[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

AmiBroker Tips - Weekly Newsletter - Issue 02/2000


  • To: "AmiBroker Mailing List" <amibroker@xxxx>
  • Subject: AmiBroker Tips - Weekly Newsletter - Issue 02/2000
  • From: "Tomasz Janeczko" <tjaneczk@xxxx>
  • Date: 26 Nov 2000 12:35:59 -0000

PureBytes Links

Trading Reference Links

Issue 4/2000 AmiBroker Tips weekly newsletter.
Issue 4/2000.
Copyright (C)2000 Tomasz Janeczko. 
All back issues available from:
http://www.amibroker.com/newsletter/ 

IN THIS ISSUE
1 Welcome
2 Tutorial: Working with composites
3 AFL Formula Library: Implementing alerts on trend lines
4 Tip of the week: How to automate assigning stocks to sectors/industries ?
1 Welcome
Welcome to the 4th issue of AmiBroker Tips newsletter. 

In tutorial column I describe how to set up composites correctly so that AD-Line, TRIN indicators are shown properly.

In AFL corner I discuss a method of detecting trend line breaks. This is somewhat tricky stuff to do in current version of AFL and future version willhave better support for doing such things but for a while you are limited to this solution.


By the way: Do you find this newsletter useful? Have any comments/suggestions or article ideas. Please don't hesitate to drop a line to newsletter@xxxxxxxxxxxxxx

2 Tutorial: Working with composites
AmiBroker allows to plot composite indicators such as Advance-Decline line and Arms Index (TRIN). However for proper functioning they need some additional setup - mainly defining base stock (index) which is taken into accountwhen performing calculations.

In order to make Advances/Declines and TRIN work you have to:

1.. Open Categories window using Stock->Categories menu item.
Select base index for given market in Markets tab and Base indexes for - Composites combo.
For example if you are following NYSE this can by ^DIJ (Dow Jones Average)



2.. Choose Stock->Calculate composites... menu item to open the window shown below and mark Number of advancing/declining issues and Apply to: all quotes, All markets
   

3.. Click Calculate . From now on ADLine and TRIN indicators should be visible.
Q: Why does AB need "base index"?
A: Just because it may happen that not all stocks are quoted every businness day and AB needs must calculate number of 
advancing/declining issues per market. So it checks the "base index" quotations dates and tries to find corresponding quotes of all stocks belonging to that market to find out how many issues advanced, declined and not changed at all.

Q: What are "Volume for base index" and "Copy volume to all indexes" checkboxes for?
A: "Volume for base index" and "Copy volume to all indexes" are provided incase you DON'T have real volume data for index quotes. In that case AmiBroker can calculate volume for index as a sum of volumes of all stocks belonging to given market.
First option assigns calculated volume only to "base index", the second copies the volume figure to all indexes belonging to given market.

3 AFL Formula Library: Implementing alerts on trend lines
A trend line is a sloping line drawn between two prominent points on a chart. Rising trend lines are usually drawn between two troughs (low points) toillustrate price support while falling trend lines are usually drawn between two peaks (high points) to illustrate upside price resistance. The consensus is that once a trend has been formed (two or more peaks/troughs have touched the trend line and reversed direction) it will remain intact until broken. 

The trend line is described by well-know linear equation:

y = ax + b

where x represents time (bar number), y represents price, a defines the slope of the line and b defines initial offset. The main problem in defining appropriate AFL formula is finding the values of these two latter coefficients. If a trend line is drawn between two important lows the slope of the line could be calculated by subtracting the second low price from the first low price and dividing the result by a number of bars between the lows:

a = ( low2 - low1 ) / ( bars2 - bars1 )

Calculating offset (b) value is trivial when we shift the time scale so x=0 is located at the first low. In this case b=low1.

