ure out how much time each stock spends in a trade. For example, if each stock
examined spends an average of 25 percent of its time in a trade, theoretically we
then could spend 100 percent of the time in the market, in one stock or another, by
moving in and out of four stocks, if we always could exit one trade and immedi-
ately enter into a new trade.
But because no four stocks will move in perfect synchronization like this, we
might need to track another one or two stocks, to always be prepared to take a
trade. In doing so, however, there also might be situations when we can’t take a
trade because we might be fully invested already. Better to miss a trade because
we’re fully invested than to miss a profit opportunity because we’re not tracking
enough stocks.
Likewise, if the average time spent in the market for a specific stock is 15
percent, then we need six to seven perfectly synchronized stocks to be in the mar-
ket 100 percent of the time. Adding one or two stocks for a little overlap, we might
need to track seven to eight stocks, so that we can have at least one open position
at any time.
Given that most (short-term) strategies spend around 15 to 20 percent in the
market per stock traded, and given that we will try to be in no more than 10 stocks,
on average, simultaneously, this means that we need to track 60 to 70 stocks. The
more systems we trade, the fewer the markets we need to track, because each sys-
tem adds to the time spent in the market for any individual stock. (This gives rise
to two interesting questions we will leave unanswered in this book, but that are
nonetheless important to contemplate: First, are we better off diversifying via the
number of markets monitored or the number of systems traded? Second, should
the systems themselves be looked upon as separate asset classes?)
One question we will answer is how wide, in percentage terms, is one average
true range? Knowing this, we will know how many average true ranges away from
the entry price we should place the MMP, so that it will be 15 percent on average.
The answer is that, at the time of writing, one average true range is approximately
4 percent wide in relation to the close of the same bar. This number is calculated
over the last 2,500 days on the 58 stocks used to research this book. To place the
MMP 15 percent away from the entry price, on average, we therefore need approx-
imately four true ranges, rounded to the nearest whole numbers.
Incidentally, all this makes perfect sense from a risk management point of
view. The logic is as follows: The lower the volatility, the closer SL and MMP will
be to the entry price, and the more shares and money we dare tie up in any indi-
vidual trade, because the volatility and risk is low. Also, because the risk is low,
we don’t need to diversify as much, which we can’t do anyway because each trade
ties up more money than normal. On the other hand, if the volatility and the risk
is higher than normal, the further away SL and MMP are from the entry price.
Thus, we avoid getting stopped out too frequently, while at the same time the fewer
shares and less money we dare tie up in any one position. Also, because the risk isCHAPTER 26 Dynamic Ratio Money Management 309