Inside Advantage Special Intermarket Classic Issue May 1998 Murray A. Ruggiero, Jr., Editor In Volume 2, Issue 3 o f Inside Advantage, we presented intermarket relationships for predicting the S&P500 using Treasury Bonds and the Commodities Re search B ureau Index. In this iss ue, we will show how different S&P500 weekly stock groups can be used to predict both T-Bonds and crude oil on a weekly basis. W e are limited to weekly analysis because the data for these groups is reported weekly. Next, we have an article by Ryan Jones on money management and the difference between fixed fractional trading like optimal f and fixed ratio trading, which he invented. Ryan's money management methodology makes it possible to turn $20,000 a year in profits and several trades a week into over $1,000,000 within five years. W e have also included a basic ve rsion of his form ula coded in TradeS tation on our disk service for th is iss ue. W e will begin our analysis with several different stock groups, which can be used to predict T-Bond market movement. W e used the intermarket divergence concept of price relative to a moving average for different S&P500 stock groups using weekly data for the period 1/1/86 to 12/30/97. W e included these stock groups in our analysis: S&P 500 Steel Group S&P500 Capital Goods Group S&P500 Paper and Forest Group S&P500 Chemical Specialty Group S&P500 Chemicals Group S&P500 Aluminum Group S&P500 Retail Stocks Group S&P500 Hom e Building Group

Using optimization on the moving average parameters for both T-Bonds and the intermarkets from 2 to 20 time periods revealed some interesting relationships. The S&P500 Steel Group dominates the top sets of parameters with 30 of the top 40 sets using the S&P500 Steel Group as the intermarket. Seven sets of parameters using the Steel Group as the intermarket produce more than $100,000 in net profit during our test period. The strength of steel stocks is strongly correlated to the strength of the economy and for this reason, they are predictive of T-Bonds. Other markets rounding out the first page are the Ca pital Go ods G roup, C hemicals Group, A lum inum Group, and Sp ecialty Chemicals Group, with the S&P Chemicals and Capital Goods Group being the most useful markets for predicting T-Bonds. W inning percentages are very high in this study. On the long side, five se ts of p arameters produced m ore than 90% winning trades and all sets won than 70% of th eir trades! A relatively higher percentage of returns was produced on the short side with profits split 60% long and 40% short from many of the top sets of parameters. The drawdowns are consistent over these top pairs, but are relatively high being between $17,000 and $36,000. Many of the better sets of parameters with over $90,000 in profits had drawdowns between $21,000 and $26,000. This drawdown characteristic is high, but remember, if market conditions change on Tuesday, we are fo rced to stay in the trade until the following M onday due to our weekly

(c)1995, 1996 All Rights Reserved Historical backtested performance results have certain inherent limitations because they have been produced with hindsight. Just because a method or pattern was profitable in the past does not mean it will be pro fitable in the fu ture. Trading futures is very risky a nd no t for eve ryon e and you can lose money trading stoc ks.

2 Inside Advantage timeframe. In general, the time period for the moving average of T-Bonds is 2 to 4 weeks, however, the periods for the SP500 stock groups are not as consistent. The average trade values are very high with many combinations showing over $3,000 profit on the long side and over $1,00 0 profit on the s hort side. T hese relationships can be helpful in developing a bond based mutual fund trading system for longer holding periods, or they can be used in the development of a T-Bond futures trading system which combines both daily and weekly time frame analysis. One set of parameters using a two week average for T-Bonds and a 30 week average for the steel group produced the am azing results shown in Table 1 over our analysis period. Ne t Pro fit $108,560 Trades 50 W in% 68 Average Trade $2,131 Drawdown $-21162 Table 1 The largest losing trade was $-16,675 during the rally of 1993. Since January of 1995, this system has worked incredibly well producing $65,729 during this period ending 12/30/97. Of that amount, $44,000 was on the long side with a drawdown of $-2,469 . There were 16 trades during this period of which 81% were winners with an average trade of over $4,000!. During 1997, it made $9,500, winning 5 of 7 trades with an open trade as of 12/30/97 of $2,500. Crud e O il and In term ark et Analysis The S&P500 and T-Bonds are not the only markets that can be predicted using intermarket analysis. Crude oil can also be predicted using some of the S&P500 stock groups. Let's analyze different S &P 500 oil related stock groups using the concept of intermarket divergence of price relative to a moving average over the period 1/3/84 to 12/30/97. Th e stock groups we selected were: S& P5 00 Do mestic O il S&P500 Service and Equipment