So our mathematical formula for the trendline between two important lows will look like this:

y = ( x - bars1 ) * ( low2 - low1 ) / ( bars2 - bars1 ) + low1

While determining low prices is simple (just point your mouse over the dominant low and read the low price from a data tooltip that appears on the screen), determining the bar number is not that simple. You can of course count bars by hand but this is simply too much work (especially when you don't have Florida volunteers for a recount :-) ). Luckily we have AFL that allows us to do it in automatic way. All we have to do is to make a running total of bars (our x coordinate) using cum() function:

x = cum( 1 );

and then find out where low occured using valuewhen() function:

bar1 = valuewhen( low == low1, x, 1 );
bar2 = valuewhen( low == low2, x, 1 );

Since trend lines are different for each stock, now I will show you the whole thing using AXP (American Express) quotes.
We can observe quite nice trend on this stock, with two important lows on March 9th, 2000 (low price 39.7648) and June, 22th 2000 (low price 51.9375) as show in the picture below:



Note that StartY and EndY parameters of the trendline are exactly equal thelow prices of the days - this is extremely important since we will be searching for this values using valuewhen() function (actual lows could be determined using data tooltip).



So we have startvalue = 39.7648 and endvalue = 51.9375 and we can writean AFL formula for the trendline:

x = cum(1);

startvalue = 39.7648;
endvalue = 51.9375;

startbar = lastvalue( valuewhen( low == startvalue, x, 1 ) );
endbar = lastvalue( valuewhen( low == endvalue, x, 1 ) );

a = (endvalue-startvalue)/(endbar-startbar);
b = startvalue;

trendline = a * ( x - startbar ) + b; 

A trend line could be now drawn with a price chart using the following assignments:

graph1 = trendline;
graph0 = close;

/* some color + style settings */
graph0style=64;
graph0color=2;
graph1style = 5;
graph1color = 8;

Now we can test trend line break using the following formulas:

buy = cross( close, trendline ); /* buy signal when close crosses abovethe trendline */
sell = cross( trendline, close ); /* sell signal when close crosses below the trend line */


Note that these tests are correct only for single stock, so in fact we should check the ticker name before:

buy = name()=="AXP" AND cross( close, trendline ); 
sell = name()=="AXP" AND cross( trendline, close ); 

As you can see the whole procedure is a little bit confusing and need to berepeated for every stock individually. But what about making it automatic?Yes - it is possible in AFL! AmiBroker Formula Language has the functions for detecting important lows and highs (through(), peak() functions) and wecan use them to generate automatic trend lines. Just let AmiBroker two last important lows for us using the following formula:

perchg = 10;

startvalue = lastvalue( trough( low, perchg, 1 ) );
endvalue = lastvalue( trough( low, perchg, 2 ) );

where perchg is a variable that controls minimum change threshold for finding lows. The rest of the formula remains the same, so complete automatic trend line formula using lows and 10% minimum change looks as follows:

x = cum(1);

perchg = 10;

startvalue = lastvalue( trough( low, perchg, 1 ) );
endvalue = lastvalue( trough( low, perchg, 2 ) );

startbar = lastvalue( valuewhen( low == startvalue, x, 1 ) );
endbar = lastvalue( valuewhen( low == endvalue, x, 1 ) );

a = (endvalue-startvalue)/(endbar-startbar);
b = startvalue;

trendline = a * ( x - startbar ) + b; 

graph0 = close;
graph1 = trendline;
graph0style=64;
graph0color=2;
graph1style = 5;
graph1color = 8;

I am not saying that this formula is perfect. It sometimes generates strange trend lines and it strongly depends on perchg parameter. You can of course use peak() function instead of trough() to base your trend line on highs instead of lows.

As for the future - in some next version of AmiBroker the support for alerts on studies will be enhanced so watch out!

( Note: the formulas presented here are also available from http://www.amibroker.com/library.html ) 

4 Tip of the week: : How to automate assigning stocks to sectors/industries?

Note: This functionality is available only in Windows version of AmiBroker

In the first issue of AmiBroker Tips newsletter AmiBroker I discussed usingof AmiBroker's OLE automation interface for accessing stock data. In this article I will give you another example of automation: assigning stocks to industries using simple JScript. For starters I recommend reading the firstarticle before proceeding with this one. 

