Why Is Position Sizing Important?
Position sizing is the process of determining HOW MANY contracts to trade
when your system gets a signal. Position sizing is one of the most important and
least-understood concepts with losing system traders. The purpose of position
sizing is to control risk, enhance returns and increase robustness through
market normalization. Position sizing can end up being more important than when
you actually buy or sell! Unfortunately, most systems and testing platforms seem
to ignore it completely (or worse, apply it illogically).
One of the biggest problems
with many trading systems is that they risk too much of a trader’s equity on any
given trade. Most professionals agree that you should never risk more than 1% to
3% of your equity on any given trade. This also applies to the amount of risk
per sector. For example, risking 2% per trade in highly correlated markets like
2 year bonds, 5 year bonds, 10 year bonds and 30 year bonds is essentially
risking 8% in the same trade, far in excess of what’s prudent. Overtrading this
way can produce what appear to be incredible-looking results. This is usually
just a case of using too much leverage and risking too large a percentage of the
account per trade (or sector) and or “cherry-picking” an optimal starting date
(like right before a series of winning trades).
When you run a “Worse
Case Analysis” at those high-risk levels, you see that your risk of ruin
climbs dangerously high. A series of bad trades or starting on the wrong day
could cause you to lose it all (or have an enormous drawdown). The bottom line
is that when you put a trade on, you should know exactly what percentage of your
equity you will lose if your wrong. This percentage should be a very small
amount of your available trading capital. This also means you need to know your
actual risk when you enter the trade (excluding slippage). Some systems like
moving average crossover reversal systems don’t know how much risk they are
taking. This is because the system does not know how far the market needs to
move to actually trigger an exit, etc. We think it’s dangerous to trade this way
and don’t recommend it.
Another big problem is the lack
of market normalization (such as single-contract based results). For example, we
don’t think it makes sense to trade one contract of natural gas with an average
daily volatility of around $2,000 for every one eurodollar contract with an
average daily volatility of around $150. Doing this would imply that natural gas
is a more important market than the eurodollar. We don’t think that’s a good
idea, if the eurodollar has a trend we want to give it just as much weight as
natural gas (or any other market). In the previous example, you could just
simply remove the eurodollar from the equation and get roughly the same
performance. In essence, the results have been inadvertently biased to natural
gas even if both markets are traded the same way (an average $150 winning trade
in the eurodollar is not going to offset an average $2000 losing trade in
natural gas, etc.).
The reason you trade a basket
of commodities is to be diversified, however, if most of your profits and losses
come from a few of the markets in the portfolio your not really diversified. The
problem is that going forward, you are going to be dependent on those few
markets to perform. It’s far better to know that any market has the potential to
perform at an equal level instead of being dependant on specific markets within
that portfolio. We think this type of position sizing and money management is
the most robust method.
It’s likely that most systems
ignore position sizing or apply it illogically because most software packages
have been designed to work with single-contract based testing. In fact, of the
countless back testing products available for sale we are only aware of
one software package that can properly do
position sizing and money management testing. There are many products that
claim to do it (software add-ons, Excel
spreadsheet macros, eye-candy type products etc.). However, we have found that
almost all of these products don’t do position sizing
and money management correctly (there are quite a few reasons for this — email
me for details).
Other problems include vendors
that only report the smaller drawdown numbers like “closed trade” drawdowns or
“average annual” drawdowns etc. There are also problems with position sizing
concepts such as as “Optimal F” or “Fixed Ratio.” In our opinion, both of these
are actually just a dangerous form of hindsight-biased curve fitting. Along
these lines is another common fallacy that says you should find your “best”
single contract based system FIRST and
THEN apply position sizing to it. This is not the
correct approach; position sizing can completely change the risk-to-reward
profiles of single contract based systems. A system that looked great with a
smooth equity curve on a single contract basis can look far less attractive when
all markets are equally weighted for robustness (as they should be).
For all the reasons cited
above, we make sure our systems are developed and rigorously tested with what we
feel is the correct type of position sizing logic and money management
software. We believe this increases the robustness and significance of our
testing results. This also helps avoid the inadvertent optimizing that can occur
with other types of position sizing / money management based testing software.
Feel free to email or contact
me with any questions or comments on this subject.
Dean Hoffman