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Re: Forecast Oscillator



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Steve,
Since the TIMESERIES calc method of a moving average is the 
moving average x the slope, give this a whirl:
 
T1:=Input("Time Periods",2,250,13);P1:=Input("Data: 1=C 
2=Median 3=Typical 4=Wt. 
Close",1,4,1);P2:=If(P1=1,C,If(P1=2,MP(),If(P1=3,Typ(),If(P1=4,WC(),C))));T2:=Input("Signal 
Periods",1,200,3);V1:=Input("Threshold",0,10,3);A2:=((P2-Ref(Mov(P2,T1,TIMESERIES),-1))*100)/P2;A2;Mov(A2,T2,E);V1;-V1
 
Maybe yaa, maybe nah...
 
-Corey.
 
<BLOCKQUOTE dir=ltr 
style="PADDING-RIGHT: 0px; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #000000 2px solid; MARGIN-RIGHT: 0px">
  ----- Original Message ----- 
  <DIV 
  style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
  Steve 
  Karnish 
  To: <A title=metastock@xxxxxxxxxxxxx 
  href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx 
  Sent: Thursday, January 10, 2002 7:59 
  PM
  Subject: Re: Forecast Oscillator
  
  Sorry Nick,
   
  I don't have an "expert".  The picture can 
  be duplicated by selecting the Forecast Oscillator and setting it to 13 
  periods.  The system tester is simply:
   
  Enter long:  
  Cross(-3.4,ForecastOsc(CLOSE,13))
   
  Enter 
  short: Cross(ForecastOsc(CLOSE,13),3.4)
   
  I always trade the following day's opening (you 
  must set the tester to delay "1"...to represent entry on the "next" day.  
  Also, due to the nature of this oscillator, any testing/optimizing of trigger 
  levels must take in consideration that each issue can develop a range from 2 
  to about 15 percent.  This makes optimizing levels for individual issues 
  a bit of a pain.
   
  Take care,
   
  Steve
  <BLOCKQUOTE dir=ltr 
  style="PADDING-RIGHT: 0px; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #000000 2px solid; MARGIN-RIGHT: 0px">
    ----- Original Message ----- 
    <DIV 
    style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
    <A title=nick.channon@xxxxxxxxxxxxx 
    href="mailto:nick.channon@xxxxxxxxxxxxx";>Nick Channon 
    To: <A title=metastock@xxxxxxxxxxxxx 
    href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx 
    Sent: Thursday, January 10, 2002 7:03 
    PM
    Subject: Re: Forecast Oscillator
    
    Steve, that looks very good. Could you kindly 
    save me time by posting the expert?
    Many thanks,
    Nick
    <BLOCKQUOTE dir=ltr 
    style="PADDING-RIGHT: 0px; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #000000 2px solid; MARGIN-RIGHT: 0px">
      ----- Original Message ----- 
      <DIV 
      style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
      Steve 
      Karnish 
      To: <A title=metastock@xxxxxxxxxxxxx 
      href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx 
      Sent: Friday, January 11, 2002 6:56 
      AM
      Subject: Re: Forecast 
Oscillator
      
      Thanks Peter,
       
      I use this formula much differently than 
      Chande suggests.  I've had a lot of success with a 13 period 
      FO.  I plot the formula and establish equidistant levels (from 
      zero) that trigger buy and sell signals.  Simple, but 
      effective.  This approach is graphically displayed in the 
      attachment.  I like the FO because it can be somewhat "adaptive" (and 
      it can pull twenty bucks out of crude).  
       
      Thanks again, Equis doesn't "trust" us with 
      the formula.  If you "click" on the little "arrow&?", on the 
      task bar, in MetaStock and drop it on the Forecast Oscillator you get the 
      following blurb:
       
      "The oscillator is above zero when the 
      forecast price is greater than the actual price.  Conversely, it's 
      less than zero if its below."
       
      Of course, this is totally false (the 
      opposite is true).  Which of edition of MetaStock do you believe 
      they might correct their mistake?
       
