资金管理(英语连载）

缩水基金

Money Management 8

Money Management

An essential element to success in trading is ignored in almost all trading or market timing books or articles. It's surprising given its importance that very few writers devote any time to the discussion of money management practices and principles. This chapter will present one approach to money management that is general and could be easily supplemented by other methods if you desire. The goal here is to provide recommendations for a simple, viable approach to allocating funds and managing your portfolio.
This book is not intended to include a course on money management. However, if there is one subject within the realm of trading that is vital to a trader's financial survival and at the same time totally overlooked as critical, it is the discipline of money management as it applies to trading success. If market indicators and systems were always precise in identifying tops and bottoms, the necessity for prudent money management skills would not exist.
Unfortunately, such is not the case. Even if a system were 99 percent accurate, the 1 percent failure rate could conceivably wipe out a trader who did not apply money management methodology. The following techniques for your consideration in designing a prudent and viable money management program may appear simplistic upon first glance. However, making procedures complex serves only to obfuscate the obvious, easy, and straightforward approach to sound money management. These recommendations regarding the design of a money management methodology are a compilation of various techniques I have developed and employed successfully throughout the years.
Before you enter any trade, you should be convinced that the trading event will prove to be profitable. Otherwise, why even attempt the trade? Obviously, no decision in life is always correct and this applies invariably to the markets. In the case of the markets, however, you are not able to undo a bad decision and recover your losses from a trade.
This lesson came early in my career. Discretionary decisions or trading hunches or guesses may prove profitable on occasion, but how do you quantify and duplicate this decisionmaking process in the future? Consequently, the following suggestions are directed not only toward developing -a series of mechanical, objective approaches to trading decisions and money management but also to enable you to replicate your decision-making process regardless of the time period and the number of markets followed. The primary considerations are consistency, objectivity, and portability. Additionally, you need to be sensitive to diversification of market timing techniques, as well as markets monitored. By implementing a number of unrelated methods, you will be able to sufficiently diversify your portfolio and thereby reduce your level of risk. In other words, by applying a combination of market timing approaches, each of which uses a different trading philosophy, you will be able to operate as if you had a number of trading advisors managing your funds. Obviously, these techniques should be applied on paper before introducing them real time into your trading regimen. Once the techniques have been sufficiently tested to ensure performance results and nuances, the money management disciplines must be introduced. The other chapters of the book pertain to the methodologies, so this discussion is devoted to a basic approach of managing trades and your investment.
First, you should allocate percentages of capital equally to various mechanical market timing models. Therefore, if you have developed and decided to use three noncorrelated mechanical approaches, then you should designate the same percentage participation to each. You may choose to vary this approach. For example, if one system is two times more effective than another, then you would double by position size or if the frequency of trading for one method is twice as active as another technique, you may wish to reduce portfolio commitment by 50 percent.
However, for sake of discussion, assume that all systems are equally effective. Assuming a total of 100 percent, you may not wish to allocate in total more than 30 percent to these systems collectively at any one time. Also assume for purposes of simplicity that you have elected to follow 10 individual markets for each system. Consequently, your maximum exposure would be no greater than 30 percent of your beginning equity, and that is only if each model has its maximum investment exposure of 10 markets at any one time and each market is being traded simultaneously at the same time (10 markets times 3 trading methods times 1 percent apiece equals 30 percent exposure).
How are you to measure your investment commitment in terms of number of futures contracts, for example? Rather than subscribe to an esoteric portfolio management methodology with numerous complicated variables connected by advanced statistical formulas, you should rely on the market itself to dictate your level of exposure at any point of time. Specifically, the various futures exchanges determine the margin requirements to trade markets. Typically, as trading activity becomes volatile, the margin requirements increase. At that time, you should reduce your exposure because you would have specifically allocated only a 1 percent commitment to that market for this particular market timing method. Conversely, when price activity becomes inactive and less volatile, you would increase your investment exposure, hopefully, awaiting a breakout and increased volatility. Consequently, margin requirements serve as a barometer for fund allocation.
To clarify this process, the market itself is the best source for dictating market exposure. This measure can easily be determined through simple calculations. The various futures exchanges evaluate the volatility and volume of markets continuously. If for any reason, they believe that the potential exists for wide daily swings in the market and, concurrently, the risk of erosion of a trader's margin, then, typically, they will be inclined to raise margin requirements. Therefore, whenever margin requirements are raised, market exposure as measured by the number of contracts traded should be adjusted accordingly. In other words, say you assume a portfolio size of $1 million, the use of three trading systems, and the limitation of trading only 10 markets in each. The maximum exposure can be no greater than $300,000 dollars, since that amount accounts for 30 percent of $1 million, the maximum account size defined above. It is unrealistic to assume that positions will exist in each and every market at any one period of time, however. In any case, this allocates $100,000 to each of three markets. In turn, this would imply that for each method, each market would represent $10,000 dollars. Now suppose the margin requirement in one market is $ 1,000. Then 10 contracts could be traded at any one time. If volatility increases, the exchange may decide to raise margin requirements by an additional $1,000 to $2,000, thereby forcing you to reduce your position size to five contracts (5 x 2,000 = $10,000 and 10 x $1,000 = $10,000). What has effectively occurred is a portfolio contract-size adjustment of 50 percent due to a 100 percent increase in margin requirements. If the volatility has increased sufficiently that the exchange is compelled to raise margin requirements, and you are still positioned in the market and have not been stopped out of the trade, then it is likely that the market has moved in your favor. In that case, the money management discipline and methodology described here requires closing out profitable positions, and prudent trading would also dictate profit taking. The initial exposure was a function of margin requirements, and the change was made as a result of market volatility and potential risk as defined by the increase in margin requirements.
Once in a trade, stop losses must be introduced. Generally, you should apply a standard stop loss and not risk any more than 1 percent of your portfolio on any one trade. Should you desire to increase this stop loss, you should reduce accordingly the size of the position or exposure you have in that market and at that method at that particular time.
For example, you should always maintain a 1 percent risk level, but if you wanted to increase the dollar stop loss to double that amount, you should reduce your market exposure by 50 percent. All other increases in stops would be adjusted accordingly as well.
As the portfolio size in one method and in one market increases, you should adjust your stop loss and profit-taking levels and make certain that your exposure does not constitute an undue weighting in the portfolio. In fact, as the profit in a position increases, you should reduce the position size to maintain a maximum portfolio exposure and, ideally, in effect you will be investing only the profits generated in the trade.
The approach described here is simplistic but effective. High-tech mathematical modeling and sophisticated statistical techniques can be introduced, but experience indicates that minimal improvements will be produced.
Although this approach to money management is devoted to high-margin futures, a similar approach can be easily applied to stock portfolios.
In conclusion, it is critical that a trader design and implement a methodology that is capable of being measured for performance statistics historically. Once confident of the results and comfortable with the implementation, a trader should paper-trade the method and then apply it real time to the markets with funds in small lots or shares. As you gain experience and confidence with the method, the position size can increase. Discipline is a prerequisite. If you conform to the general money management guidelines discussed in this chapter and then add improvements to the schedule to fill in any blanks in procedure, a difficult and critical component of trading success will have been addressed and satisfied.

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The Kelly formula


A simple case of the Kelly formula is where you either double your wager (i.e. you get back your bet plus an equal amount) with probability p or else lose it all with probability q = 1-p . The Kelly system says that in this case the optimum fraction of your capital to risk is f=p-q.
For example, if you have a system in which you double your money with a 60% probability and lose it all with a 40% probability then your optimal fraction to bet is
f = p - q = 60% - 40% = 20%.
The mathematical reason that its true is actually quite simple.
In the double or nothing case above, the log of your return per bet after W wins and L losses using this system is:
(W/N) log(1+f) + (L/N) log(1-f) where N=W+L.
If N is large then W/N=p and L/N=q. Maximizing this expression in f using calculus gives f=p-q, as expected.

Thus, if the assumptions are satisfied, your portfolio will grow at the highest rate if you invest the optimal f each time. One problem with the Kelly criterion is that it implies a larger maximum drawdown than most people would be comfortable with. Most people would likely want to choose a fraction to bet which is less than the Kelly fraction even at the expense of optimality. Another problem is that you often don't know what p is.
For purposes of illustration, I have used the same simple double or nothing setup that Kelly uses in his original article but the entire idea generalizes substantially beyond this.
Since you probably don't know what p and q are you could just pick an X% and Y% that are sufficiently small. For example, you could choose X% as 3% or 5%, say. A number of practically oriented books and articles recommend that sort of approach.
William Gallacher's book, Winner Take All, is another source which mentions and critiques Optimal f in the context of futures trading.

Louis Kates
lkates@alumni.princeton.edu

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Tips & Hints:

Should you desire to increase this stop loss (1% of cap.), you should reduce accordingly the size of the position or exposure you have in that market and at that method at that particular time. ð adjust stop loss and profit-taking levels
As the profit in a position increases, you should reduce the position size to maintain a maximum portfolio exposure and, ideally, in effect you will be investing only the profits generated in the trade (!).

Random Entry Strategy:

The initial strategy demands that with any trade on, right or wrong, the stop and exit system would either leave you in the good trades or get you out of the bad trades at a small loss and under certain circumstances get you on the other side. The random initial entry perspective forces you to develop a very disciplined trading strategy and trading rules to go along with it. More importantly, it gets you away from looking for all the answers in the various entry systems which were being promoted.
The stop and exit rules for the system were developed with an extreme perversion to optimized values and being very careful to watch the degree of freedom which I allowed the system to have. Once you have a set of profitable stop and exit rules, you can concentrate on developing an entry system that was more intuitive than the random 'flip of the coin' method. This step in the development of a system, by definition, became much less important.

The importance of discipline in your trading regime can not be overstated, especially on exits. This discipline was a welcomed (and badly needed) side effect of developing a trading system with this methodology.


Trailing or multiple contracts:

Enter all contracts on the entry and exit half (or a portion) at the primary exit signal, stop is moved to breakeven on the remainder and we trail the remainder until the secondary target or we get stopped out. Each trade has an associated stop plus a primary and secondary exit ð at the time of entry, all possible exits signals are known and quantified

I use threshold levels to increase my trading size. My formula is:
2x max historical drawdown + margin = equity needed to trade 1 S&P contract.
So a 50% drawdown to me means a real 25% drop in equity.
By drawdown I'm talking about my total net running drawdown. I always use stops on my individual trades which keeps my max. daily net loss around 3% to 5% depending how many systems trade that day (I use 3 systems). The recent volatility in the S&P's has forced me to almost double my stops over the last 6 months which has made the drawdowns deeper.

Turtle System trading signal:

1. Enter a long/short when a tradable (!) exceeds its 20 day highest/lowest close.
2. Exit a long/short when a tradable (!) reverses to inside its 10 day highest/lowest close. (wenn letzter "theoretischer Trade" ein Verlust war, nur eine Position eingehen [theoretischer Trade: wenn weitere Kriterien' nicht erfüllt?])
The second part on money management describes when to increase or decrease the number of contracts traded.
The hint I can give is "volatility". Focus on the volatility of each individual market. Then think of in terms of "units". Derive your starting capital into measureable "units" based on volatility.

The Turtles managed the absolute risk this way:

1. Take the average of the True Range over 10 days
2. If this is rising, trade with FEWER contracts. This allows the stop (=risk) to be
wider and so you risk a constant amount of money but with fewer contracts
3. If average TR is lower, then start trading more contracts
Trailing Stop:

Let's say you buy an S&P at 900 and it rises to 902. If the S&P stays above 902 for a week and then falls below 900, say to 898.40 then you get stopped out at that point, 898.40, assuming no slippage. A Trailing $400.00 trailing stop would get you out at 900.40 assuming that the S&P did not get any higher than 902.

Risk-Reward-Ratio:

10% risk per trade: you may think, that if you have 100000 you could risk/invest no more than 10000 in one stock (e.g. 50 stocks á 200). But consider buying a stock priced at 200 with a 2$ stop loss: risking 10% means, one could buy 5000 stocks ! So risk must be thought of as the percent of equity you are willing to lose on a trade if you are wrong. Risking more than 3% is extremly risky, especially if you have 10-15 positions on at one time.

缩水基金

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Limit Orders:
A big advantage to limit orders is maintaining a predetermined Risk-Reward-Ratio for a specific trade. In other words, if you enter a trade with a stop-loss and a target price and you like to maintain a certain ratio, say 3 to 1, then you must pass if you can't enter the trade within the Risk-Reward parameters. For this reason, I like to use stop with limit orders.

Adaptive Moving Average & "Efficiency Ratio":
An exponential moving average in which the smoothing factor varies with the "Efficiency Ratio". Efficiency ratio is the ratio of total price excursion divided by the sum of all individual excursions of each bar. It equals 1 if all moves are in one direction over the lookback period.

Buy & Hold:
Take your system and gauge it against a Jan through Dec against simply buying and holding. This will let you know how much was really your system and how much was just the market.

100000 Account + Stop-Loss: $1500 13 Markets
a) simultaneously active in all markets and stopped out in all markets:
19500 Loss ð 19,5% Drawdown
b) 13 consecutive losses:
19500 Loss ð 19,5% Drawdown
c) simultaneously active in all markets and stopped out in all
markets + 5 consecutive losses:
97500 Loss ð 97,5% Drawdown (!!!)
d) 5 consecutive losses in all 13 markets (65 consecutive losses):
97500 Loss ð 97,5% Drawdown (!!!)
ð check 50% Drawdown (shutdown point) !!!


