An effective trading strategy is only part of a successfully trading plan. If you
want your trading to perpetuate, you better have some form of money man-
agement built into your overall trading approach. Money management
involves examining the concepts of risk and return in reference to investor
preference. The objective is to choose a desired rate of return and then mini-
mize the risk associated with that rate of return. Money management concepts
should be used to make the most efficient use of trading capital. We can’t
emphasize enough the importance of using money management in a trading
plan. The Money Manager strategy is a simple system that incorporates and
demonstrates some simple money management concepts. The concepts we are
presenting go beyond simple profit objectives or protective stops. These ideas
fall within the realm of the underlying trading strategy. We go beyond this and
move into the areas of capital allocation. The concepts that are presented in
this strategy are based on capital preservation and market normalization. We
all know what capital preservation is, but some may not understand the concept
of market normalization. The ability to diversify equal amounts of capital
across a portfolio of different markets is the backbone of any money manage-
ment scheme. If we want to risk 5% of our equity on soybeans and 5% on
Treasury bonds, we need the ability to treat the two markets on apples to
apples basis. Most of the time one contract of Treasury bonds exhibits more
risk than one contract of soybeans. Since we want to maintain a constant
amount of capital to risk on the two markets, we will need to trade less Trea-
sury bonds and more soybeans. Let’s say the implied market risk for Treasury
bonds is $1000 and $500 for soybeans. If we were risking $2000 on each mar-
ket, we would then trade 2 contracts of bonds and 4 contracts of soybeans. We
are maintaining the same amount of risk by varying the number of contracts
for the two markets.
Measuring market risk is the first step in the market normalization
process. Money managers use several different measures to monitor market
risk: average true range, mean change in closing prices, standard deviation in
closing prices, and numerous others. The Money Manager strategy uses the
standard deviation in closing prices to calculate market risk.
Inputs: initCapital(100000),rskAmount(.02);
Vars: marketRisk(0),numContracts(0);
marketRisk = StdDev(Close,30) * BigPointValue;
The StdDev function returns the standard deviation in terms of points, so we
multiply by BigPointValue (dollar value of a big point move) to get market risk
in terms of dollars. Once we know the market risk, we then can calculate the
number of contracts
Building Winning Trading Systems with TradeStation
numContracts = initCapital * rskAmount / marketRisk;
For demonstration purposes, let’s assume we are trading the Japanese Yen and
the market risk is equal to $750. The number of contracts would be calculated
by using the formula from above:
numContracts = 100000 * .02 /750
numContracts = 2000/750
numContracts = 2.66667
Since we can only trade with whole contracts, we round down to the nearest
whole number. Since market risk is the denominator in our formula, whenever
market risk increases the number of contracts decrease, hence, the risk aversion
component of our money management scheme. In similar fashion to the Ghost
Trader, the Money Manager was designed as more of a template than an actual
trading strategy. We wanted to provide the tools necessary to build a money
management platform. The source code for Money Manager follows.