First we should set up our sectors and industries using Stock->Categories window. The difference between a sector and an industry is that industries "belong" to sectors, for example: "Air Courier", "Airline", "Railroads", "Trucking" industries belong to "Transportation" sector. So an assignment to an industry implicts assignment to a sector. If you don't want to have detailed industries you can just assign first 32 industries to 32 sectors on one-by-one basis. 

Now let's suppose that we have a text file that contains tickers, full company names and a industry number. Industry number should correspond our settings in Categories window. A sample file would look like this:

ELM,ELINK MEDIA LIMITED,0 
GCN,GOCONNECT LIMITED,0 
SGN,SINGLETON GROUP LIMITED,1 
AHH,AGRO HOLDINGS LIMITED,1
ATP,ATLAS PACIFIC LIMITED,1
AFF,AUSTRALIAN FOOD & FIBRE LIMITED,1
ASR,AUSTRALIAN RURAL GROUP LIMITED,1
ARP,ARB CORPORATION LIMITED,2
ATL,AUTO ENTERPRISES LIMITED,2
ALO,AUTO GROUP LIMITED,2
BER,BERKLEE LIMITED,2
ADB,ADELAIDE BANK LIMITED,3
ANZ,AUSTRALIA & NEW ZEALAND BANKING GROUP LIMITED,3
BOQ,BANK OF QUEENSLAND LIMITED.,3
BWA,BANK OF WESTERN AUSTRALIA LIMITED,3


and our Categories are set up so sectors and industires have one-to-one relationship with the following (zero-based) numbering 0 - "Advertising & Marketing", 1- "Agriculture & Related Services", 2- "Automotive & Related Services" and 3- "Banking".

The script for importing the data file will look like this:

/* change this line according to your data file name */
var filename = "industry_data.txt";

var fso, f, r;
var ForReading = 1;
var AmiBroker;
var fields;
var stock;

/* Create AmiBroker app object */
AmiBroker = new ActiveXObject( "Broker.Application" );

/* ... and file system object */
fso = new ActiveXObject( "Scripting.FileSystemObject" );

/* open ASCII file */
f = fso.OpenTextFile( filename, ForReading);

/* read the file line by line */
while ( !f.AtEndOfStream )
{

r = f.ReadLine();

/* split the lines using comma as a separator */
fields = r.split(","); 

/* add a ticker - this is safe operation, in case that */
/* ticker already exists, AmiBroker returns existing one */
stock = AmiBroker.Stocks.Add( fields[ 0 ] ); 

stock.FullName = fields[ 1 ];
stock.IndustryID = parseInt( fields[ 2 ] );


}

/* refresh ticker list and windows */
AmiBroker.RefreshAll();

The whole thing is just reading the file line by line and assigning the fields to properties of stock automation object. It's so simple :-). The only thing that you might want to change is the name of the file with a data - my example uses "Industry_data.txt" file name but this can be changed according to your naming convention. A complete script could be found here and a sample data file is here. 

.... and that's all for this week - hope you enjoyed reading 


--------------------------------------------------------------------------------

AmiBroker Tips weekly newsletter. Issue 4/2000. Copyright (C)2000 Tomasz Janeczko. All back issues available from: http://www.amibroker.com/newsletter/

 



------=_NextPart_002_0018_01C057AC.9C3B5760
Content-Type: text/html;
charset="iso-8859-2"
Content-Transfer-Encoding: quoted-printable

