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Re: [amibroker] Re: Expectancy - and related



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Greetings all --

A couple of comments that relate to some of the recent posts.

1.  In my opinion, and the opinion of others with much more experience in modeling and simulation than I (George Box, for one), a visual look at the equity curve may be the best single indicator available.  I always start with it.

2.  I find it helpful to me to run some tests, then graph the equity curves and record associated trading system metrics (expectancy, percent winners, win-to-loss ratio, holding period, etc).  Print out the equity curves and arrange them on the floor in the order of preference.  Look at the trading system metrics associated with each equity curve.  Doing this a few times gives me a little feeling for what metrics are important and what values are good values.

3.  If the value of a metric is growing large because the denominator is small, and that denominator represents the risk of the system, then the slope of the equity curve can be increased by increasing the leverage used.  But beware of what happened to Long Term Capital Management when they increased leverage beyond reasonable and prudent limits.

Thanks,
Howard



On Mon, Apr 7, 2008 at 9:13 PM, Grant Noble <gruntus@xxxxxxxxxxx> wrote:

Thanks Howard. I entered this thread because someone posted:


> The K-ratio isn't worth the space it takes up: RRR is simpler.

I was wondering about the K-ratio bashing. This lead to me realising that I have difficulty in
really "feeling" what these metrics mean and how they differ. Would you normally start from visual
inspection of equity curves and then go to the stats?


Howard B wrote:
> Greetings all --
>
> It is possible to use a metric such as Power Factor, or the closely
> related Terminal Relative Wealth, or Net Profit, as the objective
> function when optimizing and choosing among alternatives.
>
> But beware.
>
> Optimizing to maximize any of these will very often reward a system that
> has not only a high return, but also a high drawdown. I recommend using
> one of the metrics that automatically rewards both high equity growth
> and equity smoothness. The equity smoothness part minimizes drawdowns.
>
> Try RRR, KRatio, Ulcer Performance Index, CAR/MDD, or RAR/MDD.
>
> Thanks,
> Howard
>
>
>
>
> On Sat, Apr 5, 2008 at 6:49 PM, brian_z111 <brian_z111@xxxxxxxxx
> <mailto:brian_z111@xxxxxxxxx>> wrote:
>
> The mathematical _expression_(s) OR antecedents of PowerFactor are:
>
> where
>
>
>
> Wins == 55
> Losses == 45
> ave%Won == 3
> ave%Lost == 2
> PowerFactor (notational format) is 3^55/2^45
> InitialEquity == 1
>
> then
>
> finalequity == 1 * 1.03^55 * 0.98 *45 == 2.047485;//PowerFactor
> equation
> POF (geometric mean) == (2.04785/1)^(1/100) == 1.00719 etc;
>
> There is a temporary post at the UKB with the POF equation
> demonstrated in a spreadsheet.
>
> Note: it is not recommended to use GM as an ObjectiveFunction without
> a full understanding of the caveats (stated and implied) by
> RalphVince's work on optimalF.
>
> Also my take on it, including BinomialSimulation, won't be debugged,
> at the very least, until after I post on the subject at the UKB (if
> at all).
>
> brian_z
>
> http://www.amibroker.org/userkb/
>
>
> --- In amibroker@xxxxxxxxxxxxxxx
> <mailto:amibroker%40yahoogroups.com>, "brian_z111" <brian_z111@xxx>

