How Dr. Kacher made over 18,000% in the stock market in 7 years

(Excerpt from our book Trade Like An O'Neil Disciple: How We Made 18,000% in the Stock Market).


It's one thing to learn an investment system with the idea that you should be able to use it to make reasonable profits in the stock market overtime, perhaps having a triple-digit annual gain from time to time, but it's another thing to see how it is all put into practice. It's also interesting to hear how some individuals have made big money in the stock market, achieving unheard of gains in excess of, say, 1,000 percent in a single year, or some other ridiculous number like 18,000 percent over seven years. Most investors, however, have not seen what it looks like from the driver's seat, and when they hear of someone who has produced such performance numbers, it begs the question, "Exactly HOW was that done?" In this chapter and the next, we will give some insight into how we achieved big gains in the stock market-the stocks we bought, the market conditions under which they were bought, and our thought processes and decisions as we maneuvered through it all in real time.

By following along with us as we go through the experience of making big gains in the market, you may find that it is not as complicated as you might think. In the end, it is about working hard to put yourself in the position of being in the right place at the right time; that is, when a leading stock is just starting a huge upside price run. There is skill involved, and there is also some luck, but it is luck that you have to create for yourself by being in the right place at the right time. Once a position in a big leader has been taken and fully sized within your portfolio, the process becomes even simpler as you think less and sit more. Find the wave, catch the wave,and ride the wave for as long as it will take you. In this manner, investing is a lot like surfing, and when done properly, it can be just as exhilarating.

The rest of this chapter and the next will take the reader through periods in our separate trading careers where we made our biggest gains. Using annotated charts to illustrate what we were experiencing and thinking at the time, we get as close as we can to giving the reader a sense of what it was like to operate in real time during significant bull markets and windows of opportunity and to come away with huge profits that enabled us to achieve financial independence.



"A journey of a thousand miles begins with a single step."
 -Lao-tzu, Chinese philosopher (604 BC-531 BC), The Way of Lao-tzu


I had always wanted to work for William O'Neil after learning that he and his protégé David Ryan had produced exceptional long-term investment track records that outperformed the markets over multiple market cycles. When I read William O'Neil's book, How to Make Money inStocks back in 1989, it revolutionized my way of thinking about the market. O'Neil's hybrid method of applying both fundamental and technical analysis,as well as the "M" in CANSLIM-a technique that enables one to stay on the right side of the market-resonated deeply within me.

So began my journey. From 1989 onward, I devoted many hours to the pursuit of making sense of the markets. In these early years, I created all sorts of econometric timing models based on a myriad of economic indicators that seemed to have predictive value. However, I later found that most of these indicators only worked over a period of less than 15 years; thus should markets change, these indicators would lose their ability to predict.I realized that studying 15 years worth of data was insufficient. Not surprisingly,in the years ahead, my market direction model kept returning to the purity of price/volume action of the major indices. As I developed my skills at reading charts, price/volume action in timing the markets eventually became the most important variable. I also spent much time poring over individual stock and stock market data so that I could learn what variables and situations drove stocks higher.

All these research studies not only put my trading account on track,but years later when I was hired atWilliam O'Neil + Co, Inc., O'Neil noticed the breadth and depth of my market knowledge, so during the six years I was at O'Neil's firm, I was given the freedom to use all of the company's resources to carry out my studies. In some cases, I worked directly with O'Neil, and took the helm of some of his pet research projects including the 1998 Model Book study. Naturally, being his right-hand stock market research man, I shared my research findings with him, sometimes calling him late at night, as he said I could call him any time no matter how late it was if I felt I had made a significant discovery. Here was someone who clearly shared my passion for the markets. My decision to switch out of nuclear physics into the world of investments had been exactly the right thing to do. I always say once one finds one's true passion in life and takes the necessary steps to make the dream a reality, circumstances tend to align in one's favor.

The 1998 Model Book project examined top performing stocks from 1992 to 1998, and to date, I have gone through nearly 20 market cycles going all the way back to the 1920s to study the stocks that made huge gains in each cycle. I have carefully studied each stock in detail to determine which fundamental and technical variables predicted success with the highest probability, and I came up with a set of variables that the winning stocks shared.