<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<HTML><HEAD>
<META content="text/html; charset=iso-8859-2" http-equiv=Content-Type>
<META content="MSHTML 5.00.2614.3500" name=GENERATOR>
<STYLE></STYLE>
</HEAD>
<BODY>
<DIV>
<TABLE border=0 cellPadding=0 cellSpacing=0 width="100%">
<TBODY>
<TR>
<TD>
<DIV align=center><B><IMG alt="" border=0 hspace=0 
src="cid:001101c057a4$3a4c35e0$0100007f@xxxx";><BR>Issue 4/2000</B></DIV></TD>
<TD width="15%"><FONT size=-2>AmiBroker Tips weekly newsletter.<BR>Issue 
4/2000.<BR>Copyright&nbsp;(C)2000&nbsp;Tomasz&nbsp;Janeczko. <BR>All back 
issues available from:<BR><A 
href="http://www.amibroker.com/newsletter/";>http://www.amibroker.com/newsletter/</A></FONT></TD></TR></TBODY></TABLE>
<H5>IN THIS ISSUE</H5>
<H5>1 Welcome<BR>2 Tutorial: Working with composites<BR>3 AFL Formula Library: 
Implementing alerts on trend lines<BR>4 Tip of the week: How to automate 
assigning stocks to sectors/industries ?</H5>
<H5>1 Welcome</H5>
<P>Welcome to the 4th issue of AmiBroker Tips newsletter. </P>
<P>In tutorial column I describe how to set up composites correctly so that 
AD-Line, TRIN indicators are shown properly.</P>
<P>In AFL corner I discuss a method of detecting trend line breaks. This is 
somewhat tricky stuff to do in current version of AFL and future version will 
have better support for doing such things but for a while you are limited to 
this solution.<BR></P>
<P>By the way: Do you find this newsletter useful? Have any comments/suggestions 
or article ideas. Please don't hesitate to drop a line to <A 
href="mailto:newsletter@xxxx";>newsletter@xxxx</A></P>
<H5>2 Tutorial: Working with composites</H5>
<P>AmiBroker allows to plot composite indicators such as Advance-Decline line 
and Arms Index (TRIN). However for proper functioning they need some additional 
setup - mainly defining base stock (index) which is taken into account when 
performing calculations.</P>
<P>In order to make Advances/Declines and TRIN work you have to:</P>
<OL>
<LI>Open Categories window using <I>Stock-&gt;Categories </I>menu 
item.<BR>Select base index for given market in <B>Markets</B> tab and <B>Base 
indexes for</B> - <B>Composites</B> combo.<BR>For example if you are following 
NYSE this can by <B>^DIJ</B> (Dow Jones Average)<IMG alt="" border=0 hspace=0 
src="cid:001201c057a4$3a5cfec0$0100007f@xxxx";><BR><BR><BR></LI>
<LI>Choose <I>Stock-&gt;Calculate composites... </I>menu item to open the 
window shown below and mark <B>Number of advancing/declining issues</B> and 
<B>Apply to: all quotes</B>, <B>All markets<IMG alt="" border=0 hspace=0 
src="cid:001301c057a4$3a5cfec0$0100007f@xxxx";></B><BR>&nbsp;<BR></LI>
<LI>Click <B>Calculate</B> . From now on ADLine and TRIN indicators should be 
visible.</LI></OL>
<P><I>Q: Why does AB need "base index"?</I><BR>A: Just because it may happen 
that not all stocks are quoted every businness day and AB needs must calculate 
number of <BR>advancing/declining issues per market. So it checks the "base 
index" quotations dates and tries to find corresponding quotes of all stocks 
belonging to that market to find out how many issues advanced, declined andnot 
changed at all.</P>
<P><I>Q: What are "Volume for base index" and "Copy volume to all indexes" 
checkboxes for?</I><BR>A: "Volume for base index" and "Copy volume to all 
indexes" are provided in case you DON'T have real volume data for index quotes. 
In that case AmiBroker can calculate volume for index as a sum of volumes of all 
stocks belonging to given market.<BR>First option assigns calculated volumeonly 
to "base index", the second copies the volume figure to all indexes belonging to 
given market.</P>
<H5>3 AFL Formula Library: Implementing alerts on trend lines</H5>
<P>A trend line is a sloping line drawn between two prominent points on a chart. 
