        174 2 .005462709     .2086389
        175 2  .01207985   -.10969877
        176 2 .013802183    .10318407
        177 2 .022718094    .29257214
        178 2 .004700374    -.2366491
        179 2 .004386538 -.0024751995
        180 2 .005752772   -.02129074
        181 2 .007845905    .04335041
        182 2 .006333977  -.065104224
        183 2 .005497316   .021753816
        184 2 .007141759  .0037902505
        185 2 .005127982    -.0101394
        186 2 .006305829    .03135045
        187 2  .01694326    -.0224728
        188 2 .006311047 -.0025284954
        189 2 .009498115  -.021753816
        190 2  .01144282  -.016960636
        191 2 .015725248   -.13805278
        192 2 .023222476    .04864619
        193 2 .016055752    -.1982754
        194 2  .06492129   -.20145097
        195 2   .1656582   -1.3009998
        196 2  .12633483     .4123676
        197 2  .05336738    -.3253563
        198 2  .04322393    .54591703
        199 2 .023571543   -.10919936
        200 2  .02383995  -.007722039
        201 2  .01842131     .1901077
        202 2  .10762425   -.01948218
        203 2  .02146371   -.04689976
        204 2 .011512837      .279152
        205 2 .024182616   -.04233433
        206 2  .03887922      -.16411
        207 2 .028643524    -.2042156
        208 2   .0820109    .15191607
        209 2  .12951487   -.07669263
        210 2  .02036335  -.014598786
        211 2  .01993032     -.150481
        
        end
        format %tq Date
        
        xtset Sectornumber Date
        
        xtline Variance
        
        graph export sukaldi.png, replace width(1000)
        I get the graph below.
        Click image for larger version

Name:	sukaldi.png
Views:	1
Size:	81.0 KB
ID:	1415384

        Comment


        • #5
          After I copied your code it came to my mind that Sectornumber is not an unique number. That is why I use REITID to identify the unique entities. There are thus multiple firms which can operate in the same sector. Can this be the reason it doesn't work for my whole sample?

          Comment


          • #6
            Yes, probably so. The question is how you organize your data. Since you want to do the graph by sector and plot Variance by date, you need to have just one observation for each date in each sector. That shouldn't be a problem because your calculation of Variance creates a unique value of Variance for each sector out of the many observations from different firms in that sector. Your example data actually only shows one observation per sector. But since that apparently does not represent your real situation, you can do this:

            Code:
            by Sectornumber, sort: keep if _n == 1 // SELECT ONE OBS PER SECTOR
            xtset Sectornumber Date
            xtline Variance, by(Sectornumber)
            This code drops much of the original data. If you need it back, just add -preserve- before the above commands, and -restore- after.

            Comment


            • #7
              Despite your efforts, I still can't get it to work. I have included a link to my data output from Stata and my syntax (including the code for the variance graph). If it's not too much to ask I would really like your help with this.
              HTML Code:
              https://www.dropbox.com/sh/dn16nakia2cuqhv/AACZ9ee5PphEyCQfCkMmAmbHa?dl=0
              BTW. I read that you can override the -xtset- command, by typing -xtline varlist, i(Sectornumber) t(Date)-. So I tried that, but it didn't help either

              Comment


              • #8
                Rob, I'd be happy to try to help, but I do not download Excel files from strangers. Excel files can contain active malware, and it's just a risk I won't take. If you replace that with a Stata data file, I'll give it a look.

                But let me ask first, why not just post the contents of the do-file and some -dataex- output for the data here?

                Comment


                • #9
                  Sorry, that was never my intention. I've replaced the excel file with the stata output. Eitherway, here it goes:

                  *do.file
                  Code:
                  *Version 15
                  clear all
                  
                  * Create *.dta files for excel worksheet Sheet1. (use allsheets for all sheets)
                  import excel "C:\Users\Rob Sukaldi\Dropbox\Master\Msc Finance\Thesis\Data\Panel Data.xlsx", sheet("Panel Data") firstrow
                  
                  *Change working directory to:
                  cd "C:\Users\Rob Sukaldi\Dropbox\Master\Msc Finance\Thesis\Data\Stata"
                  
                  *Formatting Date such that stata interprets it as quarterly data
                  format Date %td
                  gen QDate = qofd(Date)
                  format QDate %tq
                  drop Date
                  rename QDate Date
                  format Date %tq
                  