S&P500 Oil and Gas Drilling S& P5 00 International Integrated O ils S&P500 Oil Composite Group The four groups are all predictive of crude oil, but the Oil Composite Group produced the top fo ur sets of p arameters in term s of profit even tho ugh it has not be en very profitable over the past 12 months. The International Integrated Group has had better recent pe rformance. W e tested price relative to a moving average over 2 to 30 weeks and fou nd that good results with reasonable drawdowns were produced even on weekly data. T wo sets of pa ram eters using the O il Co mposite Group produced over $70,000 in profit with over $20,000 on the short side. In fact, over these groups, the top seven sets of parameters produced over $20,000 profit on the short side. Thirteen sets o f param eters produced over $60,000 in net profit with10 of them showing drawdowns of less than $10,000. The win ning percenta ge ran ged in the low 60's among the top 30 sets of parameters. The most profitable sets of parameters cluster around using a two week moving average for crude oil and moving averages in the range of 10 to 16 for the selected stock group. W e also found that except for the top five sets of param eters, which were dominated by the O il Co mposite G roup tha t all of the oil groups were equally represented over the top 30 sets of param eters. Let's look at two examples, the first uses the Oil Composite Stock Group with a 2 week moving average of oil and a 16 week moving average of th e stock group. O ur re sults are as follows for this set of parameters over our analysis period as shown in Table 2: Ne t Pro fit $76,909 Trades 66 W in% 59 Average Trade $1,165 Drawdown $-9,190 This system made about $1,000 in 1997. Table 2 Anothe r com parable set of parameters

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

3 Inside Advantage using 2 and 18 time periods with the Integrated Oils Stock Group as the predictor made about $68,000 during this period with 67% winning trades, and it also made $1000 in 1997. The problem with these system s is that they will give up m uch o f their profits after a prolong ed m ove in the direction of the trade . Anothe r mo re important problem was the failure of several bullish signals. This was because the oil stocks were dragged up by the market and not because of improved fu ndam ental of oil. W e can im prove the robustness of th e relationship between oil stocks and crude if we decorrelated these stocks to the S&P500 and then use the trend of this decorrelated series in our analysis. This is not as important in bonds because of the positive correlation between stocks and bonds over the past few decades. These systems show that the S&P500 stock groups can be predictive of both the bond market and the crude oil market. Because of the availability of data on a weekly basis, we need to combine them with other methodologies to develop a tradable system in T-Bonds because of the high drawdown characteristic on a weekly time frame. In crude oil, the results are closer to acceptable, but could be improved if we were able to add timing on a daily time frame. The goal was to show that the S&P500 stock groups are an overlooked intermarket indicator, which can be used as part of a multi time frame intermarket based system. Another area of research would be developing our own S&P500 stock groups which are calculated on a daily basis for u se to define intermarket divergence on a daily timeframe. An advantage of this approach is the ability to fine tune our groups to make them more predictive of the market we are trading. W e can add or rem ove stocks based on this concept which will prevent a fundamental event like a takeover of a large cap company from skewing the intermarket corre lation. The concept of using stock groups for market prediction is very powerful and works

well because of the research dollars spent of the equity side. Equity analysts spend tremendous amounts of money researching the fundamental elements of the underlining commodities, which affect these stocks. W e can tap into this research by using stock groups to predict various commodities. This is an exciting area of intermarket analysis, which we will cover in more detail in the futu re. Intermarket Divergence as a Predictor of Future Market Returns In many of my previous newsletters and magazine articles, we have presented sim ple intermarket divergence systems. One issue that we have not addressed in any of these articles is how N day returns are affected by intermarket divergence and how these returns have changed over time. Let's use the New York Stock Exchange Utility Average (NNA) and the Commodities Research Bureau Index to reexamine the T-Bond market to study how predictive intermarket divergence is on 5,10 and 15 day timeframes. W e will use parameters which have been used in systems we have previously presented so that we can use our returns in the context of the system performance of the same parameters using classic intermarket divergence on a stop and reversal basis. We will start our analysis by looking at the Day only session of T-Bonds prices versus the NN A. W e will use the core system from my April, 1998, article in Futures Magazine, which uses the concept of intermarket divergence o f closing price relative to a moving average. We will use an 8 day moving average for T-Bonds and an 18 day moving average for th e N NA . Th is basic concept produced the following results over the period 1/1/88 to 12/30/97 with $50 deducted for slippage and com missions. Combined Long Side Short Side Ne t Profit $111,093 $81,712 $29,381 Trades 125 62 63 Win% 60% 60% 60% Ave Trade $888.74 $1317.94 $446.37 D raw D ow n $-8,582 $-9,358 $-9,815