The Money Manager Code
{The Money Manager}
{Demonstrates the programming and use of a money management scheme.}
{The user inputs initial capital and the amount he wants to risk on each
trade.}
Inputs: initCapital(100000),rskAmt(.02);
Vars: marketRisk(0),numContracts(0);
marketRisk = StdDev(Close,30) * BigPointValue;
numContracts = (initialCapital * rskAmt) / marketRisk;
value1 = Round(numContracts,0);
if(value1 > numContracts) then
numContracts = value1 - 1
else
numContracts = value1;
numContracts = MaxList(numContracts,1); {make sure at least 1 contract is
traded}
Buy("MMBuy") numContracts shares tomorrow at Highest(High,40) stop;
SellShort("MMSell") numContracts shares tomorrow at Lowest(Low,40) stop;
if(MarketPosition = 1) then Sell("LongLiq") next bar at Lowest(Low,20) stop;
if(MarketPosition =-1) then BuyToCover("ShortLiq") next bar at
Highest(High,20) stop;
Overall the logic should be easy to follow. However, there is some code that
may not be totally intuitive. The formula that we used to determine the num-
ber of contracts doesn’t always produce a whole number. Since we are trading
want your trading to perpetuate, you better have some form of money man-
agement built into your overall trading approach. Money management
involves examining the concepts of risk and return in reference to investor
preference. The objective is to choose a desired rate of return and then mini-
mize the risk associated with that rate of return. Money management concepts
should be used to make the most efficient use of trading capital. We can’t
emphasize enough the importance of using money management in a trading
plan. The Money Manager strategy is a simple system that incorporates and
demonstrates some simple money management concepts. The concepts we are
presenting go beyond simple profit objectives or protective stops. These ideas
fall within the realm of the underlying trading strategy. We go beyond this and
move into the areas of capital allocation. The concepts that are presented in
this strategy are based on capital preservation and market normalization. We
all know what capital preservation is, but some may not understand the concept
of market normalization. The ability to diversify equal amounts of capital
across a portfolio of different markets is the backbone of any money manage-
ment scheme. If we want to risk 5% of our equity on soybeans and 5% on
Treasury bonds, we need the ability to treat the two markets on apples to
apples basis. Most of the time one contract of Treasury bonds exhibits more
risk than one contract of soybeans. Since we want to maintain a constant
amount of capital to risk on the two markets, we will need to trade less Trea-
sury bonds and more soybeans. Let’s say the implied market risk for Treasury
bonds is $1000 and $500 for soybeans. If we were risking $2000 on each mar-
ket, we would then trade 2 contracts of bonds and 4 contracts of soybeans. We
are maintaining the same amount of risk by varying the number of contracts
for the two markets.
Measuring market risk is the first step in the market normalization
process. Money managers use several different measures to monitor market
risk: average true range, mean change in closing prices, standard deviation in
closing prices, and numerous others. The Money Manager strategy uses the
standard deviation in closing prices to calculate market risk.
Inputs: initCapital(100000),rskAmount(.02);
Vars: marketRisk(0),numContracts(0);
marketRisk = StdDev(Close,30) * BigPointValue;
The StdDev function returns the standard deviation in terms of points, so we
multiply by BigPointValue (dollar value of a big point move) to get market risk
in terms of dollars. Once we know the market risk, we then can calculate the
number of contracts
Building Winning Trading Systems with TradeStation
numContracts = initCapital * rskAmount / marketRisk;
For demonstration purposes, let’s assume we are trading the Japanese Yen and
the market risk is equal to $750. The number of contracts would be calculated
by using the formula from above:
numContracts = 100000 * .02 /750
numContracts = 2000/750
numContracts = 2.66667
Since we can only trade with whole contracts, we round down to the nearest
whole number. Since market risk is the denominator in our formula, whenever
market risk increases the number of contracts decrease, hence, the risk aversion
component of our money management scheme. In similar fashion to the Ghost
Trader, the Money Manager was designed as more of a template than an actual
trading strategy. We wanted to provide the tools necessary to build a money
management platform. The source code for Money Manager follows.
The Money Manager Code
{The Money Manager}
{Demonstrates the programming and use of a money management scheme.}
{The user inputs initial capital and the amount he wants to risk on each
trade.}
Inputs: initCapital(100000),rskAmt(.02);
Vars: marketRisk(0),numContracts(0);
marketRisk = StdDev(Close,30) * BigPointValue;
numContracts = (initialCapital * rskAmt) / marketRisk;
value1 = Round(numContracts,0);
if(value1 > numContracts) then
numContracts = value1 - 1
else
numContracts = value1;
numContracts = MaxList(numContracts,1); {make sure at least 1 contract is
traded}
Buy("MMBuy") numContracts shares tomorrow at Highest(High,40) stop;
SellShort("MMSell") numContracts shares tomorrow at Lowest(Low,40) stop;
if(MarketPosition = 1) then Sell("LongLiq") next bar at Lowest(Low,20) stop;
if(MarketPosition =-1) then BuyToCover("ShortLiq") next bar at
Highest(High,20) stop;
Overall the logic should be easy to follow. However, there is some code that
may not be totally intuitive. The formula that we used to determine the num-
ber of contracts doesn’t always produce a whole number. Since we are trading