Rising trend lines are usually drawn between two troughs (low points) to 
illustrate price support while falling trend lines are usually drawn between two 
peaks (high points) to illustrate upside price resistance. The consensus isthat 
once a trend has been formed (two or more peaks/troughs have touched the trend 
line and reversed direction) it will remain intact until broken. </P>
<P>The trend line is described by well-know linear equation:</P>
<BLOCKQUOTE>
<P><I><FONT face="Times New Roman, Times, serif">y = ax + 
b</FONT></I></P></BLOCKQUOTE>
<P>where <I><FONT face="Times New Roman, Times, serif">x</FONT></I> represents 
time (bar number), <I><FONT face="Times New Roman, Times, serif">y</FONT></I> 
represents price, <I><FONT face="Times New Roman, Times, serif">a</FONT></I> 
defines the slope of the line and<I> <FONT 
face="Times New Roman, Times, serif">b</FONT></I> defines initial offset.The 
main problem in defining appropriate AFL formula is finding the values of these 
two latter coefficients. If a trend line is drawn between two important lows the 
slope of the line could be calculated by subtracting the second low price from 
the first low price and dividing the result by a number of bars between the 
lows:</P>
<BLOCKQUOTE>
<P><I><FONT face="Times New Roman, Times, serif">a = </FONT></I><FONT 
face="Times New Roman, Times, serif">(<I> low2 - low1 </I>) / (<I> bars2 - 
bars1 </I>)</FONT></P></BLOCKQUOTE>
<P>Calculating offset (<I><FONT 
face="Times New Roman, Times, serif">b</FONT></I>) value is trivial when we 
shift the time scale so <FONT face="Times New Roman, Times, serif">x</FONT>=0 is 
located at the first low. In this case <I><FONT 
face="Times New Roman, Times, serif">b=low1</FONT>.</I></P>
<P>So our mathematical formula for the trendline between two important lowswill 
look like this:</P>
<BLOCKQUOTE>
<P><I><FONT face="Times New Roman, Times, serif">y = </FONT></I><FONT 
face="Times New Roman, Times, serif">(<I> x </I>-<I> bars1 </I>) * (<I>low2 
</I>-<I> low1 </I>) / ( <I>bars2 </I>-<I> bars1 </I>) + 
<I>low1</I></FONT></P></BLOCKQUOTE>
<P>While determining low prices is simple (just point your mouse over the 
dominant low and read the low price from a data tooltip that appears on the 
screen), determining the bar number is not that simple. You can of course count 
bars by hand but this is simply too much work (especially when you don't have 
Florida volunteers for a recount :-) ). Luckily we have AFL that allows us to do 
it in automatic way. All we have to do is to make a running total of bars (our x 
coordinate) using cum() function:</P>
<BLOCKQUOTE>
<P><CODE>x = cum( 1 );</CODE></P></BLOCKQUOTE>
<P>and then find out where low occured using valuewhen() function:</P>
<BLOCKQUOTE>
<P><CODE>bar1 = valuewhen( low == low1, x, 1 );<BR>bar2 = valuewhen( low == 
low2, x, 1 );</CODE></P></BLOCKQUOTE>
<P>Since trend lines are different for each stock, now I will show you the whole 
thing using AXP (American Express) quotes.<BR>We can observe quite nice trend on 
this stock, with two important lows on March 9th, 2000 (low price 39.7648) and 
June, 22th 2000 (low price 51.9375) as show in the picture below:</P>
<P><IMG alt="" border=0 hspace=0 
src="cid:001401c057a4$3a5cfec0$0100007f@xxxx";></P>
<P>Note that StartY and EndY parameters of the trendline are exactly equal the 
low prices of the days - this is extremely important since we will be searching 
for this values using valuewhen() function (actual lows could be determined 
using data tooltip).</P>
<P><IMG alt="" border=0 hspace=0 
src="cid:001501c057a4$3a5cfec0$0100007f@xxxx";></P>
<P>So we have startvalue = 39.7648 and endvalue = 51.9375 and we can write an 
AFL formula for the trendline:</P>
<BLOCKQUOTE>
<P><CODE>x = cum(1);</CODE></P>