5 Systems: sum all positions up to arrive at the final trade:
get a net position of 3 contracts long (5 long - 2 short)

Bring the two files into Excel, and add the NetProfit columns together to get the combined equity curve.
weight the equities: for example, if I have equities for BP, DM, JY and SF I may create an equity curve of 2*BP + 1*DM + 1*JY * 1*SF where the coefficients 2,1,1,1 are inputs

15% in margin: 2-5% DM, 2-4% DAX, 2-4% Gold, 1-2% Euro-$
ð so increase number of contracts within these limits

accept a 50% reduction in Return if it comes together with a 30% reduction in Drawdown

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Portfolio-Stop: -7-8% monthly: Stop !
Return p.a.: = 3 * Drawdown
Drawdown + Regression-Analysis:
45° + deleverage at a parallel line ABOVE the 45° line (to let room for further losses)


Drawdown 40%
Recovery 100%
Net Return 20,0% =(1-40%)*(1+100%)-1
when using a proportional Trading System, the ratio of recovery should be a constant:
X 2,50
(1-Drawdown)*(1+2X)-1 = 0
D = (X-1) / (2*X)
30,0% optimal Drawdown ð trade 1/4 less (from 40% to 30%)
22,5% new Net Return


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Third Of A Series On The Successful Use of Money Manage-ment To Improve Your Trading Results - Tom D'Angelo

http://www.commoditytraders.com/issue/tom.html


This is the third in a series of articles which describe how to construct a professional and disciplined money management plan, designed to allow the trade to manage his trading in the same manner as a successful business. Refer back to my previous articles in Vol 4-1 and Vol 3 8 for a detailed discussion of the Profit Center methodology and calculation of the required money management statistics.

In this article I will discuss the Performance Report. The Performance report is a summary of all the significant money management statistics for each individual Profit Center. Each Profit Center is a business and the Performance Report is a management report which reveals your success or failure in managing that business.

The Trading Plan is the trader's strategy for the next trade based on the information provided by the Performance Report. The Trade Journal is an "after the fact" critique of the Trading Plan after the trade is closed out with a profit or loss. I will discuss the Trading Plan and Trade Journal in my next article.

There appears to be lots of interest in the Real Success trading methodology. I have not purchased this course but I will try to describe a sample Performance Report for Real Success methodology traders.

First, if I was trading the Real Success method, I would set up the following Profit Centers:

RS(M)- All trades taken from the Real Success Methodology

RSDAY - All Real Success day trades. Overnight Real Success trades can be entered into a Center named RSONITE

RSSP500 - Real Success trades segregated by the future traded (RSSWISS, RSBEANS etc)

RS3MIN - All Real Success trades taken off of 3-minute bars RS5MIN - All Real Success trades taken off of 5-minute bars

RS3MINSP500 - All SP500 trades taken off of 3-minute bars (RS3MINSWISS for all Real Success trades taken off of 3-minute bars for Swiss Franc, etc)

Substitute 5MIN for 3MIN to segregate trades taken off of 5-minute bars. Example, RS5MINSP50O for all SP500 trades taken off of 5-minute bars.

Helpful hint - If you are planning to paper trade the Real Success methodology first, simply add a P to the end of all the Profit Center names. The P signifies a paper trading Profit Center. For example, paper trading the Real Success method with 5-minute SP500 bars, you would enter the trades into a Center named RS5MINSP500P. After you have about 20 paper trades in each Center, calculate the statistics I described in Vol 4-1 of CTCN and you will have excellent information as to your performance paper trading the Real Success methodology for each Profit Center.

Results of the paper trades can then be compared with real time results by using the Performance Report.

When you begin real-time trading, create The Profit Centers I have described above (without the P at the end of the name) and enter the real-time trades into those Centers.

After 20 real-time trades have been entered into a Profit Center, you will have a good data base of trading information and can complete your first Performance Report.

The following is a brief description of the items contained in the Performance Report.

Profit Center Name - Name of Profit Center analyzed.

Example, RS5MINSP500 for all trades taken from Real Success methodology trading 5 minute SP5OO bars.

Profit Center Type and Goals - Description of the Profit Center and the financial goals the trader is attempting to achieve.
For Example, Profit Center RS5MINSP500 will contain only SP500 trades taken from the Real Success methodology based on 5-minute bar charts.

After 100 paper trades, the trader has achieved 60 profitable trades (6O%) and 40 unprofitable trades (40%). Average Profitable trade was $600, average unprofitable trade was $400 for a ratio of 1.50. The Profit Factor was calculated to be 1.23. Net profits after 100 hypothetical paper trades are $2000.

Worst drawdown was $1800. Best series of winners was 6 with $1600 in profits. Worst series of losers was 4 with $1550 in losses. The trader will try not to lose more than 3% of capital on any one trade. These statistics of hypothetical paper trades can then be used as goals to be achieved with real-time trades.

The remainder of the Performance Report lists statistics from real-time trading.

Initial Capital - $30,000. This serves as the funding requirement for the business to cover margin requirements and trading losses.

Drawdown - Current drawdown in progress = $1050. Largest actual real-time drawdown = $2300

Series - Worst series of consecutive losers = 4 with a loss of $1300 in the series of 4 trades. Best series of winners = 6 with a profit of $1700 in the series of 6 trades.

Current series in effect - 2 consecutive profitable trades with a profit of $600 in the series of 2 trades.

Largest profitable trade - $ 950 on 3/11/96

Largest unprofitable trade - $1020 on 2/ 5/96

Optimum number of contracts to trade = 3, based on Ralph Vince's formula.

Trading efficiency - 57% winners and 43% losers.

Average profitable trade = $500. Average unprofitable trade = $300. Ratio of profitable to unprofitable = 1.67.

Range of losing trade as % of capital = 2.1% to 4.3%

Profitability - Profit Factor = 1.14. Profit Center is profitable with profitability trending upwards. I use graphs to determine the trend of profitability with the Pro-Graphics module of my MANAGER money management software. I will describe in my next article how I use the trend of profitability to determine how many contracts to trade.

Current net profit after 60 real-time trades $1100. Current Capital = $31,100 which equals $30,000 Initial Capital plus $1100 net profit.

Thus, the trader has established a business named RS5MINSP500 which is producing revenues (profitable trades) and expenses (losing trades + commissions). The Performance Report informs him of his trading performance in the RS5MINSP500 business as well as enabling him to compare actual real-time results with goals derived from hypothetical paper trades.

The Performance Report takes the trader out of the dark and into the light. He knows exactly his trading performance for each of his businesses and can instantly explain to anyone his profitability and efficiency as a speculator.

Most traders experience psychological problems due to the fact that they attempt to manage a business (i.e. trade) without any type of organizational structure which can provide them with the information necessary to execute disciplined, informed and educated trading decisions.

Nearly all traders manage their trading using monthly broker's statements which provide a "macro" view of their trading.
These statements only inform you as to your overall profit or loss for all your trading. This type of data is totally inadequate for the professional trader who requires more detailed information such as provided by the Profit Center methodology.

Hopefully, the reader has begun to see why many aspiring traders experience the same psychological problems....fear, greed, anxiety, inability to "pull the trigger" etc. The average trader operates in a fog. He has no money management methodology to provide the structure for successfully managing his trading business. Since he operates in the dark, he inevitably becomes uncertain and anxious. Continually floundering around in the dark makes the situation worse and worse, like a snowball rolling downhill.

You cannot successfully manage any type of business without first organizing your trading performance into a meaningful structure which reveals trading strengths which can be exploited and weak areas which must be eliminated or reduced.

The Performance Report provides the basis for formulating the Trading Plan. The Trading Plan is the strategy for the next trade based on the trader's trading performance as revealed by the Performance Report. I will also explain how the Performance Report is used to formulate the Trading Plan as regards to how many contracts to trade.

After the Trading Plan has been executed and the trade closed out with a profit or loss, the trader completes the Trade Journal. The Trade Journal is the "after the fact" critique of the Trading Plan. These three reports are specifically designed to eliminate the psychological problems which plague most traders and create an environment conducive to executing rapid, informed and educated trading decisions.

The Trading Plan and Trade Journal will be described in my next article as well as how this type of methodology promotes psychological stability and significantly reduces stress.

I will also describe how to file all the reports so that the trader will now be operating in a professional, disciplined and informed trading environment . . . similar to a successful business and structured to engender confident trading decisions.
This type of environment is specifically designed to advance the trader up the learning curves of the three disciplines necessary to achieve successful long-term successful speculation: Trading methodology; psychological discipline and; money management.

For a free booklet describing the reports I use and information on a newly completed book I wrote on money management, feel free to contact me at 800-MONEY30.


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System Testing Observation
Adam White

Here is an interesting observation I made while system testing.

Say you run a system test over 10,000 bars of data, then print out a chart of the system's equity line. Then repeat the test, but start 100 bars later. Let's say two trades were included in those 100 bars, so they've been dropped. Now print the second equity line and compare it to the first. You'd get exactly the same equity line, but 100 bars shorter. Right?
- Wrong!

When I do this I get a radically different equity line on the second test, i.e., they are not near mirror images of each other. My hunch is that a form of the chaotician's "butterfly-effect" has arisen: changing any given trade's market position (long, short, flat) will effect in a chain reaction all the subsequent trades in complex and unexpected ways. Here dropping the first two trades could very well change the system's market position when the third trade is calculated, and so on.

I believe this observation has profound and unfortunate implications for the robustness of system testing. It's a second and more subtle problem that lies behind the mere curve fitting/optimization problem.

If dropping a couple of early trades will always effect later trades, then there's no truly "neutral" starting point with any test data. Where your test data starts determines the final test results just as much as your system does.

Editor's Note: Not too many CTCN members are aware of this but I have known about this for some time. The success or failure of many different mechanical systems is predicated to a surprising and varying degree on the sequence of events just prior to the first actual trade generated by the system.

The trade setup and timing of the first trade can have a profound effect on the subsequent trading results. The circumstances and timing of entry into the first trade can sometimes make a huge difference in the overall trading performance.


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Max Robinson Has A Unique Way To Use Closing Price To Mimic A Moving Average

Keep up the good work. Anyone that is trying to do something good will be criticized or disliked by someone. But remember, you are helping many, while only a few are unhappy.

I have the System 2000. It does help identify turning points and congestion areas in the market. But then one needs an entry method.

The secret of all financial success is money management. How much can you risk on this trade, and still be financially able to take some losses and still be able to trade when the profitable trade finally comes by. Study Vol 4-1 of CTCN, articles are really enlightening (D'Angelo & ??). Can't read name?

I have two Ken Roberts courses. They have some good ideas in them and one of them convinced me to let go of some old anger.

Every one needs to understand that the constitution may guarantee equality under the law, but we are not born with the same abilities. Some of us just will never become a winning trader, but we might become a successful painter.

Larry Williams latest video had lots of information in it.

I have a mathematical way of using the close of today's market to compute an average that is similar to the 9-day and 40-day average.

My method is much easier and quicker to compute than most averages, since you only deal with today's close. This method picks turning points and acceleration points like any system that I have seen. But like all of the other systems, one has to apply his own entry and money management plan to it.

The big problem I believe we all have is fear and greed. Most of us are so greedy that we can't stand to be wrong 5 or 6 times out of every 10 trades. So we keep searching for the Holy Grail. In order to get over the fear of losing, one has to find a system and run it on old data until you realize that it may work okay!
Call anytime 308-775-3140.

缩水基金

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All about Stops
Donald Turnbull

Here are some thoughts that might prove useful to neophyte traders like me. They may duplicate many that you have already published, but I have not had the pleasure of reading.

I do not trade the S&P index because the margin requirements are so high it would take too big a proportion of my account to cover them. I would then have one position with, perhaps a 50% chance of success (and a 50% chance of failure).

Editor's Note: The S&P 500 margin is indeed very high for overnight position trades. The last time I checked it was $12,500 at my brokerage firm. This is one of the main reasons the S&P is not recommended for overnight trades.
However, like most brokers, my broker reduces the margin sharply for daytraders, where it's only $3,500.

In fact, I have heard it said by some of our members that certain brokers do not require any margin providing no trades are carried overnight. I am not sure if that's correct information and have not verified it to be correct, but have heard it said many times.

For similar reasons, I do not trade Japanese Yen, where one full point is worth $1,250. The difference between the high and low in one day can be $6,000. This is too rich for my trading style.
Instead I trade low margin trades like pork bellies, live meats and beans, and have a number of trades going at one time.

Just suppose I have 5 trades going, each with a 50% chance of success (and a 50% chance of failure). The statistical probability of all five failing is .5 x.5 x .5 x .5 x .5 which in .03125 or only 3%.

Editor's Note: Are Don's figures correct? Is it true that five trades involving 50% odds results in only a 3% chance of having five straight losers? If so, why does your editor frequently hear about certain systems or trading advisors having far more than five consecutive losers. Many of those systems are in fact ranked much better than a 50% success ratio by either the developer or Futures Truth Ltd.

In fact, I have heard of some systems or trading advisors that claim perhaps a 60 or 70% (or even better) success rate yet sometimes will have say ten, or even 20 (or more) straight losing trades. How is this possible, if Don's failure possibility is only 3%, or even less than 3% based on profitable trade percentages considerably higher than 50%?

I recall some years ago I read in one of the major trading publications(I believe it was Barrons Newspaper) that Jake Bernstein had (if I remember correctly), 23 straight losing trades. I know Jake and he is perhaps the most respected and most knowledgeable commodity expert there is. Jake has also written 23 books on trading commodities and is incredibly knowledgeable on trading. Jake is also a psychiatrist (or a psychologist . . . I always get the two confused) and no doubt has great discipline and trading skill. I am sure Jake will normally have at least 50% winning trades. So how is it possible someone like Jake could have over 20 consecutive losers? I am not picking on Jake as many other famous traders and experts have also had 20 or more straight losing trades over the years.

What is the chance of this happening, if in fact the profitable trade percentage is 50%, or even higher? If the chance is extremely small, why has your editor heard about this happening numerous times over the years, involving a vast number of popular systems, methods, and well known trading advisors or respected advisory services?

The probability of at least one or more successes is 1-(.5x.5x.5x.5) which is 93.755% . That's a lot better than the 50% mentioned above.

With tight stops, the losses are limited to an average of $300. With 4 losses, this amounts to $1,200. Profits are allowed to run and usually average $2,000. This results in small but virtually certain profits.

In actual practice, by limiting my trades to the recommendations of an advisory service, like Steve Myers on Futures (Summerfield, FL, 1 800-835-0096), probability of success is much higher.

I have heard it is bad practice to order a position "at the market." Before placing an order, I phone my broker's quoteline and get the high, low and last figures. Then I place a limit order at the "last" figure. Is there a better way of doing it?