I also created and then refined a market direction model, discussed in full in Chapter 7, so that I would be on the right side of the market whether we were in an uptrend or a downtrend. The model has never missed a bull or bear market, and I have used it under fire and in real-time since 1991,my first successful year in the market. In back tests, it has well outperformed the major averages returning an average of +33.1 percent per year since 1974, the first year of thorough back testing. To ensure the robust nature of the model, I have also spot tested the model in the 1920s and1930s, which produced results that handily outperformed the leading market averages. The systematic portion of the model is a statistical formalization of price/volume action within the major indices. The discretionary portion of the model observes other factors such as behavior of leading stocks, sentiment/psychological indicators, and involves exchange-traded fund (ETF) selection, position sizing, and degree of leverage, depending on the strength of the signal.

Years after I had formulated my model, a salesperson who was retiring in 1999 and had been with William O'Neil + Company, Inc. since the late 1960s came to my office and gave me a large stack of original William O'Neil + Company, Inc. market calls that were dated from 1968 to 1999.I went carefully through each one and charted William O'Neil's buy and sell signals on the market. I saw that O'Neil never missed a bull or bear market. This further confirmed the validity of O'Neil's method in using price/volume of the major indices to time markets, and further underscored the importance of my statistically formalizing price/volume action of the major indices.

Prudent market timing by moving to the sidelines when the market was weak and buying leading stocks in leading industry groups when the market was in an uptrend resulted in a return of 18,241.2 percent, which works out to 110.5 percent on an annualized basis over the seven-year period from January 1996 to December 2002. *The rules I formulated are not my rules nor Wall Street's rules, but rules that are based on how the market actually works and how top stocks actually behave. Let's delve deeper by examining each year up close.



I made only minor headway with my personal account (PA) during the first quarter of 1996 as the market was what we might call "sideways" or mostly trendless. Over the years, I have found such trendless, choppy, and sideways markets to be the most challenging because it is easy to get nickeled and dimed as the market whips you in and out, forcing you to take many small losses that begin to add up over time. While getting nickeled and dimed, one must avoid being drawn and quartered.

In mid-March of 1996, I noticed a few high-quality stocks breaking out such as Iomega Corp. (IOM), shown in Figure 2.1. IOM had a natural monopoly on portable storage in the form of portable hard drives. They were the first company to effectively market the portability of their hard drives and so enjoyed this first-mover advantage in a space that had little competition at the time. At the time of the breakout, IOM had a 700 percent increase in earnings to 16 cents per share in its most recent quarter and a 287 percent increase in sales. In the prior quarter of September 1995, they had shown only 3 cents of profit per share so 16 cents represented a huge acceleration into profitability. Additionally, sales accelerated over the prior 6 quarters from -2 percent, 2 percent, 16 percent, 60 percent, 138 percent,to 287 percent.

IOM's base served as a beautiful launch pad for the stock. I put the usual 25 percent of my trading account into IOM on March 18 as it gapped up to new highs, even though very few stocks were still consolidating due to the sideways action in the general market.

When buying a stock breaking out of a base, you want the base to have strong, constructive and proper characteristics to help ensure that your stock possesses the best chance of a successful breakout. I used to carry around a hard copy of

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FIGURE 2.1 Iomega Corp. (IOM) daily chart, breakout 1996. Chart courtesy of eSignal, Copyright 2010.

the William O'Neil+Company, Inc. Daily graphs©, so that I could mark it up and learn the difference between constructive and defective bases, and I recommend this old-fashioned technique to anyone who wishes to improve his chart reading abilities. General market action was a key variable. For example, in a weak, down-trending market, the strongest stocks would often form the left-hand side of what would eventually become a constructive cup-and-handle or double-bottom base. The strongest stocks act like springs. Once the weight of the market comes off,they spring forward, breaking out of sound bases they had formed during the market correction and doing what they wanted to do all along-go higher.

As more leading stocks broke out of sound bases in April, I began to increase the number of positions I had. I quickly found myself on full margin by mid-April, enjoying the rally from late March into June and sitting in my typical 12 to 18 positions. Incidentally, I've noticed that my trading style in terms of position sizing, number of positions, and risk levels has not changed over the years. It is independent of account size, such that whether I was running a small account in 1996 or running big money for Bill O'Neil in 1999 onwards, I still tend to hold 12 to 18 positions in any uptrending market. I will typically put 15 to 25 percent of my trading account into each stock, then either add to the initial position a second, third, and even a fourth time

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FIGURE 2.2 Iomega Corp. (IOM) daily chart, 1996: the top.Chart courtesy of eSignal, Copyright 2010.

provided the stock sets up logical buy points as it presses higher. Otherwise, I will sell at least half the position if the stock hits my mental sell alert, or will sell to free up capital for new buys in fundamentally strong and potentially faster stocks breaking out of sound bases.

