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VERY
thought provoking Chuck! Thank you for the post.
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<FONT
face=Tahoma size=2>-----Original Message-----From: Chuck Rademacher
[mailto:chuck_rademacher@xxxxxxxxxx] Sent: Tuesday, April 22, 2003
11:19 PMTo: amibroker@xxxxxxxxxxxxxxxSubject:
[amibroker] Real world trading - brainstorming
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.
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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.
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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.
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<FONT face=Arial color=#0000ff
size=2>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.
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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 <FONT
face=Arial color=#0000ff size=2>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.
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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.
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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.
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<FONT face=Arial color=#0000ff
size=2>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:
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<FONT face=Arial color=#0000ff
size=2>~Composite311 (will contain returns based on using a
3/11 crossover)
<FONT face=Arial color=#0000ff
size=2>~Composite312 (will contain returns based on using a
3/12 crossover)
<FONT face=Arial color=#0000ff
size=2>etc.
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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.
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Each
composite file would contain the equity curve information resulting from using
the applicable crossover periods.
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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.
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<FONT face=Arial color=#0000ff
size=2>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.
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<FONT face=Arial color=#0000ff
size=2>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.
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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.
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<FONT face=Arial color=#0000ff
size=2>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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<FONT face=Arial color=#0000ff
size=2> Send
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