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I am of the view that one's position size would be best served if it
is a function of trade risk (MaxRisk in AB) and equity rather than
volatility. After finding the optimum quality (quality = expectancy
* opportunities) of a system by disabling position sizing rules, re-
enabling the position sizing rules will result in better performance
than before, especially if the sizing is a function of trade risk
and equity.
In my opinion, the market condition (trending/cyclic) does matter
when considering what type of stops to use and the type of stop (SAR
for e.g.,) may take into account the volatility. Welles Wilder
Volatility Index System is such a system study described in the
book "New Concepts in Technical Trading Systems," Trend Research,
P.O. Box 128, McLeansville N.C. 27301.
This study sets trailing stops based on a multiple of the
volatility. When a market or a stock gets less volatile, the stops
come in closer to protect profits; when volatility increases, the
stops gradually expand away from the price to avoid being hit by
random price spikes.
This system tends to trade less frequently than some other's and can
make more per trade, with fewer commissions. Other systems may be
more aggressive and make a little more in the end, but with more
trading.
Wilder originated the idea of Average True Range (ATR) which Larry
Williams later incorporated into almost all of his systems. The
Volatility Index measures the ATR and then uses a fraction of it to
add or subtract from the "most significant close in a trade" ("SIC",
i.e.: the highest or lowest close since the position was taken.) A
constant factor is then multiplied by the ATR to get the "ARC," or
Average Range times Constant. The stop-and-reverse (SAR) is placed 1
ARC below the SIC if the system is long, and 1 ARC above the SIC if
the system is short.
The bottom line is that since the SAR is calculated from an extreme
close, rather than from just the previous day's close, the system
can't miss a trend - it can be whipsawed, but if the market starts
to drift on low volatility, the stops will come in tighter, and
reverse the trade if it goes the wrong way. Since the close changes
every day, while the extreme points change only when new equity is
being made, this system, based on the trade extremes rather than the
daily closes, is very smooth and can stick with a trend for long
periods. It has the advantage over other trend followers in that it
self regulates for volatility; this can reduce the lag associated
with moving averages and oscillators, without increasing the false
signals.
This unique and valuable indicator combines well with other studies,
and allows you to filter your signals in accordance with the trend,
thus enhancing accuracy and profitability while reducing drawdown.
I've used this indicator for filtering both day and position trades.
It works well with 15 minute, 30 minute and 1 hour charts as well as
with daily charts.
one shouldn't look at just the cross-overs for signals, this is too
simplistic. One should watch the distance between the stops and the
price action. When that distance becomes very wide, a snap-back will
often take place instead of the trend change you might otherwise
expect. One should watch especially for breakout signals to confirm
the true direction at these important junctures.
When plotting Wilder's Volatility one'll need to input both a long
and short factor. Wilder's original study uses the same factor for
both long and short, but it is better to enter separate values. This
will be useful in a market that has an established trend. Make the
factor smaller in the direction of the trend. If the trend is up,
make the long factor a little smaller; this will bias the system to
be more sensitive in that direction. The reverse rules apply in a
down market.
A smaller factor makes the stops closer on that side of the market.
Wilder suggests factors of 2.8 to 3.2 but there's no set rule and
one should experiment with different markets. It can also be used
as a most excellent filter.
Wilder suggests ATR period of 7 but you can experiment. Longer
periods make the indicator smoother but tend to negate the automatic
volatility adjustment feature.
rgds, Pal
--- In amibroker@xxxxxxxxxxxxxxx, "Paul Ho" <paultsho@xxxx> wrote:
> Hi Al,
> I have been think about portfolio heat for a bit and am glad that
you
> raise the issue, You have asserted heat=n*risk, risk the risk for
each
> stock. I am not sure if this is realistic view.......
> for stock that is perfectly corelated, I think you are correct. On
the
> otherhand, for stock that are totally un-correlated, then
> heat^2=n*risk^2; or heat=sqrt(n)*risk..... Dont ask me to prove
it, i
> havent been to university for over twenty years, but i am sure
someone
> if the forum can.
> So how do we deal with stock that are correlated but not
perfect.......
> I've think a bit, and thats what I've come up with
> assuming a stock's risk can be split into two components
> 1. stock specific risk r1
> 2. market risk r2
> risk=r1+r2;
> r1 has no correlation with the market, and r2 has perfect
correlations
> therefore portfolio heat = n*r2+sqrt(n)*r1;
> So how do we find the ratio of r1:r2, I am not sure, but I suggest
the
> following
> find out sector correlationship with the market, and use that as
your
> ratio, if your universe is diverse, then may be a 60:40 is a good
> start........ i am open to suggestions here......
> I've gone further than that, like someone else to add more to this
> theory...
> Cheers
>
>
> Paul Ho
> TrustNet
> P O Box 212
> Ashburton Victoria 3147
> * <mailto:paul.ho@x...> paul.ho@xxxx
> ( 0400059655
>
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