                  * Set REITID as to represent the entities (i) and setting Date as time variable (t)
                  sort REITID Date
                  label variable Date "Date"
                  xtset REITID Date
                  sort REITID Date
                  
                  *Generating and labeling Average: Leverage, Return, Log Return, Variance, Total Assets/TD/TE/TL/MarketCap.
                  gen TotalLeverage = TotalDebt/TotalAssets
                  gen TotalReturn = Dividend + Price
                  by REITID: gen TotalLogReturn = log(TotalReturn[_n])-log(TotalReturn[_n-1])
                  
                  egen SD = sd(TotalLogReturn), by(Date)
                  gen Variance =  SD^2
                  drop SD
                  And dataex output.
                  Code:
                  input float Date byte Sectornumber float(Variance TotalLogReturn)
                  171 1          .            .
                  172 1  .01271399    .07647028
                  173 1 .014478557    .13145871
                  174 1 .005462709     .1797182
                  175 1  .01207985     .1280671
                  176 1 .013802183    .12089758
                  177 1 .022718094   -.02627064
                  178 1 .004700374    .07014332
                  179 1 .004386538      .098901
                  180 1 .005752772  -.012686453
                  181 1 .007845905    .14680628
                  182 1 .006333977  -.035694007
                  183 1 .005497316    .10743682
                  184 1 .007141759     .1601549
                  185 1 .005127982   .004204398
                  186 1 .006305829      .074752
                  187 1  .01694326  -.018864773
                  188 1 .006311047    .04138524
                  189 1 .009498115 -.0045783743
                  190 1  .01144282    .04413582
                  191 1 .015725248   -.05722305
                  192 1 .023222476   -.04872722
                  193 1 .016055752    -.0510096
                  194 1  .06492129    .08726103
                  195 1   .1656582    -.5275189
                  196 1  .12633483   -.28661945
                  197 1  .05336738     .1991516
                  198 1  .04322393     .1398275
                  199 1 .023571543    .11157066
                  200 1  .02383995    .05644141
                  201 1  .01842131   -.05937822
                  202 1  .10762425    .12065474
                  203 1  .02146371   -.04043105
                  204 1 .011512837    .03625132
                  205 1 .024182616    .07122423
                  206 1  .03887922   -.08280947
                  207 1 .028643524    .07350249
                  208 1   .0820109    .11163995
                  209 1  .12951487    .02777962
                  210 1  .02036335    .06785064
                  211 1  .01993032     .0103463
                  212 1 .025130564     .1011951
                  213 1  .08419436   -.11554944
                  214 1  .06420892 -.0004016963
                  215 1  .07555228   .006008491
                  216 1   .0840135    .06081253
                  217 1    .134007    .06228115
                  218 1 .007738933  -.018172609
                  219 1  .18569894    .14843237
                  220 1  .10825178    .09344856
                  221 1  .14502089     -.187984
                  222 1 .026267266   .032185115
                  223 1   .0886342    .09677877
                  224 1   .3085793    .06493157
                  225 1  .07441192  .0039215563
                  226 1  .07664512    .01992873
                  227 1  .01925132    -.1026542
                  228 1  .09450532   -.07764153
                  229 1 .009929138   -.08239751
                  171 2          .            .
                  172 2  .01271399   .008298767
                  173 2 .014478557   .032523055
                  174 2 .005462709     .2086389
                  175 2  .01207985   -.10969877
                  176 2 .013802183    .10318407
                  177 2 .022718094    .29257214
                  178 2 .004700374    -.2366491
                  179 2 .004386538 -.0024751995
                  180 2 .005752772   -.02129074
                  181 2 .007845905    .04335041
                  182 2 .006333977  -.065104224
                  183 2 .005497316   .021753816
                  184 2 .007141759  .0037902505
                  185 2 .005127982    -.0101394
                  186 2 .006305829    .03135045
                  187 2  .01694326    -.0224728
                  188 2 .006311047 -.0025284954
                  189 2 .009498115  -.021753816
                  190 2  .01144282  -.016960636
                  191 2 .015725248   -.13805278
                  192 2 .023222476    .04864619
                  193 2 .016055752    -.1982754
                  194 2  .06492129   -.20145097
                  195 2   .1656582   -1.3009998
                  196 2  .12633483     .4123676
                  197 2  .05336738    -.3253563
                  198 2  .04322393    .54591703
                  199 2 .023571543   -.10919936
                  200 2  .02383995  -.007722039
                  201 2  .01842131     .1901077
                  202 2  .10762425   -.01948218
