Money Management 4

back to

Money Management 3

Money Management-Keywords:
money-management, betsizing, bet sizing, position sizing, asset allocation, position sizing, bet size, bet sizing, cash flow management, trade management, position management, money management, position management, risk control, optimal exposure, betsize, betsize selection, size of a trade, portfolio heat, portfolio management, portfolio exposure, risk management, optimal betsize, optimal trade size, trade size, position size, constant size bets, adjusting betsize, betsize adjusting, number of contracts, leverage

Martingale Method (part 1):

The proper way to use it, especially if your system has less than a 50/50 win/loss ratio, is to use your research to see what is the maximum number of losses you have ever had in a row.
Let's say it's 8. Then what you would do, is start increasing contracts, (I recommend 1 at a time), until you get a win, and then go back to your base unit.
For example:
After 8 losses in a row, trading 3 contracts each, you would then increase your contracts to 4. If it is a winner, then go back to 3. If it is a loser, you would go to 5 contracts, etc.. until you win.
This is the most conservative use of the Martingale method. More aggressive uses are:
1. Start increasing after the average number of losses in a row. So here you find out what your average losing trades in a row are.
2. Increase more than 1 contract at each time. So instead of increasing 1 contract after each ....loss, you might go 2 or more. This should not be done unless your system has a better than ....50/50 win/loss ratio.
The Martingale method, was invented for casino betting, and unfortunately, doesn't work well there, for several reasons.
- Table Limit keeps you from increasing your bet after many losses.
- Inability to remove portion of bet after start of game
- Maximum win is double bet
In futures, the situation is much different:
- No table limit, though you can reach margin limit
- You can remove positions whenever you want
- Maximum win can be many times the average loss
I personally recommend the use of this method and use it every day. Your goal when trading is to make your wins larger than your losses and there is no better way to capitalize on your wins than this.
I start increasing 1 contract after 3 losses, until I win. 80%-90% of the time I win then, and the rest of the time, the market takes me a few more rounds, and then rewards me.
Although exceeding 8 losing trades in a row while increasing has never happened to me, my current plan for that situation is to stop increasing after the 9th loss. Hopefully I will never have to write about that event, though I am always expecting it to happen.
Now since we are far from graduation, I don't want any of you using this method, unless you are 100% capitalized to take 10 losses in a row, increasing each time, plus you already have a winning system. I will be going over this strategy much more after graduation.
I do have something that all of you can start researching now and which should help a lot of new traders be successful in their trading, and you will find that in part 2 of this mini-series.

Martingale Method (part 2):

*** Only take trades after "x" losing trades in a row. ***

For example:
Let's say your research shows you that on average you suffer 3 losing trades before you get a winner. So you would be OUT of the market and would watch the market, and wait patiently waiting for 3 losers in a row. Only then would you risk capital and start trading. You should then take every trade after that until you win.

Now here you have a couple of options:
1) Start after the 3rd loser with a higher starting base of contracts than you normally would. (If normally you would only consider starting with 1 contract, think about trading 2).
2) Consider increasing contracts by 1 after each loss thereafter. So if on that 4th trade you ....lose it, then add 1 contract and take the next trade. Keep on doing so until you win.

The name of the game in trading is Win BIG and lose small. This risk management tool allows you to do that.
The reason this works well, is that the markets go into streaks of losing periods (choppy markets) and eventually take off in a big way in one direction. This method allows you to be a part of that without enduring all the losing trades.
This is NOT a miracle solution. One of the problems that you will encounter is that your wins might be very small.
For example, let's say you wait for the 3 losing trades and then get in, but that one is a loser and you lose 4 ticks. Then the next one is a loser and again you lose 4 ticks, but the following one is a winner but you only get 8 ticks out of it.
While you may have broke even you ended up losing because of commissions. On average this may happen to you 30% of the time, so be prepared for it. The rest of the time you should have nice trends.
So one last plug on working on your risk/money management tools and less on indicator selection. Ok?

How correlated are the drawdowns of the various components of your portfolio, and what will the effect be of a worst case event on the entirety of the capital you have been entrusted with?

Please note: A Neutral Position is a signal! Neutral means that the system is not currently in the market but is looking to enter either a long or short position.

