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You can control exactly how much is allocated to each trade, by using
custom backtester logic, without having to manipulate any statistics.
For example; I have a script that calculates position size based on a
number of factors, but then prevents the position size from exceeding
a "realistic" maximum. The end result is that you get the compounded
profits up to a maximum.
If your optimization period is a short to moderate length, the
maximum is not reached and the statistics computed reflect
your "Compounded" scenario and are valid for comparison against any
other strategy.
Though, it is true that this just delays the inevitable, which is
skewed statistics once the maximum position size is hit, at which
point the statistics begin to take on your "Clamped" effect.
I find that this most closely models what I would do in real trading
anyway. If the capital became so plentiful as to exceed a realistic
position size, I would start looking for other vehicules in which to
place the excess. I would not continue increasing the position size
beyond the realistic measure. As such, the backtested statistics
reflect reality.
Mike
--- In amibroker@xxxxxxxxxxxxxxx, "Robert Grigg" <robert@xxx> wrote:
>
> I have been thinking through the process of evaluating
the "goodness" of a
> trading system using AB metrics and have become perplexed. Can
someone who
> has unravelled this issue previously help?
>
> There seem to be two general approaches to portfolio sizing while
doing a
> back-test.
>
> The first is to only back-test using the "Initial Equity" amount.
> Generally, we might start using fixed position sizes and a fixed
maximum
> number of positions. In later developmental iterations we might use
risk
> based position sizing or other processes where we vary position
sizing up to
> the maximum amount of Initial Equity. I generally refer to this
evaluation
> approach as "Clamped Equity". This approach tends to give an
equity curve
> that is linear.
>
> The second approach is to compound profits and place trades up
to "Current
> Equity". (In AB terms our Position size is set to a % of Current
Equity).
> This is referred to as "Compounding Profits". The equity curve can
take on
> an exponential appearance.
>
> In real life trading most people tend to do a bit of both. However
in
> back-testing mode the "Compounding Profits" model (with a
notionally good
> system) can quickly become infeasible. (If only I had this system
in
> 2000...).
>
> So, now to the crux of the problem. The "Clamped Equity" approach,
with a
> notionally good system, produces a profit that is quarantined.
Accumulated
> profit can be used to top-up draw-downs but the amount in trades
never
> exceeds initial equity. In AmiBroker metrics, Exposure % is always
> calculated on a bar by bar basis of mark-to-market holding against
current
> mark-to-market equity. However, in the "Clamped Equity" testing
approach,
> the quarantining of profits is intentional and it seems to me that
it would
> be more useful to look at the Exposure as a % of the "Clamped
Equity" (i.e.
> the "Initial Equity")?
>
> Exposure% is also used as a divisor in other metrics such as Net
Risk
> Adjusted Return %, Risk Adjusted Return %, Max System % Draw-down,
> CAR/MaxDD and RAR/MaxDD and so these metrics also may be less
useful given
> this testing approach.
>
> I can see that comparisons between competing models, with the same
test
> period is valid. However, I do not feel so secure if I am doing
> Walk-Forward back-testing using a complex objective function,
particularly
> if I am using weighted components that contain Exposure% and others
that
> don't.
>
> I know that it is relatively easy to use the Custom Back Tester to
produce
> amended statistics. However, I am concerned that I have not found
any other
> discussions of this issue on this or other forums, so maybe I have
muddled
> thinking and it is not a real issue. Any discussion would be
appreciated.
>
> Robert
>
------------------------------------
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