<P><CODE>startvalue = 39.7648;<BR>endvalue = 51.9375;</CODE></P>
<P><CODE>startbar = lastvalue( valuewhen( low == startvalue, x, 1 ) 
);<BR>endbar = lastvalue( valuewhen( low == endvalue, x, 1 ) );</CODE></P>
<P><CODE>a = (endvalue-startvalue)/(endbar-startbar);<BR>b = 
startvalue;</CODE></P>
<P><CODE>trendline = a * ( x - startbar ) + b; </CODE></P></BLOCKQUOTE>
<P>A trend line could be now drawn with a price chart using the following 
assignments:</P>
<BLOCKQUOTE>
<P><CODE>graph1 = trendline;<BR>graph0 = close;</CODE></P>
<P><CODE>/* some color + style settings 
*/<BR>graph0style=64;<BR>graph0color=2;<BR>graph1style = 5;<BR>graph1color = 
8;</CODE></P></BLOCKQUOTE>
<P>Now we can test trend line break using the following formulas:</P>
<BLOCKQUOTE>
<P><CODE>buy = cross( close, trendline ); /* buy signal when close crosses 
above the trendline */<BR>sell = cross( trendline, close ); /* sell signal 
when close crosses below the trend line */</CODE></P></BLOCKQUOTE>
<P></P>
<P>Note that these tests are correct only for single stock, so in fact we should 
check the ticker name before:</P>
<BLOCKQUOTE>
<P><CODE>buy = name()=="AXP" AND cross( close, trendline ); <BR>sell = 
name()=="AXP" AND cross( trendline, close ); </CODE></P></BLOCKQUOTE>
<P>As you can see the whole procedure is a little bit confusing and need tobe 
repeated for every stock individually. But what about making it automatic? Yes - 
it is possible in AFL! AmiBroker Formula Language has the functions for 
detecting important lows and highs (through(), peak() functions) and we canuse 
them to generate automatic trend lines. Just let AmiBroker two last important 
lows for us using the following formula:</P>
<BLOCKQUOTE>
<P><CODE>perchg = 10;</CODE></P>
<P><CODE>startvalue = lastvalue( trough( low, perchg, 1 ) );<BR>endvalue = 
lastvalue( trough( low, perchg, 2 ) );</CODE></P></BLOCKQUOTE>
<P>where <I>perchg</I> is a variable that controls minimum change thresholdfor 
finding lows. The rest of the formula remains the same, so complete automatic 
trend line formula using lows and 10% minimum change looks as follows:</P>
<BLOCKQUOTE>
<P><CODE>x = cum(1);</CODE></P>
<P><CODE>perchg = 10;</CODE></P>
<P><CODE>startvalue = lastvalue( trough( low, perchg, 1 ) );<BR>endvalue = 
lastvalue( trough( low, perchg, 2 ) );</CODE></P>
<P><CODE>startbar = lastvalue( valuewhen( low == startvalue, x, 1 ) 
);<BR>endbar = lastvalue( valuewhen( low == endvalue, x, 1 ) );</CODE></P>
<P><CODE>a = (endvalue-startvalue)/(endbar-startbar);<BR>b = 
startvalue;</CODE></P>
<P><CODE>trendline = a * ( x - startbar ) + b; </CODE></P>
<P><CODE>graph0 = close;<BR>graph1 = 
trendline;<BR>graph0style=64;<BR>graph0color=2;<BR>graph1style = 
5;<BR>graph1color = 8;</CODE></P></BLOCKQUOTE>
<P>I am not saying that this formula is perfect. It sometimes generates strange 
trend lines and it strongly depends on <I>perchg</I> parameter. You can of 
course use peak() function instead of trough() to base your trend line on highs 
instead of lows.</P>
<P>As for the future - in some next version of AmiBroker the support for alerts 
on studies will be enhanced so watch out!</P>
<P><I>( Note: the formulas presented here are also available from <A 
href="http://www.amibroker.com/library.html";>http://www.amibroker.com/library.html</A> 
) </I></P>
<P><B>4 Tip of the week: : How to automate assigning stocks to 
sectors/industries ?</B></P>
<P><I><FONT size=-2>Note: This functionality is available only in Windows 
version of AmiBroker</FONT></I></P>
<P>In the <A href="http://www.amibroker.com/newsletter/01-2000.html";>first 
issue</A> of AmiBroker Tips newsletter AmiBroker I discussed using of 
AmiBroker's OLE automation interface for accessing stock data. In this article I 
will give you another example of automation: assigning stocks to industries 
