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Have you completed lesson 9’s action steps?
If not, complete those steps before reading on.
Analyzing Trading Systems
The astute system tester may have realized that a slight
change in a trading system’s variables can have dramatic effects
on its profitability. But is profitability the only criteria by
which you should be evaluating a trading system?
Clearly the answer is NO!
Here are just a few other criteria you need to look at:
- Are you satisfied that your system is reliably profitable?
- Will your draw downs wipe out your account?
- Is your system trading in a way you can tolerate?
- Can you tolerate long periods of no trading or too much trading?
- Can you tolerate a large string of losses?
To fully answer these, and other similar questions, you must analyze
the results from your back testing. Unfortunately, with the plethora
of trading statistics that most back testing programs provide, this
can easier said than done. I believe you really only need to pay
attention to a few critical statistics. Here are the ones I pay
close attention to:
Win/Loss Ratio
When you assess the performance of a trading system, one of the
first statistics that gives you a good indication of the strength
of that system is the Win/Loss ratio. Quite simply, this is the
ratio of the average winning trade in dollar terms, against the
average losing trade in dollar terms.
If this ratio indicates you are, on average, winning more than you
are losing, you are on the right track. However, realize that this
statistic on its own isn’t enough because it doesn’t consult how
much was risked to produce that gain or loss.
Risk Multiple
The risk multiple (R-Multiple) builds upon the win/loss ratio in
that this is the win/loss ratio compared to the amount of money
risked to make that win/loss.
It's a measure of the reward obtained from the trade compared to
the amount of risk taken for the trade.
For example, if you risk $100 and make a profit of $500, then you
have made 5 times the amount you risked in the trade, in which case,
you have an R-mulitple of 5. This means that for every $1 you risked
you were rewarded with $5.
Similar to the win/loss ratio, this statistic on its own isn’t enough
to determine whether a trading system is worth trading.
Expectancy
A trading system’s expectancy is perhaps one of the most powerful
statistics you can have because it is a way of quantifying the performance
of a system that is independent of the size of the trading float.
Simply it answers the question how much money can my system, on
average make for every dollar that I risk?
In short, it returns the expected dollar return for each dollar
risked by the trading system. This is different to the reward risk
ratio which we described above, that was a specific ratio of reward
to risk. Expectancy defines a return in dollar terms for every dollar
that you risk.
For example, a system with positive expectancy is one in which a
positive dollar return is expected for each dollar risked. If your
system has an expectancy of +0.75, on average you would expect to
make .075 times the amount you risked in the trade. If you risk
$1, then you would expect to make on average $0.75 for every trade
you take.
As a guide, if you can achieve expectancy of $0.60, you have a good
profitable trading system.
Number of Trades
Then there’s, the number of trades a system gives over the course
of a year. I find this an invaluable, yet rarely talked about, statistic.
Your trading system should not give too many or too few trades.
The number of trades that a trading system gives should be approximately
the same as what can realistically be taken.
The two sides of the coin are equally dangerous. If a system gives
too many trades, you will be forced to choose between signals, therefore
adding ambiguity to the system. With ambiguity comes human discretion
and this often has a detrimental effect on the performance of the
trading system.
On the other hand, if a system gives too few trades, your trading
capital will not be fully utilized and you may not be taking full
advantage of the available trading opportunities.
So how do you calculate the optimal number of trades for a trading
system? I’m glad you asked ? :)
This is done with the calculation called “opportunity.” In short,
opportunity helps determine your optimal opportunity for a trading
system.
Opportunity = (240 / Average Days In Trade) * (Trading Float / Average
Trade Size)
For example the optimal opportunity for a trading system with the
following variables would be:
Float = $25,000
Average Days In Trade = 19
Average Trade Size = $3,500
Opportunity = (240 / 19) * (20,000/3,500) = 72 trades per year.
Annual Profitability Return
Lastly, with the statistics we’ve now covered, we can calculate
the annual profitability return of your trading system. The profitability
of a trading system is the combination of the expectancy and opportunity.
Now, it’s simply a matter of plugging in the values you have already
calculated into the formula below:
Annual Profitability Return = Expectancy * Opportunity * Percentage
Risk Per Trade (Percentage Risk Per Trade Defined In Trading
Secrets Revealed).
For example, if a system with an expectancy of .75 had an opportunity
of 72 trades per year and we risked a maximum of 2% per trade, the
annual profitability return would be calculated as follows:
Annual Profitability Return = .60 * 72 *2% = 86.4% p.a.
Can you see the power within these statistics? Statistics really
is a topic worthy of a complete course itself. They really do provide
tremendous insight into a trading system.
If you found this topic interesting and would like to further expand
your understanding of this topic. You may be interested in looking
further into Dr. Van Tharps work. In fact, he has a fantastic course
that covers these topics, and many others, critical to the understanding
of system design.
Tharp’s course is called Developing
a Winning Trading/Investing System That Fits You, and I have
found it invaluable. Although it’s not critical, you can purchase
your copy online by clicking
here.
Let’s make you a market wizard. |
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