Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
/*	
  
Submitted	
  by:	
  Akanksha	
  Jain	
  
*/	
  
/*	
  
Project	
  Requirements:	
  
1)	
  Read	
  the	
  ASCII	
  d...
proc	
  contents	
  data	
  =	
  currency;	
  
run;	
  
	
  
proc	
  sort	
  data	
  =	
  currency;	
  
	
  
by	
  date;	
...
 
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  
	
  

	
  
	
  
	
  
	
  
	
  
	
  ...
proc	
  sql;	
  
	
  
select	
  std(usdlr3m)*sqrt(250)	
  as	
  STD_usdlr3m,	
  	
  
	
  
	
  
	
  
std(usdlr2y)*sqrt(250)...
*/	
  
%macro	
  title_corr(start_dt,	
  end_dt);	
  
	
  
title	
  "Correlation	
  Matrix	
  for:	
  &start_dt	
  -­‐	
  ...
 
proc	
  printto	
  print=ann_vol	
  new;	
  	
  
run;	
  	
  
	
  
%vol_corr(60,60)	
  
	
  
	
  
	
  
	
  
Upcoming SlideShare
Loading in …5
×

Tool to calculate Annualized Volatility over a period of time: SAS Macros, SQL Procedures and Arrays

1,937 views

Published on

This program uses advanced SAS programming techniques, PROC SQL, and SAS macros to establish the following requirements:
- Build a filter for potentially bad data of variable Date and flag a warning for that observation in the log
- Calculate the annualized volatility for each random variable and correlation matrix for all the random variables for a length of time period (one month, for example), call it a time window.
- Output the volatility and correlation coefficient matrix need into a flat ASCII file.
- Relax the above specifications to allow (1) the weekly basis to vary to any number of days (2) the length of a time period to vary to any number of days.
- Output the lower triangle of correlation coefficient matrix (including the diagonal elements) for each time window of all the above random variables into a flat file.

Tool used:
SAS 9.3_M1

Techniques used:
SAS Macros
SQL Procedures
Arrays

Published in: Technology, Education
  • Login to see the comments

  • Be the first to like this

Tool to calculate Annualized Volatility over a period of time: SAS Macros, SQL Procedures and Arrays