Editor's Note: I do not necessarily agree it's a "bad practice" to trade with market orders. In fact, our Real Success Methodology uses market orders more frequently than limit orders, especially when entering into a new position. We also use market orders extensively on exits involving targets and stops.

Market orders have several major advantages over limit orders. One major advantage is you occasionally have difficulty verifying you are actually in a trade or out of a trade due to uncertainty involving a limit order being filled. On the contrary, with a market order you always know you are filled and in the trade or out of the trade. Another advantage is a market order will normally have less slippage than a limit order. In fact, as witnessed in CTC's Real Success Videos, sometimes we actually have positive slippage with market orders, rather than the usual negative slippage involving limit orders.

When profits accumulate and my account grows above my target figure, I have my broker send me a check for the difference. That way, I am not tempted to get into larger and larger trades. This may not be the way to become a millionaire, but it suits my risk tolerance level.

Moore Research Center publishes a list of "optimum" stop values, beyond which a commodity rarely recovers, and within which it often recovers. Their "optimum" stops seem to me to be too high. They are all in the range of $1,200 to $1,500.
To go along with my philosophy of having a number of trades going at a time, I think that tight stops are appropriate. This may stop you out of some trades that eventually recover and make a huge profit. But even in these cases, if you have confidence that the market will eventually rise, and you watch the market closely, you can get back in again and lose only one round-turn commission. However, if the commodity doesn't recover, you've saved yourself a lot of money.

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Money Management, Optimal f

BALANCING ACT By Mike DeAmicis-Roberts

Comparing optimal f and probability of ruin can give you better insight into the risk-reward parameters of your trading.


As many traders know, success depends as much on money management strategy as it does on a particular trading system. Optimal f and probability of ruin (POR) are two key money management concepts that help you determine how to best allocate capital for maximum growth and minimal risk to your account.

In some cases, however, these formulas conflict. We will overview the meaning and application of optimal f and POR and discuss a method (and offer some free Windows software) for evaluating systems by comparing these two formulas.

See Futures' downloads page for a copy of this software and "Profiling Optimal f And POR" for directions on using it.

Optimal growth Optimal f, popularized by Ralph Vince in his book Portfolio Management Formulas (Wiley 1989), is the ideal percentage of capital to allocate for any particular trade - the amount of equity that will result in the greatest gain to the account (see "Without money management, you don't have a system," Futures, Building a Trading System special issue, October 1994). This amount, which determines how many contracts you can trade, is based on the profit and loss profile of a trading system, rather than a percent of account equity.

Optimal f allows the trader to maximize the profitability of a system. If you trade with a higher or lower percentage of equity, you run the risk of not capitalizing enough on your winning trades or getting hit too hard on your losing trades.

The POR is the likelihood your system will reach a point of success or failure, that is, the chance that you will blow out your account before hitting your financial goal. Ruin is defined as the account level at which a trader stops trading. The POR is calculated using the percentage win, the average win, the average loss, the account size, the account size at ruin and the account size at success.

Because the probability of ruin increases with the amount risked, it's important to limit the amount of capital you commit to each trade. By trading smaller portions of the account equity, there is a greater chance a well-tested system will perform closer to its historical results. Traders who risk a larger percentage of account equity are more susceptible to variation from the expected results because of the small trade sample size.

Unfortunately, finding the optimal f and POR for a system is a computationally intensive process, (although the math involved is not difficult). As a result, few traders know the optimal f or POR for their systems. In most cases, this leads to diminished returns and increased risk.

Optimal f and POR calculations do not always suggest the same risk parameters. By comparing optimal f and POR, you can determine if the amount of capital risked at the optimal f value results in an unacceptably high POR. On the other hand, a trader may wish to increase the POR for the chance of exponentially higher returns. Ultimately this is a decision every trader must make. The optimal f amount suggests how much to risk; the POR value gives you an idea of the relative risk associated with trading this amount.

Application When evaluating a system for the optimal f, you find that the total returns lie on a curve, with the optimal f value at the apex. Moving the same amount to the left or right of the apex curbs the potential returns of a system by approximately the same amount. For example, if the optimal f for a system is 25%, then a trader can expect about the same amount of returns while trading at either 20% or 30% of the account.

The same cannot be said about the POR. In short, the more a trader risks, the greater the POR: It always will be higher when trading more than the optimal f and lower when trading less. Generally, if you don't want to trade at the optimal f value, it's wise to trade at a lower value to decrease your risk of ruin.

In some instances, it might not even be possible to trade a system at optimal f. For example, a trader with a $15,000 account and an optimal f of 5% can only risk $750 on any trade. This may not be an adequate amount in markets like the bonds and S&Ps.

Another problem is when the optimal f amount does not translate evenly into whole contracts. Using the example above, the trader should risk only $750 on each signal. If a single contract position implies a $500 risk to the account, the trader must decide if it is better to trade one or two contracts, which in turn influences the POR for the account.

There are no strict rules - "you should always trade y percent of optimal f" or "x is an acceptable POR." Optimal f and POR analysis does not give a trader any specific guidelines on how to trade. Rather, it shows the risk and reward associated with using a certain money management strategy for a trading system. You can then use this information to better evaluate the prudence of your trading approach.


Mike DeAmicis-Roberts is a researcher-programmer specializing in risk management and neural network technology with Comet Management in Hollister, Calif.
His internet address is: mike@chipx.com



MONEY MANAGEMENT INTRODUCTION
http://www.bhld.com/brochure/money.html

Money management is a part of an over-all investment system. Most people never have a formal money management strategy, yet every investment must address the two basic money management questions "What should I invest in?" and "How much should I invest?"

Your over-all investment system includes your money management strategy and several trading and investment models. You may have a number of investment models which you have never formalized, such as accumulation of savings, purchase of long term bonds and so forth.

The money management information you develop with Behold! cannot utilize information about those parts of your investment system which are not formalized within Behold! yet those other parts will affect the degree of risk which your are willing to accept for the trading and investment models you develop with Behold!

The money management features in Behold! address two main questions:

(A) What is the best way to allocate my money among my formalized trading
models and potential markets?

(B) With the capital on hand how many contracts (shares) should I buy?

This second question is particularly important to commodity traders as the leverage available to them allows carrying more contracts than is wise.

The question concerning capital allocation is vital to any trader who has sufficient capital to allow trading more than one stock or commodity.

Definition of Terms:
The Performance Summary for a single file or for a set of files for a single commodity (a roll-over report) shows two pieces of information at the bottom of the "All Trades" section, Optimal Capital and TWR.

Optimal Capital can be defined as: The amount of capital which you "should" have used to back up each commodity position, in order to achieve the highest rate of gain.

TWR is an acronym for terminal wealth relative. It is the ratio of final capital to initial capital which you would have achieved had you backed each position with the optimal capital.

Both of the above definitions assume that all profits/losses are to be plowed back into trading, and that you have the ability to carry fractional positions. Note that TWR in Behold! is an annualized number to allow comparisons between tests of different lengths.

"q" If you test a portfolio (with more than one stock or commodity) and check the box Calc Optimum Allocation then you will get two other types of data. One is simply labeled as "q" and the other is a list of numbers showing the optimal fraction of capital which should have been allocated to each security. Use of the capital allocation numbers and "q" will allow a commodity trader to obtain a Geometric Optimal Portfolio: that portfolio of the commodities tested which will give the highest growth rate.

For a better description of the terms and an in depth understanding of their derivation you should read the book Portfolio Management Formulas by Ralph Vince. For those with a mathematical bent it would be good to read his second book The Mathematics of Money Management.

Optimal Capital, TWR, the optimal capital allocation in a portfolio and the "q" value are all computed using data taken for trading with a fixed number of positions. They are not effected by the manner in which you vary the number of positions you are trading.

Trade Testing Options in Behold!

There are many ways to do portfolio performance testing, and in order to allow you to get what you want (which is not necessarily what we expect) the money management features in Behold! have been placed under your direct command. Thus we do not determine exactly what is "optimum" and then force you to live with it.

The Test Options dialog is use to set many testing options, of which the following are of interest now.

#Positions:
Single. This selection will require Behold! to always open a single position. This is the way that you should do your initial system development.

by Rules This selection allows you to write rules which control the number of positions opened. Your rules can access trade information such as the amount won or lost on the previous trade, current working capital and Worksheet data such as RSI, ADX and so forth.

Auto Behold! will calculate the number of positions to open as current working capital divided by the capital per position ($Posn) which is set in the same dialog. The initial working capital is set in this dialog in the Capital, Single file test item.

The next items determine how your working capital is changed by your trading results.

None Means no reallocation. All of your wins accrue to your working capital, and all losses are subtracted from working capital.

Percentage A certain percentage of each win will be taken away, to simulate re-capitalizing losses in other markets. A certain percentage of each loss will be replaced, to simulate re-capitalization using profits from other markets.

Dynamic This choice is only applicable to tests on portfolios.

The last item of interest is Monthly Withdrawal. This item allows you to determine how withdrawing a portion of your working capital, to cover expenses and so forth, will effect trading results.

Optimal Capital

The information in this section is mainly of interest to commodity traders, however stock traders should always assure themselves that the Optimal Capital value shown in the main Trade Test report is well above the cost of the stocks they are trading.


Portfolio Capital Allocation

Proper diversification of your investment capital would recognize all of your investments and allocate capital among them in order to obtain the maximum rate of return with the minimum relative risk. Capital Allocation in Behold! can only determine the best way to allocate your capital among the trading models and securities which you have formalized with Behold!

IF you run a Portfolio trade test and check the Calc Optimum Allocation box you will get three new items at the top of the full portfolio report. These are "Q" and the optimal % Capital allocation as determined for the securities tested in your portfolio. See Vince's book for a discussion of "Q."

As an example of the allocation information, see the example below.

Financial.PTF Initial Capital = 100000 "Q"(E/V) = 2.29
IMMEUD Actual %Capital = 100.00 Optimal % 62.55
TBOND Actual %Capital = 100.00 Optimal % 37.45

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Money Management 9

A small Quizlet:    (T: Theory, Q: Question, A: Answer, E: Explanation)  
T:  It is better to trade 2 different assets at the time than to trade 2 different trading systems simultaneously.  
Q:  True or False?
Click here to see the answer (after thinking, not guessing...)


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Money Management


Dr. Van K. Tharp on Money Management & Position Sizing

Drawdowns
Manage Other's Money
Definition
Models



An Excerpt from Dr. Tharp's Report on Money Management.

John was a little shell-shocked over what had happened in the market over the last three days. He'd lost 70% of his account value. He was shaken, but still convinced that he could make the money back! After all, he had been up almost 200% before the market withered him down. He still had $4,500 left in his account. What advice would you give John?

Perhaps your answer is, "I don't know. I don't have enough information to know what John is doing." But you do have enough information. You know he only has $4,500 in his account and you know the kind of fluctuations his account has been going through. As a result, youhave enough information to understand his money management -- the most important part of his trading. And your advice should be, "Get out of the market immediately. You don't have enough money to trade." However, the average person is usually trying to make a big killing in the market, thinking that he or she can turn a $5,000 to $10,000 account into a million dollars in less than a year. While this sort of feat is possible, the chances of ruin for anyone who attempts it is almost 100%.

Ralph Vince did an experiment with forty Ph.D.s. He ruled out doctorates with a background in statistics or trading. All others were qualified. The forty doctorates were given a computer game to trade. They started with $1,000 and were given 100 trials in a game in which they would win 60% of the time. When they won, they won the amount of money they risked in that trial. When they lost, they lost the amount of money they risked for that trial.

Guess how many of the Ph.Ds had made money at the end of 100 trials? When the results were tabulated, only two of them made money. The other 38 lost money. Imagine that! 95% of them lost money playing a game in which the odds of winning were better than any game in Las Vegas. Why? The reason they lost was their adoption of the gambler's fallacy and the resulting poor money management.

Let's say you started the game risking $1000. In fact, you do that three times in a row and you lose all three times -- a distinct possibility in this game. Now you are down to $7,000 and you think, "I've had three losses in a row, so I'm really due to win now." That's the gambler's fallacy because your chances of winning are still just 60%. Anyway, you decide to bet $3,000 because you are so sure you will win. However, you again lose and now you only have $4,000. Your chances of making money in the game are slim now, because you must make 150%just to break even. Although the chances of four consecutive losses are slim -- .0256 -- it still is quite likely to occur in a 100 trial game.

Here's another way they could have gone broke. Let's say they started out betting $2,500. They have three losses in a row and are now down to $2,500. They now must make 300% just to get back to even and they probably won't do that before they go broke.

In either case, the failure to profit in this easy game occurred because the person risked too much money. The excessive risk occurred for psychological reasons -- greed, the judgmental heuristic of not understanding the odds, or in some cases, the desire to fail. However, mathematically their losses occurred because they were risking too much money.

What typically happens is that the average person comes into most speculative markets with too little money. An account under $50,000 is small, but the average account is only $5,000 to $10,000. As a result, these people are practicing poor money management just because their account is too small. Their mathematical odds of failure are very high just because they open an account that is too small.

Hundreds of thousands of hopefuls open up their speculative accounts yearly, only to be lead to the slaughter by others who are happy to take their money. Many brokers know these people don't have a chance, but they are happy to take their money in the form of fees and commissions. In addition, it takes many $5,000 accounts to feed a single multi-million dollar account that consistently gets a healthy rate of return.

Look at the table below. Notice how much your account has to recover from various sized drawdowns in order to get back to even. For example, losses as large as 20% don't require that much larger of a corresponding gain to get back to even. But a 40% drawdown requires a 66.7% gain to breakeven

Drawdown Gain to Recover
5 Percent 5.3% Gain
10 Percent 11.1% Gain
15 Percent 17.6% Gain
20 Percent 25% Gain
25 Percent 33% Gain
30 Percent 42.9% Gain
40 Percent 66.7% Gain
50 Percent 100% Gain
60 Percent 150% Gain
75 Percent 300% Gain
90 Percent 900% Gain

and a 50% drawdown requires a 100% gain. Losses beyond 50% require huge, improbable gains in order to get back to even. As a result, when you risk too much and lose, your chances of a full recovery are very slim.