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

4 Inside Advantage It can be seen that this system is profitable on both the long and the short side of the market. This is a stop and reversal system, which is always in the market. Let's study N day returns after an intermarket divergence between T-Bonds and NNA using the same set of parameters that were used to produce the above results. Our new study of intermarket dive rgence will be different fro m our system in that we are measuring returns after a holding period of N days averaging all days in which a divergence occurs not just the first divergence in a given direction, which is how our earlier system worked. W e will use an 8 day moving average of T-Bonds and an 18 day moving average for the NN A w hich are the sam e parameters used in our system. Let's see how different holding periods affect our returns using this same set of param eters. T hese results are shown in Table 3. N day Returns After an Intermarket Divergence Note: Bullish Divergence should produce positive results and Bearish Divergence should produce negative results The results are show n in decimal equivalents for bond pricing. Holding Period 3 Day Bu llDiv .21675 Be arD iv -.11213

5 Day 10 Day

15 Day

.33724 .54678 -.10836 -.03656 Table 3

.5591 .07550

Let's discuss the results shown in T able 3. First, we can see that the returns due to a bullish intermarket divergence between TBonds and the NN A level off after 10 days, while the short side shows its peak profit after three days. We can also see that these average returns are much lower than the average trade of our system, which is over 1.3 points per trade on the long side, and about .50 points on the short side. This is because all divergences are

included in our analysis, while our system measured returns off of the first divergence in a given direction. W e can also see that we actua lly begin to lo se money by holdin g 15 days after a bearish divergence. The results shown in Table 3 represent the results over our complete analysis period. In checking the stability of these results over time, it is evident that they have been very consistent on the long side of the market. If we look at 10 day returns after a bullish divergence, results have been consistently around .50 over our analysis period. On the short side, however, our re sults have deteriorated over time with current ten day returns which are barely negative. This is a result of the great bull market in bonds since the bottom in 1994. During the 1994 and 1990 bear markets in T-Bonds, the average returns on the short side from the beginning of our analysis period to the lows of each of these bear markets improved greatly using a ten day holding period, for example on 9/27/90 it was -.4367. These returns on the bearish side became neutral at -.06 985 on 9/21/9 2 before stabilizing in the -.15 range. Once again, the returns became more negative during the 1994 bear m arket with a low of -.3 2093 on 10/26/94. In the next example, we will look at the relationship between the CRB index and TBonds. First, we will revisit using them in an intermarket divergence system, which has been discussed in som e of my earlier n ewsletters and articles. Then, we will use the same parameters as the system and measure N day returns. Once again, we will measure the returns of all of the breakouts and not just the first one to occur in a given direction. W e will use the concept of classical intermarket divergence of price relative to a moving average of T-Bonds and the CRB futu res index. Let's loo k at the results of th is system using a 6 day moving average for TBonds and a 18 day moving average for the CR B. O ur re sults over the period 1/1/88 to 12/30/97 are as follows with $50 deducted for slippage and commission:

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

5 Inside Advantage Combined Long Side Short Side Ne t Profit $71,005 $60,793 $10212 Trades 183 91 92 Win% 59% 67% 51% Ave Trade $388 $668 $111 D raw D ow n$-19,319 $-13,442 $-23,149 Table 4 W e can see that the CRB is very good at predicting when T-Bonds will rise, but not as good at predicting downturns in T-Bonds as the NNA when using our simple intermarket dive rgence concept. W e can see that we win 67% of o ur trades on the long side, but only 51% on the short side. Our average trade is only $111.00 on the short side while we make about six tim es that am ount on the long side. Table 5 shows N day returns after an intermarket divergence based on T-Bonds and the C RB Inde x using the sam e parameters shown in Table 4. Note: Bullish Divergence should produce positive results and Bearish Divergence should produce negative results. The results in Ta ble 5 are decima l equiva lents for bond pricing. Holding Period 3 Day 5 Day 10 Day Bu llDiv .18756