using simple JScript. For starters I recommend reading the <A 
href="http://www.amibroker.com/newsletter/01-2000.html";>first article</A>before 
proceeding with this one. </P>
<P>First we should set up our sectors and industries using 
<I><B>Stock-&gt;Categories</B></I> window. The difference between a sector and 
an industry is that industries "belong" to sectors, for example: "Air Courier", 
"Airline", "Railroads", "Trucking" industries belong to "Transportation" sector. 
So an assignment to an industry implicts assignment to a sector. If you don't 
want to have detailed industries you can just assign first 32 industries to32 
sectors on one-by-one basis. </P>
<P>Now let's suppose that we have a text file that contains tickers, full 
company names and a industry number. Industry number should correspond our 
settings in <B>Categories</B> window. A sample file would look like this:</P>
<BLOCKQUOTE>
<P><CODE>ELM,ELINK MEDIA LIMITED,0 <BR>GCN,GOCONNECT LIMITED,0 
<BR>SGN,SINGLETON GROUP LIMITED,1 <BR>AHH,AGRO HOLDINGS LIMITED,1<BR>ATP,ATLAS 
PACIFIC LIMITED,1<BR>AFF,AUSTRALIAN FOOD &amp; FIBRE 
LIMITED,1<BR>ASR,AUSTRALIAN RURAL GROUP LIMITED,1<BR>ARP,ARB CORPORATION 
LIMITED,2<BR>ATL,AUTO ENTERPRISES LIMITED,2<BR>ALO,AUTO GROUP 
LIMITED,2<BR>BER,BERKLEE LIMITED,2<BR>ADB,ADELAIDE BANK 
LIMITED,3<BR></CODE><CODE>ANZ,AUSTRALIA &amp; NEW ZEALAND BANKING GROUP 
LIMITED,3<BR>BOQ,BANK OF QUEENSLAND LIMITED.,3<BR>BWA,BANK OF WESTERN 
AUSTRALIA LIMITED,3<BR></CODE></P></BLOCKQUOTE>
<P>and our Categories are set up so sectors and industires have one-to-one 
relationship with the following (zero-based) numbering 0 - "Advertising &amp; 
Marketing", 1- "Agriculture &amp; Related Services", 2- "Automotive &amp; 
Related Services" and 3- "Banking".</P>
<P>The script for importing the data file will look like this:</P>
<BLOCKQUOTE>
<P><CODE><FONT color=#0000ff>/* change this line according to your datafile 
name */</FONT><I><BR></I>var filename = "industry_data.txt";</CODE></P>
<P><CODE>var fso, f, r;<BR>var ForReading = 1;<BR>var AmiBroker;<BR>var 
fields;<BR>var stock;</CODE></P>
<P><CODE><FONT color=#0000ff>/* Create AmiBroker app object 
*/</FONT><BR>AmiBroker = new ActiveXObject( "Broker.Application" );</CODE></P>
<P><CODE><FONT color=#0000ff>/* ... and file system object */</FONT><BR>fso = 
new ActiveXObject( "Scripting.FileSystemObject" );</CODE></P>
<P><CODE><FONT color=#0000ff>/* open ASCII file */</FONT><BR>f = 
fso.OpenTextFile( filename, ForReading);</CODE></P>
<P><CODE><FONT color=#0000ff>/* read the file line by line */</FONT><BR>while 
( !f.AtEndOfStream )<BR>{</CODE></P>
<BLOCKQUOTE>
<P><CODE>r = f.ReadLine();<BR><BR><FONT color=#0000ff>/* split the lines 
using comma as a separator */</FONT><BR>fields = r.split(","); <BR><BR><FONT 
color=#0000ff>/* add a ticker - this is safe operation, in case that 
*/<BR>/* ticker already exists, AmiBroker returns existing one 
*/</FONT><BR>stock = AmiBroker.Stocks.Add( fields[ 0 ] ); 
<BR><BR>stock.FullName = fields[ 1 ];<BR>stock.IndustryID = parseInt( 
fields[ 2 ] );<BR></CODE></P></BLOCKQUOTE>
<P><CODE>}</CODE></P>
<P><CODE><FONT color=#0000ff>/* refresh ticker list and windows 
*/</FONT><BR>AmiBroker.RefreshAll();</CODE></P></BLOCKQUOTE>
<P>The whole thing is just reading the file line by line and assigning the 
fields to properties of stock automation object. It's so simple :-). The only 
thing that you might want to change is the name of the file with a data - my 
example uses "Industry_data.txt" file name but this can be changed according to 
your naming convention. A complete script could be found <A 
href="Industries.js">here</A> and a sample data file is <A 
href="Industry_data.txt">here</A>. </P>
<P><I>.... and that's all for this week - hope you enjoyed reading</I> </P>
<HR>

