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Chuck,
Discussion on the Sharpe ratio is welcome here.
I would like to discuss that subject.
I only meant that all of my energy at the moment is going into
producing the projects core material so I can't join in.
The back end of the project is pitched at Ami's new-users so that is
why I choose this forum which is where most of them live.
I am looking forward to joining in the other forums; TS and AT etc.
At the moment I am breaking new ground in Ami every day so it is too
much to take in all the forums, feedback centre and the full range
of support material available all at the same time so I am only
following this forum for a while.
BrianB2.
--- In amibroker@xxxxxxxxxxxxxxx, "cstrader" <cstrader232@xxx> wrote:
>
> I'm enjoying the thread -- but I think we should move it to the
Amibroker-ts
> group where it probably should be. And so I will post my further
comments
> on the Sharpe ratio there.
>
> Thanks
>
>
> chuck
>
> ----- Original Message -----
> From: "brian.z123" <brian.z123@xxx>
> To: <amibroker@xxxxxxxxxxxxxxx>
> Sent: Tuesday, November 07, 2006 7:21 PM
> Subject: [amibroker] Re: Margin of Error
>
>
> > Hello Ton,
> >
> > Thankyou for the compliment.
> >
> > In the example given it makes no difference what timeframe you
are
> > working, as Win/Loss is a number ratio.
> >
> > For other statistics that are measured in magnitude e.g. StDev,
the
> > weekly value will be greater than the daily value so the maths
will
> > take care of that for us.
> >
> > There is a lot more to it than the brief discussion and small
> > example I attempted here.
> >
> > Different measures,like StDev, might be treated differently in
stats
> > e.g. StdErrorofStDev = = 0.71StDev/SqRt(N)
> >
> > Keep in mind that I am not a mathematician and not the best
person
> > to comment on maths specifics.
> >
> > I do have a very good radar system so I am mainly sharing with
the
> > forum my perception that a lot of us are short on skills in this
> > area and that it is a very important part of trading.
> >
> > I would recommend that anyone who sees some relevance in the
stats
> > component of this project should read some of the books written
for
> > traders by mathematicians and/or ask some further questions of
the
> > mathematicians in the forum.
> >
> > I ahve thoroughly enjoyed every post in the topic so far; but I
> > would say Fred hit the nail right on the head.
> >
> > BrianB2.
> >
> > --- In amibroker@xxxxxxxxxxxxxxx, "Ton Sieverding"
> > <ton.sieverding@> wrote:
> >>
> >> Good work Brian. Thanks. I like what I see but just one little
> > question. So the SE is based upon the number of trades N. Let's
say
> > N = 1.000. Any difference between N = 1.000 days or N = 1.000
weeks
> > etc. ?
> >>
> >> Ton.
> >>
> >> ----- Original Message -----
> >> From: brian.z123
> >> To: amibroker@xxxxxxxxxxxxxxx
> >> Sent: Tuesday, November 07, 2006 1:51 AM
> >> Subject: [amibroker] Margin of Error
> >>
> >>
> >> Part1 of Project Based Training No1.
> >>
> >> The objective of the project is to introduce new traders to
the
> > main
> >> concepts of system design/testing and demonstrate their
> > application
> >> in AmiBroker.
> >> At the same time it is hoped that the ideas presented will
> > provoke
> >> discussion and provide trading stimulation.
> >>
> >> All of the stages in the design process will not be
demonstrated
> > as
> >> most have already been covered elsewhere in the AmiBroker
> > support
> >> material.
> >>
> >> A basic understanding of the application of some statistical
> > methods
> >> to the trading environment is a pre-requisite.
> >> The opening topics address this need.
> >>
> >> To those who find the subject matter new *the project* will
be a
> >> workbook .
> >> To those who have experience in the subject it will be an
> >> opportunity to workshop.
> >>
> >> I would like to acknowledge my indebtedness to the academic
> >> community .
> >> I often refer to the material so generously interpreted for
the
> >> layperson and made available at websites by academic
> > specialists,
> >> particularly those associated with Universities.
> >>
> >>
> >
*******************************************************************
> >> Margin of Error.
> >>
> >> Back-testing of historical data provides traders with a
sample,
> >> typical of the trade they are testing. From that sample they
> > make
> >> inferences about the larger group, or population, of all past
> > trades
> >> and future trades, of the same type, that were not included in
> > their
> >> test window.
> >> Despite the fact that the people who teach them to back-test
> > also
> >> teach them that the past can not predict the future, some
> > continue
> >> to act as if it can.
> >>
> >> If the past can't predict the future. How can anyone trade
with
> >> confidence?
> >>
> >> The answer is that while the future can't be predicted, the
> >> likelihood of some mathematically defined outcomes can be
> > predicted
> >> with a degree of confidence.
