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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:
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">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">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 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">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">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">Arthur
Merrill also had a good explanation in a recent issue of <SPAN
style="FONT-SIZE: 9pt">STOCKS & <SPAN
style="FONT-SIZE: 9pt">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">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">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">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">
....
<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">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">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">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">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">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">• 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">• 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">• 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">• 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">•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">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">•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>•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">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">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">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
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">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">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 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">shows,
%F provided a timely warning of an impending trend change just before the
OEX 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">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">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-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: 11pt; FONT-FAMILY: Arial">& <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: 11pt; FONT-FAMILY: Arial">& <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
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