  1. 1. /*   Submitted  by:  Akanksha  Jain   */   /*   Project  Requirements:   1)  Read  the  ASCII  data  file  into  SAS.  The  variable  names  are  date  (mmddyy8.)   usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m  gbplr2y  gbplr3y  gbplr5y   gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y  demlr10y  (in  this  order).     2)  The  definitions  of  above  variables  are  that  they  are  log  of  daily  quote  ratio  of   some  currencies.   3)  In  your  program,  build  a  filter  for  potentially  bad  data  of  variable  Date  and  flag  a   warning  for  that  observation  in  the  log.  For  example,  if  the  date  has  a  value  of   10/32/89,  then  this  record  should  be  identified,  and  a  waning  flag  should  be  issued.   4)  Calculate  the  volatility  for  each  random  variable  and  correlation  matrix  for  all  the   random  variables  for  a  length  of  time  period  (one  month,  for  example),  let's  call  it  a   time  window.  The  volatility  and  correlation  coefficient  matrix  need  to  be  output  into   a  flat  ASCII  file.  The  time  window  that  we  want  to  calculate  volatility  from  moves   over  time  on  a  weekly  basis.  The  volatility  is  defined  as  standard  deviation  of  the   above  variables  (except  date,  a  nonrandom  variable).  Note:  the  volatility  calculation   here  is  based  on  daily  data;  the  volatility  you  need  to  get  is  annualized,  which  can  be   done  by  multiplying  a  factor  of  square  root  of  250  to  the  daily  volatility.   5)  Relax  the  above  specifications  to  allow  (1)  the  weekly  basis  to  vary  to  any   number  of  days  (2)  the  length  of  a  time  period  to  vary  to  any  number  of  days.   6)  Output  the  lower  triangle  of  correlation  coefficient  matrix  (including  the  diagonal   elements)  for  each  time  window  of  all  the  above  random  variables  into  a  flat  file.   */     options  mlogic  mprint  symbolgen  nonumber  nodate;     filename  mylib  'Z:BerkeleyAdvanced_SAS_Project';     data  currency;     infile  mylib('output.txt');   input  date  mmddyy8.  usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m   gbplr2y  gbplr3y  gbplr5y  gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y   demlr10y;     format  date  mmddyy8.;     year_  =  year(date);     month_  =  month(date);     day_  =  day(date);   run;     proc  print  data  =  currency;     title  'data  set  Currency  -­‐  reading  an  ASCII  file  into  a  SAS  data  set';   run;    
  2. 2. proc  contents  data  =  currency;   run;     proc  sort  data  =  currency;     by  date;   run;     filename  ann_vol  'Z:BerkeleyAdvanced_SAS_Projectann_vol.txt';       /*   Macro  VOL_CORR  does  the  following:   1)  Uses  the  data  set  CURRENCY  (which  is  created  from  an  ASCII  file  and  has   variables:   Date  (mmddyy8.)  usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m  gbplr2y   gbplr3y  gbplr5y  gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y  demlr10y).  These   variables  are  the  log  of  daily  quote  ratio  of  some  currencies.   2)  Flags  a  warning  in  the  log  if  the  date  has  a  bad  value  such  as  10/32/89,  and   creates  a  variable  flag_bad  which  will  have  a  value  'Y'  if  the  Date  value  is  bad  or  'N'  if   not.   3)  Calculates  the  annualized  volatility  for  the  given  variables  for  a  given  time   window  and  leap-­‐  uses  macro  VOLATILITY.   4)  Calculates  the  correlation  matrix  for  the  given  variables  for  a  given  time  window   and  leap-­‐  uses  macro  CORRELATION.   5)  Captures  the  lower  triangle  of  the  correlation  matrix  for  the  given  variables  for  a   given  time  window  and  leap-­‐  uses  macro  CORR_LOWTRI.   6)  Prints  appropriate  titles  -­‐  uses  macro  TITLE_VOL  TITLE_CORR   TITLE_CORR_LOWTRI.     */   %macro  vol_corr(win_len,leap);   data  cfinal;     set  currency  end=last;     if  month_  gt  12  or  day_  gt  31  then  do;       put  'Warning:  Observation  number:  '  _n_  'has  bad  data';       flag_bad  =  'Y';       end;     else  do;       flag_bad  =  'N';     end;     format  date_first  date_last  date9.;     if  _n_  =  1  then  do;       date_first  =  date;       put  'First  date  of  data  set  is:'  date_first;     end;     retain  date_first;     if  last  then  do;  