                  203 2  .02146371   -.04689976
                  204 2 .011512837      .279152
                  205 2 .024182616   -.04233433
                  206 2  .03887922      -.16411
                  207 2 .028643524    -.2042156
                  208 2   .0820109    .15191607
                  209 2  .12951487   -.07669263
                  210 2  .02036335  -.014598786
                  211 2  .01993032     -.150481
                  212 2 .025130564    .13566592
                  213 2  .08419436   -.22501095
                  214 2  .06420892    -.1510403
                  215 2  .07555228  -.021756716
                  216 2   .0840135   -.19596677
                  217 2    .134007    .06538277
                  218 2 .007738933   -.03871455
                  219 2  .18569894     .3327057
                  220 2  .10825178     .3604415
                  221 2  .14502089   -.04714673
                  222 2 .026267266   -.13254671
                  223 2   .0886342  -.008540305
                  224 2   .3085793    .08433416
                  225 2  .07441192   .014492993
                  226 2  .07664512   -.14698213
                  227 2  .01925132   -.07796157
                  228 2  .09450532    .04414617
                  229 2 .009929138   -.34695715
                  171 3          .            .
                  172 3  .01271399            .
                  173 3 .014478557            .
                  174 3 .005462709            .
                  175 3  .01207985            .
                  176 3 .013802183            .
                  177 3 .022718094            .
                  178 3 .004700374            .
                  179 3 .004386538            .
                  180 3 .005752772            .
                  181 3 .007845905      .194057
                  182 3 .006333977    .06472044
                  183 3 .005497316   -.15539907
                  184 3 .007141759    .12679413
                  185 3 .005127982 -.0090054665
                  186 3 .006305829   -.11326072
                  187 3  .01694326     .2179638
                  188 3 .006311047     .0899235
                  189 3 .009498115   -.03842261
                  190 3  .01144282    -.2379353
                  191 3 .015725248    -.2752447
                  192 3 .023222476   -.51825947
                  193 3 .016055752    -.5771094
                  194 3  .06492129    -.7393233
                  195 3   .1656582    -.3031185
                  196 3  .12633483    .10257933
                  197 3  .05336738     .2985151
                  198 3  .04322393    .32974285
                  199 3 .023571543   -.32020405
                  200 3  .02383995    .09978963
                  201 3  .01842131    -.3085921
                  202 3  .10762425    .19038203
                  203 3  .02146371   -.13995577
                  204 3 .011512837   .029278684
                  205 3 .024182616   -.27215666
                  206 3  .03887922    -.4509379
                  207 3 .028643524    -.4555105
                  208 3   .0820109     .7728179
                  209 3  .12951487    -.5279156
                  210 3  .02036335   -.07776166
                  211 3  .01993032    -.2142973
                  212 3 .025130564   -.27420595
                  213 3  .08419436   -.08673157
                  214 3  .06420892   .008304773
                  215 3  .07555228    .03776946
                  216 3   .0840135     .2564271
                  217 3    .134007    -.2882727
                  218 3 .007738933    -.5235708
                  219 3  .18569894    -.8370647
                  220 3  .10825178     .7041736
                  221 3  .14502089    -.3475247
                  222 3 .026267266    -.1640266
                  223 3   .0886342     .1106642
                  224 3   .3085793    -.1683605
                  225 3  .07441192   -.16435073
                  226 3  .07664512   -.04486088
                  227 3  .01925132    .05111153
                  228 3  .09450532    .04027611
                  229 3 .009929138   -.12691316
                  171 3          .            .
                  172 3  .01271399            .
                  173 3 .014478557            .
                  174 3 .005462709            .
                  175 3  .01207985            .
                  176 3 .013802183            .
                  177 3 .022718094            .
                  178 3 .004700374            .
                  179 3 .004386538            .
                  180 3 .005752772            .
                  181 3 .007845905            .
                  182 3 .006333977            .
                  183 3 .005497316            .
                  184 3 .007141759            .
                  185 3 .005127982            .
                  186 3 .006305829            .
                  187 3  .01694326            .
                  188 3 .006311047            .
                  189 3 .009498115            .
                  190 3  .01144282            .
                  191 3 .015725248            .
                  192 3 .023222476            .
                  193 3 .016055752            .
                  end
                  format %tq Date