In June 1996, my account peaked at +72 percent, year-to-date, by the time the market topped that summer. Over the next several days, each stock I owned then began to hit my sell alerts, so I sold. With IOM, I used the 10-day moving average to guide my mental sell alert, as Figure 2.2 shows, and thus placed my mental stop slightly under the 10-day. After IOM peaked on May 22, it sliced through the 10-day moving average on big volume on May 28. I put my mental stop 1/16th under the low of that trading day, or 36.31, and so I sold my position the next day as the stock reached my mental sell stop. That said, it could be argued that a climax top occurred in those three up days on high volume at the peak. Back in 1996,I did not understand climax tops well enough to sell into them and found that I preferred to sell on weakness instead of strength as it more suited my trading personality.

Incidentally, I use the 10-day as a sell guide for the fastest names,as they tend to get support around the 10 day as they move higher. For slower stocks, or for stocks that trade with more volatility, I use the50-day moving average as my guide on where to sell. Should the stock penetrate the 50-day, I will then put the stock on standby sell to see whether it should be sold or held. We cover this selling strategy in detail in Chapter 6.

I eventually found myself 100 percent in cash by mid-June. I had no idea the market was going to have a mini-crash but I always stick to my rules. Here is a key but obvious point that ensures that you will not fall in love with your stock and hold it past its prime. Buy based on both fundamentals and technicals, but sell purely on technicals. Technical action should always be the final judge when selling a stock.

The NASDAQ Composite proceeded to drop -19.6 percent from its peak set on June 6, as Figure 2.3 shows. Many of the high-growth stocks I owned suffered far more severe corrections since such stocks tend to be more volatile. But I was protected, because I was in cash.

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FIGURE 2.3 NASDAQ Composite Index daily chart, 1996. The Nasdaq breaks down and trends lower before finding a bottom in July 1996. Chart courtesy of eSignal, Copyright 2010.


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FIGURE 2.4 NASDAQ Composite Index daily chart, 1996. The timing model issues a buy signal on August 1, 1996.Chart courtesy of eSignal, Copyright 2010.


The market continued its correction until it finally found a bottom in July. Shortly thereafter my timing model issued a buy signal on August 1, 1996, as we see in Figure 2.4. I also noticed stronger leading names just starting to break out of sound bases, always a good sign as it signals that a potential new bull phase in the market is emerging. Stronger names are often the first to break out, and when this occurs in synchronicity with a buy signal, it is highly constructive. So, listening to these stocks shouting to be bought, I began to buy in earnest once again.

By December 1996, one of the big buzzes in the market was the impending year 2000 or "Y2K" crisis. Companies that were coming up with solutions to help computer systems to cope with the date change from a"19" prefix to a "20" prefix were garnering interest from investors. It is one thing to buy into a big story on the basis of the buzz alone, but in this case certain "Y2K" stocks like the year 2000 stocks TSR Inc. (TSRI), Zitel Inc.(ZITL), and Accelerate Inc. (ACLY) had been discussed at length on how they could avert potential disaster as the clocks ticked over to January 1,2000. I took notice of these stocks, which were the major players in this subsector as they broke out of proper bases. So I bought. The buys put me over the 100 percent mark in my personal account, and I finished the year up +121.57 percent. All it takes is one or two good homeruns in any given year to make up for all the small losses. As a general rule, following the method of buying fundamentally strong stocks at the right pivot points, then moving to cash when the market is weak puts the odds greatly in your favor so that you will achieve that golden 100 percent return in a given year, provided you are in a bull market environment. If you are in a bearish environment, you still might be able to hit one or two homeruns, which will counteract any small losses.



During the first quarter of 1997, the market was in a downtrend. By April, some portfolio managers with whom I was speaking were ready to throw in the towel for the year as frustration ran high. I had stayed mostly in cash during this period as my timing model had been on a sell signal, and there were almost no stocks worth buying. Then on April 22, my timing model gave a buy signal, shown in Figure 2.5-the first buy signal since early January-and I noticed fundamentally strong stocks in sound bases starting to break out.

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FIGURE 2.5 NASDAQ Composite Index daily chart, 1997.Chart courtesy of eSignal, Copyright 2010.


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FIGURE 2.6 NASDAQ Composite Index daily chart 1997. The Asian Contagion.Chart courtesy of eSignal, Copyright 2010.