.23699

.14278

Be arD iv .04231

.06490 Table 5

.22318

These results are much different than our results for N NA . First, the bullish results pea k on day 5 a t .23699, and then drop off quickly at 10 days to only .14278. W e also lose money on th e short side, in fact, after 10 days the positive returns are greater after a bearish divergence than they are after a bullish one. These results are different than our system results because of the strong effect of the first divergence in a given direction being m ore predictive. The results of using the CRB Index to predict T-Bo nds has been relatively stable over time. Using a five day holding period, the

CRB Index bearish divergence has held a return of jus t abo ve zero since 1991. Before 1991, the CRB Index was better at predicting drops in price in the T-Bond market using our current set of parameters and definition of intermarket divergence. On the long side, the CRB Index was not predictive of 5 day returns until late 1990 when the returns, which had rema ined near zero since 1988 rose an d have ranged between .14 and .25 since early 1991. These two examples are just the beginning to our N day return of intermarket divergence analysis. There are many different ways to approach this study and each will provide interesting results. Another analysis we could use is to study first divergence in a given direction. The results of this analysis will be much different than our current analysis using all divergences because first dive rgence is generally m ore predictive o f market direction. W e can also filter our divergence based on different market conditions. This is an exciting area of research and with the tools supplied on our disk service you can begin your own study. Ne xt M on ths Featu re Article Next month’s feature article will discuss the concept of range expansion breakout. The most common use of this concept in a system is defining a breakout by taking a percentage of the range off of the open. Made famous by Larry Williams and Toby Crabel, the range expansion breakout methodology presents a broad range of uses. It can be used for day trading the S&P or short term trading many different markets. It can also be used for longer term trend following systems as it works on intraday and end of day data. Next month, we will study the classical breakout using either range or true range and then I will show you my new research which greatly improves the results of this classical method.

Money Management Can Make Your

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

6 Inside Advantage Dreams Come True By Ryan Jones Th ere is no question that today's trader is more equipped with knowledge, ideas, strategies, indicators, and the ability to combine these elements into his trading than ever in the history of this industry. Yet, it is amazing that the statistics of profitable traders versus those who lose money remains relatively constant year after year. These statistics are bleak, at best, with upwards of 80% to 90 % of all traders losing money at year-end. Traders may trade to make more money than they would investing in conventional investment vehicles. Yet, the percentages indicate that few make money trading and m ost do not accomplish that goal. There are many reasons and many theories as to why these facts remain true. One of these reasons is because people get involved in trading with very short-term goals. T hey are falsely led to believe that the short term goal of getting rich quick is valid and even realistic through trading futures and commodities because trading itself is short-term in comparison to standard inve stm ent vehicles. Ho wever, if on e is going to successfully trade in thes e m arkets, one must have a long er-term outlook. There are two basic aspects of trading with the first being where to get in and where to get out of w hich m arkets. Th is aspect is covered through indicators, oscillators, moving averages, price action patterns, trading systems, software, newsletters, hot lines, fun damental reports, and the list goes on. It encompasse s exit rules such as where to place stops, where to place profit targets, trailing stops and whatever other means is used to decide when to exit a trade. This aspect covers all types of trading: options trading, futures trading, sp reads, writing o ptions, short-term trading, day-trading, long-term trading, breakout trading, trend-fo llowing trading, and again the list goes on. Sadly, mo st traders’ emphasis is placed solely on this one aspect of trad ing. I believe that a trader's emphasis is c onfined to this one aspect as a result of their inability or

unwillingness to address a longer term trading plan. If you happen to be in the camp that does not regard money management principles as a highly important and powerful aspect of trading, consider the following example: A coin flipping game is offered in Las Vegas. The rules are that a coin is going to be flipped in the air 100 times. If the coin lands heads up, you will lose $1.00 for every $1.00 you bet. But, if the coin lands tails up you will win $2.00 for e very $1.00 you bet. Ob viou sly, if this game were really offered in Vegas, the coin would not have a tails side, but that is beside the point. Regard this game as having an equal chance of landing heads or tails with each flip. You are given $100.00 to bet on the coin flipping game. You may bet as m uch or as little as you wish on each flip in $1.00 minimum increments. However, being the savvy trader that you are, you are going to apply some sort of money management rules to maximize your return over the 100 flips. These are your choices. You may risk 10% of the account each flip of the coin. You may risk 25% of the account each flip of the coin You may risk 40% of the account each flip of the coin. You may risk 51% of the account each flip of the coin.

