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I'll be posting a more formal explanation of my viewpoint, based on
this thread, at the UKB within the next two weeks.
The current "Expectancy" post will be renamed to "Evaluation Metrics"
and extended.
I will show the derivation of a class of metrics, that are based on
the primary evaluation inputs, and the relationships between them
(including their restatements).
I hope to make it sufficiently clear why I am interested in root
cause evaluation and, at the least, provide enough info for peopple
to make informed decisions about when and where to use these metrics:
Win/Loss
PayOff Ratio
aveProfit/Loss
ProfitFactor
Expectancy
bars held
I will introduce some minor evaluation metrics, that are new to
trading (AFAIK) - at least they are not included in AB's builtin
metrics.
Possibly the post will be extended at a later date to include the
Annualised metrics and those based on Equity curve analysis.
I might include a formal definition of PowerFactor or at least
clarify why I elected to introduce the term to the trading community.
brian_z
--- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@xxx> wrote:
>
> Another FTR.
>
> IMO Expectancy as defined by Van Tharp is not the best way to
> measure "the edge" or how much we expect to win on average each
time
> we trade (flip the coin).
>
> Van Tharp uses $values as the unit of measure for a win or a loss.
> If adjusted data is being used for backtesting the absolute value
of
> the win, or loss, in $ terms will have been lost in the adjusment
> process (the further back in history you go the greater will be the
> error).
>
> I believe standardizing to % won or lost will minimize those errors
> (wins and losses are measured in relative terms).
>
> A better way is to measure individual trader performance in mean %
> won or lost (growth).
>
> Example (using Excel).
>
> initial equity = $10,000
> final equity = $10,500
> period = 10
> growthfactor (per period) = (10,500/10,000)^(1/10) = 1.0049
>
> You expect to win (on average) 0.49% each time you trade.
>
> net return per trade = the edge (in%) - commissions (in %)
> = 0.49 - 0.11
> = 0.38
>
> To cross check the growth factor (reverse the equation):
>
>
> 10000 * 1.0049^10 = 10500
>
> Note: that is the mean expected growth rate.
> To estimate variance requires a simulation (MonteCarlo ?)
>
> brian_z
>
>
> Re "Another way to define ProfitFactor is:
>
> Number Wins/Number Losses * average % Win/average % Loss"
>
> FTR -
>
> A lot of my work is original so it is not out of the question that I
> use terms in ways that others don't.
>
> I'm not sure about the above definition.
> I can't find any reference to it in the 20 - 30 books I have here so
> possibly I made it up (in which case I would call it something else
> like PowerFactor).
>
> Anyway I intended it as the companion metric for a basic simulation
> that I have done in the past in Excel (it uses binomial probability
> and a distribution of the trade sample to plot equity curves).
>
> I haven't worked out if it is possible and/or how to calculate
> expectancy from PowerFactor - it was always my intention to rely on
> simulation for the metrics.
>
> brian the dross maker
>
>
>
> --- In amibroker@xxxxxxxxxxxxxxx, "brian_z111" <brian_z111@ wrote:
>
> Chris,
>
> Re Profit Factor and Expectancy
>
> I thought you might be interested since you focus on Expectancy as
> the driver, which is similar to my focus on PF (it's the first
> place
> I look).
>
> ProfitFactor and Expectancy are kissing cousins, mathematically and
> conceptually.
>
> Profitunity = Expectancy per trade * number of trades per time
> period.
>
>
> Yes, I believe VanTharp first used the term Expectancy, although I
> haven't read his book. That is what I meant (I picked the term up
> from others who must have read him).
>
> AB's version of PF is correct so that:
>
> gross profit - gross loss = net profit
> net profit/number of trades = expectancy in $ (on a per trade
basis)
>
>
> Another way to define ProfitFactor is:
>
> Number Wins/Number Losses * average % Win/average % Loss
>
> To standardize the backtests over time I am only interested in the
> %
> win or loss so that is how I first started using that definition of
> PF. Then later on I started to see what a useful evaluation metric
> it
> was.
>
> Since I start by looking at the PF, and then look at Expectancy or
> PA% later on, I thought I would share my observations with you.