I bought the strongest of stocks, then as the rally continued, I would sell the weakest names to make room for any new strong names breaking out. I was effectively force feeding any available buying power into the strongest names. The market continued on its uptrend into October. I then was surprised to see that just over a few days, by October 17, most all of my stocks suddenly hit their sell alerts, just a few days before the market imploded. The massive sell off was caused by the Asian currency crisis,shown in Figure 2.6. I had no idea this crisis was going to occur when it did nor that the market would sell off so hard. But as I had always done before,I sold when my stocks hit their sell alerts. Thus, I was safely in cash a few days before the markets got slammed. My drawdown off the peak was just-6.5 percent compared to the -16.2 percent drawdown in the NASDAQ.

Incidentally, my success-to-failure rate in 1997 was one of the lowest ever, with the number of my losing trades outnumbering my winning trades by roughly 4:1, or a success rate of just over 20 percent. Yet I was able to achieve a triple digit return, just barely (102 percent according to my accounting,98 percent according to KPMG) because the home runs made all the difference. I point this out to illustrate that the number of profitable trades is perhaps the least important variable with this investment methodology. The percent gained on a trade is a far more important variable. That said, in other bull market years, my success rate is usually closer to 50 percent.



While the first quarter of 1998 was highly profitable, the months from July through early October were some of the most challenging. Shortly after the market peaked in mid-July, my stocks hit their sell alerts so I ended up back in cash just several days after the peak. The market then staged a feeble rally in September. Very few high-quality stocks were breaking out of sound bases; thus there was little to buy that month. I remember, however, many investors buying that month eager to assume the rally was continuing. But when October came around, the markets sold off very hard, absolutely demoralizing many investors. Many had year-to-date losses by that point. Figure 2.7 shows the big market bounce on October 8 that led a few days later to my timing model issuing a buy signal on October 14.I also noticed a few high-quality stocks breaking out of sound bases in the ensuing days such as eBay Inc. (EBAY). EBAY was a most interesting IPO.

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FIGURE 2.7 NASDAQ Composite Index daily chart, 1998 lows.Chart courtesy of eSignal, Copyright 2010.

It had one of the best business models and had first-mover advantage in its space much like Yahoo! Inc. (YHOO) for search engines and for online retail. EBAY came public on September 24, but despite its brilliant business model proceeded to lose more than half of its value due to the nasty bear market that caused the NASDAQ to lose -33.1 percent. So even though EBAY had one of the strongest business models, it sold off hard with the rest of the market, thus neatly illustrating why fundamentals are only half the story. No matter how great a stock's fundamentals, a serious bear market will usually drag a stock down.

When my timing model signalled a buy shortly after the market bottomed, it only took a few days for EBAY to hit its buy alert. On October 26,EBAY gapped up out of what I call a U-pattern or what Gil Morales refers to as an "IPO U-Turn" as we see in Figure 2.8. These rare U-patterns can be seen in the strongest of stocks. The stock is so strong that it is not going to wait to form a handle, and the length of the base is often four weeks or less.I bought my first position in EBAY on the gap up, and then bought a second position as the stock bounced off its 10-day moving average. I have found that the strongest stocks often constructively trade around their 10-day moving average, using it as support to rest briefly before continuing their move higher.

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FIGURE 2.8 eBay, Inc. (EBAY), daily chart, 1998. The "IPO U-Turn."  Chart courtesy of eSignal, Copyright 2010.


Meanwhile, many investors had been so demoralized by the brutal bear market that began in July and thus were skeptical as the market bounced in October. I remember some stayed short the market into November as the market rose like a rocket. And as the market continued to rally, it forced those who were reluctant to buy, to either cover their short positions or admit their error and start buying. However, they were late buyers, and so they missed some of the most compelling breakouts. The best stocks are sometimes the first ones to break out shortly after a new uptrend begins as they often offer the best gains. EBAY was an excellent example of this.

The fourth quarter of 1998 turned out to be a highly profitable quarter. As the technology sector led the way higher, stocks that had first-mover advantages in their space often well outperformed their peers, making them true market leaders. I screened for stocks with top fundamentals, which included having great business models and then investigated whether any had a first-mover advantage. I then pruned the list further by investigating each stock in detail. Of the few stocks that made the cut, I put mental buy alerts on each, so that when the stock traded through its buy alert, my software would immediately alert me.

