Daily simulations are
conducted at my end to
reinforce the
effectiveness of the
trading strategy (as
well as mental
reinforcement) and to
display how the trading
results can vary on a
daily, weekly and
monthly basis. When
running thousands of
simulations I tend to
use an in-house built
Monte Carlo Analysis
tool, however when
simulating trading
results for a single
month then I tend to use
the following website
http://www.roll-dice-online.com.
How I use this website
to conduct trading
simulations is as
follows.

The key data point
needed is firstly the
mean win rate for my
trading strategy which
is 55%. Presently I am
putting on trades where
my risk is £100 and my
reward is around £180 (*Please
note this simulation
conducted in May 2018
was based on 1.8R but
since Mid July I have
moved towards a 2.75R
model*). I
am also trading on
average about 4 times
per day. This is based
on a bank of £5000 so my
risk per trade is 2% of
my bank which is within
the acceptable norm of
up to 3% in financial
trading (I try to model
financial trading rather
than typical sports
betting).

Therefore with
roll-dice-online.com
these are the values I
enter.

1. I pick a 9 sided dice
because its the closest
representation I can
obtain of a dice that is
able to provide a 55%
win rate simulation
(meaning that 5/9 * 100
= 55.555%). So when
rolling the dice if the
numbers 1, 2, 3, 4 or 5
come up then we define
that as a trading win
and if the numbers 6, 7,
8 or 9 come up we count
that as a trading loss.

2. We roll the
dice 4 times as this
represents the 4 trading
opportunities per day.

3. Number of rolls is 31
as this represents the
number of trading days
in most months.

4. In the tables further
below I divide the days
into weeks so days 1-7
is Week 1, days 2-14 is
Week 2 and so on.

4.
Click here for the
raw data results. For
day 1 (the first test
result) we see 2,
6,
8,
8.
This means for day 1
there was 1 winner and 3
losers.

5. Since my winning
trades are £180 and my
losing trades are
-£100 this means
my profit for day 1 was
-£120

6. This is the logic we
apply for test result 2
all the way down to test
result 31 in the raw
data file.

7. The only other point
to be aware of is if my
first 3 trades are
losing trades then my
daily stop loss is
reached (happy to lose
the battle) and I stop
trading. So the maximum
loss I will take in any
day is
-£300. The
tabulation and
conversion of the raw
data file into daily
profit and loss is as
follows.

8. So based on this
simulation for a months
worth of trades the
total net profit is
£8420. (I am aware there
can be slippage due to
betfair costs, possibly
having to take slightly
less profit for some
trades based on how
price is moving etc but
the £8420 is a target).

9. Out of 31 trading
days, 26 days were
profitable days and 5
days were non profitable
so percentage of
profitable days is
83.87%.

10. The mean of the
losing days is
-£156 and the
mean of the winning days
is £353.84. Therefore
the winning day on
average is 2.2 times
more than the losing
day.

11. If I plot the equity
curve (based on daily
results) it would look
like the below.

12. If I plot the
standard deviation and
daily equity analysis it
would look like this

13. The data clearly
shows that the strategy
has a strong positive
expectancy despite the
fact that I am only
winning 55% of the time.
However it is the power
of the risk reward ratio
and the ability to trade
at least 125+ times per
month which helps to
ensure the strategy has
great potential.

14. If you keep clicking
"roll dice" it will keep
presenting new sets of
data so If I was to go
through this exercise
again the amount earned
per month could be down
to £6000 or up to
£10,000. This is due to
the science of random
normal distribution so
the idea behind a Monte
Carlo Analysis is to
simulate this
experiment thousands of
times and then take the
average of all those
simulations.

15. When you see my live
daily results (click
here) you can
then compare it to this
simulation and when you
see me going 4-5
profitable days in a row
with a strong equity
climb instead of being
in disbelief you can go
back to this simulation
or run your own
simulation to mirror the
type of results you
would expect from a
strategy with the
parameters I provided.
If you see week 3 above
you will see a whole
week where every day was
profitable. I can also
see that there is
normally no more than 2
losing days per week.

16. Imagine earning on
average £8400 per month.
This equates to an
annual salary of **
£100,800**. Remember
this is tax free as
earnings from activities
considered gambling by
the UK government are
not taxable. I know
people who do IT
contracting where
earning £700 per day is
the top end of the
contracting earning
scale. If you take £3500
for the 5 day
contracting week it
equates to an annual
salary of £182,000.
Deduct the 40% income
tax and the net annual
income is **£109,200**.
For the sake of making 4
trades per day and not
having the stress of
having to be in a 9-5
job with a boss sitting
over your head I know
which job I would
prefer.

17. The final and most
important point here is
this. By increasing my
position sizing it
naturally increases my
earning potential. So if
my liability instead of
£100 was now £150
meaning my winning
trades were now £270,
imagine the increase
this would make to the
annual earnings. This is
why I had to develop my
own system rather than be
limited by system
peddlers wanting to
convince me that its not
possible to be earning
more than £2000-£3000
per month trading full
time.

*I realized I had to
think completely
differently to how 90%
of the sports trading
industry think and
approach trading. It had
to be a probabilistic
and systematic approach
based on science and not
human bias.*

My reward needs to be
higher than my risk, my
win rate simply needs to
sustain the reward to
risk ratio (without
having the pressure of
trying to be right all
the time) and to avoid
severe volatility/variance
(randomness) for
weekly and monthly
results I need to be
trading at least 30
times per week where
possible rather than
just taking the odd 1-6
trades per week and
crying when variance
hits and results in a
losing week. Every
component is a critical
aspect of the whole.

If you enjoyed this
simulation insight then
make sure you join my
biweekly webinars which
begin in May. Please
note I am not charging
or selling anything.
Instead I remember
promising that if I ever
made a success out of
trading I would try to
give back by sharing the
fundamentals (click
here) of what
helped me because I was
in a very dark place
with my trading
previously and know the
frustration, turmoil and
desperation it can breed
when you are following
peoples systems and tips
that simply don't work
long term.

You are different to
every one else in the
world. You are unique.
So why not build
something that resonates
with you and works for
you.

Look forward
to seeing you on my webinars and will keep
you updated on twitter
nearer the time.