> wrote:
> >
> > PowerFactor is part of, what is for me, a rather ambitious project.
> >
> > I can't do it justice in an off the cuff post (that would be prone
> to
> > confusing both of us) - so you don't go away empty handed (everyone
> > gets a prize).
> >
> > RalphVince's work is based on estimating the optimal fraction of
> our
> > captial to invest in any trade and the measure of success is the
> > maximum geometric mean.
> >
> > GM = (final equity/initial equity)^ (1/number trades)
> >
> > It can be standardised to annual return by plugging in the ave time
> > per trade + turn around time.
> >
> > He gives a method whereby we can estimate the GM from the trade
> > returns (average $value or ave%) and the SD of the trade series.
> >
> > One of the criticisms of OptimalF is that it relies on the trade
> > series largest loss, as the critical factor, but the largest loss
> > might not be the largest that we can experience in the future, so
> in
> > this regard it is an agressive money management technique.
> >
> >
> > That is where I am making an effort to clarify his work for my own
> > use.
> >
> > I am using BinomialSimulation as a type of 'visual maths' to
> > crosscheck my 'equations' against his and other accepted maths
> tools.
> >
> > I am attempting to get a more accurate estimate of the 'worst case'
> > scenario, in a way that has meaning to me.
> >
> >
> > This is where ProfitFactor and PowerFactor come in (PowerFactor is
> > really just the geoemtric mean in notation form - the notation
> > reminds me of the important part the W/L ratio and the PayOff ratio
> > play in the final trading outcomes (equity curve profiles derived
> > from them).
> >
> > Outside of that it doesn't have any importance.
> >
> > As far as the valule of the geometric mean goes it would be far
> > better to reference RV's work.
> >
> > From RV "The Mathematics of Money Management" - "The real growth
> > function in trading (or any event where the PeriodReturn is not
> > constant) is the multiplicative product of the PeriodReturns.
> >
> > So PowerFactor is just the notational form of that, say:
> >
> > Wins = 55
> > Losses = 45
> > ave%Won = 3
> > ave%Lost = 2
> > PowerFactor = 3^55/2^45
> >
> > As I said, it is just a notation to remind me of the importance of
> > the PayOff ratio (3/2) and the fact that I can control that, at the
> > design stage, via my stops - compared to W/L where the variance is
> a
> > function of sample error.
> >
> > Where I am heading in future posts is:
> >
> > a) to show the relationship between fixed amount (contracts or
> number
> > of shares) trading and reinvestment trading (compounded equity
> > curves) and how that the difference is summarized by
> > ProfitFactor/PowerFactor OR geometric mean
> >
> > b) to find a simpler way (equation) to calculate the worst case
> risk
> > (drawdown?), relative to time, using only the basic inputs from the
> > trade series i.e. win, loss and amount won/lost as % (no MonteCarlo
> > etc required).
> >
> > The pathway there is to include variance in the PF type equations.
> >
> > Hope I haven't made that too complicated - I am building to a more
> > measured and understandable presentation at the UKB (look for
> > upcoming posts on expectancy, blackswans, random generators etc).
> >
> > Where did I settle in Australia?
> >
> > I am in regional NorthQueensland 'amongst the plum trees with lots
> of
> > gum leaves' etc.
> > NFA actually appeals to me more but my partner has other ideas.
> >
> > brian_z
> >
> >
> >
> >
> >
> >
> >
> > --- In amibroker@xxxxxxxxxxxxxxx
> <mailto:amibroker%40yahoogroups.com>, Grant Noble <gruntus@> wrote:
> > >
> > > > Hope that gives you something stimulating to think about.
> > >
> > > Dude, I'm totally overstimulated! Do you have a formula for
> > PowerFactor?
> > > BTW where did you end up settling in Australia?
> > > GRANT
> > >
> > > brian_z111 wrote:
> > > > Grant,
> > > >
> > > > Apologies for late comments (I've been to the beach but
> mentally
> > > > flagged your question before I left).
> > > >
> > > > You might be interested in my generic opinion.
> > > >
> > > > My trumpeting on expectancy, ProfitFactor and PowerFactor are
> > based
> > > > on my efforts to identify and understand the root causes of
> > equity
> > > > curve growth and variance (underneath it all is there anything
> > else
> > > > that really concerns us).
> > > >
> > > > It is rather like the difference between the average driver and
> a
> > > > professional driver. Average drivers, on their annual holidays,
> > are
> > > > typically concerned about MPH, hours to arrival and fuel costs
> > > > whereas a professional driver (F1 racer) is a 'power user;
> > concerned
> > > > about performance drivers e.g. engine power (HP or watts), oil
> > > > pressure, fuel efficiency, road conditions etc, oil temperature.
> > > >
> > > > My personal approach is to focus my enquiry on the 'power'
> > factors of
> > > > trading performance.
