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>It would also help if you believed in the need to use actual prices
>instead of backadjusted prices and that you have access to such
>information.
Does 'backadjusted prices' mean split-adjusted price data?
Phsst
--- In amibroker@xxxxxxxxxxxxxxx, "Chuck Rademacher"
<chuck_rademacher@x> wrote:
> I have come up with some fairly profitable ways of using one of AB's
very
> powerful features (AddToComposite). Perhaps my approach is already
old hat
> to many of you, in which case it's easy to hit the delete button. I'm
> hoping, however, to stir up some dialogue regarding the concept in hopes
> that we can help each other through brainstorming the idea(s) even
further.
>
> In order to best utilise what I am proposing, you would ideally have a
> system that generates lots of trades (1,000 plus) and you would
already be a
> believer in backtesting over several years of data. It would also
help if
> you believed in the need to use actual prices instead of
backadjusted prices
> and that you have access to such information. You can still
benefit from
> this approach without these conditions being true, but not as much.
>
> The first idea that I'm going to describe assumes that stocks in
different
> price brackets do better than other stocks and that the bracket of
the best
> performers changes over time. I have proven, at least to myself,
that this
> assumption is valid. I'm sure all of you have heard commentators
saying
> that the mid-cap stocks have been outperforming the large-cap
recently or
> the micro-cap stocks have been the best performers over the last 30
days,
> etc.
>
> Let's assume that you have a fairly profitable system that generates too
> many trades in proportion to the amount of cash you have available.
One
> way of reducing the number of trades would be to only take trades
for stocks
> in the price range that has been performing the best in recent
times. I
> made several composite files that contain the average returns for
various
> price brackets. For instance, I made a composite file containing the
> returns for stocks in the $1 to $5 price range, $6 to $10 price
range, etc.
> I used a simple formula (close/ref(close,-20)) for determining the
returns
> and wrote the composite with a count for how many stocks met the
criteria
> each day as well as the total returns for all of the stocks meeting the
> criteria each day.
>
> When I run a scan or optimization using my trading system, I can
read these
> composite files (using the Foreign function) and calculate average
returns
> for each price bracket. Each day, I can determine which price
brackets
> are performing the best (or worst for shorting) and filter my trades
to only
> trade the best one or two price brackets. Of course, you can use
various
> smoothing techniques to filter out some of the noise.
>
> By placing this price bracket ranking in one of my Exploration
columns, I
> can place my orders for the day by working my way down the buy (or
short)
> signals in sequence until I run out of cash.
>
> I have backtested this technique and it adds enough additional
profit to the
> bottom line to make it worthwhile. Sectors and/or industries work
well if
> substituted for price brackets.
>
> Here's another idea, very much related to the one above. Let's say
that
> you like to use moving average systems. Or you would like to use
them, but
> have trouble making them dynamic enough to adjust to various market
> conditions and cycles. For sake of simplicity, we'll just look at a
> simple two-period crossover system. Let's say that the short timeframe
> might range from three to eight days and the long timeframe might go
from
> eleven to 20 days. What I did in this case was make the following
> composite files:
>
> ~Composite311 (will contain returns based on using a 3/11 crossover)
> ~Composite312 (will contain returns based on using a 3/12 crossover)
> etc.
>
>
> I then run my system over historical data, creating a composite for
each of
> the possible timeframes (3/11, 3/12, 3/13, etc.). Tedious for
sure. If
> you are determined to use a moving average crossover system,
however, this
> is worth the effort.
>
> Each composite file would contain the equity curve information resulting
> from using the applicable crossover periods.
>
> The actual trading system would determine (each day) which of the
various
> timeframe possibilities has been performing over the last 20, 30,
etc. days
> and would use the relevant timeframes for trading going forward.
>
> There is a problem with what to do with trades that were entered
using one
> pair of timeframes when you switch to using another. But you have
to deal
> with this problem anyway if you are going to use any sort of dynamically
> adjusted moving average or similar system.
>
> Another idea that I am playing with has two composite files. One
containing
> the results derived from trading the same system on stocks paying high
> yields and the other for stocks with low debt/equity ratios.
Through time,
> I can see definite times when one of these groups has better returns
than
> the other. Emphasis of investors and traders seems to switch from
yield to
> debt and back again over time.
>
> Just a couple of ideas. The first one (price brackets) seem to
have the
> best reward for the amount of time invested. Substituting sectors for
> price brackets produced some interesting results. It frequently
pays to
> buy the worst performing sectors as long as the peformance is
working its
> way back to the top. Of course, you could substitute actual market
cap for
> price brackets too.
>
> Have a think... you'll surely come up with some ways to use and/or
improve
> on what I've done.
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