balance on balance on balance on balance on

As your account balance increases, the size of your bet will also increase. As the account balance decreases, the size of your bet on the next flip will decrease. If you choose a 10% bet, and the next flip of the coin is a winner. The bet of $ 10 on that flip won $20. Your account balance is now $120 and you bet 10% of th e new am ount on the next flip or $12. If the flip is a loser, you lose only $12 and the account balance is $108. Round down and the next bet will be $10 again. This one is a winner and you are up to $128. And the cycle goes on for 100 flips of the co in. W hich of the a bove

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

7 Inside Advantage options would you choose? Do es it make a big difference? If you chose: 10%, your account would have grown to $4,700 after 100 flips! 25%, your account would have grown to $36,100 after 10 0 flips!!! 40%, your account would have grown to $4,700 after 100 flips! 51%, your account would have decreased down to $31 after 100 flips! This assum es that the flips wou ld have been 50/50 regardless of order. The question was “Does it make a big difference” and the answer is a resounding YES! By increasing the percentage at risk on each flip by only 15% (going from 10% to 25%) increased the total return by 768% !!! W e’ll get back to this exam ple later... The bottom line is that money management does play a huge role in the overall success of traders. It will play a huge role in how successful you are as a trader in the next 5 years. What can proper money management do? 1) K eep you fro m being blown out. 2) Allow you to approach system trading with a plan and the ability to continue trading even if the system fails m iserably. 3) Increase profits 5 to 10 fold (500% to 1,000%) without increasing the overall risk of the account. 4) Protect those profits should the system end up failing miserably. Consider the following example: One trader trades a relatively inexpensive hotline for one year. During that one year, the trader’s account reaches $27,000 in profits. Th e fo llowing year, the hotline only makes $15,000. Th e total profits of th e trader is now $42,000. Another trader also trades the same

hotline for the first year. However, this trader applied conservative money management principles to the trading. T he first year, his profits reach $63,000 instead of $27,000, which is an increase of 23 3% from the first trader. Th e second yea r, how ever, total pro fits were $113,000 instead of $15,000 bringing the total profits fo r the two years of trad ing up to $176,000, which computes to a total increase of 419% more profits fo r the second trader. The third year of trading for the hotline takes a terrible turn. It loses $15,000. Trader number 1 is at $27,000 in profits for the three years of trad ing. Trader num ber 2 however is at $102,000 in total profits. This means that trader number one gave back ALL (100%) of the profits gained during the second year of trading while the second trader only gave back 65% of the profits gained during the second year. The question for this example is, which trader do you want to be? W e will begin our look at money management with the most common m ethod called the Fixed Fra ctional method. Th is method encompasses everything from risking no more than 2% - 3% of your account on each trade to trading one contract for every $10,000 in your account to wh at is called Optimal f, which stands for optimal fixed frac tion. Th is article will take a brief look at each while pointing out the pros and cons of using such highly recommended m ethods. The first is risking 2% - 3% of your account on each trade. This is recommended by many brokers and used by most CTA’s and CP O's. It states that a trade r will not risk m ore than 2% or 3% of the total account balance on each trade. For this example, the total current account balance will be $25,000. Th e next trade signal comes in the Bonds with $1,000 total risk on the trade per contract. Since no more than 2% can be risked on each trade, a sim ple math calculation is performed to determine how many contracts should be

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

8 Inside Advantage traded. That calculation is as follows: Total risk on trade divided by total percent of account at risk. $1,000 / 2% or .02 = $50,000. In other words, to follow the rules of this method the Bo nd trade can not be placed. T he reason is because the total % of the account being risked is 4%. (Total $$ at risk / account balance = total percentage at risk) Using this percentage, risk can also be translated into trading one contract for every $50,000 in the account. There are a couple of things that should be pointed out about using this m ethod. First, it is not very efficient. Using this method with the example given about the two traders leaves the first trader trading one contract the entire time assuming that trader started out with at least $50,000 in his trading account. It also assumes that the trader did not go into an im mediate drawdown. If the trader goes into an immediate drawdown, according to the rules, the trader can no longer take the trades, as the risk on the account will be greater than 2% of the account on each trade. Th e next m etho d we loo k at is the “1 contract for every $10,000 in your account” method. This one is widely recommended because of its simplicity and general ease of implementation. I find interesting the number of traders who are willing to use this for those two reasons. Hundreds, even thousands of hours, thousands, even hundreds of thousands of dollars are sp ent on w here to g et in and where to get out of which markets, but money management is reduced to a 3.5 second line of “1 co ntrac t for every $10,000 ”. Few trad ers know the actual effect this statement has on the overall performance of a system . 1 contract for every $10,000 in an account is just another way of saying that you are going to risk X% of your equity on each trade. For example, if your largest potential losing trade is $1,500 and you trade 1 contract for every $10,000 in your acc ount, you are risking 15% of your account on the next trade. The calculation for this is: largest loss / required equity per contract = % at risk on

