Money Management
system expectancy
The average profit and loss is also referred to as the expectancy of a trading
system. Assume that we would like to gauge our trading performance by the num-
ber of wins and losses per every 10 trades. Assume that our system’s winning per-
centage is 40 percent, that is, %win = 40 percent. Assume also that we set up our
system with a R/r ratio of two to one, where all positions exit when $Reward = $2
and $risk = $1. Let the total trades be denoted by T. So the average profit and loss
for every 10 trades is calculated as follows (ignoring trading costs, slippage, etc.):Average P L Profit Loss Total Trades T
R number$ / ($ $ ) / ( )
[($
=−
=× oof wins r number of losses T
R number of wins T) ($ )] /
[($ ( / )
−×
=× )) ($ ( ) / ))]
($ ) ($
−×
=×−×
r number of losses T
R win ratio r loss ratiioExpectancy)
($. ) ($. )
$.
=×−×
=+
=
2 0 4 1 0 6
0 20
Assume now that we lost the first 10 trades:Expectancy=×−×R win ratio r loss ratio
=×−×($ ) ($ )
($. ) ($. 2 0 0 1 1 0))
Expectancy=−$ 1 per trade(We say that we have negative expectancy.)
How many trades do we need to recover from losing the first 10 trades? Because
we make +$2 per every $10 trades, we need $Loss/$2 = $10/$2 = 5 windows = 50
trades to recover. How many trades do we need to recover if that happens again?
Assuming our system becomes consistent again and begins performing at %win =
40 percent, we would need 50 × 2 = 100 trades. In fact, the more the trader tries to
trade to get back to breakeven, the greater the chance that it will happen again. The
trader would literally get drawn into a downward spiraling equity decline from
which the trader may never escape. Also, imagine the trader’s frustration after los-
ing the last 10 trades after making money in the first 50 trades. The trader would
be back to breakeven again. So what’s the solution out of this dilemma? Well, one
answer is money management, via the application of stochastic‐based exit tech-
niques and effective R/r ratio, capital, risk, stop, and trade sizing.non‐Controllable factors
Although there may parameters we can alter and amend, there are two critical
variables that we have no real control of, and those are the %win and win/loss
distribution. We have absolute control over the R/r ratio since we can place the
stoploss and take profit at any price we so choose. This essentially renders expec-
tancy as non‐controllable, a performance metric of historical performance. See
Figure 28.20.