       
      Take Care, 
       
      Steve
       
       
       
       
       
      ----- Original Message ----- 
      <BLOCKQUOTE dir=ltr 
      style="PADDING-RIGHT: 0px; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #000000 2px solid; MARGIN-RIGHT: 0px">
        <DIV 
        style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
        <A title=investor@xxxxxxxxxxxxx 
        href="mailto:investor@xxxxxxxxxxxxx";>Peter Gialames 
        To: <A 
        title=metastock@xxxxxxxxxxxxx 
        href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx 
        Cc: <A title=kernish@xxxxxxxxxxxx 
        href="mailto:kernish@xxxxxxxxxxxx";>kernish@xxxxxxxxxxxx 
        Sent: Thursday, January 10, 2002 
        9:45 AM
        Subject: RE: Forecast 
        Oscillator
        
        <FONT face=Arial color=#0000ff 
        size=2>Not sure if this is what you are looking for but 
        ...
        <FONT face=Arial color=#0000ff 
        size=2> 
        <FONT face=Arial color=#0000ff 
        size=2>Peter Gialames
        <FONT face=Arial color=#0000ff 
        size=2> 
        
        Here is the text from 
        S&C V. 10:5 (220-224): Forecasting Tomorrow's Trading Day by Tushar 
        S. Chande, Ph.D.
         