every trade. If your largest potential loss is $1,000 then you are risking 10% of your equity on every trade. There are a couple of things that should be pointed out about this m ethod as well. First, it is a flat statement that does not take into account any consideration the m arkets that are being traded, how many markets are being traded, the single trade risks of those markets, and much less the over-all potential drawdown of the m arkets. Let m e give you some num bers that will illustrate why these things need to be taken into consideration. Let’s say you are trad ing a long er-term bond and currency system. Because of the nature of longer term trading, your stops are not exactly small ranging in the $1,200 to $2,000 area. If your stop on the next trade is $2,000 and you are trading 1 contrac t for every $10,000, you are risking 20% of your account on this trade. If you have $100,000 in the account, you divide that $100,000 by $10,000 and should place 10 contracts on this trade. If it is a loser, your account goes down to $80,000 on a single trade. But that is not the bad part. If you suffer three of these losers in a row, (which I have done before trading a long -term system of mine) your account drops from $100,000 to $52,000 on just three trades! That computes to a 48% drawdown potential on TH RE E trades! And, it does not m atter w here your account is, it will always be exactly the same. $1,000,000 has a potential drawdown of $480,000 on just three trades. W ith this method of managing your money, I could stop and the point would still be quite clear. Bu t to drive home the argument, I will go to the next most commonly wide-spread recommended money management method called Optimal f. Then, I will tie the 1 contract for every $10,000 method with the Optimal f method before going into what should be used. Optimal f is short for the optimal fixed fraction to be used on any given trading method and/or system . For exam ple, I gave a coin

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

9 Inside Advantage flipping illustration where risking 25% of your account would have yielded more return than any other percentage possible. 25% is the Optim al f of tha t particular situation. Optim al f is not 25% for every trading situation. As a matter of fact, Optimal f is different for every trading situation.

I think I have made a pretty good argument for finding a better solution to the type of m oney managem ent to use in trading . There are literally dozens of other reasons why any type of fixed fractional method should be avoided, but I do not think I need to continue to beat the proverbial dead horse.

Notice that risking 10% of the account on the coin flipping example yielded the same amount of profits as risking 40%. 25% is at the peak. This means that 11% yields the same as 39%, 20% yields the same as 30% and 24% yields the sam e as 26% . It is a perfec t bell curve. However, notice that this bell curve ends at 50% beca use a t 51%, the positive expectation actua lly loses money.

There were three main problems that led me to do extensive research on the subject of money managem ent. The first was the fact that the fixed fra ctional method was the only method available. The second was the fact that since I have a very low tolerance for risk, implementing a small fixed fraction such as 2% - 3% on each trade satisfied my low risk tolerance, but sent my alarm of impatience screaming. It would take forever for money management to have any real effect on my trading by using that method. The only other alternative was to increase that percentage, which sent my risk tolerance alarm screaming and I think the Optim al f nailed the last nail in that coffin. This is why and how I developed the Fixed Ra tio m oney m anagem ent method.

This bell curve exists with every trading system , methodology and performance record. Trading is not a controlled statistical game like flipping a coin. The win/loss ratio on each trade is different and the odds of the next trade being a winner is not necessarily a fixed number either. Optimal f is determined by filing the past history of trades through a mathematical form ula (which is not releva nt fo r this article) to determine what the Optimal f W AS for the last however many trades. Notice that I said was. It is impos sible to project wh at Op timal f will be in the future. This becomes rather important when you realize that if you trade a fixed fraction that is higher than the optimal f, you could actually end up losing money. For example, if you calculate Optimal f for the past 100 trades at 15% and trade risking 15% on every trade, the next 100 trades may have an Optimal f of only 10%. If that is the case, you are trading too much risk. If you were to trade 21% you would lose m oney. Go ing b ack to the 1 contrac t for every $10,000 scenario, Optimal f for trading may only be 10% and a $2,000 losing trade is risking 20% according to that method. You will end up making the exact same amount of money as you wo uld by not using money management at all.