>
> When doing design work PF has the advantage of giving us two
> metrics
> that tell us a lot about the trade e.g. if the expectancy is OK but
> the W/L ratio is < 50% I don't like it - I am not comfortable with
> long losing sequences followed by one big win (not only
> temperamentally but also based on my rules for design).
>
> When I look at the ave%W/ave%L it tells me how much of the positive
> PF is due to the W/L ratio and how much is due to my stops e.g. you
> can leave your stops the same and change the signal to benchmark
> signals against each other.
>
> These kinds of things are vitally related to the design process.
>
> After I think I have an interesting trade I look at expectancy/PA%
> to
> see if I it is profitable cf to costs (commissions etc - I don't
> include commissions in backtests - I add them mentally later).
>
> Since ave%W/ave%L is only a ratio it is possible to have good PF
> but
> not have a paying system e.g. if your ave win is 0.2% and your ave
> loss is 0.1% you have a good ratio but you dont actually win much
> i.e. the expectancy is low.
>
> It also brings risk into the equation since if you increase the
> risk
> (move your stops) for the same PF the Expectancy goes up.
>
> Eventually you have to look at the %PA since that pays the annual
> grocery bill.
>
> Obviously high frequency * high expectancy is a very exciting year
> e.g. I consider turn around time for my systems - it is great to
> have
> a high powered trade but if you are in for two days and then have
> to
> wait 6 days for another trade to come along your frequency/PA%
> comes
> right down.
>
> There is a lot in what I am saying - I have spent 100 of hours in
> theroretical and practical consideration of evaluation - I have
> only
> put a cryptic explanation here.
>
> (In my first post I also meant to add that variance in the equity
> curve is derived from binomial probability of the W/L and variance
> in
> the distribution of the trades, where the trades are measured in %
> +_ )
>
> I understand that is probably a bit more info than you wanted but I
> have talked about it a little in the past here and there and I
> promised a couple of guys I would explain some more one day - today
> was the day.
>
>
> brian_z
>
> --- In amibroker@xxxxxxxxxxxxxxx, ChrisB <kris45mar@ wrote:
>
> Hi Brian
>
> Thanks for this extra comment.
>
> Your immediate prior post had me confused because by PF I assumed
> you
> meant Profit Factor and
> the nearest I can understand this, is that
>
> Profit Factor = Gross Profit / Gross Loss
> or as in the AB reports:
> Profit Factor = Total Profit / Total Loss.
>
> I didn't understand how this related to a time series or per
> annum
> gain.
>
> However reading between the lines of this last post, I think you
> may be
> referring to van Tharp's (was it he who coined this phrase? )
> Profitunity factor?
>
> Where ....
>
> Profitunity = Expectancy per trade * number of trades per time
> period.
>
> In which case it makes a little more sense to me.
>
> If not, I am happy to stand corrected.
>
> Regards
>
> ChrisB
> brian_z111 wrote:
>
> I like PF (a derivation of it) and expectancy is really PF
> translated
> in return over time (PA%).
>
> FTR - to explain further what I meant about PF (my take on it).
>
> PF is the trades profile (a kind of quality measure) comprising
> two
> components (W/L ratio and ave%W/ave%L ratio).
> The W/L ratio tells us something about the buy signal whereas
> the
> %
> W/L ratio tells us something about the exits (profit and loss
> stops)
> although they are interdependent.
>
> The W/L ratio is binomial and indicates the tendency towards
> runs
> (losing/winning streaks) and the %W/%L quantifies that e.g. as
> an
> equity curve.
>
> PF is the theoretical edge (as ratio).
>
> Looking at the two components of PF can tell us more about the
> trade
> than looking at PF alone.
>
> Expectancy standardises the edge (PF) to a per trade basis and
> quantifies it (as %).
>
> Expectancy * trade frequency (trades per periods e.g. year)
> quantifies the edge as return per period e.g. year.
>
> brian_z
>
> --- In amibroker@xxxxxxxxx ps.com
> <mailto:amibroker%40yahoogroups.com, "brian_z111"
> <brian_z111@ ...
> wrote:
>
> Chris,
>
> This won't help you much but I thought I would chip in here,
> anyway.
>
> On the contrary - I think it is very apt and insightful.
>
> I used to spend *hours* every week manually updating data
> etc
> . What an agonising waste of time!.
>
> I agree with you.