        
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Using linear regression as a crystal ball for forecasting the 
        market? After all, if you were to be able to
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>determine tomorrow's high, low and close for trend changes and 
        placement of stop points, it would
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>simplify your life immeasurably. Can it work? Tushar Chande 
        explains how it can be done.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Wouldn't you trade better It you could "see" the future? A simple 
        linear regression can provide an
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>objective forecast for the next day's high, low and close. These 
        ingredients are essential for a trading
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>game plan, which can help you trade more mechanically and less 
        emotionally. Best of all, a regression
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>forecast oscillator, %F, gives early warning of impending trend 
        changes. The linear regression method is
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>well known for finding a "best-fit" straight line for a given set 
        of data. The output of the regression are
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>the slope (m) and constant (c) of the 
        equation
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>(1)Y = mX + c
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Here, m and c are derived from a known set of 
        values of the independent variable X and dependent
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>variable Y. The relative strength of the linear relationship 
        between X and Y is measured by the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>coefficient of determination r <SPAN 
        style="FONT-SIZE: 10pt">2 , which is the ratio of 
        the variation explained by the regression line to the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>total variation in Y. Here is a table to help interpret the 
        values of r 2 , 
        which range from 0 to 1:
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>The coining of the term "regression" can be attributed to Sir 
        Francis Galton, who observed in the late
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>1800s that tall fathers appeared to have as a rule short sons, 
        while short fathers appeared to have as a rule
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>tall sons. Galton suggested that the heights of the sons 
        "regressed" or reverted to the average. Technician
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Arthur Merrill also had a good explanation in a recent issue of 
        STOCKS & 
        COMMODITIES, and 
        Patrick
        Lafferty 
        recently wrote on an application of multiple regression to gold trading. 
        Virtually all introductory
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>books on statistics have a detailed discussion of the linear 
        regression method.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Successful professional traders emphasize the importance of 
        having a trading plan. A trading game plan,
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>much like that of a football team, clearly defines specific 
        actions under different conditions. The linear
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>regression method is very useful in developing a forecast for the 
        next trading day's high, low and close
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>based on the last five trading sessions. The method is general 
        and broad-based enough so that it can be
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>used with stocks, indices or commodities. The forecast is the 
        basis of my trading plan: I can define what I
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>should do if the market rises above the forecast high, falls 
        below the forecast low or stays within the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>forecast range. This way, I can avoid being emotional and trade 
        as mechanically as possible by having a
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>plan to rely on.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 9pt">FORECASTING WITH LINEAR 
        REGRESSION
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">I 
        like to use at least 10 days of data and develop a forecast for the 
        high, low and close. The five-day
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>regression is a good choice for short-term trading. You can use 
        any length of regression you like. Here
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>are the calculations with the daily close in a spreadsheet 
        format:
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">1 
        Perform a linear regression with the first five days of data to obtain 
        the slope m and constant c such
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>that
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">X 
        Value    Daily Close
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>   
        1                Day 
        1
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>   
        2                Day 
        2
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>  ....
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>   
        5                
        Day 5
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">2 
        Forecast the next day's close with the slope m and constant c 
        from step 1:
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>(2) Forecast close (Day 6) = 6m + c
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">3 
        Record m, c and r 2 on the same line as Day 5. Record the 
        forecast from step 2 one day ahead, with
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Day 6. Note when we are using five days' data, the first forecast 
        is for Day 6.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">4 
        Step the calculation ahead one day such that
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">5 
        Record m, c and r 2 as in step 3.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">6 
        Calculate the regression forecast oscillator, %F, as
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>(3)
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 10pt">%F  = ((Y-Yforecast)/Y)*100
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>where Y is the close for Day 6 and Y(Forecast) is the forecast 
        for Day 6 from step 2 (from Day 5).
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">7 
        Record the oscillator on the same line as Day 6.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">8 
        Step the calculations ahead one day at a time until the most recent 
        day.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Technically, we can use the linear regression to develop a point 
        forecast (single value) for the next day
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>(as in step 2) or a range (interval) of values with a certain 
        confidence level. The interval widens, greater
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>the variation in the data and greater the desired confidence 
        level.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">I 
        use the forecast oscillator, %F, to determine if my forecast is above or 
        below the actual market data.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Since
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 10pt">%F  = ((Y-Yforecast)/Y)*100
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 10pt"> 
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 10pt">where Y can be any market 
        variable for stocks, indices or commodities, %F measures the 
        percent
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>deviation of the actual value from its forecast. In a trading 
        market, %F changes its sign before a
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>significant trend change. In trending markets, %F tends to change 
        sign early in the trend. I interpret %F in
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>the context of the r 2 
        Of the regression. A low value of r <SPAN 
        style="FONT-SIZE: 10pt">2 plus a change in sign of 
        %F is a good signal of a
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>change in trend. Market extremes and periodicity can also be 
        observed on the %F charts.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 9pt">DEVELOPING A TRADING 
        PLAN
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>You can use the forecasts to develop a specific trading plan to 
        suit your trading style. I use the forecasts
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">in 
        several ways.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Forecasts as stops. I use the high and the low as 
        action points. If the market exceeds the forecast high, it
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>wants to go up. To trade with the trend, I put a buy stop a few 
        ticks above the high. If the market falls
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>below the forecast low, it wants to go down. Hence, I set a sell 
        stop a few ticks below the forecast low. If
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>you want to trade against the trend, sell short near the forecast 
        high and buy near the forecast low.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Forecasts as intraday range scale. The forecasts 
        provide a scale for evaluating the trading day. The
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>market can stay within the expected range or go outside. On a 
        down day, the intraday high is well below
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>the forecast high and may be below the forecast close. On an up 
        day, the market stays well above the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>forecast low and often above the forecast close.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>General rules for trading with forecasts. Here are 
        some general rules:
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">&#8226; 
