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 This is a useful scan that was in the AFL library 
  
JAson  
  
EnableRotationalTrading ();
SetOption ("WorstRankHeld", 5);
PositionSize = - 100;
PositionScore =  0;
WatchlistNum =  1;
Filter= 1;
NumColumns= 0;
function  CalculatePosition(st, Lt1, Lt2, Lt3, Lt4, Lt5, Lt6)
{ 
score= 0;
if(st > Lt1) score++;
if(st > Lt2) score++;
if(st > Lt3) score++;
if(st > Lt4) score++;
if(st > Lt5) score++;
if(st > Lt6) score++;
return score;
} 
  
// walk through the watchlist grabbing all the symbols to calculate RS vsourse 
List =  CategoryGetSymbols(categoryWatchlist, WatchlistNum);
for (i=0; (sym = StrExtract(List, i)) != "";i++)
{ 
if(sym != Name())
{ 
f =  RelStrength(sym);
st3 =  EMA(f, 3);
st5 =  EMA(f, 5);
st8 =  EMA(f, 8);
st12 =  EMA(f, 12);
st15 =  EMA(f, 15);
Lt30 =  EMA(f, 30);
Lt35 =  EMA(f, 35);
Lt40 =  EMA(f, 40);
Lt45 =  EMA(f, 45);
Lt50 =  EMA(f, 50);
Lt60 =  EMA(f, 60);
z=BarCount -  1;
// uncomment the following if you want to do some backtesting or if you likewaiting around
// a long time for the exploration to complete
//for(z=0;z < BarCount;z++)
{ 
PositionScore[z] = PositionScore[z] + CalculatePosition(st3[z], Lt30[z], 
Lt35[z], Lt40[z], Lt45[z], Lt50[z], Lt60[z]); 
PositionScore[z] = PositionScore[z] + CalculatePosition(st5[z], Lt30[z], 
Lt35[z], Lt40[z], Lt45[z], Lt50[z], Lt60[z]); 
PositionScore[z] = PositionScore[z] + CalculatePosition(st8[z], Lt30[z], 
Lt35[z], Lt40[z], Lt45[z], Lt50[z], Lt60[z]); 
PositionScore[z] = PositionScore[z] + CalculatePosition(st12[z], Lt30[z], 
Lt35[z], Lt40[z], Lt45[z], Lt50[z], Lt60[z]); 
PositionScore[z] = PositionScore[z] + CalculatePosition(st15[z], Lt30[z], 
Lt35[z], Lt40[z], Lt45[z], Lt50[z], Lt60[z]); 
} 
} 
} 
AddTextColumn (FullName(), "Name");
AddColumn (PositionScore[BarCount - 1], "RS");_______________________________________________________________ Quad Rate Serial Abby <quad_pumped_abby@xxxxxxxxx> wrote:  
I would like to do an exploration for the change in RS of a sector over various periods, say one week, two weeks, etc.  I extracted the RS of the sector versus the S&P Equal Weight Index using:
  Strength = RelStrength ( "SPEW-X", fixup = 1 );
  Then I found the change over the time periods in question.
  Of course, when you look at a plot of the RS for a symbol or sector it appears the numerical value of the RS is directly correlated to the price of the underlying.  Thus, the numerical change in RS would be meaningless against a different priced sector.  
  I thought the simple solution was to divide the RS value by the closing price, thus normalizing the results.  But this caused the RS charts and values to be identical for every sector.  
  Is what I'm trying to do an impossibility with Amibroker or is
 my approach all wrong?  Any help would be appreciated.
  Thanks,
  Bret
 
 
 
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