The 2% money stop is for accounts <$50,000.
Risk a certain percentage of money invested on the entry, then raise that percentage, as well as trailing the stops.

Hallmrcdi@aol.com:

The chance of a coin being flipped one time landing on heads is not 50%. It is either 0% or 100%. It is either heads or it is not. The 50% chance is based on an expected average that is itself based on multiple, even 10,000 flips or more, that have nothing at all to do with the outcome of the single real flip that is happening at this moment. We make a terrible mistake and waste our money by soley relying on statistical abstractions and by applying them to a
particular casino, table, session, or hand of cards to determine what is "good" or bad."
Again, the single coin flip is either heads or tails. What has happened for all time past and all time future has nothing at all to do with the outcome of the moment. It truely is a single event. Instead, the recreational gambler's real friend is variation. While one cannot predict when variation will occur, one can predict that it will with certainty occur. The amount one bets during an extremely positive string of wins in a statistically short occurance will determine if the recreational gambler comes away a big winner, while making sure to sit at a single deck game (the factor that drives the edge lower than anything else) is nearly useless.

Van Tharp:
3 Money-Management algorithms (min will be taken):
1) 1% of core capital:
a) (core capital - Total outstanding risk)*0,01 = x
b) x / $ value of initial stop = Nr. Contracts I

2) new risk limited (total risk <=25% of equity): before execution: equity * 25% - total risk= y
if y >0, y / $ value of initial stop = Nr. Contracts II

3) ongoing volatility (10 day M.A. of ATR): max 2% of equity

If a share doubles in one year and halves in the next we have an arithmetic return of:
100% - 50 %/2=25% per annum
and a compound gain of 2 x 1/2 = zero.
If the right proportion of risk capital is put to that risk, a six percent geometric return can be extracted.

Trading can be mastered if you concentrate your efforts on how you will react to price rather than desiring to predict it. Reacting is a business decision, predicting is an ego play.

Traders want to make money. Losses in the long run don't matter.
Forecasters (prophets) want to be right (ego). And that's all that they are concerned about.

Don't decide anything (ego), let the market do that job for you (business).

Like any other business you have a business plan and the financial portion of that plan is the most important.
In this business your inventory is stocks, bonds, futures or options. Like any other business you define what an acceptable loss is on an item and what is an acceptable profit for the risk undertaken. Like any other business
if the item of inventory doesn't do what you expected it to do, you put it on sale and liquidate it to raise capital to purchase inventory that will do what you want it to do. Your acceptable loss is your stop. Your money management
system tells you how much that is. Your mark up is dependent upon your trading system and trading style. It doesn't make any difference if you are a day trader or an investor. Like any business, some turn there inventory 10 times a day, some 20 times a year and some only twice a year. Your trading style and inventory volatility will tell you what your turnover rate will be. Trading is a business and if you treat it as anything else you will be a loser.

Losing traders spend a great deal of time forecasting where the market will be tomorrow. Winning traders spend most of their time thinking about how traders will react to what the market is doing now, and they plan their strategy accordingly.

If one were to ask a successful trader where he thought a particular market was going to be tomorrow, the most likely response would be a shrug of the shoulders and a simple comment that he would follow the market wherever it wanted to go.

Winning traders acknowledge their emotions and then examine the market. If the state of the market has not changed, the emotion is ignored. If the state of the market has changed, the emotion has relevance and the trade is exited.

Establish a trading and money management strategy to determine how much of the available funds should be used at each buying opportunity. In particular, at the start, such money must be held in reserve for future buying. Later, when some stocks have been sold at a (hoped for) profit, there may be a considerable amount of cash available for new purchases. What percentage should be deployed at the next buy signal? Is it better to build up cash reserves resulting from profitable sales in order to wait for a subsequent market decline and even better buying opportunities? Part of the money management would deal with potential "stop-loss" sales and what do to when all of the funds have been invested and there is a new buy signal. Should some stock be sold to provide funds for the buy, or should the signal be skipped?