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Managing Other People's Money

In the futures industry, when an account goes down in value, it's called a drawdown. Suppose you open an account for $50,000 on August15th. For a month and a half, the account goes straight up and on September 30th, it closes at a high of $80,000 for a gain of 60%. At this point, you may still be in all of the same trading positions. But as a professional, your account is "marked to the market" at the end of the month and statements go out to your clients indicating what their respective accounts are worth.

Now, lets say that your positions start to go down in value around the 6th of October. Eventually, you close them out around the 14th of October and your account is now worth about $60,000. And let's say, for the sake of discussion, that your account at the end of October is worth $60,000. Essentially, you've had a peak-to-trough drawdown (peak = $80,000, trough = $60,000) of $20,000 or 25%. This may have occurred despite the fact that all of your trades were winners. It doesn't really matter as far as clients are concerned. They still believe that you just lost $20,000 (or 25%) of their money.

Let's say that you now make some losing trades. Winners and losers, in fact, come and go so that by August 30th of the following year, the account is now worth $52,000. It has never gone above $80,000, the previous peak, so you now have a peak-to-trough drawdown of$28,000 -- or 35%. As far as the industry is concerned, you have an annual rate of return of 4% (i.e., the account is only up by $2,000) and you are now labeled as having 35% peak-to-trough drawdown. And the ironic thing is that most of the drawdown occurred at a time in which you didn't have a losing trade -- you just managed to give back some of your profits. Nevertheless, you are still considered to be a terrible money manager. Money managers typically have to wear the label of the worst peak-to-trough drawdown that they produce for their clients for the rest of their lives.

Think about it from the client's viewpoint. You watched $28,000 of your money disappear. To you it's a real loss. You could have asked for your money on the first of October and been $28,000 richer.

Trading performance, as a result, typically is best measured by one's reward-to-risk ratio. The reward is usually the compounded annual rate of return. In our example, it was 4% for the first year. The risk is considered to be the peak-to-trough drawdown which in our example was35%. Thus, this traders reward-to-risk ratio was 4/35 or 0.114 -- a terrible ratio.

Typically, you want to see ratios of 2 better in a money manager. For example, if you had put $50,000 in the account and watched it rise to$58,000 you would have an annual rate of return of 16%. Let's say that when your account has reached $53,000, it had drawn down to$52,000 and then gone straight up to $58,000. That means that your peak to trough drawdown was only 0.0189 ($1,000 drawdown divided by the peak equity of $53,000). Thus the reward-to-risk ratio would have been a very respectable 8.5. People would flock to give you money with that kind of ratio.

Let's take another viewpoint and assume that the $50,000 account is your own. How would you feel about your performance in the two scenarios? In the first scenario you made $2,000 and gave back $28,000. In the second scenario, you made $7,000 and only gave back$1,000.

Let's say that you are not interested in 16% gains. You want 40-50% gains. In the first, scenario you had a 60% gain in a month and a half. You think you can do that several times at year. And you're willing to take the chance of giving all or most of it back in order to do that. You wouldn't make a very good money manager, but you might be able to grow your own account at the fastest possible rate of return if you could "stomach" the drawdowns.

Both winning scenarios, plus numerous losing scenario, are possible using the same trading system. You could aim for the highest reward to risk ratio. You could aim for the highest return. Or you could be very wild, like the Ph.D.s in the Ralph Vince game and lose much of your money by risking too much on any given trade.

Interestingly enough, a research study (Brinson, Singer, and Beebower, 1991) has shown that money management (called asset allocation in this case) explained 91.5% of the returns earned by 82 large pension plans over a ten year period. The study also showed that investment decisions by the plan sponsors pertaining to both the selection of investments and their timing, accounted for less than 10% of the returns. The obvious conclusion is that money management is a critical factor in trading and investment decision making. (Determinants of Portfolio Performance II: An Update, Financial Analysts Journal, 47, May-June, 1991, p 40-49.)

You now understand the importance of money management. Let's now look at various money management models, so that you can see how money management works.

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Money Management Defined

Money management is that portion of one's trading system that tells you "how many" or "how much?" How many units of your investment should you put on at a given time? How much risk should you be willing to take? Aside from your personal psychological issues, this is the most critical concept you need to tackle as a trader or investor.

The concept is critical because the question of "how much" determines your risk and your profit potential. In addition, you need to spread your opportunity around into a number of different investments or products. Equalizing your exposure over the various trades or investments in your portfolio gives each one an equal chance of making you money.

I was intrigued when I read Jack Schwager's Market Wizards in which he interviews some of the world's top traders and investors. Practically all of them talked about the importance of money management. Here are a few sample quotes:

"Risk management is the most important thing to be well understood. Undertrade, undertrade, undertrade is my second piece of advice. Whatever you think your position ought to be, cut it at least in half." -- Bruce Kovner

"Never risk more than 1% of your total equity in any one trade. By risking 1%, I am indifferent to any individual trade. Keeping your risk small and constant is absolutely critical." -- Larry Hite

"You have to minimize your losses and try to preserve capital for those very few instances where you can make a lot in a very short period of time. What you can=t afford to do is throw away your capital on suboptimal trades." -- Richard Dennis

Professional gamblers play low expectancy or even negative expectancy games. They simply use skill and/or knowledge to get a slight edge. These people understand very clearly that money management is the key to their success. Money management for gamblers tends to fall into two types of systems -- martingale and anti-martingale systems. And investors and traders should know about these models.

Martingale systems increase winnings during a losing streak. For example, suppose you were playing red and black at the roulette wheel. Here you are paid a dollar for every dollar you risk, but your odds of winning are less than 50% on each trial. However, with the martingale system you think you have a chance of making money through money management. The assumption is that after a string of losses you will eventually win. And the assumption is true -- you will win eventually. Consequently, you start with a bet of one dollar and double the bet after every loss. When the ball falls on the color you bet, you will make a dollar from the entire sequence of wagers.

The logic is sound. Eventually, you will win and make a dollar. But two factors work against you when you use a martingale system. First, long losing streaks are possible, especially since the odds are less than 50% in your favor. For example, one is likely to have a streak of 10 losses in a row in a 1,000 trials. In fact, a streak of 15 or 16 losses in a row is quite probable. By the time you reached ten in a row, you would be betting $2,048 in order to come out a dollar ahead. If you lose on the eleventh throw, you would have lost $4,095. Your reward-to-risk ratio is now 1 to 4095.

Second, the casinos place betting limits. At a table where the minimum bet was a dollar, they would never allow you to bet much over $50 or$100. As a result, martingale betting systems, where you risk more when you lose, just do not work.

Anti-martingale systems, where you increase your risk when you win, do work. And smart gamblers know to increase their bets, within certain limits, when they are winning. And the same is true for trading or investing. Money management systems that work call for you to increase your risk size when you make money. That holds for gambling and for trading and investing.

The purpose of money management is to tell you how many units (shares or contracts) you are going to put on, given the size or your account. For example, a money management decision might be that you don't have enough money to put on any positions because the risk is too big. It allows you to determine your reward and risk characteristics by determining how many units you risk on a given trade and in each trade in a portfolio. It also helps you equalize your trade exposure in a portfolio.

Some people believe that they are "managing their money" by having a "money management stop." Such a stop would be one in which you get out of your position when you lose a predetermined amount of money -- say $1000. However, this kind of stop does not tell you "how much" or "how many", so it really has nothing to do with money management.

Nevertheless, there are numerous money management strategies that you can use. In the remainder of this report, I'm going to present different money management strategies that work. Some are probably much more suited to your style of trading than others. Some workbest with stock accounts, while others are designed for futures account. All of them are Anti-martingale strategies.

The rest of this article is continued in Dr. Tharp's special report on money management.

缩水基金

A Special Report on Money Management By Van K. Tharp Ph.D.

In this special report, written by Van K. Tharp, Ph.D., you'll learn dozens of different models of money management-one of which could make a big difference for you. The biggest secret that most people neglect in their quest for big profits is proper money management. Research has proven that about 90% of the variance in performance between portfolio managers is due to money management. For the average trader, it makes the difference between losing, and winning big-depending upon your objectives. Probably the most valuable book any trader could own.


What you will learn from this report:

How to meet your objectives using money management

The definition of money management

27 models of money management with three ways to measure equity

How to design high reward risk systems for managing money

Four techniques to produce maximum profits

Dr. Tharp calls this type of money management a "secret" because few people seem to understand it, including many people who've written books on the topic. Some people call itrisk control, others call it diversification, and still others call it how to "wisely" invest your money. However, the money management that is the key to top trading and investing simply refers to the algorithm that tells you "how much" with respect to any particular position in the market.

As if the issue of money management weren't confusing enough on its own, there are also many psychological biases that keep people from practicing sound money management. And, there are practical considerations, such as not understanding money management or not having sufficient funds to practice sound money management.

This report is written to give you an overall understanding of the topic and to show you various models of money management. To order this exclusive report call IITM at800-385-IITM (4486) or at 919-852-3664. The report is $79.95 plus shipping and handling.

Last revised: July 08, 1999

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Five Tips To Give You More Discipline

They Will Help You Earn Bigger, More Consistent Profits (Without the Stress) by Changing Your Thinking -- GUARANTEED!

Responsibility
Mistakes
Mental State Control
Change What You're Doing
Scan Your Body

Tip #1: Take Responsibility for Everything That Happens to you. One of the keys to peak performance is to make the assumption that you create everything that happens to you. For example, if you give your money to someone and then run off with it, you must still take responsibility. You made the decision to give that person money. You made a decision about how much information you needed from that person before you gave them money. Thus, even though they committed an illegal act, you are still ultimately responsible.

When this sounds like I'm asking you to feel guilty for you mistakes, the truth is exactly the opposite. What I am asking you to do is set yourself free by taking control over the rest of your life instead of being a victim.

Tip #2: There are only two types of mistakes. You might say that you biggest problem is your spouse. If you believe that, then it is probably true. In addition, you are also doomed to repeat that mistake for the rest of you life. No, I'm not saying that you can't divorce your spouse. You probably can and may do so. But you will probably just find another spouse that will give you the same problems. However, if you look at the problem different, such as noticing that I get angry when my spouse does X, then you have taken a step toward controlling the problem. The reason is that you have now traced the problem to a mental state that you can elect to own -- your anger. You don't have to get angry at your spouse when that person does X. You can elect to have another response. That is the essence of discipline.

Now you can also apply this to the process of trading or investing. The mistakes you make are in some way related to negative mental states -- whether it's an inability to pull the trigger or compulsiveness, you can trace it to a negative mental state.

Tip #3: Discipline Involves Controlling Your Mental State. My home study course has over 15 ways to control your mental state. This means that you control your life and not your mental state. You don't have to be the victim of fear. Instead, you can just notice "Oh, I'm starting to do that fear thing and I need to take control."

Tip #4: If you don't like the results you are getting, respond differently! How are you producing fear or the mental state you don't want? Notice what you are doing and do something else or do it differently. For example, are you producing fear by something you tell yourself? Then tell yourself something else. Or change the nature of the voice. Try saying the same thing in a voice like Mickey Mouse. If you are producing fear by something your are seeing in your mind, then picture something else. Or you might change the nature of the picture. Make it black and white or move it further away. This amounts to taking charge of the way you run your brain.

Tip #5: Change what you are doing with your body to change the reaction of your mind. When your mental state is inappropriate, then scan your body. Notice what you are doing with your body. If there is tension, relax that area. If your posture is bad, straighten up. Also notice your breathing. Take regular deep breaths and you can literally change your state. As an exercise, try imitating people's walking. Notice what it feels like to walk in another person's shoes. This will convince you how important it is to change what you do with your body to change your mental states.

Next time you are having a problem trading, ask yourself how am I doing this? Change what you are doing with your body, and if you do it right, you should notice a big change in your behavior.

For more information about discipline see Dr. Tharp's Home Study Course or the Peak Performance Trading Seminar.

Last revised: July 08, 1999

缩水基金

BASIC TECHNIQUES

Exploiting Positions With Money Management by Daryl Guppy

Here's a trading technique adding positions to successful trades.

Even in a bull market, there is a feeling of triumph when a trade goes our way. When this happens, the novice trader feels that getting the trade right is enough in itself and that profits will automatically follow. He is invariably disappointed when profits turn out to be smaller than expected, and often, he will redirect his attention to derivative markets to try to leverage winning trades into larger profits. This in turn exposes him to a higher level of risk than he anticipates. A better solution would be to apply money management techniques to equity markets to grow profits more effectively. This is also an important way of reducing risk.

The entry is just after the 10- and 30-day moving average crossover signal, and it was made at $5.52. The exit at $6.37 is also triggered by the crossover of the 10- and 30-day exponential moving average. The return on trading capital depends on how the initial position taken at $5.52 is added to in October 1998. We buy 6,000 shares for a total cost of $33,120. If this same parcel were sold at $6.37 following a simple buy-and-hold strategy, then we collect $5,100 profit for a 15.3% return on capital employed in the trade.

Here's how risk changes, even with comparable positions and stop-loss exits. Risk, here, is trade risk, measured by the dollar loss incurred with adverse price movements. This includes both capital reduction and reduction in open profit. Risk is directly related to the money management technique selected. By comparing outcomes, the trader can exploit his winning positions more effectively. Let's examine a method to increase profits while reducing risk that I call the grow-up strategy. I use the name to distinguish it from adding to winning positions using constant dollar or constant position size.

When traders first approach the market, they concentrate on choosing the right analytical tools. They believe that if they get this right, profits will automatically follow. As time goes on, however, they realize that success is more closely tied to the way they trade and to trading discipline. They understand analysis tools are a starting point, not an end point. Truly successful traders take the next step by using money management to control risk.

Fund managers and institutional traders have a selection of well-defined money management formulas. Texts by Ralph Vince and Fred Gehm serve well as a good introduction to this area, but their solutions are less applicable to private traders. The private trader finds generally less information available, and even less of it applicable to portfolios at his level of capital. Take a closer look at the strategies for loading up the winners. Many trading books suggest that loading up winners is a good strategy, and because it is so self-evident, traders spend no time exploring the outcomes of their advice.

