On 08.10.2009, 18:01:36 NickW wrote:
> Hi,
>
> This is a great thread. Thanks for all the valuable information.
>
> Using SQN is something I've struggled with aswell where is punishes the
> outliers. When designing trend following systems, 5% of the trades are the
> big winners that makes trend following work, so you really don't want to
> punish the system for having few great winners. I am going to look more
> into semideviation to see how that can solve that problem.
>
> Thanks
> Nick
>
> On Thu, Oct 8, 2009 at 7:50 AM, Howard B <
howardbandy@xxxxxxxxx> wrote:
> > Hi Mike --
> >
> > CAR is compound annual rate of return. Expectancy is the percentage (or
> > dollar amount, but not for this discussion) gain on the average trade.
> > The final value of the trading account, Terminal Relative Wealth in some
> > descriptions, is: (1 + expectancy) raised to the power of the number of
> > trades. When there are a few large trades included, this relationship is
> > slightly different, but not enough to worry this discussion. CAR is: (1
> > + annual gain) raised to the power of the number of years. These are
> > both based on geometric means. Aren't they the same, or so close that
> > they act the same when used as an objective function?
> >
> > Van Tharp defines System Quality Number on page 28 of "Definitive Guide
> > to Position Sizing." SQN = (expectancy / standard deviation) times
> > squareroot of number of trades. SQN decreases when a median trade is
> > replaced by either a large win or a large loss. It is possible to
> > redefine the metric so that large wins are not penalized, such as by
> > using the semi-deviation instead of the standard deviation as the
> > denominator. But without making that change, outliers, both good and
> > bad, do affect SQN by reducing it.
> >
> > What happens with open (or potentially open) trades at the boundaries of
> > walk forward periods is difficult to handle in both theory and practice.
> > Tomasz' implementation is to close all open trades at the end of each WF
> > period; and go into each WF period flat, not taking a new position until
> > there is a new signal. This creates a potentially serious distortion of
> > results when trades are typically held a long time (a large proportion of
> > a WF period) or when there are a few large trades that comprise the
> > majority of a system's profit or loss.
> >
> > I think this leads to a conclusion that we both agree on -- high quality
> > trading systems that can benefit from position sizing are based on high
> > frequency trading with very careful control over losses, and even control
> > over gains.
> >
> > Thanks for listening,
> > Howard
> >
> > On Wed, Oct 7, 2009 at 2:36 PM, Mike <
sfclimbers@xxxxxxxxx> wrote:
> >> Howard,
> >>
> >> Assuming that SQN is the t-test for expectancy, then optimizing on the
> >> t-test of expectancy (i.e. SQN) is not the same as optimizing on CAR.
> >>
> >> The primary reason that CAR is a poor target for optimization is that
> >> outliers can significantly improve the calculation. The exact opposite
> >> is true for SQN.
> >>
> >> SQN rewards consistency and punishes outliers. Consistent winners with a
> >> few large wins will improve CAR but hurt SQN, resulting in different
> >> parameter combinations being selected during an optimization.
> >>
> >> As for writing a custom method, AmiBroker's stats are calculated based
> >> on the assumption that all open trades are closed out at the backtest
> >> boundary date. Many open trades, or even just a few large open trades,
> >> can skew these values.
> >>
> >> For high frequency strategies or strategies using heavy position sizing,
> >> creating a custom function is the only way to get reliable measurements.
> >>
> >> Mike
> >>
> >>