As a simplified illustration of how hard it is to time the market, assume that you are 70% accurate calling market turns. If you are in the market, two calls are required: a sell and a subsequent buy. The probability of being correct (buying back in at a lower price than your selling price) is 70% times 70%, or 49%. That shows you have to be very good (and most people are not much better than a coin toss) to be successful at market timing.

I have a clearly defined sell strategy, and I will sell for three reasons, all of which helps me to control risk. My belief is that capital preservation is every bit as important as making it grow.
1) I set upside price targets for all of our investments, using future estimates and premiums or discounts to the S&P 500 market multiple. As I approach 90% of our upside target, I will begin to sell. I am never afraid to take profits. Second, if a stock declines about 15% or so from where I bought it, I will sell part of the position, maybe five or ten percent, and quickly reevaluate my catalyst or my reason.
2) If at any time during my ownership period, my catalyst changes for the negative, I will sell my entire position. I do not hesitate to admit that I am wrong.
3) Finally, and the third reason to sell, is that I am very opportunistic and am always looking for better returns elsewhere. The marketplace is often inefficient and irrational, and I try to take advantage of short-term volatility and the inefficiencies of information flow amongst other mutual funds.

Dennis Holverstott dennis@coinet.com:

risk {disaster stop} = factor_1 * volatility
#_contracts = factor_2 * account_size / volatility

So, #_contracts is proportional to account_size/risk. To find factor_2,
program the system to trade 10 contracts at peak volatility and more when
volatility is lower. Export the "volatility adjusted" P/L numbers to a
file and divide them by 10. Run a monte carlo sim (thanks dkomo) on the
results and you will have a pretty good idea of possible drawdowns
(volatility adjusted). Then, you can choose a factor_2 that matches your
risk tolerance.

Once you have studied TA enough to realize how true this is, you will be ready to think about playing with the big boys in the futures pits.
The sooner you accept reality and purge fantasy from your brain the sooner you will be on your way to actual success in trading.

* Good markets don't give you a good opportunity to buy. *

If you believed the ads and could make $1000 a day on $10,000 capital, you could get 200% return every month. Compound that out and you will own the world in a few years.

Stocks are never too high to buy and never too low to sell.

A bull market will made us look smarter than we really are.
"A rising tide lifts all boats."

I am a technician and will do what the market tells me.

There is no way to provide an estimate of the absolute worst outcome (in the same sense that the tails of continuous probability distributions are unlimited).

It's the Execution or implementation of your trading plan that is the bigger challenge.
Throw out 99% of all the crap I learned about oscillators, divergence's, Elliott Wave, cycles, timing, seasonals, Gann, pitchforks, volume, fractals, RSI, stochastics, overbought/oversold (this is a good one - the stock indexes, currencies and cotton for example everyone said were overbought and topping in February and March this year). Look what they did. Needless to say, I don't pay attention to this anymore either, etc., etc. The list goes on to infinity almost. I went back to the basics. I went back to a few simple chart patterns, (a simple moving average and trendline now and then for a visual aid).
Most people make finding the method the big challenge. That is because there is so much junk thrown at traders. They feel like a child in a candy store and have to try every doodad in the place. When they are done, they are sick and never want to see another candy store (trading gizmo) again. They could have had the plain piece of milk chocolate at the front of the store (simple method price patterns) which would have done everything they desired and fulfilled all their needs.

The addition and removal of winning positions at key turning points in a market may hold the key.

Trade to make money, not to be "right" or satisfy some personal agenda. The key to success is to know your limitations and don't trade outside your psychological and risk comfort zones.

Then the trade you entered begins to perform well, and trends in a wave type pattern earning back not only the $1,200 previously lost on the first 3 trades, but another $3,000 on just one contract. Once this trade gets going and confirms a trend, you begin to prudently add on one more contract at a time on each new short spurting rally to the next higher level. Now you're up over $8,000 on the one trade with a trailing sell order (covered in the 3 month course) following the price up so that when the market turns down, you're out with healthy gains.