My objective is to increase the total position size as the trade continues to move in my favor. The ultimate outcome is to have most of my trading capital tied up in positions making money rather than in positions losing money.

Despite intensive analysis and research of potential and actual trading positions, many traders approach money management armed with a collection of old wives' tales. High on this list of adages is the assumption that traders improve trading outcomes by adding to winning positions. The concept is sound. The way the concept is implemented, however, is often less successful.

Most traders reach for one of two common strategies. The first is to add new positions to a winning trade of the same parcel size (that is, the same number of shares in each new position) as the initial position; the second is to add new positions that are the same dollar size. Both strategies appear successful while the trend continues, but they expose the trader to unexpected risk when the trend reverses.

Daryl Guppy is an author and a private equity and derivatives trader. He speaks regularly on trading in Australia and Asia. He can be contacted via www.ozemail.com.au/~guppy.

Excerpted from an article originally published in the September 1999 issue of Technical Analysis of STOCKS & COMMODITIES magazine. All rights reserved. © Copyright 1999, Technical Analysis, Inc.

缩水基金

CLASSIC TECHNIQUES

Matching Money Management With Trade Risk

by Daryl Guppy

Manage your trades using technical analysis by identifying risk points as well as setting profit objectives. This Australia-based author shares some of his favorite techniques.

Most of us think trading is a rational process, but many private traders approach trading the same way that other people approach a wishing well. Those people throw money into the well, make a wish and wait for their wish to come true. In the same vein, some private traders throw money into the market and all they wish for is a profit. Sometimes the wish comes true, but most times, just like a wishing well, it is a waste of money and time. For traders using the market as a substitute for a wishing well, trading is a very emotional experience.

With that in mind, let's take a closer look at the way emotion interferes with good trading and at some of the ways that chart analysis can help us establish trading objectives more effectively.

Most readers will protest that trading is not like a wishing well; we don't just toss money in and hope for fat profits. By and large, we prefer to believe that we are too sophisticated for that. Instead, we analyze the tradable instrument in question, applying sound technical analysis to charts and price data, and then, and only then, make a trading decision. This is a rational process, and if our analysis is correct, the tradable's price will increase when we go long.

Unfortunately, describing the entry decision in pretty words and trading jargon does not alter the trader's intent nor the outcome. Trading based on the wishing-well approach is characterized by poor trade management illustrated by the lack of a plan. Just hoping to make a profit is not a plan. It is an objective, but it tells us nothing about how we are going to get there.


Assume that all the sound analysis has been done, and Woodside appears to be irresistible at$8.60. As prices tumble toward the chosen entry level, the trader must concentrate on the possibility that his or her decision might be wrong.

Daryl Guppy is a full-time private position trader. He is the author of several books, including Share Trading: An Approach to Buying and Selling (with editorial assistance from Alexander Elder) and Trading Tactics: An Introduction to Finding, Exploiting and Managing Profitable Share Trading Opportunities and Trading Asian Shares: Buying and Selling Asian Shares for Profit. He is a regular contributor to the Sydney Futures Exchange magazine. He can be contacted via E-mail at www.ozemail.com.au/~guppy.

Excerpted from an article originally published in the May 1998 issue of Technical Analysis of STOCKS & COMMODITIES magazine. All rights reserved. © Copyright 1998, Technical Analysis, Inc.



--------------------------------------------------------------------------------

October 1998 Letters to the Editor

SECURING OPTIMAL F

Editor,

In your July 1998 issue, you published an article titled "Secure fractional money management." The technique uses Ralph Vince's optimal f, and purports to limit the drawdowns that occur when optimal f is applied. But the authors do not consider the biggest problem with optimal f applications.

Optimal f is a random variable. It depends on the largest loss experienced to date and all the trade results to date. Because these variables are subject to large statistical fluctuations, optimal f is subject to random variations. The method set forth by the authors does not address the drawdowns that can occur when future trades are subject to an optimal f different from the calculated value.

A partial solution is to just replace the largest loss to date in Vince's formula with a conservative choice of a larger loss. Still, the resulting optimal f will be exposed to large variations from the trade history employed. The best way to address these problems is to simply rerun the optimal f calculation over several different time frames containing the same number of trades and then average the results for optimal f. That way, the result will be much more "secure."

PAUL H. LASKY via E-mail

------------------------------------------------
INSECURE ABOUT SECURE F

Editor,

The article "Secure fractional money management" by Leo J. Zamansky and David C. Stendahl that appeared in the July 1998 issue of STOCKS & COMMODITIES contains a major error. Optimal f is not the percentage of equity to trade, as stated in the article. Optimal f is used to figure the number of contracts to trade:

number of contracts to trade = (equity) (opt f)/-profit of worst trade

The equations that the authors give are correct, but because of their error in thinking, they misapply the equations.

In the example of the three series given in the article, the authors correctly come up with an optimal f of 1/3. But then to interpret this as being able to buy only three contracts is wrong. Using their interpretation, you could buy only three contracts in each of the series and end up with $101,500, a terminal wealth relative (TWR) of 101,500/100,000 = 1.015. This is far from the TWR of 1.185 that is seen in their Figure 3. Using the correct interpretation, you don't buy three but 66 contracts!

66.666 = 100,000 * 1/3/(500)

You always round down the number of contracts. Then, after winning $33,000 in the first, the second series gets 88 contracts: 88 = 133,000/(1,500). The third series gets 118contracts: 118 = 177,000/(1,500). You end up with $118,000, giving TWR = 1.18.

The authors' calculation of maximum drawdown of $7,500 is dwarfed by the actual maximum drawdown, which is 5/3 of equity, or $220,000, as it occurs in series 2. The correct value of the secure f is 0.01.

Perhaps the authors became confused with equalized optimal f (see page 83 of Ralph Vince's The Mathematics of Money Management). In this method, you can come up with a number that is a fraction of equity to trade with, but this number is neither f nor optimal f. (As far as I know, Vince does not identify this fraction, but it is evident from his equations.) In this method, you use the percentage loss or gain for each trade. In the authors' example, the trades become ($500/$10,000 = $0.05, 0.05, -0.05) instead of ($500, 500, -500). In this case, the equalized optimal f = 1/3; it is the same as optimal f because the buy price was always $10,000. Now use this equation: fraction of equity = equalized optimal f/ - return of worst losing trade

For the equalized optimal f of 1/3, the fraction of equity is 666.7% = (1/3)/(0.05). Yes, this does mean you are buying on margin. For the equalized secure f of 0.01, the fraction of equity is 20%.

After getting every other interpretation wrong, the authors do come up with the correct final answer of 20%. This leads me to believe that they do have access to a program that correctly generates these numbers for them.

Despite my criticism, Zamansky and Stendahl are to be congratulated for the idea of secure f. Fixed fractional money management is a wonderful and complex subject that deserves some attention. Too bad this article got the fundamentals wrong.

BRADEN A. BROOKS via E-mail
------------------------------------------------
Leo Zamansky and David Stendahl reply:

Thank you for the feedback about our July 1998 article, "Secure fractional money management."

Mr. Brooks is correct in saying that according to Ralph Vince, the formula is number of contracts =(equity) * (optimal f) / (- profit of worst trade). He is also correct that according to this formula, we buy66 contracts, not three. However, as we assumed in the article, one contract price is $10,000. To buy 66contracts, we need to have enough money to buy 66 contracts at $10,000 each. That makes66*$10,000 = $660,000. And that amount should be only one-third of the total capital available, which, as stated, is $100,000. The question we are answering is: How many contracts can we buy following optimal f? The answer is $33,000 / $10,000 = 3. If the contract price were $500, then the number of contracts to purchase would be exactly 66. If the contract price were less than $500, then the number of contracts to purchase also would be exactly 66.

Vince, in his book Portfolio Management Formulas, states on page 80, "Margin has nothing to do whatsoever with what is the mathematically optimal number of contracts to have on." We emphasize the word mathematically. In real trading, if you need to buy one contract, you need to have a certain amount of money in your account, say x, and if you buy n contracts, you need to have the amount of money equal to n*x. In the article's example we call it price, but in reality it is a margin requirement. Inother words, the formula for the number of contracts should be adjusted to the price of the contract and be modified to look as follows:

number of contracts to trade = (equity) (opt f)/max [price of contract, -profit of worst trade]

We agree that we should have specified that. Of course, if you follow this number of contracts purchased, the TWR is not going to be 1.18, because the contract price is too high and does not allow you to buy the number of contracts that would maximize it. However, the lower the price of a contract, the closer you will come to the calculated maximum of TWR.

We develop tools to use in trading futures. We cannot introduce a calculation that is not based on real trading rules. In real futures trading, the margin requirement per contract always exists and has a very similar meaning to the contract price in the game introduced.

As to the software we use to obtain our results, we use only the software written by us. In fact, readers can download the secure f calculator from our Web site, as mentioned in the article, and run it to obtain values for both secure f and optimal f. This should demonstrate the validity of this approach.

We appreciate the feedback from Mr. Brooks, who makes the important point regarding the difference between optimal f as a mathematical concept and trading using optimal f given the constraints imposed by the reality of futures trading.

--------------------------------------------------------------------------------
Quizlet-Answer:    (A: Answer, E: Explanation)
A: False:
E:  You will never find 2 assets with a satisfying continuous correlation structure (above all at the downside when there usually is a high degree of correlation). You could even trade a single commodity with a portfolio of patterns and models.
It might be easier to breed a custom correlation structure by synthesizing trading models than to find and apply those correlations offered by the markets.

缩水基金

Money Management 10


Money Management, kNOW, DeAmicis


Table of Contents

· General Introduction - Recommended
· Book Introduction - Recommended
· Overview of Applying Money Management - Recommended
· You Have A System
· Bias toward mechanical systems?
· A statistical winner?
· What's a valid sample?
· Evaluating Different Money Management Methods
· What Is Money Management?
· Selecting A Money Management Method to Use
· An IMPORTANT distinction
· Overview of Money Management Techniques
· Organization of Following Sections
· No Money Management Technique
· Multiple Units/Contracts Technique
· Fixed Dollar Value Trading Technique
· Fixed Percent of Account Trading Technique
· Adjust Trading on Win or Loss Technique
· Crossing Equity Curves Technique
· Applying the Optimal f Technique
· Summary of Techniques/Methods
· Using Optimizations
· Before Comparing Money Management Techniques
· How to Compare Money Management Techniques
· Comparing Results on the Basis of Total Profit
· Comparing Results for the Smallest Drawdown
· Comparing Results for the Profit/Margin Ratio
· Comparing Results for the Profit/Drawdown Ratio
· Comparing the Profit/Time Ratio
· How Important is the System's Percent Win Ratio
· Z-Score and Confidence Limits
· The Optimal f
· The Probability of Ruin
· Conclusion

GENERAL INTRODUCTION

A Brief Overview of the Book, Manual and Software

The Money Software Company, LLC thanks you for your purchase, faith and interest in the kNOW Money Management Program and welcomes you to the arcane but extremely important world of "Risk Management".

Half of investing/trading is knowing what and when to trade. The other half is kNOWing what amount to risk. This manual, book and software seeks to assist and educate the investor/trader on this very important second half of investing and trading, the art and science of risk management.

The value of unique money management techniques (not just stops, pyramiding, percent of account value, etc.) is finally being recognized as being as important as the investing/trading system used. In fact, there are numerous examples where the utilization of proper money management techniques has turned a losing investing/trading system into a winner and taken a marginal or successful system and substantially increased the return while reducing the financial and psychological trauma of losses/drawdowns. However, the reason more people do not thoroughly understand the subject, is because until recently there was no easy way to test and evaluate different money management techniques. This is the reason the Money Software Company, LLC developed and is now offering the kNOW Money Management Program.

The kNOW (k =$1,000s-NOW) Money Management Program was designed for both the professional and the less experienced investor/trader in order to allow them to enter individual trades or import investment/trading results (Trade Station, SuperCharts, Excel, etc.) and run thousands of variations and "what if scenarios" on seven major money management techniques. This means that users can now easily determine which money management technique(s) and/or method(s) meet their needs in terms of: maximizing profits, smoothing out the equity curve, diversification for stability, or the reduction of drawdowns. The kNOW Program is applicable for any investing/trading system pertaining to futures, options, equities, mutual funds or any other type of investment with specific profit and loss results.

The money management techniques/approaches discussed include such items as the Optimal f, probability of ruin, Z-scores and Confidence limits, fixed fractional trading, crossing equity curves, optimal risk allocations and much, much more.
It should be noted that through out the book/manual/software the term technique and approach refers to the seven major money management methods being discussed while the term option refers to variations or additional things the user can do with the different techniques/approaches. Also, through out the book and manual the term trade and trader are used, this is synonymous with investing and investor and when the term contract is used it is synonymous with a "unit". A single "unit" can be one, five, ten+ future contracts, 100+ shares of stock, 100+ options or even 100+ shares of a mutual fund. The user determines the size, value and type of instrument to make up a "unit". When the term system is used it means a defined investing/trading method for getting in and out of the market(s) with specific and historical profit and loss results. It should also be noted that the kNOW Money Management Program is applicable for many different investing/trading systems and time frames but is not applicable for the buy and hold investor.

It is the Money Software Company's sincere hope and desire that through the combination of the money management information and the software tools provided, traders and investors will have everything they need to make informed and educated investment decisions about money management. With the knowledge of how different money management techniques/approaches work with different types of systems, investors and traders can now easily pick the method(s) that best achieves the desired profit and risk objectives.

Thank you again for your acquisition of the kNOW Money Management Program. All of us at the Money Software Company LLC sincerely hope it will be both educational and profitable to you and your trading/investing philosophy and systems.

缩水基金

Book Introduction

"k" as in thousands.
"NOW" as in immediately.
kNOW as in understanding how to make thousands immediately.

Welcome to the kNOW Money Management Program.