> > > >
> > > > Hence the topic of my discussion with Gerry, who made some
> > > > interesting observations on PowerFactor and the key metrics
> that
> > are
> > > > associated with it.
> > > >
> > > > In Excel simulations of no win (breakeven) fair coin tosses,
> that
> > I
> > > > have performed in the past, I was astounded at the range of
> > possible
> > > > equity outcomes (no two equity curves are the same and they
> form
> > a
> > > > cone that fans out on either side of the breakeven line and
> that
> > > > continues to expand with time OR N tosses of the coin).
> > > >
> > > > This is what Ralph Vince was referring to when he said "that is
> > just
> > > > how perverse the equity curve of a fair coin is".
> > > >
> > > > He also gives the 1st and 2nd arcsine laws that predict the
> > amount of
> > > > time we can expect the equity curve to stay on one side of the
> > b/e
> > > > line and the max/min of the equity curve.
> > > >
> > > > Ralp Vince "The Mathematics of Money Management".
> > > >
> > > > The equity curve outcomes that I achieved in my 'push the excel
> > buton
> > > > and see' trials were very similar to the simulated equity
> curves
> > in
> > > > Howards QTS book - page 309.
> > > >
> > > > My argument is:
> > > >
> > > > - we can only trade successfully with an edge
> > > > - the edge is based on the 'predictable behaviour' of a market
> > event
> > > > e.g. chart pattern'
> > > > - a predicatable pattern will exhibit the properties of a coin
> > toss
> > > > (albeit a biased coin)
> > > > - the equity outcomes of a biased coin toss are varied
> > > >
> > > > therefore any evaluation method that doesn't reference variance
> > is
> > > > unlikely to be useful to me.
> > > >
> > > > That is why I have an interest in Binomial Simulation and
> metrics
> > > > like ProfitFactor and PowerFactor (they are close to the inputs
> > of a
> > > > Binomial Simulator - which is alternative approach to MCS and
> it
> > > > doesn't rely on a rescrambling of the sample set.
> > > >
> > > > So, based on my chosen approach I see no point in considering
> the
> > > > metrics of one equity curve - if you go OOS OR toss the coin
> > again
> > > > you will get an entirely different equity outcome.
> > > >
> > > > That is why I am more interested in what causes equity lines to
> > grow
> > > > (increases the geometric mean) and controls equity curve
> drawdown
> > (so
> > > > I can put the setting where I want it).
> > > >
> > > > K-ration is a measure of equity curve smoothness whereas
> > > > RiskRewardRatio is a 'root cause' metric.
> > > >
> > > > There are a lot of different opinions about what constitutes
> > reward
> > > > and risk but if you are talking about RR as defined in
> > Markowitz's
> > > > Modern Portfolio Theory then it is something I don't have a
> great
> > > > deal of understanding on but I definitely regard drawdown
> as 'the
> > > > risk', probability as teh drive and variance as a quantity not
> to
> > be
> > > > ignored.
> > > >
> > > > BTW my efforts with BS are complementary to Ralph Vinces work
> > > > (possibly it will make a little corner of his work more
> > accessable to
> > > > the maths layperson). IMO RV's work is brilliant. He is the
> > analyst
> > > > who 'blew me out of the water'.
> > > >
> > > > Hope that gives you something stimulating to think about.
> > > >
> > > > brian_z
> > > >
> > > > --- In amibroker@xxxxxxxxxxxxxxx
> <mailto:amibroker%40yahoogroups.com>, Grant Noble <gruntus@> wrote:
> > > >>> The K-ratio isn't worth the space it takes up: RRR is simpler.
> > > >> care to elaborate?
> > > >>
> > > >> gerryjoz wrote:
> > > >>> In an earlier post, expectancy was associated with profit
> > factor.
> > > >>> It is more closely related to payoff ratio.
> > > >>> In Van Tharp's book, 2nd edition, "Trade your way...", page
> 204
> > et
> > > >>> seq, he calculates
> > > >>> Expectancy = average profit/ # trades
> > > >>> divided by average loss.
> > > >>> Payoff ratio is average profit/average loss,
> > > >>> so
> > > >>> Expectancy = payoff ratio/# trades.
> > > >>> --which can give very low numbers, and makes the concept
> rather
> > > >>> dubious if you are using it as an absolute value for
> comparing
> > > > systems
> > > >>> with different numbers of trades. It might be better to use
> > > > trades per
> > > >>> annum.
> > > >>> To be fair Van Tharp only gives that way of calculating
> > > > expectancy as
> > > >>> a default if the risk of a trade isn't able to be calculated
> > > > taking
> > > >>> into account a pre-determined proportion of equity. For that,
> > you
> > > > need
> > > >>> to read the whole chapter.
> > > >>> Personally i find CAR/MDD, RRR more relevant, along with the
> raw
> > > >>> Payoff ratio.
> > > >>>
> > > >>> The K-ratio isn't worth the space it takes up: RRR is simpler.
> > > >>>
> > > >>> regards
> > > >>> Gerry
> > > >>>
> > > >>>
> > > >>>
> > > >>>
> > > >>>
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