<P><FONT size=-2>AmiBroker Tips weekly newsletter. Issue 4/2000. 
Copyright&nbsp;(C)2000&nbsp;Tomasz&nbsp;Janeczko. All back issues available 
from: <A 
href="http://www.amibroker.com/newsletter/";>http://www.amibroker.com/newsletter/</A></FONT></P>
<P> </P></DIV>
<DIV>&nbsp;</DIV></BODY></HTML>

------=_NextPart_002_0018_01C057AC.9C3B5760--

------=_NextPart_001_0017_01C057AC.9C3B5760
Content-Type: image/gif;
name="logo.gif"
Content-Transfer-Encoding: base64
Content-ID: <001101c057a4$3a4c35e0$0100007f@xxxx>
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------=_NextPart_001_0017_01C057AC.9C3B5760
Content-Type: image/gif;
name="tut2categories.gif"
Content-Transfer-Encoding: base64
Content-ID: <001201c057a4$3a5cfec0$0100007f@xxxx>
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------=_NextPart_001_0017_01C057AC.9C3B5760
Content-Type: image/gif;
name="tut2recalc.gif"
Content-Transfer-Encoding: base64
Content-ID: <001301c057a4$3a5cfec0$0100007f@xxxx>
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------=_NextPart_001_0017_01C057AC.9C3B5760
Content-Type: image/gif;
name="4chart.gif"
Content-Transfer-Encoding: base64
Content-ID: <001401c057a4$3a5cfec0$0100007f@xxxx>
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------=_NextPart_001_0017_01C057AC.9C3B5760
Content-Type: image/gif;
name="4properties.gif"
Content-Transfer-Encoding: base64
Content-ID: <001501c057a4$3a5cfec0$0100007f@xxxx>
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------=_NextPart_001_0017_01C057AC.9C3B5760--

Attachment:
Description: Binary data
ELM,ELINK MEDIA LIMITED,0 
GCN,GOCONNECT LIMITED,0
SGN,SINGLETON GROUP LIMITED,1 
AHH,AGRO HOLDINGS LIMITED,1
ATP,ATLAS PACIFIC LIMITED,1
AFF,AUSTRALIAN FOOD & FIBRE LIMITED,1
ASR,AUSTRALIAN RURAL GROUP LIMITED,1
ARP,ARB CORPORATION LIMITED,1
ATL,AUTO ENTERPRISES LIMITED,1
ALO,AUTO GROUP LIMITED,2
BER,BERKLEE LIMITED,2
ADB,ADELAIDE BANK LIMITED,3
ANZ,AUSTRALIA & NEW ZEALAND BANKING GROUP LIMITED,3
BOQ,BANK OF QUEENSLAND LIMITED.,3

Attachment: Description: "BWA,BANK OF WESTERN AUSTRALIA LIMITED,3"