Hi, The author of the indicator appears to have created it within MetaStock (given that the images displayed in the article are MetaStock charts). He does list his contact address at the end of the article on page 30. I can PM you the contact information if you end up not being able to find it.

I don't know where the last two lines of code in v2 came from - they don't belong there. Roy

Hi kapogin Wilders() is a slightly different form of Exponential Moving Average compared to the conventional Mov(E) function. Typically an Exponential Moving Average (EMA) starts on bar one of the nominated data array (CLOSE for example), and on each subsequent bar adds a portion (percentage) of new data while retaining a portion (remaining percentage) of old data. In the EMA formula below you’ll see that Periods is converted to Rate (Ratio), and Rate is the percentage (ratio or fraction) of NEW data to be used, whilst (1-Rate) determines the percentage (fraction or ratio) of OLD data that is to be retained and added to the percentage of new data to arrive as the EMA value for the current bar. {Exponential Moving Average} Periods:=Input("Periods",1,999,9); Rate:=2 / ( Periods +1); If(Cum(1)=1, C, C*Rate + PREV*(1-Rate)); If the Periods parameter is 9 then the ratio of new data to old is 2/10 (0.2). or in percentage terms, 20%. Therefore the amount of old data retained is 80% Adding the two values together gives 100% of the new EMA value because the relative percentages of old (PREV) and new (data array) values must always add up to 100% C*0.2 + PREV*(1-0.2); Here 20% of C for the new data component and 80% of PREV for the PREVious bar’s value adds up to (is equal to) 100% of the new EMA value. What many MetaStock users do not realize is that fragments of ALL old data are present in the current EMA value. The older the data the less influence it has on the current EMA. It’s for this reason that I suggest using 5 times as much data as the Periods parameter of any EMA or Wilders to be sure of getting a reasonably accurate EMA result. Wilders Smoothing, the Wilders() function in MetaStock, is also an Exponential Moving average. However it is seeded (or initialized) by taking the first valid value of an SMA (Simple Moving Average) as the starting point. From there it’s very similar to the EMA discussed above, the difference being that the rate or ratio is different for any given Periods parameter. For this emulation the rate or ratio of new data is 0.1111 (recurring), and the ratio of old data is 0.8888 (recurring.) {Wilders Smoothing} Periods:=Input("Periods",1,999,9); Rate:=1 / Periods; If(Cum(1)<=Periods, Mov(C,Periods,S), PREV*(1-Rate) + C*Rate); When sufficient data is loaded a 10 period Wilders() will generate a 19 period Mov(E) Here is a discrete formula for RSI (Relative Strength Index). This emulation should make it easier to create variants of the original function. You might find it helps to rename each variable so that you can recognize the role of each variable. {RSI} N:=Input("Periods",2,99,10); C1:=Ref(C,-1); U:=Mov(( C>C1 ) * ( C-C1 ), N, E ); D:=Mov(( C<C1) * ( C1-C ), N, E ); 100 - (100 / ( 1 + (U / (D + (D=0) )))); I hope this gives you some insight into at least Wilders(), Mov(E) and RSI(). Hopefully you’ll take the time to experiment with these formulas. If you do I’m sure you’ll make discoveries of your own. Roy (mstt)