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Re: Forecast Oscillator



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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="BORDER-LEFT: #000000 2px solid; MARGIN-LEFT: 5px; MARGIN-RIGHT: 0px; PADDING-LEFT: 5px; PADDING-RIGHT: 0px">
  ----- Original Message ----- 
  <DIV 
  style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
  <A href="mailto:nick.channon@xxxxxxxxxxxxx"; 
  title=nick.channon@xxxxxxxxxxxxx>Nick Channon 
  To: <A 
  href="mailto:metastock@xxxxxxxxxxxxx"; 
  title=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="BORDER-LEFT: #000000 2px solid; MARGIN-LEFT: 5px; MARGIN-RIGHT: 0px; PADDING-LEFT: 5px; PADDING-RIGHT: 0px">
    ----- Original Message ----- 
    <DIV 
    style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
    Steve 
    Karnish 
    To: <A 
    href="mailto:metastock@xxxxxxxxxxxxx"; 
    title=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="BORDER-LEFT: #000000 2px solid; MARGIN-LEFT: 5px; MARGIN-RIGHT: 0px; PADDING-LEFT: 5px; PADDING-RIGHT: 0px">
      <DIV 
      style="BACKGROUND: #e4e4e4; FONT: 10pt arial; font-color: black">From: 
      Peter 
      Gialames 
      To: <A 
      href="mailto:metastock@xxxxxxxxxxxxx"; 
      title=metastock@xxxxxxxxxxxxx>metastock@xxxxxxxxxxxxx 
      Cc: <A 
      href="mailto:kernish@xxxxxxxxxxxx"; 
      title=kernish@xxxxxxxxxxxx>kernish@xxxxxxxxxxxx 
      Sent: Thursday, January 10, 2002 9:45 
      AM
      Subject: RE: Forecast 
Oscillator
      
      <FONT color=#0000ff face=Arial 
      size=2>Not sure if this is what you are looking for but 
      ...
      <FONT color=#0000ff face=Arial 
      size=2> 
      <FONT color=#0000ff face=Arial 
      size=2>Peter Gialames
      <FONT color=#0000ff face=Arial 
      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">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">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">the 
      slope (m) and constant (c) of the equation
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">(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">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">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">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">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">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">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">(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">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">(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">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">the 
      context of the r 2 <FONT 
      size=3>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">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">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">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">&#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">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">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">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">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">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 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-FAMILY: Arial; FONT-SIZE: 16pt">The high daily volume of 
      OEX 
      <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 16pt">index options traded makes the 
      S&P
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 16pt">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-FAMILY: Arial; FONT-SIZE: 16pt">approach.
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">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">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">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">The 
      high daily volume of OEX <FONT 
      size=3>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 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">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">and 
      8. The %F zero crossings were timely indicators of trend change. Features 
      observed with OEX <FONT 
      size=3>charts
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none">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">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">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-FAMILY: Arial; FONT-SIZE: 8pt">REFERENCES
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">Lafferty, Patrick [ 1991 ]. "A 
      regression-based oscillator," <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11.5pt">Technical Analysis of 
      STOCKS 
      & 
      <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 8pt">COMMODITIE<SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">S,
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">Volume 9: 
      September.
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">Merrill, Arthur [1991]. 
      "Fitting a trendline by least squares," <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11.5pt">Technical Analysis of 
      STOCKS 
      & 
      <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 8pt">COMMODITIE<SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">S,
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">Volume 9: 
      December.
      <P class=MsoNormal 
      style="MARGIN: 0in 0in 0pt; mso-layout-grid-align: none"><SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">Pfaffenberger, Roger, and 
      James Patterson [1987]. <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11.5pt">Statistical Methods for 
      Business and Economic<SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">s,
      <SPAN 
      style="FONT-FAMILY: Arial; FONT-SIZE: 11pt">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