                  Comment


                  • #10
                    OK. Your data contain multiple observations per combination of Sectornumber and Date. But Variance is constant within each combination of Sectornumber and Date, as it should be. You can't -xtset Sectornumber Date- without first reducing the data set to one observation per Sectornumber Date combination. Assuming you don't want to discard data that way, here's another approach that preserves the data: identify one observation for each Sectornumber Date combination and use those in -graph twoway line, by()-:

                    Code:
                    //    VERIFY UNIQUE VALUE OF VARIANCE FOR EACH DATE IN EACH SECTOR
                    by Sectornumber Date (Variance), sort: assert Variance[1] == Variance[_N]
                    
                    egen byte flag = tag(Sectornumber Date)    // SINGLE OUT ONE OBS PER Sectornumber-Date COMBO
                    
                    graph twoway line Variance Date if flag, by(Sectornumber) sort
                    
                    
                    graph export Sukaldi.png, width(1000) replace
                    which gives me:
                    Click image for larger version

Name:	Sukaldi.png
Views:	1
Size:	78.9 KB
ID:	1415638

                    Comment


                    • #11
                      Thank you very much, this does show me 13 graphs per sector. Since they all look very similar, is there an easy way to show the minimum/maximum of the graph an a table?

                      Comment


                      • #12
                        So, it sounds like you want:

                        Code:
                        tabstat Variance, by(Sectornumber) statistics(min max)

                        Comment


                        • #13
                          Hello,

                          If I run your code it gets stuck on:

                          Code:
                          summarize Variance Date if flag, by(Sectornumber) sort
                          option by() not allowed
                          That is, after the graphs are generated. These graphs however, are similar I think. Becasue when I use -tabstat- I get the following output:

                          Code:
                          tabstat Variance, by(Sectornumber) statistics(min max)
                          
                          Summary for variables: Variance
                               by categories of: Sectornumber (Sector number)
                          
                          Sectornumber |       min       max
                          -------------+--------------------
                                     1 |  .0043865  .3085793
                                     2 |  .0043865  .3085793
                                     3 |  .0043865  .3085793
                                     4 |  .0043865  .3085793
                                     5 |  .0043865  .3085793
                                     6 |  .0043865  .3085793
                                     7 |  .0043865  .3085793
                                     8 |  .0043865  .3085793
                                     9 |  .0043865  .3085793
                                    10 |  .0043865  .3085793
                                    11 |  .0043865  .3085793
                                    12 |  .0043865  .3085793
                                    13 |  .0043865  .3085793
                          -------------+--------------------
                                 Total |  .0043865  .3085793
                          ----------------------------------

                          Comment


                          • #14
                            summarize Variance Date if flag, by(Sectornumber) sort
                            option by() not allowed
                            does not appear anywhere in my code, and it's not, as Stata tells you, legal syntax. -summarize- does not have a -by()- option. You can get the same functionality by using the -by:- prefix with -summarize-. But -tabstat- is easier anyway.

                            Comment


                            • #15
                              Code:
                              by Sectornumber Date (Variance), sort: assert Variance[1] == Variance[_N]
                              
                              egen byte flag = tag(Sectornumber Date)    // SINGLE OUT ONE OBS PER Sectornumber-Date COMBO
                              
                              graph twoway line Variance Date if flag, by(Sectornumber) sort
                              tabstat Variance, by(Sectornumber) statistics(min max)
                              Gives me the graphs as you have already shown in your previous post and the -tabstat- does what it is supposed to do. However, it shows me the same values for every sector as I showed in my post. I was wrong when I typed:
                              Code:
                               
                               summarize Variance Date if flag, by(Sectornumber) sort
                              I figured another way of analyzing the sector variance is by creating a new variable:
                              Code:
                              egen SD1 = sd(TotalLogReturn), by(Sectornumber Date)
                              gen SectorVariance = SD1^2
                              drop SD1
                              
                              xtline SectorVariance, i(Sectornumber) t(Date)
                              Eventually it doesn't really matter but I just thought that it should be possible to do this with the 'normal' Variance variable. That seemed nicer.

                              Comment

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