> >> Statistics is the mathematical discipline that manages that
very
> >> well.
> >>
> >> The caveat is that to apply statistical methods to trading
> > samples,
> >> the assumption is made that they are the result of a random
> > process.
> >> Where the trading system chosen is biased to non-random
> > behaviour it
> >> will be prone to failure if the market acts contrary to that
> > bias.
> >>
> >> For that reason system traders are faced with a choice between
> >> attempting to define market behaviour e.g. a trend, and pick a
> >> system to suit that, or search for a universal signal that is
> >> consistent irrespective of any assumed market bias.
> >>
> >> If statistics can predict the likelihood of future trading
> > outcomes,
> >> how accurate will it be?
> >>
> >> *Standard error* or *margin of error* offers traders a
solution
> > but
> >> they are not subjects that are often discussed.
> >>
> >> In his book ,*Design, Testing, and Optimisation of Trading
> > Systems*
> >> (John Wiley & Sons, 1992), Robert Pardo raises the issue of
the
> >> accuracy of trading *predictions* based on the size of the
> > sample
> >> used:
> >>
> >> * The sample size must be large enough to allow the trading
> > system
> >> to generate a statistically significant sample of trades.
> >> A sample of one trade is certainly insignificant, whereas a
> > sample
> >> of 50 trades or more is generally adequate.*
> >>
> >> He uses Standard Error as a measure of significance:
> >>
> >> StdError = = 1/SquareRoot(sample size),
> >>
> >> 1/SqRt(50) = = 14.1%.
> >>
> >> There is little by way of further explanation provided.
> >>
> >> Applying the formula to a greater number of samples:
> >>
> >> Where N = = the number of trades in the sample
> >>
> >> StdError factor = = 1/SqRt(N)
> >> StdError% = 1/SqRt(N) * 100
> >>
> >> If N = = 2500 the StdError% = = 1/SqRt(2500) * 100 = = +/- 2%
> >> If N = = 10000 the StdError% = = 1/SqRt(10000) * 100 = = +/-
1%
> >>
> >> A trade sample of 10000 to provide statistical accuracy of 1%
is
> > not
> >> easily achievable for traders, although a lot easier than
> > accurately
> >> surveying the eye colour of Polar Bears.
> >>
> >> Pardos equation is in fact, a rounding of the StdError
equation
> > for
> >> a 95% level of confidence:
> >>
> >> Margin of error at 99% confidence = = 1.29/SqRt(N)
> >> Margin of error at 95% confidence = = 0.98/SqRt(N)
> >> Margin of error at 90% confidence = = 0.82/SqRt(N)
> >>
> >> Later in the project I will use a basic random number
generator,
> >> within Xcel, to provide a visual aid that traders can use to
> >> understand the *sample* concept and decide for themselves what
> >> constitutes an adequate sample.
> >>
> >> Wikipedia provides some additional clarity on the subject:
> >>
> >> http://en.wikipedia.org/wiki/Margin_of_error
> >>
> >> *The margin of error expresses the amount of the random
> > variation
> >> underlying a survey's results. This can be thought of as a
> > measure
> >> of the variation one would see in reported percentages if the
> > same
> >> poll were taken multiple times. The larger the margin of
error,
> > the
> >> less confidence one has that the poll's reported percentages
are
> >> close to the "true" percentages, that is the percentages in
the
> >> whole population.*
> >>
> >> *An interesting mathematical fact is that the margin of error
> >> depends only on the sample size and not on the population
size,
> >> provided that the population is significantly larger than the
> > sample
> >> size, and provided a simple random sample is used. Thus for
> >> instance...the running example with 1,013 random
samples..would
> >> yield essentially the same margin of error (4% with a 99%
level
> > of
> >> confidence) regardless of whether the population....consisted
of
> >> 100,000 or 100,000,000.*
> >>
> >> In short the tail of the trading system sample is swinging the
> >> trading system cat.
> >>
> >> BrianB2
> >>
> >> The material contained in this topic is for educational and
> >> discussion use only.
> >> It is not intended as financial advice and should not be
> > construed
> >> as such.
> >> The author is not an accredited academic or financial advisor.
> >>
> >
> >
> >
> >
> >
> > Please note that this group is for discussion between users only.
> >
> > To get support from AmiBroker please send an e-mail directly to
> > SUPPORT {at} amibroker.com
> >
> > For NEW RELEASE ANNOUNCEMENTS and other news always check DEVLOG:
> > http://www.amibroker.com/devlog/
> >
> > For other support material please check also:
> > http://www.amibroker.com/support.html
> >
> > Yahoo! Groups Links
> >
> >
> >
> >
>
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