Be fore I go any furth er, I do want to acknowledge for those extremely brilliant traders out there who are saying, “A ratio and a fractio n are the same th ing” that ye s, generally, a ratio and frac tion are the same thing. However, I want to make clear that the point of refe rence is com pletely different. At no tim e does the Fixed Ratio method reference the percentage being risked on every trade. It is a Fixed Ratio of something entirely different. And with that out of th e way, the m ethod... The Fixed Ratio method accomplishes two things. First, it does not take long for the method to have a substantial effect on my trading and in particular, my profits. And second, my risk level is very tolerable, known and controlled at all times. The formula for increasing and decreasing the number of contracts (or options or shares of stock) is as follows:

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

10 Inside Advantage Sta rting with 1 contract: Largest Drawdown / 2 = Variable Input Sta rt account balance + (1 * Variable Input) = account level which must be reached before number of c ontracts is increased. Largest Drawdown = $10,000 Variable Input = $5,000 Starting account balance = $25,000 Number of contracts traded = 1 Account level to increase to 2 contracts = $30,000 $25,000 + (1 * $5,000) = $30,000 PL I (Previous level of increase). For trading a num ber of c ontracts greater than 1: PLI + (number of contracts traded * Variable Input) = account level required for additional increase. PLI = $30,000 Variable Input = $5,000 Number of contracts traded = 2 Account level to increase to 3 contracts = $40,000 $30,000 + (2 * $5,000) = $40,000. Essentially, this method requires that the same amount of profits be generated for each contract being traded prior to increasing to an additional unit. In the fixed fractional method, one contract was being traded for every X dollars in the account. For example, the 1 contract for every $10,000 in the account stated that, regardless of the number of contracts being traded, there would always be an increase once another $10,000 in the account was accumulated. Therefore, if you start out trading one contract with $10,000 in the account, you would go to two contracts once the account reached $20,000. One contract alone would have to pull in $10,000 to increase. But, what happens when there is $100,000 in the account and you are trading 10 contracts ? You increase at $110,000. W hat 1 contract was required to produce in the beginning is now being required with 10

contracts. W hat took m aybe 30 trades to produce the first increase in contracts now may only take 3 trades to produce. A $1,000 winning trade will now increase contracts from 10 to 11. Ho wever, with the Fixed Ra tio m ethod, if it takes $5,000 in profits to increase from one to two contracts, it will take $50,000 in profits to increase from 10 to 11. (10 * $5,000 = $50,000). W hat took 15 trades on average to increase fro m 1 to 2 contracts will take on average 15 trades to increase from 10 to 11 and 15 trades on average to increase from 99 to 100. The term Fixed Ratio comes from the fact that whatever variable input used is a fixed ratio to the largest drawdown. If the largest drawdown is $10,000 and the variable input used is $5,000, then the variable input is a fixed ratio of 2 :1 to the drawdown. If the variable input is $2,500 then it is a fixed ratio of 4:1 to the largest drawdown. Before breaking this method down further and illustrating it’s pote ntial power, there are a fe w general rules of thu mb to keep in mind. F irst, the h ighe r the ra tio, the more aggressive the method is. This, in turn, means that the lower the ratio, the mo re cons ervative the m etho d is. M ore aggressive means more profits and m ore risk and more cons ervative means less profits and less risk. Second, there is no “O ptim al r” or optimal fixed ratio that will yield more than o thers. There is no bell curve with this method. Finally, the lower the variable input, the higher the profits regardless of what relationship it is to the largest drawdown. For example, if the largest drawdown is $10,000 and a variable ratio of $5 ,000 is traded, it will not yield as many profits as a system that has only $5,000 in drawdowns and a 2:1 ratio of $2,500 is used for the variable inpu t. However, the total % of the account at risk is relatively the same at any given time. Therefore, the lower the drawdown of a system and/or portfolio, the more effective th e Fixed Ra tio will be. One of the most popular questions I get when traders learn this m ethod has to do with