I once knew a very successful trader that told me the way he decided whether or not to enter the market was to throw two old chicken bones over his shoulder. Depending on how they landed, he would buy, sell or stay out of the market. When I pointed out to him this was not a very reliable entry method, he agreed, but stated that it made little difference because in the long run money management was everything.

Most investors and traders have heard that money management is half of every great trading system. In fact, some traders feel their money management approach or technique is more important than their trading system. As you will soon learn during the reading of this book, the correct money management technique(s) can mean the difference between success and failure. The best investing/trading system with poor money management ends up still being a poor system. On the other hand, a poor investing/trading system with good money management techniques can be a good system. It is even possible, in some cases, to take a losing system and make it profitable with the right money management techniques.

The science of money management is:

1.Knowing how and when to use different money management techniques and approaches that:

· Maximize the return on an account
· Keeps the risk and drawdown within psychological and financial levels acceptable to the trader.

2.Knowing the relationships between different money management approaches and different statistical peculiarities of a given investing/trading system:

· Variability of the results.
· Probability of success or ruin.
· Correlation between wining and losing trades, etc.

Many articles have been written on how to maximize the return on an account. These articles have helped bring the science of money management to new levels. However, most of the articles and books on this subject have neglected to discuss the risk and psychological ramifications of maximizing the return on an account. In most cases, maximizing the return on an account will expose traders to a larger risk of going bankrupt or, at the minimum, larger drawdowns. Most people do not want to see a 50%+ drawdown on their accounts, even if it is only a loss of profit. For professional money mangers, a 30% drawdown can begin to wreck a career for the simple reason the institutions and individuals that invest with money managers want to see drawdowns only in the 10-15% range.

The kNOW Money Management Program will give you the opportunity to see your investment/trading system analyzed using hundreds of different money management techniques and approaches. Then, when you kNOW the effects of the different money management techniques on your investment/trading system, you can intelligently choose the one that is right for your financial and psychological goals.
Please look over all of the material in this manual. It is meant to inform, educate and stimulate you. Also, please give us your feedback, questions, insights and direction so that we can do additional upgrades and new money management articles. We feel that the kNOW Money Management Software Program is a dynamic entity and thus will be growing in intelligence and capability, just like it's users.

Mike DeAmicis-Roberts - President
Money Software LLC



Overview of Applying Money Management

It is frequently said that money management is half of investing/trading. This is true in the sense that the two major aspects of any investment/trade are when and how much. In reality, much more is going on in an investment/trade. There are psychological aspects to trading and there are execution aspects to trading. If traders are either to scared to trade or they have brokers that consistently get bad fills, it will also effect the profitability of any system. Overall, many aspects come into a solid trading approach and money management is only one piece of the puzzle. But, it's a very big piece. In fact the more professional traders become, the more important money management becomes.

Money management is something all traders can apply. But, in order to apply money management effectively, trader's needs to have a defined system for entering and exiting the market with a historical and accurate profit and loss record. Although some traders don't use a defined system, these days, most traders do have some type of a trading approach/system. Having a well tested trading system helps insure that traders get consistent trading results from future trades, within normal statistical boundaries. It is understanding these statistical boundaries that represents a large aspect of managing an account both effectively and efficiently. The main way traders learn to understand these statistical boundaries is to have a large sample of tested trades. However, what is a correct number of trades to have? The initial sections of this book cover these kinds of issues.

When you have an investing/trading system you feel comfortable with, it is time to start exploring how money management can help improve the results of the system. Often times when one hears about money management, the topics are interesting, but have limited relevance to most traders on a day to day basis. Ideas like "don't trade into an economic report" or "keep 25% of your account in savings bonds" does not tell traders how much to risk on the next trade. This book will deal only with the "nuts and bolts" aspects of investing/trading: how to risk your money on a trading system for maximum gain or risk management and steer away from the more casual money management ideas.
The process of applying the correct money management approach and/or technique consists of a few but very important steps (they are not necessarily in order of importance):

Learn the value and benefits of applying different types of money management options and techniques.
· Determine on a personal level what is correct for you. Deciding how much you are willing to risk and/or bear and how much profit is desired is very important when picking the correct money management techniques and options.
· Learn how to compare and analyze the different money management techniques/approaches. Users of the kNOW Software will always receive a detailed set of results after applying a specific money management technique to a trading system. It is then important to know how to compare the latest results to the results received from previous simulations. There are trade-offs here. It is not as simple as picking the one with the best profit.

The what, why and how of money management is the general format and sequence of this book. This may be out of order for some people. Some traders would rather learn how to compare different money management techniques before learning about them. Or, should deciding what technique you want as a trader be the first step, or the last?
However, it is felt the format and sequence of the following presentation is the most reasonable method for traders and users of the kNOW Program to learn. This book is really a jumping off point for traders to begin analyzing their own systems, and this format will leave them best prepared for their own explorations. Also, there are some peripheral topics that are discussed along the way, that pertain to the subject at hand.
When traders have completed these steps, they will then be well positioned to make the best money management decisions. Decisions that will materialize themselves into increased profits, lower drawdowns and better mental health. (What more could one ask for?)

缩水基金

The first major section in this book is the "what" section. It explains to the reader what the major types of money management are and discusses the advantages and disadvantages of the following seven major money management approaches and techniques:

1.No Money Management - This technique is the default method that many traders use. It consists of entering the market with one unit/contract every time a trading system gives a signal to enter the market. This method has advantages and disadvantages that will be discussed later.

2.Multiple Units/Contracts - This technique is very similar to the one above, but the difference is traders would take multiple units/contracts. Although similar to the No Money Management technique, this method has some definite peculiarities to be concerned about.

3.Fixed Dollar Value for Risk- In this technique traders define how much money to risk on any given investment/trading signal. For example, a money manger may choose to risk up to, but not more than, $1000 on each trading signal.

4.Fixed Percent of Equity - In this technique, traders define what percent of the account value to risk on any given trading signal. For example, a money manger may choose to risk up to, but not more than, 5% of the account on each trading signal.

5.Adjust Trading on Win or Loss - This technique is often called the pyramiding (up or down) or Martingale (normal or reverse) approach. In this technique, traders determine how much to trade after successive wins or losses. For example, after losing trades, they may decide to double up on the next trading signal, to recoup the losses.

6.Crossing Equity Curves - With this technique, traders define a long and short average (3 and 8 for example) of the trade profit and losses. When the short average is greater than the long average, it means the system is doing better than it did in the past. Based on this information, they would enter the market. If the short average is below the long average, they would trade. The profit or loss from all trading signals, whether taken or not, are calculated in the average.

7.Applying the Optimal f - This section goes over what the Optimal f is and how to apply it as a money management technique. Many people are familiar with this approach, but it does have some dangers to watch out for.

Upon completion of this section, traders will know most of the "nuts and bolts" about different money management techniques and variations and options to these techniques but even more important, they will kNOW about their own trading systems. Traders will also be able to determine the profitability and risk factor for their personal trading systems by utilizing any one or all of these money management
approaches/techniques.

But, before traders try and figure out the profit potential of their trading systems, they should first try and determine what is right for themselves. This is the next important section in this book and the shortest. Basically, in order for traders to accurately choose the best money management technique(s), they need to decide what kind of risks and rewards they want or are welling to endure. Each one of the money management techniques discussed can impact and transform a trading system differently. Some of the techniques will allow traders to make a very high profit, while others will allow the traders to minimize the drawdown on their trading system. A system may have a high probability of ruin, but incredible profit values. In order for traders to pick the best method, they will need to be honest with themselves on how they want their accounts to grow. Some people need security, others need rapid growth. Who knows what you need, better than you?

Once traders are comfortable with what they want, they can then move on to the sections of this book discussing how to compare different techniques and trading systems. Systems can and should be compared in many different ways. No one ratio tells the whole story. Astute traders will look at their trading possibilities from several different angles, before deciding what is best for them. This section of the book looks at nine different ways to compare systems:

1.The total profit
2.The drawdown
3.The profit / margin ratio
4.The profit / drawdown ratio
5.The profit / time ratio
6.The percentage of winners
7.The Z-score and confidence limits
8.The Optimal f
9.The probability of ruin

Each of these methods for evaluating results has different advantages and disadvantages. Traders should be aware of these differences before using any of these methods to evaluate a trading system. Only after using several or all of these techniques can traders make an informed and intelligent decision for or against the value of a trading system. Not looking at a trading system's results from several angles may leave traders in the unhappy situation of picking the wrong approach. Choosing the wrong approach could leave traders with a less fulfilling and unprofitable trading experience.
Choosing the correct approach will allow traders to feel more comfortable about their trading. This comfort can manifest itself by allowing traders to focus on the other aspects of trading that effect the profitability of a system, such as the psychological aspects for example. Overall, the more comfortable traders are, the better.

Periodically throughout this book, references will be made to what is still not known about money management. This book contains a great amount of useful information on the application and value of money management but it is not a definitive encyclopedia on the subject. It is very obvious there is still much to be learned about the arcane subject of money management. For example, is there a way of knowing in advance which money management method will work best with a particular trading system? There probably is, but the authors of this book do not know how to determine this and most traders probably do not know either. Or, is there a way a money management technique can tell if a trading system has broken down? Another question, yet to be answered. It seems there is a great deal more to learn about the theory of money management than is known at this point in time.
The same three or four trading systems have been used as examples throughout this book. It is the intent of the authors not to deceive the reader with a trading system that is optimized for a particular money management technique and thus give the reader the wrong impression. Additionally, these systems are included in the software, so the reader has the opportunity to check them out if desired.

In summary, this book is a tool for traders to receive the basic knowledge that is required to start exploring the principals of money management. The software is the tool that will allow traders to take this knowledge into the real world and in turn take this process of exploration to places this book hasn't gone to.....yet.

缩水基金

You Have A System Bias Towards Mechanical Systems?

In order for traders to take an effective approach to money management, the trading results must have some consistency or some common denominator. Usually, the easiest way to achieve this end, it to have a mechanical trading system. A mechanical trading system allows traders to take subjectivity out of their trading. It is assumed, at some deep level, that a truly mechanical trading system has a particular set of results associated with it. And, it and to the extent that past situations are similar to the future, this mechanical system will perform in a similar manner, in the future. Based on this assumption, it is possible to collect data on a trading system (percent win, average profit per trade, etc.) and expect it to perform, within statistical boundaries, in a similar manner.

It would be very hard to be a professional money manager who didn't make this assumption. What's the alternative? It is hard to believe that pure luck has propelled some traders to greatness. We are inclined to believe in trading systems because they seem to work. Many systems only work for a short time, but others seem more solid.
Humans excel at finding patterns. Humans excel at following patterns. Perhaps this is why trading systems work?

An example of a mechanical trading system might be: "Enter the market with a long position and a protective stop loss of 200 points, when a 10 period moving average crosses up and over a 30 period moving average of the closing price. This is a fairly simple form of a trading system. However, today's systems can also be complex neural networks using genetic algorithms to filter the final entry and risk parameters. Traders may never be able to verbalize what exactly triggered the trades, other than "My software told me." Luckily, it doesn't matter to the traders' accounts if they know why X follows Z, or why this price action leads to that market move. It only matters to their accounts when traders apply a trading system to make money.

Trading systems spring to mind easily, almost intuitively. "When the market does X then it usually goes up." Luckily, there are many pieces of software on the market that can help traders automate their trading systems. Once a particular system is automated, traders can run it through a couple of years of historical data to see how well that particular pattern worked. The process of automating a system is important for two main reasons.

1.Automating a system takes the subjectivity out of the results. For example, if traders know that a particular system wins 73% of the time and the system has been thoroughly tested; it is reasonable to assume this system will continue to perform in this general manner. (If traders begin to "second guess" the system, they invariably make things worse. Unfortunately, it is Murphy's law and a cold reality to many traders, who have chosen to second guess their systems and missed the biggest winners.) In short, having an automated system helps insure that a well-tested trading system will continue to perform the same way.

2.Having an automated system, with well-tested results, gives traders specific information about the characteristics of their systems. If a trading system has been tested thoroughly, it is possible to find out unique characteristics about that system. (For example, Confidence limits, standard deviations, Z-scores, POR, etc.) When this is known, it is possible to find ways to exploit these unique characteristics. There are techniques for risking capital that can be specifically tailored to a particular trading system, but only thorough testing of that system will yield reliable data. These "specifically tailored" money management techniques can help traders get more profit, for less risk, from the same old system.

Having an automated system is very important, but it is not absolutely necessary. It is possible that discretionary and/or fundamental investors/traders could have a long enough trading record to show consistency. For example, if discretionary traders have a large number of recorded trades (100 or more, as an example); it is reasonable to assume they will have a reliable trading record. The same thought process might apply to a system that re-optimizes itself every 10 trades. The point is, if there is a sufficient history to develop reliable information on the trading system, then it is time to consider money management.

The main goal is to have an investment/trading system that will perform the same way in similar circumstances. At the deepest level, a system is an attempt to characterize a peculiarity about the market. The "peculiarity" could be the monetary manifestation of the fear and greed of the trading pit or the method by which bank computers hedge their stock holdings or even weather patterns over the mid-west. It is very important that traders learn if there is a peculiarity, if it is consistent and how to exploit it. Part of exploiting and maximizing a trading system is knowing how to risk your money.

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A statistical winner?

It has frequently been published, especially in books on gambling, that there is no use trying different money management systems if the system is not a statistical winner. This means that on a statistical basis, at the end of a trading period, you should have more money than you started with. With this definition, it can be stated that a system is a statistical winner when:

(Average winning trade) * (% winners) (Average losing trade) * (% losers)

Although many books say there is no use in trading a statistically losing system, there are exceptions to this statement. When traders have a statistically losing system, most conventional forms of money management will not work. This is because they rely equally on all the trades in a system to factor into the account value.
On the other hand, when traders have a statistically losing system, it may be possible to implement strategies that do not rely on all the trades equally. For example, there are trading systems that tend to always have two losers or winners in a row. (This can be determined by interpreting the Z-score and Confidence limits of a system. This is discussed later in this book.) If this is known about a system, it is possible to devise a money management approach that takes a smaller position after a loss and a bigger position after a win. The results of this approach may minimize the losses and actually turn a losing system into a winning one!