> Efficient use of time (a.k.a what works?) and leaving risk
> behind
> are
> two major drivers behind the development of my style e.g.
> fundamental
> analysis requires a constant renewal of information whereas
> with
> technical analysis the acquisition phase diminishes with time.
>
> Support and resistance are
> still at the same level, and is never tick precise.
>
> I agree S&R is not tick precise.
> In fact I am inclined to the view that it is generally a
> little
> imprecise.
>
> Take a classical (theortical) example of support - one buyer
> with
> enough clout to make a difference is buying at a target - say
> it is
> a
> whole number $20.00. In real life he or she is a person with
> emotion
> so 20 becomes 19.95. Also in real life the order has to be
> physically
> filled so spreads and market movement around 20.00 means 'buy
> at
> 20'
> becomes +- 0.20.
>
> I am not a long term intraday trader but my observations so
> far
> at
> that S&R are easily identified on intraday charts than EOD
> charts.
>
> The issue is: is the expectancy positive and can I continue
> to
> trade
> this. All three maintained a positive expectancy and when
> this
> fell
> away
> this was the "stop trading this system" signal.
>
> I agree that expectancy is a significant metric.
> I like PF (a derivation of it) and expectancy is really PF
> translated
> in return over time (PA%).
>
> PF is like the HP of an engine.
> The more grunt you have the less you are affected by the
> little
> bumps
> (data errors, slippage, variance etc).
>
> Even a coin with a strong bias will produce its run of outs.
>
>
> Thanks for your post,
>
> Good stuff.
>
> brian_z
>
>
>
> --- In amibroker@xxxxxxxxx ps.com
> <mailto:amibroker%40yahoogroups.com, ChrisB <kris45mar@ wrote:
>
> Brian
>
> This won't help you much but I thought I would chip in here,
> anyway.
>
> I used to spend *hours* every week manually updating data,
> checking
> splits consolidations rights issues etc every week with
> data
> from
> Justdata comparing with ASX published data in the back of
> the
> old
> Shares
> magazine. What an agonising waste of time!.
>
> Now I only look at Fx. With this being retail broker based
> the
> data
> is
> never clean.
>
> Toward the end of last year I ran a simple once a day
> system
> on
> three
> different (demo: yes I know) platforms, entering Limit
> entries
> for
> the
> day in the morning and off to work for the day, as a kind
> of
> real
> time
> walk forward test. Surprising how much time this took to do.
>
> In the evening most times all three platforms had either
> filled
> my
> orders or not, but it was surprising to see how many times
> Platform1 and
> Platform2 would have filled my limit entry, and one of them
> had
> got
> stopped out, whereas the other had got to the Take Profit.
> On
> other
> days
> Platform1 and Platform2 would have filled my entry order but
> Platform3
> ran without me: a missed trading opportunity.
> At the end of the month all three platforms were in profit,
> just
> by
> different amounts.
>
> Because I get my Fx data through MT3 plugin these are not
> exactly
> the
> same prices as my live trading account.
> To be honest I don't think this matters. Support and
> resistance
> are
> still at the same level, and is never tick precise.
> Others may choose to disagree.
>
> Just following three Fx data providers will show you by how
> much
> each
> can differ, notwithstanding the different time zones and
> therefore
> differing candles we get. And that is not even talking about
> economic
> news times!
>
> The lesson for me was clear : the individual trade result is
> irrelevant.
> The issue is: is the expectancy positive and can I continue
> to
> trade
> this. All three maintained a positive expectancy and when
> this
> fell
> away
> this was the "stop trading this system" signal.
>
> That to me is one of the advantages of Fx : no database
> hassles.
> No
> company reports, no shareholder statements, no Chess holder
> statements
> and the inevitable shareholder bits of paper coming through
> the
> mail
> after I have long closed the trades.
>
> The other way to think about it would be: well if Provider1
> has
> different Ticks to Provider2, just backtest and optimize
> for
> each
> respectively over the same time frame and the same tickers.
> If
> your
> parameters and results differ widely this may be a message
> that
> your
> system is marginal. On the other hand, if all is well and
> the
> results
> are very similar, you have just done your own "should I
> care
> how
> clean
> my data is?" test.
>
> Regards
> ChrisB
>
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