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The mean profit or loss would be the same. I woudn't think it would be
possible to say ahead of time about the variance, but I'm not sure about
that. However, I do believe you have to determine what timeframe you are
interested in. Are you interested in asking whether you would have been
successful using the system over the 500 weeks that you have data for? Or
are you interested in determining what proportion of 100 week periods would
have been successful?
----- Original Message -----
From: "brian.z123" <brian.z123@xxxxxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
Sent: Wednesday, November 08, 2006 9:22 PM
Subject: [amibroker] Re: Margin of Error
> The question is:
>
> If I have 10 years of data and that provides 500 Monday samples for
> a Calender Effect study would the margin for error be less or more
> if I tested the sample in one segment (500 trades) or undertook 5
> tests with 100 samples and then combined the results in some way?
>
> If so, what is the best way to use the 5 samples to get the
> population outcomes.
>
> No offence taken if you are too busy to answer.
>
> BrianB2.
>
> --- In amibroker@xxxxxxxxxxxxxxx, "quanttrader714"
> <quanttrader714@xxx> wrote:
>>
>> One way to approach this is with a form of the block bootstrap, by
>> resampling blocks of consecutive observations of random length
> with
>> replacement.
>>
>> --- In amibroker@xxxxxxxxxxxxxxx, "sebastiandanconia"
>> <sebastiandanconia@> wrote:
>> >
>> > I only offer this as a consideration when using such testing,
> not as a
>> > criticism of Monte Carlo Simulations. A subtle but significant
> point
>> > (IMO) when using MCS: They may or may not be applicable to
>> > trading/investing, because the markets don't always behave
> randomly.
>> >
>> > An example of when a MCS would clearly be appropriate: Let's
> say you're
>> > a defense contractor manufacturing a part for the International
> Space
>> > Station. The part is critical, but because of limitations in
>> > engineering technology it has a high failure rate, and there's
> no way of
>> > forecasting in advance if a part will fail. However, although
> the
>> > failure rate is high, it's also very consistent. Until
> technology
>> > advances sufficiently the only practical solution is to keep
> plenty of
>> > spares on-hand.
>> >
>> > A MCS could tell you what the optimal number of spares to keep
> on-hand
>> > would be. The part failures are random, but MC could tell you
> the
>> > likelihood of two, three, five, ten, etc., consecutive
> failures. You
>> > might determine that there would only be a 1/100,000 chance that
> 6
>> > spares in a row would fail, so you might advise NASA to stock at
> least 6
>> > spares at all times.
>> >
>> > Some trading systems, though, will be successful because they
> take
>> > advantage of repeating sequences of events, not random events.
> Business
>> > cycles go through a specific sequence, company growth follows a
> certain
>> > pattern from infancy to maturity, price trends/reversals follow a
>> > sequence, etc. If trades based on reliable, repeating patterns
> are
>> > taken out of order by a MCS such that a massive drawdown or a
>> > bankrupting series of losers occurs, that can distort the value
> of the
>> > trading method by putting the trades in an order that wouldn't
> occur.
>> >
>> > Soapbox alert!:) Another reason that "Why does it work?" is
> such an
>> > important question with trading systems, since a good answer to
> that
>> > question can lead to a good answer for another important
> question, "When
>> > WON'T it work?"
>> >
>> >
>> > S.
>>
>
>
>
>
>
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>
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