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    <title>topic Re: Regression in SAS Forecasting and Econometrics</title>
    <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729594#M4069</link>
    <description>Thank you Koen for the help.&lt;BR /&gt;&lt;BR /&gt;I have tried and it is not actually working properly. Indeed, it takes quite a long time as my dataset is big, not to say enormous.&lt;BR /&gt;&lt;BR /&gt;I will try to look for something a little bit more efficient. Still, thank you for this BRUTE FORCE APPROACH.&lt;BR /&gt;</description>
    <pubDate>Sat, 27 Mar 2021 21:59:14 GMT</pubDate>
    <dc:creator>RDellaVilla</dc:creator>
    <dc:date>2021-03-27T21:59:14Z</dc:date>
    <item>
      <title>Time Series regression</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729592#M4065</link>
      <description>&lt;P&gt;&lt;SPAN&gt;Hello, I have to perform this following task in a replication step aimed at a research.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;"To compute FFC-adjusted returns for day&amp;nbsp;&lt;/SPAN&gt;&lt;EM&gt;t&lt;/EM&gt;&lt;SPAN&gt;, I first estimate individual stock factor loadings by regressing&amp;nbsp;&lt;/SPAN&gt;&lt;STRONG&gt;delisting-adjusted excess returns&lt;/STRONG&gt;&lt;SPAN&gt;&amp;nbsp;on the FFC four factors (&lt;/SPAN&gt;&lt;STRONG&gt;including an intercept&lt;/STRONG&gt;&lt;SPAN&gt;) on a&amp;nbsp;&lt;/SPAN&gt;&lt;STRONG&gt;120-trading day rolling window&lt;/STRONG&gt;&lt;SPAN&gt;&amp;nbsp;from t –150 to t –31&amp;nbsp;&lt;/SPAN&gt;&lt;STRONG&gt;trading days&lt;/STRONG&gt;&lt;SPAN&gt;&amp;nbsp;for each stock".&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;I think I have properly sorted out my dataset so as to have the data in the desired form. Still, I have troubles in performing this time series regression. Moreover, my sample is really big, so I would require something which does not takes ages to run.&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Any suggestions on how to carry on?&amp;nbsp;&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Thanks,&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Riccardo&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 27 Mar 2021 21:00:13 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729592#M4065</guid>
      <dc:creator>RDellaVilla</dc:creator>
      <dc:date>2021-03-27T21:00:13Z</dc:date>
    </item>
    <item>
      <title>Re: Regression</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729580#M4067</link>
      <description>&lt;P&gt;To compute FFC-adjusted returns for day &lt;EM&gt;t&lt;/EM&gt;, I first estimate individual stock factor loadings by regressing &lt;STRONG&gt;delisting-adjusted excess returns&lt;/STRONG&gt; on the FFC four factors (&lt;STRONG&gt;including an intercept&lt;/STRONG&gt;) on a &lt;STRONG&gt;120-trading day rolling window&lt;/STRONG&gt; from t –150 to t –31 &lt;STRONG&gt;trading days&lt;/STRONG&gt; for each stock&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;this is exactly my issue.&amp;nbsp;&lt;/P&gt;&lt;P&gt;I feel I have sorted out data properly, setting the date of interest t, and the estimation window for each date t. I now have predict the value in t with the estimation period data.&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 27 Mar 2021 17:17:57 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729580#M4067</guid>
      <dc:creator>RDellaVilla</dc:creator>
      <dc:date>2021-03-27T17:17:57Z</dc:date>
    </item>
    <item>
      <title>Re: Regression</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729582#M4068</link>
      <description>&lt;P&gt;You want to make rolling window datasets (or even rolling window SSCP's - sum-of-squares-and-cross-products) to perform your regressions, correct?&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;You can take a look at these papers/presentations/comments I made on this subject:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;OL&gt;
&lt;LI&gt;Philadelphia SAS User's Group (2019) - slide deck.&lt;BR /&gt;
&lt;P&gt;&lt;A href="http://www.philasug.org/Presentations/201903/Rapid_Rolling_Window_Regressions.pdf" target="_blank"&gt;Rapid Rolling Window Regressions via Home Made Sum of Squares and Cross Products (philasug.org)&lt;/A&gt;&lt;BR /&gt;&lt;BR /&gt;&lt;/P&gt;
&lt;/LI&gt;
&lt;LI&gt;Northeast SAS Users Group (2012) - paper presentation&lt;BR /&gt;
&lt;P&gt;&lt;A href="https://lexjansen.com/nesug/nesug12/fi/fi08.pdf" target="_blank"&gt;Rolling Regressions with PROC FCMP and PROC REG (lexjansen.com)&lt;/A&gt;&lt;/P&gt;
&lt;/LI&gt;
&lt;LI&gt;SAS Communities forum&lt;BR /&gt;
&lt;P&gt;&lt;A href="https://communities.sas.com/t5/SAS-Procedures/How-to-create-rolling-windows-with-different-numbers-of/td-p/317642" target="_blank"&gt;How to create rolling windows with different numbe... - SAS Support Communities&lt;/A&gt;&lt;/P&gt;
&lt;BR /&gt;&lt;BR /&gt;&lt;/LI&gt;
&lt;/OL&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 27 Mar 2021 18:37:02 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729582#M4068</guid>
      <dc:creator>mkeintz</dc:creator>
      <dc:date>2021-03-27T18:37:02Z</dc:date>
    </item>
    <item>
      <title>Re: Regression</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729585#M4066</link>
      <description>&lt;P&gt;Hello,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;If you have your input data set right (I guess you shifted the target column such that the x-vector for day [t-31] is in the same observation as the target y for day [t]?), then use THE BRUTE FORCE APPROACH as explained in this paper:&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Rolling Regressions with PROC FCMP and PROC REG&lt;BR /&gt;Mark Keintz, Wharton Research Data Services, University of Pennsylvania&lt;/P&gt;
&lt;P&gt;&lt;A href="https://www.lexjansen.com/nesug/nesug12/fi/fi08.pdf" target="_blank"&gt;https://www.lexjansen.com/nesug/nesug12/fi/fi08.pdf&lt;/A&gt;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;After creating the data set RWIN (TYPE=VIEW), like done on page 1, call your procedure (for example proc autoreg) with the by-variable "w".&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;This&amp;nbsp;BRUTE FORCE APPROACH is of course greedy. Much more efficient techniques can be programmed.&lt;/P&gt;
&lt;P&gt;Let us know if the real-time (time-to-completion) of your PROC by w takes too long.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;By the way, for time series regression it's better to post your question in the SAS Forecasting and Econometrics board.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Good luck,&lt;/P&gt;
&lt;P&gt;Koen&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Sat, 27 Mar 2021 18:55:10 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729585#M4066</guid>
      <dc:creator>sbxkoenk</dc:creator>
      <dc:date>2021-03-27T18:55:10Z</dc:date>
    </item>
    <item>
      <title>Re: Regression</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729594#M4069</link>
      <description>Thank you Koen for the help.&lt;BR /&gt;&lt;BR /&gt;I have tried and it is not actually working properly. Indeed, it takes quite a long time as my dataset is big, not to say enormous.&lt;BR /&gt;&lt;BR /&gt;I will try to look for something a little bit more efficient. Still, thank you for this BRUTE FORCE APPROACH.&lt;BR /&gt;</description>
      <pubDate>Sat, 27 Mar 2021 21:59:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/Time-Series-regression/m-p/729594#M4069</guid>
      <dc:creator>RDellaVilla</dc:creator>
      <dc:date>2021-03-27T21:59:14Z</dc:date>
    </item>
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