        Use the forecasts only if r 2 is greater than 0.1. Higher the value of r 
        2 , the greater the confidence in the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>forecasts.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">&#8226; 
        A trend change is imminent when r 2 falls below 0.1. Prepare to close 
        longs.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">&#8226; 
        A trend is in place if r 2 is greater than 0.6. As a trend follower, you 
        could wait for this value to be
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>exceeded before opening positions. This would keep you out of 
        short-term fluctuations.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">&#8226; 
        An early warning of a trend change is provided by a zero-crossing of %F, 
        the forecast oscillator.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Prepare to tighten stops and look for changes in slope and 
        coefficient of determination for
        <FONT 
        size=3>confirmation.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">&#8226;A 
        change in trend is confirmed by a change in slope of the regression. 
        Open positions in direction of
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>trend change. To trade against the trend, look for peaks in slope 
        and strength of the linear trend.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>&#8226;The trend will usually change in the direction of %F.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>&#8226;Always be prepared for a market move against the forecast. Use 
        stops!
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>A SAMPLE TRADING 
        PLAN
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">I 
        have developed a forecast for the high, low and close for January 20, 
        1992, from the previous five
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>trading days, seen in Figure 1. The market was making new highs 
        the previous week. Was a downward
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>movement imminent? Let's look at the data from Friday, January 
        17, 1992:
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>The market was trending moderately (0.4<= r <SPAN 
        style="FONT-SIZE: 10pt">2 <0.6), but the forecast 
        oscillator %F was negative for
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>high, low and close, warning of a possible change in trend. The 
        relatively small slope of the regression
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>for the high meant the market was meeting resistance. The slope 
        of the regression for the close had turned
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>down from the high values during the recent strong uptrend. The 
        forecast, however, called for a strong
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>close near the highs of the day, but that seemed doubtful, given 
        the low slopes in a moderating trend. The
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>plan was to watch for a change in trend. If the market opened 
        weak, a bearish strategy was called for. For
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>example, I would consider buying the Standard & Poor's 100 
        Index OEX <FONT 
        size=3>January 390 puts, or selling
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>short the S&P 500 March futures contract.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 16pt; FONT-FAMILY: Arial">The high daily volume of 
        OEX 
        <SPAN 
        style="FONT-SIZE: 16pt; FONT-FAMILY: Arial">index options traded makes 
        the S&P
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 16pt; FONT-FAMILY: Arial">100 index an interesting 
        application of me regression forecast
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 16pt; FONT-FAMILY: Arial">approach.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>The market opened at the Friday close and weakness was evident at 
        the open, as the S&P 500 futures
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>opened lower. It was clear in early trading that the trend would 
        be down, as the market traded well below
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>the forecast high and close. Clearly, the forecast range provided 
        a good scale, since it reinforced the
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>concept that the market was weaker than the trend of the prior 
        five days. A bearish stance would have
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>been profitable.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 9pt">THE NATURE OF REGRESSION 
        FORECASTS
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>The high daily volume of OEX 
        index options traded makes the S&P 100 index an 
        interesting application
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">of 
        the regression forecast approach. I have examined a time period from 
        early October 1991 to
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>mid-January 1992. The OEX 
        close and its forecast are in Figure 2; the r 
        2 values in 
        Figure 3; %F in Figure
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">4, 
        and Figure 5 has %F around the mid-November plunge.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Several observations can be made from the <SPAN 
        style="FONT-SIZE: 9pt">OEX analysis. First, the 
        forecast lags the OEX <FONT 
        size=3>in an uptrend
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">or 
        in a downtrend. Second, the close and the forecast cross over several 
        days before a trend change. This
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>crossover can be seen as a zero crossing in the %F chart. 
        Significant trend changes are preceded by
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>trendless periods with values of r <SPAN 
        style="FONT-SIZE: 10pt">2 near zero. Strong trends 
        are accompanied by high values of r <SPAN 
        style="FONT-SIZE: 10pt">2 and
        regression 
        slope. These observations support the general rules of interpretation 
        noted above. As Figure 5
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>shows, %F provided a timely warning of an impending trend change 
        just before the OEX <FONT 
        size=3>fell 15.68 points.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">I 
        have included data for wheat (cash) from 1989 to indicate the use of 
        this approach with commodities.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>The market showed significant trends during this period with good 
        periodicity, as shown in Figures 6, 7
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>and 8. The %F zero crossings were timely indicators of trend 
        change. Features observed with OEX 
        charts
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>are also seen here; note in particular how %F can be used to 
        identify extremes in the market from Figures
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">4 
        and 8.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Simple linear regression yields forecasts of the high, low and 
        close for stocks, indices or commodities.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>these forecasts can be used to develop a trading plan. You can 
        trade with the trend, against the trend,
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>intraday or interday. The forecast oscillator, %F, provides early 
        warning of trend changes taken together
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>with the regression slope and coefficient of determination. This 
        approach works best in trending markets
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">or 
        trading range markets; it is only moderately useful in volatile markets 
        with choppy price action. These
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>objective forecasts will let you trade less emotionally and more 
        mechanically. Profits will look up when
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>you can look ahead.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>Tushar Chande holds a doctorate in engineering from the 
        University of Illinois and a master's degree 
in
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><FONT 
        size=3>business administration from the University of 
        Pittsburgh.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 8pt; FONT-FAMILY: Arial">REFERENCES
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Lafferty, Patrick [ 1991 ]. 
        "A regression-based oscillator," <SPAN 
        style="FONT-SIZE: 11.5pt; FONT-FAMILY: Arial">Technical Analysis of 
        STOCKS 
        & 
        <SPAN 
        style="FONT-SIZE: 8pt; FONT-FAMILY: Arial">COMMODITIE<SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">S,
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Volume 9: 
        September.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Merrill, Arthur [1991]. 
        "Fitting a trendline by least squares," <SPAN 
        style="FONT-SIZE: 11.5pt; FONT-FAMILY: Arial">Technical Analysis of 
        STOCKS 
        & 
        <SPAN 
        style="FONT-SIZE: 8pt; FONT-FAMILY: Arial">COMMODITIE<SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">S,
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Volume 9: 
        December.
        <P class=MsoNormal 
        style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Pfaffenberger, Roger, and 
        James Patterson [1987]. <SPAN 
        style="FONT-SIZE: 11.5pt; FONT-FAMILY: Arial">Statistical Methods for 
        Business and Economic<SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">s,
        <SPAN 
        style="FONT-SIZE: 11pt; FONT-FAMILY: Arial">Irwin.
        
          <FONT face=Tahoma 
          size=2>-----Original Message-----From: 
          owner-metastock@xxxxxxxxxxxxx 
          [mailto:owner-metastock@xxxxxxxxxxxxx]On Behalf Of Steve 
          KarnishSent: Thursday, January 10, 2002 10:34 
          AMTo: metastock@xxxxxxxxxxxxxSubject: Forecast 
          Oscillator
          List,
           
          Does anyone have the math formula for 
          Chande's Forecast Oscillator?  
           
          Thanks,
           
          <FONT face=Arial 
    size=2>Steve