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

11 Inside Advantage increasing the first contract so quickly. In the first example of the method, the starting account balance was $25,000 while the first increase came at only $30,000. Obviously, this satisfies m y level of im patience, but does it satisfy m y low risk leve l, too. Th e answer is yes. There is one thing that most traders can not get around when applying money management to trading and it does not matter what type of money management is being applied. That one thing is the first contract or first option increase. Going from one unit to two units is something every trader must do if they are going to start applying money management (pro vide d they start with one contract). Yet, it does not matter when the trader decides to increase from one to two, it is doubling the risk of th e next trade whether the trader decides to do it after only $5,000 in profits or if the trader waits to do it at $25,000 in profits. If the first trade with two units is a loser and drops the equity back below the level at which it was increased, it does not matter whether that level was at $30,000 or only $5,000, the trader is still only trading one contract in that situation. But, it does matter. If the trader who waited to increase contracts until $30,000 was achieved would have started increasing at $5,000 using the Fixed Ratio method, that trader would have not $30,000 in profits, but $90,000 in profits! This is due to the fact that for the remaining $25,000 in profits, more than one contract would be trade d. In fa ct, there would be 5 increases during that $30,000 profitable period. ($30,000 / $5,000 = 6)

great num bers. I was m istaken. To achieve $1,000,000 in total profits using a variable input of $ 5,000 with the Fixed Ra tio m ethod would only require $100,000 based on one contract. In other words, if trader number 1 accomplished $100,000 in profits starting with one contract and never increasing, that same trader could turn that $100,000 in profits into $1,000,000 in profits by applying the Fixed Ratio method using a $5,000 variable input! Further, at the $1,000,000 level, the trader would o nly be trading 20 contracts! Compare this to the trader who is using the 1 contract for every $10,000 approach. That trader would reach 20 contracts with only $200,000 in the account. Given the potential of a $10,000 drawdown, that trader is risking nearly 60% of th e account com pared to only 18% with the Fixed Ratio method at 20 contracts! In all fairness, the trader using the 1 contract for every $10,000 method would reach $1,000,000 in profits much quicker, at $1,000,000 that trader is trading 100 contracts but is still risking approximately 60% of the account should a $10,000 drawdown be suffered. This computes to a $2,000 drawdown with that method would equal where the account would be after a $10,000 drawdown using the Fixed Ratio method. The conclusion is that the Fixed Ra tio method meets the low risk levels, yet can be applied to trading quickly, effe ctive ly and with some m onstrous results. It is the best of b oth worlds. There is, of course, much more to be learned about this method which time and space in this article will not allow. You should at least have enough here to realize that fixed fractional trading should be avoided and to be able to begin applying the Fixed Ratio method to your own trading.

This brings us to the power of the method. W hen I first developed the Fixed Ra tio method, the logic of where contract increases should take place was definitely the re. Ho wever, I first thought that the method would lack the ge ometric growth potential to ach ieve Biography Ryan Jones started trading options when he was 16. By the time he was 22 years old, he had already traded nearly every possible market. Today, he specializes in money management and has developed the first new concept in money management in almost a generation. He is a well known author and speaker, and the e ditor of the “ Th e Kam iKaze T rading N ewsletter “ published by his company Rum ery and Lehman ,Inc. He can be reached at 800-978-6379

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]

12 Inside Advantage Ruggiero Associates PO Box 120738 East Haven, CT 06512 [email protected] 1-800-211-9785 / Phone/Fax: 203-488-6461

Name: City: Phone:

Address:_________________________________ Zip____________Country___________________ Email:______________________________

State: Fax:

Credit Card#:

Exp:

Signature:

Order Form Inside Advantage Newsletter (Back Issue Collection & Email Update)……...$ 125.00 Inside Advantage Newsletter (Back Issue Collection & Mailed Updates)…....$ 150.00 Trading a $25,000.00 Account……………..…………………………….…….$

35.00

Traders Secrets Book………………………….……………………….………$ 30.00

TradeStation Products TradeStation disk for this Newsletter(including money management code)..$ 10.00 Using Easy Language 2000………………………………………………….. …$ 35.00 Stock Traders ToolBox……………………………………………………….….$ 99.00 Mini Adaptive Indicators………………………………………………………...$ 40.00 Adaptive Indicators (Full Indicator)…………………………………………….$ 99.00 TradeCycles……………………………………………………………………….$250.00 Universal Seasonal…………………………………………………..……………$ 99.00 Inside Advantage Newsletter & Disk Service W/ Online Updates.……….…...$189.00 Intermarket Analysis Pro…………………………………………………………$ 99.00 Intermarket Analysis Expert……………………………………………………..$ 79.00

S/H in USA $5.00-International orders S/H $10.00

$_______________

Ruggiero Associates PO Box 120738, East Haven, CT 06512 1-800-211-9785 / 203-488-6646 [email protected]