  3. 3.                                                                                     date_last  =  date;   put  'Last  date  of  data  set  is:'  date_last;   date_diff  =  (date_last-­‐  date_first);   put  'Date  difference  in  days  is:'  date_diff;   if  &leap  eq  0  then  do;     put  'The  Leap  cannot  be  zero';   end;   else  do;     n_time_windows  =  CEIL(date_diff/&leap);     put  'Number  of  Time  windows  are:'  n_time_windows;     c_date_last  =  put(date_last,  date9.);     i  =0;     do  until(i  ge  n_time_windows);       put  'value  of  I  is:'  i;       next_date  =  intnx('day',date_first,  &win_len);       c_date_first  =  put(date_first,  date9.);       c_next_date  =  put(next_date,  date9.);       put  'char  start  date  is  c_date_first:'  c_date_first;       put  'char  end  date  is  c_next_date:'  c_next_date;   call  execute('%title_vol('||  c_date_first   ||','||c_next_date||')');   call  execute('%volatility('||  c_date_first   ||','||c_next_date||')');   call  execute('%title_corr('||  c_date_first   ||','||c_next_date||')');   call  execute('%correlation('||  c_date_first   ||','||c_next_date||')');   call  execute('%title_corr_lowtri('||  c_date_first   ||','||c_next_date||')');   call  execute('%corr_lowtri('||  c_date_first   ||','||c_next_date||')');       i=i+1;       date_first  =  intnx('day',date_first,  &leap);   put  'start  date  at  the  end  of  loop  for  next  iteration  is   date_first:'  date_first;     end;   end;             end;   run;   %mend  vol_corr;     /*   MACRO  FOR  CREATING  THE  ANNUALIZED  VOLATILITY  FOR  A  GIVEN  RANGE  OF   DATES   */   %macro  volatility(start_dt,  end_dt);  
  4. 4. proc  sql;     select  std(usdlr3m)*sqrt(250)  as  STD_usdlr3m,           std(usdlr2y)*sqrt(250)  as  STD_usdlr2y,           std(usdlr3y)*sqrt(250)  as  STD_usdlr3y,           std(usdlr5y)*sqrt(250)  as  STD_usdlr5y,           std(usdlr10y)*sqrt(250)  as  STD_usdlr10y,         std(gbplr3m)*sqrt(250)  as  STD_gbplr3m,           std(gbplr2y)*sqrt(250)  as  STD_gbplr2y,         std(gbplr3y)*sqrt(250)  as  STD_gbplr3y,         std(gbplr5y)*sqrt(250)  as  STD_gbplr5y,         std(gbplr10y)*sqrt(250)  as  STD_gbplr10y,         std(demlr3m)*sqrt(250)  as  STD_demlr3m,         std(demlr2y)*sqrt(250)  as  STD_demlr2y,         std(demlr3y)*sqrt(250)  as  STD_demlr3y,         std(demlr5y)*sqrt(250)  as  STD_demlr5y,         std(demlr10y)*sqrt(250)  as  STD_demlr10y       from  cfinal       where  date  between  "&start_dt"d  and  "&end_dt"d;         quit;   %mend  volatility;     /*   MACRO  FOR  CREATING  THE  CORRELATION  MATRIX  FOR  A  GIVEN  RANGE  OF   DATES   */   %macro  correlation(start_dt,  end_dt);   proc  corr  data  =  cfinal  pearson  noprob  nosimple;   var  usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m  gbplr2y  gbplr3y   gbplr5y  gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y  demlr10y;     where  date  between  "&start_dt"d  and  "&end_dt"d;   run;   %mend  correlation;       /*   MACRO  FOR  PRINTING  THE  TITLE  "ANNUALIZED  VOLATILITY"  FOR  A  GIVEN   RANGE  OF  DATES   */   %macro  title_vol(start_dt,  end_dt);     title  "Annualized  Volatility  for:  &start_dt  -­‐    &end_dt"  ;   %mend  title_vol;     /*   MACRO  FOR  PRINTING  THE  TITLE  "CORRELATION  MATRIX"  FOR  A  GIVEN  RANGE   OF  DATES  
  5. 5. */   %macro  title_corr(start_dt,  end_dt);     title  "Correlation  Matrix  for:  &start_dt  -­‐    &end_dt"  ;   %mend  title_corr;       /*   MACRO  FOR  PRINTING  THE  TITLE  "LOWER  TRIANGLE  OF  THE  CORRELATION   MATRIX"  FOR  A  GIVEN  RANGE  OF  DATES   */   %macro  title_corr_lowtri(start_dt,  end_dt);     title  "Lower  Triangle  of  Correlation  Matrix  for:  &start_dt  -­‐    &end_dt"  ;   %mend  title_corr_lowtri;       /*   MACRO  FOR  CREATING  ONLY  THE  LOWER  TRIANGLE  OF  THE  CORRELATION   MATRIX  FOR  A  GIVEN  RANGE  OF  DATES   */   %macro  corr_lowtri(start_dt,  end_dt);   proc  corr  data  =  cfinal  pearson  noprob  nosimple  noprint  outp  =  cfinal_corr;   var  usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m  gbplr2y  gbplr3y   gbplr5y  gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y  demlr10y;     where  date  between  "&start_dt"d  and  "&end_dt"d;   run;     data  corr_matrix_full;     set  cfinal_corr;     where  _TYPE_  =  "CORR";   run;     data  corr_array_lower  noobs;     set  corr_matrix_full;   array  full_tri  {*}  usdlr3m  usdlr2y  usdlr3y  usdlr5y  usdlr10y  gbplr3m  gbplr2y   gbplr3y  gbplr5y  gbplr10y  demlr3m  demlr2y  demlr3y  demlr5y  demlr10y;     do  i=1  to  dim(full_tri);       if  i  gt  _n_  then  full_tri{i}=.;     end;     drop  i  _type_;   run;     proc  print  data  =  corr_array_lower  noobs;   title  "Lower  Triangle  for  for:&start_dt  -­‐    &end_dt";   run;     %mend  corr_lowtri;  
  6. 6.   proc  printto  print=ann_vol  new;     run;       %vol_corr(60,60)          

×