Someone who has to be right a high percentange of the time is someone who needs constant re-inforcement that they are alright, i.e. a good person. This is all about psychology and how one feels about oneself.
But, which of the following is better: Is it better to make

A. $2, 80% of the time or
B. $6, 60% of the time or
C. $10, 40% of the time?

Assuming that the losses are the same for each profile, the answer is C. which has the lowest winning percentage because the probability times the expected value = the risk adjusted value or in this case 40% x $10 = $4 vs risk adjusted values for A. = $1.60, and B. $3.60.
People who have trouble with this concept are often victims of the educational system which teaches that the key to be successful is being right. One can see from the above example how wrong that can be. The true paradigm for trading is that IT'S OK TO BE WRONG, JUST DON'T BE WRONG FOR LONG. So, now one must make a philosophical decision as to what is more important, being right or making money. If profit is the ultimate goal and not ego then one will adapt to having a smaller percentage of winning trades in exchange for more money over time on the bottomline. To do this, for an experiment, see what happens on a minimum trade size, say a one lot, see what happens if you double your profit target, i.e. rather than going for $2, go for $4. Then keep track of both systems and see which one over several months is more profitable.

Changing the 25 X 25 System Exit

After the last big run up in bonds we observed that the logic of the "25 X 25"Bond System exits needed some
improvement. The system was operating on the assumption that in a trending market the longer we hold a
position the greater the profit. The exit strategy was intended to more or less force us to hold positions at
least 25 days or more.

The problem we discovered was that after the recent buy signal we had a huge profit after only 12 days and
the stop was still too far away. Our original logic was flawed because we equated time in the trade with
profitability rather than simply measuring profitability directly.

Big profits need to be protected regardless of how long it takes to obtain them. As usual the fix was easy
once the problem was defined. We simply added an additional exit that moves the stop up as soon as we
have 5 Average
True Ranges of profit. This is not a curve fit for one event. There were several other times in our historical
data where this exit was needed. The logic of the exits makes much more sense now. We should have
spotted this flaw earlier because we want all of our systems to be as logical as possible. We continuously
emphasize that the logic of a system is much more important than the historical performance data.

Here is the additional line of code that will convert the previous system into version 2.0:

if c> entryprice + (5 * AvgTrueRange(45)) then exitlong lowest(low,2) stop

Average True Range

In this Bulletin we will show some of our favorite applications of ATR as part of our entry logic.
Sample Applications of ATR as an entry tool:

Entry Setups: (Remember, entry setups tell us when a possible trade is near. Entry triggers tell us to do the trade now.)

Range contraction setup: Many technicians have observed that big moves often emerge from quiet sideways
markets. These quiet periods can be detected quite easily by comparing a short period ATR with a longer
period ATR. For example if the 10 bar ATR is only .75 or less of the 50 period ATR it would indicate that the
market has been unusually quiet lately. This can be a setup condition that tells us an important entry is near.

Range expansion setup: Many technicians believe that unusually high volatility means that a sustainable
trend is underway. Range expansion periods are just the opposite of the range contraction periods. Range
expansion periods can be measured by requiring that the 10 bar ATR be some amount greater than the 50 period ATR.
For example the 10 bar ATR must be 1.25 or more times the 50 period ATR.

If you are concerned about the apparent contradiction of these two theories we could easily combine them.
We could require that a period of low volatility be followed by a period of unusually high volatility before
looking for our entry.

Dip or rally setup: Lets assume that we want to buy a market only after a dip or sell it only after a rally. We
could tell our system to prepare for a buy entry whenever the price is 3 ATRs or more lower than it was five
days ago. Our setup to sell on a rally would be that we want to sell short only when the price is 3 ATRs or
more higher than it was five days ago. The choice of 3 ATRs and five days is simply an example and isn’t
necessarily a recommended choice of parameters. You will have to figure out the proper parameters on your
own depending on the unique requirements of your particular system.

