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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@xxx 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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