There are several other money management techniques and methods that do not rely on all the trades in a system equally. Any of these methods could conceivably turn a statistically losing system into a wining system. However, they can just as easily change a winning system to a losing one. By not relying on all of the trades equally, traders are opening up a new game in money management. These new approaches need to be carefully evaluated with a good dose of common sense. This book will explore these different approaches in detail.
Getting to a deeper point, why would traders want to try to turn a losing system into a winner with money management? There are several reasons why traders may want to try to improve a loser rather than trying to develop a winning system. The main reason traders may want to use this kind of approach is to compensate for drawdown periods in another system. Many successful traders have complimentary systems that compensate for each other's drawdown periods. It is possible that one of these complimentary systems can be a losing system. However, when combined with a winning system, it makes for a smooth equity growth.

One more fact that all traders are familiar with is, really good trading systems are hard to find. Anybody who has tried to look for systems knows it is an emotional game. One day you have found the holy grail Holy Grail to trading. The next day, after some additional testing, you find the system lost a million dollars between 1985 and 1996. You go back to the drawing board and start over again. On the other hand, OK systems are not that hard to find, with serious looking. There have been many traders who found a system, did thorough and complete testing, only to find out that it earned 7% a year. "I can't quit my job for 7% a year", they say, then try again, more frustrated then before. This is a pity, because good money management can often make a system like this very feasible.

Given the fact that good trading systems are hard to find, it becomes necessary to effectively use money management techniques to improve the profitability of an OK system, as much as possible. Using solid money management principals allows traders to squeeze more out of their same old system, often times with less risk. Traders can be sure that with ever increasing computer power pointed at the market, people will become faster at finding market peculiarities and exploiting them into profitable trading systems. But finding the trading system is the small part of the problem, managing the risk to the account will be the major separation between casual traders and the institutional ones, the winners from the losers.


Consider the definition of a statistically winning system again for a moment.
(Average winning trade) * (% winner) (Average losing trade) * (% losers)

Please keep in mind, this does not account for any costs, such as commissions, slippage, overhead, etc. When these numbers go into the formula above they can often shift a winning system into a losing one. Many traders often do not take the commissions and slippage in to account when evaluating systems. It can be very important. It can also add up quickly. If you are paying $50 in commissions per turn, it only takes 40 trades to spend $2000. These kinds of costs can put a $20,000 account down 10%, before calculating any profit or loss from the trades. On top of this kind of overhead, astute traders will also account for the day when they are caught in a limit move or when the market gaps way past their stop on the open of the next day. Whatever the case, these are real costs that can make or break a system. With this in mind, the definition of a statistically wining system becomes:

((Average winning trade) * (% winner)) - (all other costs) (Average losing trade) * (%losers)


What Is a Valid Sample?

In order to evaluate a trading system, it is necessary to have a sufficient number of trades to make a valid sample. This much is common sense. Knowing how many trades are necessary to make a valid sample, is not. Some traders say 10 while other say 1000. This is interesting, because to some extent, both of the traders are right. The answer lies in the definition of the word "valid." By valid, these traders mean the ability of the sample trades to predict future performance of the system.

Starting with the most conservative approach, some traders feel they need to see 1000 trades before they truly know the performance of a trading system. One's first reaction to this comment may be, "Wow, that's really conservative!" Over time, however, this point of view becomes more reasonable. This is especially true when one considers how many people, including the authors, have tried a tested trading system real time, only to watch it crash. In an informal way, there is some scientific data to back up the conclusion that a very large number of trades are needed. Those of you who are familiar with "Random Walk" indicators know that the market is moving in what appears to be a random way a fair amount of the time. Given that the market is random, at least some of the time, it is reasonable to assume the results from many of the trades taken have a random element to them. Therefore, it is necessary to have a very large number of trades in order to begin to see the actual effects of a trading system on an account, if many of the trades in the sample are random wins or losses. It is also very important to know how the system behaves independent of the market or other conditions. Also, it may take a larger number of trades to see the effects of randomness on a trading account.
Of course, the Random Walk theory may be bunk, but it does give astute traders an interesting perspective on the market and how to view the success or failure of a particular trade. There is one other thought on randomness, that could lead traders to believe a large amount of trades are necessary. It is reasonable to expect that if you flip a coin 1000 times, at some point it will come up " heads" 10 times in a row. If this happen within the first 20 flips, then a trader would not have an accurate prediction of the probabilities of flipping a coin. When these kinds of statistics are applied to money management, it becomes clear why a large sample of trades is necessary. It can take a large sample of trades just to figure out what is normal.

Taking a slightly different perspective, scientific traders will often state they need at least thirty five trades to develop any results that are statistically valid. This belief comes from mathematical proofs associated with standard deviation. As a general rule of thumb, safe traders will want at least thirty trades when testing their trading systems.
Other traders, for example, may utilize trading systems that rely on odd seasonal or market patterns and thus have very few trades. In cases like this, there may only be ten examples of this particular pattern. Is it reasonable to believe that a trader can have a reliable system with only ten samples? Who knows? It seems possible. The answer lies in whether or not the system/sample can reasonably predict future action. This is the area where money management drifts from science to art. It will take the discretion of the traders to ultimately decide this question.

The following represents thoughts that should thing that need to be considered when examining systems with small sample sets:

1.Are the market conditions similar for all of the trades? For example, was the market trending in all of the examples, or did the entry/exit signal happen before a major economic report. If the short term market conditions are similar, traders can have a degree of confidence that results are reliable. On the other hand, if some of the signals are from trending markets and others are from choppy markets, the system may not be reliable, even though other statistics look good. Also, this kind of analysis can help traders gain additional insight into their trading systems.

2.What is the distribution of the profitability of the trades? If all the winning trades seemed to make about the same amount of money, then traders can have a higher degree of confidence about the system. If the profitability of the trades is spread out over a large range, it can be a signal that the system is random.

3.To some extent, you can use the percentage of winning trades as a barometer. However, this is not "fail safe" necessarily a good method either. As mentioned above, even a system of 50% winners goes into periods where it may lose ten in a row.
It is clear there are many different perspectives on how many sample trades are required to make a reasonable test set. As mentioned above, this is one of those areas where art and experience meet science. One of the few things that can be said with certainty is that the more trades one has in their test set, the more accurate the results will tend to be. The more accurate, the better. To repeat what was said above, the answer lies in whether or not the system/sample can reasonably predict future action.


Evaluating Different Money Management Strategies

What is Money Management?

Let's define "money management" in a way that has utility to everyday traders. Money management is a way of deciding how much of an account to risk on a particular trading opportunity.
Setting aside the psychological aspects, one half of trading is deciding when to enter the market. The other half is how much to risk. In many ways these two aspects of trading are both related and separate. Traders can receive a signal to enter the market and decide to risk three contracts or four. But the trade either wins or loses in an absolute sense and it doesn't make any difference how many units/contracts the traders risked. In this sense, the two halves of a trade are independent of each other. On the other hand, the market entry half and the money management half of a trade can be tightly linked. Consider a trading situation where traders can only afford a stop loss of $500, although $750 fits perfectly below a market resistance level for a stop. The traders are then forced to put the stop at $500 due to the amount of money in their account. In this case, the money management approach, can influence the success or failure of the entry.
Whether or not your money management approach effects your trading system, it will always effect your account value. Every trade represents a risk of making or losing money. Therefore, in this respect, every decision to enter the market effects the account value in some way. The method of money management that traders decide to use determines how much their accounts are effected. The basis of these decisions rely on the wants and needs of the traders. For example, some traders might want to maximize profit while others might want to minimize the risk to an account. Most of us are in the middle somewhere.

It is my experience most traders never make informed decisions about money management. Instead, most of them fly by "gut feel." This is not a bad approach in itself; some people are good "gut" traders. But for the rest of us, going on gut feel does not give us any tools for analyzing if what we are doing is right or wrong. When we begin to examine different approaches to money management and begin to understand the dynamics of a particular trading system, we can make decisions that maximize the growth to an account while keeping the risk to a minimum.

Despite the fact that money management is half of a trade, many traders still spend five times more effort reading about trading systems than learning about the principals of sound money management. The fact there are very few good articles or books on money management is partially to blame for this disparity of effort. However, the major part of the blame lies with the traders. Despite the fact that money management can greatly effect traders' accounts, very few of them focus any effort on improving their knowledge in this area. Instead, most traders focus on timing the entry or exit to the market as a way of maximizing profit.

This is an easy trap to fall into. Firstly, the common tools for system development usually only allow for limited money management techniques/approaches, if any at all. This situation denies traders the tools to really evaluate different money management techniques/options. Secondly, the calculations involved are usually very time consuming. To use a simple example, imagine if traders wanted to know the return on their accounts if they risked exactly 10% of the account value on each trade. This kind of simple problem could take a large number of calculations to work out on a calculator. These situations and others, leave traders with very few easy options for evaluating different money management techniques and options, other than a few books and this software. Please Note: There are other money management software programs commercially available (some in excess of $10,000.00) , but to the best of the authors' knowledge, none of them offer the total capability found in the kNOW Program.

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Selecting A Money Management Method To Use?

Let us start with the negative side of things. Selecting the wrong money management techniques/approach can have a detrimental effect on your trading performance. In light of this consequence, there is only one reliable way to come to a valid conclusion, testing different approaches. To some extent, different mathematical properties (% winners, average loss, etc.) may point to certain methods over others. However, the testing of different money management techniques, (just like in trading system development), is the most reliable way to understand what to expect from a trading system. In the following chapters, this book will go over various considerations and optional methods when reviewing the results of the different money management techniques/approaches.

When developing the results for a particular money management technique and approach, traders should use the same methodology as in system development. This method takes the scientific approach to testing. First, traders should start with two or more data sets, all coming from the same trading system. Using the first data set, traders should develop the best money management methodology for that particular timeframe/system. Once they have reached some type of conclusion as to what money management technique/approach is the best for the initial data set, it can then be tested on the other data sets. The results from the first data set should then be discarded. But, this is often hard to do, since the numbers look so good. However, this first data set is naturally skewed to look good, because the goal was to try to find what worked best (optimization?). The results from the other data sets will be the most trustworthy data and will determine the true value of the money management technique(s) tested.

Many traders do not go through this process when testing their trading systems or their money management approaches. As a result, Therefore, back tested systems that may have worked wonderfully for the last couple years, fall apart in real time. The tight curve fitting of the past often does not match the future. (Please see the section on Optimizations.)

Selecting the correct money management approach will take time to test and evaluate. It will also cost money if it is done wrong. On the other hand, if serious traders take the time to find the best money management technique(s) and/or system, it will be one of the best investments they ever make. In other words, you will have to work to find out what money management approach works best for your style, goals and trading system. No traders like the additional work involved, but trading is like anything else in life; the people who work the smartest and hardest usually come out on top.

Often smaller investors will only be able to afford to take one unit/contract on any trading system signal, due to the size of their account. These traders feel that because of this fact, their money management options are limited. This is a legitimate concern, because the initial size of the account can effect how much money there is available to trade. However, it is important to keep in mind there are alternatives. For example, traders can take partial contracts on the Mid-Am or even choose not to trade at all. There is no reason why traders should open themselves up to undue risk, due to a lack of capital. If traders are in a position where they can not regulate the risk to their accounts within acceptable bounds, then they should stop trading. Traders who chooses to stop trading and wait until they have more expendable capital will usually be happier in the long run, than traders who are willing to risked it. There will always be traders that take great risks and win. The rest of us will read about them and wish we were as lucky. The reality is that for every person who pulls off a trading miracle, there are twenty that didn't. Also, it is easier on one's own mental health, family support group and ultimately the wallet, to play it safe.


An IMPORTANT Distinction

When evaluating money management techniques/approaches and, to a smaller extent trading systems, it is important to note that there are two types of processes effecting the values. It is convenient to think of these as linear and non-linear factors.

Linear factors have results such as:

1.Gross profit
2.Total profit
3.The dollar value of the drawdown

These kinds of attributes of money management techniques/approaches, will grow in a linear fashion as traders risk more or less money. This can be demonstrated with a simple example. If traders take one unit/contract, they will make $X amount of money. If traders take two units/contracts, they will make twice that amount of money. This is pretty intuitive. The problem arises because many traders assume that all money management techniques/approaches are linear.


Non-linear factors are results such as:

1.Percentage growth of the account
2.Probability of ruin
3.Standard deviation of the trades

These kinds of attributes do not grow in a linear manner. Using the example above, if traders take a one unit/contract position they may have a probability of ruin of X%. If traders take two units/contracts the probability of ruin may be up to four

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times as high. The reason for this is that the probability of ruin is tied to the success of the trades and the account size. (More details on the probability of ruin are given later in this book.) The same kind of reasoning applies to calculating the percent growth of an account.
These non-linear factors are very important when comparing various money management techniques/approaches, because it is often these factors that have more to do with a trader's success of traders than the profitability of the their systems.
To a large extent, it is not understanding, or even recognizing, there is a difference between how the linear and non-linear factors interact that causes many traders to fail. Unfortunately, most traders, and the tools they use are primarily interested in just a few basic numbers, profit and drawdown, and automatically assume they are all linear. The truth is, depending on the method of money management utilized, there are cases when the profit and drawdown are not even linear.

Below are two very relevant examples of how these non-linear aspects of money management can effect trading:

Example 1:

Assume the starting account size is $25,000 and the traders are trying to find out what percent of their account to risk on each trading signal the system gives them. This "percent of the account" will represent a different amount of money for each trade, since the account changes value with every win or loss. Traders will need to risk up to, but not over that amount of money. Therefore, on the first trade, if the traders were going to risk 6% ($1500 = 6% of $25,000), the ideal trading signal would have a risk of $1,500. (Traders would not take a trading signal that had a risk of $2000 since it is over the allotted risk. Alternatively, if the risk is $500 per unit/contract, traders would take three contracts to reach the $1500 risk goal.)