Entry Triggers:
Volatility Breakout: This theory assumes that a sudden large move in one direction indicates that a trend in
the direction of the breakout has begun. Normally the entry rule goes something like this: Buy on a stop if the
price rises 2 ATRs from yesterday’s close. Or sell short on a stop if the price declines 2 ATRs from the
previous close. The general concept here is that on a normal day the price will only rise or fall 1 ATR or less
from the previous close. Rising or falling 2 ATRs is an unusual occurrence and indicates that something out
of the ordinary has influenced the prices to cause the breakout. The inference is that whatever caused this
breakout has major importance and a new trend is beginning.
Some volatility systems operate by measuring the breakout in points rather than units of ATR. For example
the system may require that the Yen must rise 250 points from the previous close to signal a breakout to the
upside. Systems measuring points rather than units of ATR may need frequent reoptimization to stay in tune
with current market conditions. However, breakouts measured in units of ATR should not require
reoptimization because, as we previously explained, the ATR value contracts and expands with changing
market conditions.
Change in direction trigger: Lets assume that we want to buy a dip in a rising market. We combine the dip or
rally setup described above with an entry trigger that tells us the dip or rally may be over and the primary
trend is resuming.
The series of rules might read something like this: If the close today is 2.0 ATRs greater than the 40 day
moving average (this condition establishes that the long term trend is still up) and the close today is 2 ATRs
or more below the close seven days ago (this condition establishes that we are presently in a dip within the
uptrend) then buy tomorrow if the price rises 0.8 ATRs above todays low. This entry trigger shows that we
have rallied significantly from a recent low and that the dip is probably over. As we enter the trade the prices
are again moving in the direction of the major trend.
As you can see, the ATR can be a most valuable tool for designing logical entries. In our next article we will
discuss using ATR in our exit strategies and give some interesting examples.

Average True Range

Average True Range is an indespensable tool for designers of good trading systems. It is truly a workhorse
among technical indicators. Every systems trader should be familiar with ATR and its many useful functions.
It has numerous applications including use in setups, entries, stops and profit taking. It is even a valuable aid
in money management.
The following is a brief explanation of how ATR is calculated and a few simple examples of the many ways
that ATR can be used to design profitable trading systems.

How to calculate Average True Range (ATR):
Range: This is simply the difference between the high point and the low point of any bar.
True Range: This is the GREATEST of the following:
1. The distance from today's high to today's low
2. The distance from yesterday's close to today's high, or
3. The distance from yesterday's close to today's low
True range is different from range whenever there is a gap in prices from one bar to the next.
Average True Range is simply the true range averaged over a number of bars of data.
To make ATR adaptive to recent changes in volatility, use a short average (2 to 10 bars). To make the ATR
reflective of "normal" volatility use 20 to 50 bars or more.

Characteristics and benefits of ATR
ATR is a truly adaptive and universal measure of market price movement.
Here is an example that might help illustrate the importance of these characteristics:
If we were to measure the average price movement of Corn over a two day period and express this in dollars it might be a figure of about $500.00. If we were to measure the average price movement of a Yen contract it
would probably be about $2,000 or more. If we were building a system where we wanted to use the set appropriate stop losses in Corn and Yen we would be looking at two very different stop levels because of the difference in the volatility (in dollars). We might want to use a $750 stop loss in Corn and a $3,000 stop loss in Yen. If we were building one system that would be applied identically to both of these markets it would be very difficult to have one stop expressed in dollars that would be applicable to both markets. The $750 Corn stop would be too close when trading Yen and the $3,000 Yen stop would be too far away when trading Corn.
However, let's assume that, using the information in the example above, the ATR of Corn over a two day
period is $500 and the ATR of Yen over the same period is $2,000. If we were to use a stop expressed as 1.5 ATRs we could use the same formula for both markets. The Corn stop would be $750 and the Yen stop would be $3,000.
Now lets assume that the market conditions change so that Corn becomes extremely volatile and moves
$1,000 over a two day period and Yen gets very quiet and now moves only $1,000 over a two day period. If we were still using our stops as originally expressed in dollars we would still have a $750 stop in Corn (much too close now) and a $3,000 stop in Yen (much too far away now). However, our stop expressed in units of ATR would adapt to the changes and our new ATR stops of 1.5 ATRs would automatically change our stops to $1500 for Corn and $1500 for Yen. The ATR stops would automatically adjust to the changes in the market without any change in the original formula. Our new stop is 1.5 ATRs the same as always.
The value of having ATR as a universal and adaptive measure of market volatility can not be overstated.
ATR is an invaluable tool in building systems that are robust (this means they are likely to work in the future) and that can be applied to many markets without modification. Using ATR you might be able to build a system for Corn that might actually work in Yen without the slightest modification. But perhaps more importantly, you can build a system using ATR that works well in Corn over your historical data and that is also likely to work just as well in the future even if the nature of the Corn data changes dramatically.

-
In this article we will show some specific examples of how using ATR can help to make our systems more robust.
First lets look at a simple buy only system for Corn without using ATR. Here are the rules:

1. Buy Corn whenever it rises 4 cents per bushel from the opening price.
2. Take a profit whenever the profit reaches 18 cents per bushel.
3. Take a loss whenever the loss reaches 6 cents per bushel.

Now lets build the same system using ATR. (Assume that the 20 day ATR is 6 cents).

1. Buy when the price rises 0.666 ATRs from the open.
2. Take a profit when the profit reaches 3 ATRs.
3. Take a loss whenever the loss reaches 1 ATR.

We have the original system and a modified version that has substituted ATR for the important variables.
The two systems appear to be almost identical at this point. They both will enter and exit at the same prices.
Now let's assume that the market conditions change and the Corn market becomes twice as volatile so that the ATR is
now 12 cents per day instead of 6 cents. Here is a comparison of the original system and the ATR system:

1. The original entry of 4 cents per bushel from the open is now too sensitive. It will generate too many entry
signals since the daily range is now 12 cents instead of only six cents.
However, the entry expressed as 0.666 ATRs will adjust automatically and will now require the price to move
8 cents per bushel to enter. The frequency and reliability of our entries remains the same as before.

2. The original profit objective of 18 cents per bushel is much too close for a market that is now moving 12
cents per day. As a result the profits will be taken too quickly and our original system will be missing many
opportunities to make much bigger profits than usual.

However the profit target expressed as 3 ATRs has automatically expanded the profit objective per trade to
36 cents per bushel. Significantly larger profits are now being realized by the ATR system as a result of the
increased volatility.

3. The original stop loss of 6 cents per bushel will now be hit frequently in a market that is moving 12 cents
per day. If you combine these frequent stop loss exits with the overly frequent entries being generated, you
have a classic whipsaw situation and we can expect to encounter a severe string of losses. Our original
system is now failing because the market conditions have changed. We need to fix it or abandon it in a hurry.

However lets look at our ATR version of the system. The stop loss expressed as 1 ATR now sets our stop
farther away at 12 cents so it isn’t being hit any more frequently than before. We continue to have the same
percentage of winning trades only the winning trades are much larger than before thanks to an increased
profit objective. Our ATR system has a nice series of unusually large winning trades and is currently making
a new equity peak. The ATR system now looks better than ever.

In our example, the proper application of ATR has made the difference between success and failure.

Here is a system that grows:

Take a look at a commodity like March Coffee KC.
Then look at the Highest High for the last 20 days and lowest low for the last 20 days I think the HIGHEST HIGH is 125 (1/5) and LOWEST LOW is 113 (12/21) so the 20 day channel is 375 big points which is the same as $4,500 dollars.

The exit is is the difference between the HIGHEST and LOWEST at the time of the trade or 125.5-113 12/21.
This is the amount that we trail upward on this trade.

You then take your bankroll:
let's say you start trading with $1,000,000
and you only want to risk 1%
1% x 1,000,000 is $10,000
$10,000 / $4,500 = 2
you then would buy 2 contracts of Mar coffee if it broke through the high or low and you would trail the stop at 125-113 = 12 big points
(12 Big Points mean you risk 12 * 375 = $4500 per contract)

This system grows with you forever and you can take any days 20-40-100 but in TradeStation, you cannot test systems that share a common bankroll among commodities.

My first approach was to find max DD and then use it or 2X it to find an amount of contracts to buy, my second approach is to use the size of the channel to determine contract size.

I think people that know C++ and other languages can also test markets sumultaneously.
I fake test this by testing each commodity one by one...lets say I start with coffee and 1 million and risk 1%...I run all of coffee and lets say I end up with 2 million, I then use the 2 million and use it in OJ, then run it, then take that value onto the next commodity...so I use a manual linear technique which is not perfect, but gives me a rough idea.

go to

Money Management 5

^{back to top}