The following table shows the results of risking different percentages of an account on this type of money management approach:


Although the traders grew the percent to trade in a linear fashion (2%, 4%, 6%, etc.), there is nothing linear about the results. As you can see, risking 4% was the best approach for the traders in terms of profit. Risking more or less than 4% resulted in a lower profit for the traders. This kind of example shows that if traders take additional risk in a linear fashion, the return on the account is not necessarily linear. Traders should keep this in mind when exploring and/or comparing different money management techniques/approaches.

Example 2:

If we lived in a perfectly statistical world, we would all have 0.78 of a house, 1.5 children and 0.34 dog. But this is not reality. Trading systems and their results happen within a range of values. For example, you can expect a system to be within plus or minus 15% of your expected results after a sufficiently large number of examples. The correlation of your system within a particular range of expectation is one of those non-linear factors. This is not usually one of the things that most traders consider. However, understanding this principal helps traders to know if their trading system has "broken down." To illustrate this point consider the following trading system:

Percent (%) winners = 50%
The average win = $100
The average loss = $ 50
Average profit per trade = $ 25 (by deduction)

In a perfectly statistical world, traders could expect to make $25 per trade. Therefore, after 100 trades, the traders would expect to make $2500.
Unfortunately, this is not a perfect world and as traders use this system, they will probably find that the real-time results do not match the hypothetical results. The more trades there are, the less chance traders will end up having a perfect statistical outcome. To simplify the example, consider tossing a coin four times. You know that half the time you should get heads and half the time you should get tails. But statistics show us that if you flip a coin four times you will only get two heads and two tails 38% of the time. The other 68% of the time you will get some other outcome after four flips.

If we apply this back to our trading example above, statistics allow us to state the following:

As the number of trades increases

1.The total profit (real-time results) from a system will get closer to the expected profit ($25 per trade) as a percentage.

2.The total profit (real-time results) from a system will get farther from the expected profit ($25 per trade) as an actual number. In other words a little error adds up each time.

The goal of this section is not meant to be a primer for statistics or standard deviation. This is used purely as an example of the fact that there are linear and non-linear forces effecting your money management choices. Where you will probably end up and where you should end up after trading, do not have a linear correlation. This book and software will try to highlight these factors. In fact, it is the primary value of the software to allow you to understand these factors for your system.


Overview of Money Management Methods

This book and the accompanying software go over seven different techniques and approaches of money management:


1.No Money Management - This is the default method most traders use. It consists of going into the market with only one unit/contract every time a trading system gives a signal to enter the market.

2.Multiple Units/Contracts - This method is very similar to the one above, but traders may take multiple units/contracts. Although similar to the No Money Management technique, this method has some peculiarities to watch out for.

3.Fixed Dollar Value for Risk- In this technique, traders define how much money to risk on any given trading signal. For example, a money manger may choose to risk up to, but not more than, $1000 on each trading signal.

4.Fixed Percent of Equity - In this technique, traders define what percent of the account value to risk on any trading signal. For example, a money manger may choose to risk up to, but not more than, 5% of the account on each trading signal.

5.Adjust Trading on Win or Loss - This technique is often called the pyramiding (up or down) or Martingale (normal or reverse) method. In this approach, traders determine how much to trade after successive wins or losses. For example, after a losing trade, traders may decide to double up on the next trading signal to recoup the losses.

6.Crossing Equity Curves - With this technique, traders define a short and a long average (3 and 8 for example) of the trade profit. When the short average is greater than the long average, it means that the system is doing better than it did in the past. Based on this information, traders will enter the market. If the short average is below the long average, traders will not trade. The profit from all trading signals, whether taken or not, are calculated into the average.

7.Applying the Optimal f - This section goes over what the optimal f is and how to apply it as a money management system. Many people are familiar with this approach, but it does have some dangers to watch out for.

8.There is also a way to check for the best diversification plan across a set of instruments.

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Organization of Following Sections

In the following sections, three different kinds of typical systems will be used to contrast the different types of money management techniques. They all make about the same amount of money when traded on a single unit/contract basis. In these examples, the trading accounts all start with $25,000. The graphs shown below are the accounts' equity, while trading:

1.) System A - This system wins about 76% percent of the time. The risk per trade is set at $500 dollars. However, this system typically has small wins. This is similar to the type of systems that traders often develop for choppy markets or for some forms of intra-day trading.

2.) System B - This is the "typical" system. It wins about half the time. The winners are good and the losers are OK. Often, systems that use stochastics for entry and exit will give these kinds or results.

3.) System C - This is a typical trend following system. It has many losers and a few large winners. This system wins about 33% of the time, but the profit on the winners is almost double the two systems above. The results might be similar to systems that use large moving average crossovers or entering the market at Fibonachi retracements.

Different money management approaches will be applied to these three systems to illustrate some of the subtleties of the different money management techniques/approaches. However, It is important to keep in mind that the following are just examples. The intent is not to show which method is best, but to give the reader some insight into the different money management approaches, how they can effect the account, and to show the dramatic effects different types of approaches can have on an account.

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No Money Management Technique

The simplest form of money management is basically no money management.
Additionally, it is the type of money management that most small investors use. In this technique traders buy or sell one unit/contract. No adjustments are made for other factors, such as the amount of risk per trade, the amount of money in the account, the previous successes or failures, etc. This is also the type of money management that most trading system software programs default to.

The initial account size is one of the most important considerations traders can make if they choose to use this technique/approach. Depending on the account size, this technique can vary from being very dangerous to being a very safe way to approach money management. In short, the bigger the account size the better it is. When traders have small accounts, by definition, they are risking a substantial amount of the account on each trade. Many small accounts can not handle two or three losses in a row. As a result, a small account size can dramatically increase the probability of ruin for an account. (Probability of Ruin is discussed in it's own section later in the book.)

If the account size is large enough, there is little one can negatively say about this technique/approach. However, usually there is a substantial opportunity to make more money using other types of money management techniques. For example, with the No Money Management Technique, traders have do not have any way to regulate the risk or any method for compounding returns.

Here are the No Money Management Technique results for the various systems previously outlined. They are provided primarily as a reference point against the other money management techniques and to give the reader a feel of how normal these systems are.

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SYSTEM A

System Information
Type : All trades
Total Profit : $ 9490.00
Gross Profit : $ 19460.00
Gross Loss :$ (-9970.00)
Number of Trades : 45
Number of Wins : 25
Percent Win : 56%
Number of Losses : 19
Long Num Trades : 22
Long Number Win : 13
Long-Percent Win : 59%
Short Num Trades : 23
Short Number Win : 12
Short-Percent Win: 52%
Average Trade : $ 210.89
Average Win : $ 778.40
Biggest Win : $ 1840.00
Average Loss : $ (-524.74)
Biggest Loss : $ (-2445.00)
Num Avg Trade : 18
Num Avg Win : 11
Num < Avg Loss : 1

Account Information:

Starting Account Value: $ 25000.00
Highest Account Value: $ 37060.00
Final Account Value : $ 34490.00
Lowest Account Value : $ 24505.00
Starting Percent : 100%
Highest Account Percent: 148%
Final Percent : 138%
Lowest Account Percent : 98%
Worst Drawdown on a Dollar Value Basis
Drawdown as Percent : -08%
Drawdown From : $ 37060.00
Drawdown Dollar Value : $(-2860.00)
Drawdown To : $ 34200.00


SYSTEM B

System Information
Type : All trades
Total Profit : $ 5315.00
Gross Profit : $ 18565.00
Gross Loss : $ (-13250.00)
Number of Trades : 41
Number of Wins : 19
Percent Win : 46%
Number of Losses : 22
Long Num Trades : 19
Long Number Win : 13 Long-Percent Win : 68%
Short Num Trades : 22
Short Number Win : 6
Short-Percent Win: 27%
Average Trade : $ 129.63
Average Win : $ 977.11
Biggest Win : $ 3500.00
Average Loss : $ (-602.27)
Biggest Loss : $ (-2050.00)
Num Avg Trade : 36
Num Avg Win : 19
Num < Avg Loss : 7

Account Information
Starting Account Value: $ 25000.00
Highest Account Value : $ 30315.00
Final Account Value : $ 30315.00
Lowest Account Value : $ 20575.00
Starting Percent : 100%
Highest Account Percent: 121%
Final Percent : 121% Lowest Account Percent : 82%
Worst Drawdown on a Dollar Value Basis
Drawdown as Percent : -18%
Drawdown From : $ 29280.00
Drawdown Dollar Value : $ (-5200.00)
Drawdown To : $ 24080.00


SYSTEM C

System Information
Type : All trades
Total Profit : $ 6847.00
Gross Profit : $ 20917.00
Gross Loss : $ (-14070.00)
Number of Trades : 41
Number of Wins : 12
Percent Win : 29%

Dumber of Losses : 29
Long Num Trades : 19
Long Number Win : 8
Long-Percent Win : 42%
Short Num Trades : 22
Short Number Win : 4
Short-Percent Win: 18%
Average Trade : $ 167.00
Average Win : $ 1743.08
Biggest Win : $ 3500.00
Average Loss : $ (-485.17)
Biggest Loss : $ (-1200.00)
Num Avg Trade : 47
Num Avg Win : 25
Num < Avg Loss : 25

Account Information
Starting Account Value: $ 25000.00
Highest Account Value : $ 32447.00
Final Account Value : $ 31847.00
Lowest Account Value : $ 23900.00
Starting Percent : 100%
Highest Account Percent: 130%
Final Percent : 127%
Lowest Account Percent : 96%
Worst Drawdown on a Dollar Value Basis
Drawdown as Percent : -20%
Drawdown From : $ 32110.00
Drawdown Dollar Value : $ (-6410.00)
Drawdown To : $ 25700.00

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Multiple Units/Contracts Technique

This form of money management is almost identical to the No Money Management Technique described above. In terms of directions to your broker, it would only be the difference between buying or selling additional units/contracts at the same time, on the same trading signal.
As mentioned before, doubling or tripling the amounts risked can have a non-linear effect on the account in terms of the probability of ruin, plus other factors. Therefore, if you are considering this technique/approach, it is best to run your trading system through a number of scenarios using the kNOW Software, to determine how it might be effected.

One of the concerns with increasing the number of units/contracts taken is the drawdown. On the positive side, the profit increases are in a linear fashion. Therefore, in this respect, it is easy to estimate. On the negative side, the drawdown also increases in a linear fashion. If traders using this approach want to increase profits, they do so at the expense of increased drawdown. The point is, that although this may be an effective method for increasing the profitability of a trading system, it is frequently not the most effective way for controlling the drawdown. What many traders fail to account for is how bad drawdowns can effect their overall track record. If traders have any hopes of becoming professional money managers, and many do, keeping the drawdown to a minimum is one of the most important considerations, of any trading system. Often when investors, especially institutional investors, are looking for fund managers, having a low drawdown is more valuable/important than high returns. This may not be a concern for all the readers. However, to the extent that good money management is planning for the future, it is important to consider one's potential long long-term goals. You can't erase a track record or get money back after losing it.


Risking a Fixed Dollar Value for Each Opportunity Technique

Another money management technique/approach often used on the markets is to risk a fixed amount of equity on each trading signal/opportunity. This technique allows one to efficiently play the odds associated with the percentage of wins and losses in the account. For example, if traders started with a $25,000 dollar account, they could decide to risk $1000 on each opportunity. Traders would then take as many units/contracts necessary, to come as close as possible to a $1000 risk for that particular opportunity, without exceeding the desired risk. If a trading opportunity has a $1000 risk then they would only take one unit/contract. If another trading opportunity has a $500 dollar risk then two units/contracts could be taken. If a trading opportunity has a $750 dollar risk then traders would only take one unit/contract. If there was a $1500 dollar risk then the trade would be skipped completely.

This approach will give traders the confidence of knowing they will have a minimum of twenty-five trades in which to let their system "do it's stuff". This can be advantageous for some trend following systems that may only win 30% of the time. Additionally, using the values for how much to risk per trade and knowing the percentage of wins and losses can allow traders to generally predict the potential drawdown to their accounts. For example, if traders have a system that wins 50% of the time it would not be unusual for that system to have four or five losses in a row, given enough trades. Knowing this, will give the traders a reasonable expectation of losing at least $4,000-$5,000 in a run.

It is important to note that this type of money management technique may be filtering the trading system. In the previous example given, the traders would only risk $1000 per trade and if a signal were given that has a risk of $1500,then the trade would be skipped. This may seem like blasphemy to system traders that know they should take every signal. In a sense they are right. As discussed above:

As the number of trades increases:

1.The total profit (real-time results) from a system will get closer to the expected profit as a percentage.

2.The total profit (real-time results) from a system will get farther from the expected profit as an actual number.

What this means is, that by skipping this trade, traders will be farther from the expected profit, as a percentage. Is this bad? Maybe? However, if the traders continue trading, the effect of skipping a trade diminishes.

OK, so much for statistics. It is not always reasonable to let the desire to be in every trade force one into a trade that may be a large loss, which in turn greatly increases the size of the average loss. (The average loss value correlates directly with the probability of ruining an account). Filtering out some trades based upon trading signals derived from money management concerns, can be justified. However, in order to do so, it is necessary to have a large enough number of examples in the test set, (after the big ones have been filtered out), to give a valid sample/results.

This technique also allows traders to get more leverage out of their trading signals with a smaller amount of risk, by allowing them to take multiple units/contracts. Signals that have a smaller risk can be entered with more units/contracts than signals with larger risk. This allows traders to get more "bang for their buck". In other words, this allows traders to make more money out of the same type of market move, utilizing signals that have a smaller risk. In this sense, the traders have managed to put a limit on the possible losses, while leaving the potential for profits unlimited.

A few money managers use this technique/approach with success. It generally allows for a very clean and easy way to calculate the potential risk that is involved. Consider the following trading system: it wins 50% of the time and the risk is $1000 per trading signal. Since we know that in a 50% system, there is about a 1% chance of getting seven losses in a row, astute traders can expect the worst drawdown to be about $7,000. It is very convenient to be able to quantify the worst potential drawdown prior to trading real time. If for no other reason than it allows one to be mentally prepared to lose the money.