The fourth quarter of 1998 presented what I call a high-class problem. So many great stocks were breaking out of sound bases that buying power quickly became exhausted and it became a challenge to figure out which stock or stocks to sell out of my roughly 14 to 17 positions during this period to make room for potentially faster stocks breaking out. I reduced the weakest positions by half or sold them in full on the basis that their relative strength was not as high and/or their fundamentals were not quite as strong. I was then able to force-feed capital into the strongest names at all times while the market was advancing, which gave me a huge edge. This insured that, being fully on margin, 200 percent of my capital was being deployed strategically.



Part of successful investing is knowing when a fundamental part of the market changes, even though the market may have never behaved this way in the past. In the late 1990s, it was the earnings metric. Some Internet stocks that made huge gains had little to no earnings. While earnings are one of the most important variables I use to gauge the potential of a stock, I realized that sales growth was a useful metric for stocks with no earnings. Understanding the fundamental story behind the stock together with understanding how Wall Street perceived the story behind the stock proved beneficial because it is the institutional money from mutual, hedge, and pension funds that cause a stock to make huge advances. Because of this fundamental change in the market, I learned that markets sometimes change in subtle and not-so-subtle ways. While certain key fundamental and technical variables continue to work cycle after cycle and form the core of my strategy, other variables have a limited life. It is up to investors to follow the markets closely so they can see when new variables can be used to enhance profits as well as when such variables lose their predictive value. Be wary of black box methodologies that claim to be profitable without having to be fine-tuned. They may work for one or two market cycles but must be fine-tuned to keep up with changes in the markets.

In the first quarter of 1999, most of the stocks that triggered buy alerts were technology stocks since the Internet was touching so many aspects of technology. I always do what the stocks and general markets tell me to do, so I was fully margined during the uptrend that led to the April 13 reversal day in the CBOE Internet Index ($INX), shown in Figure 2.9, an index that is a good measure of performance in the Internet space. I noticed many Internet stocks had staged or were staging reversals after making huge gains.Also, the day before, on April 12, some stocks announced they were going to attach ".com" to their name. Some more than doubled in price on the announcement. This extreme buying struck me as some sort of temporary climax top for the Internet group. Then on April 14, before the market opened, I noticed many of the stocks in my portfolio were going to gap slightly down from the prior close they had set the day before. After the first few minutes of trade, they were unable to rally from their lower opening price. Noticing this and taking into account the prior action that led up to this day, I gave my trader a "shopping list" of stocks to sell just several minutes after the market opened. This "shopping list" was 14 out of the16 stocks that I held, thus I was effectively reducing my market exposure from 200 percent down to about 35 percent. The CBOE Internet Index (Figure2.9) proceeded to tank about 20 minutes after I gave my sell orders, taking the stocks down with it that I had finished selling only minutes earlier.The CBOE Internet Index overall finished the day down -9.6 percent.

That day, some of the best-performing stocks were down twice the decline in the CBOE Internet Index. Infospace, Inc. (INSP) in Figure 2.10 gives a sense of just how fast some of these stocks fell. It took just six days for INSP to get sawed in half, as it fell almost 50 percent from peak to trough.

Timing is everything, especially when it comes to handling high octane names. Like dynamite, they must be handled with care, especially if you decide to concentrate your portfolio in one sector. Had I not acted quickly when I saw the warning signs, I would have given back a much larger portion of the profits I had made during the first quarter of 1999. Being able to sell most of my positions within 20 minutes was also key. I had a rule back then by which I would hold no more than 10 percent

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FIGURE 2.9 CBOE Internet Index (INX) daily chart, 1999.Chart courtesy of eSignal, Copyright 2010.


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FIGURE 2.10 Infospace (INSP) daily chart, 1999.Chart courtesy of eSignal, Copyright 2010.


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FIGURE 2.11 NASDAQ Composite Index, 1999.Chart courtesy of eSignal, Copyright 2010.

of the average daily trade in a stock. Today, times have changed, so here in the year 2010,I would put no more than 5 percent of the average daily trade into any one position, and also focus more on the mid-to-larger-cap names that are less subject to noise.

While the first quarter of 1999 was a gift, the second and third quarters of 1999, as shown in Figure 2.11, were the most treacherous I had experienced since 1991, a year that marked the first time I was able to beat the major market averages: 1999 also represented the largest drawdown for my timing model of -15.7 percent and the largest for my personal account of nearly -50 percent. While the KPMG verification shows my drawdown was about -30 percent, my real drawdown was larger at nearly -50 percent because I was intentionally not trading a sizeable portion of the account that was earmarked for taxes. Thus, the base of capital I was trading was substantially smaller than what was actually in my account. This resulted in larger drawdowns than reported by KPMG, but also resulted in larger annualized gains than reported by KPMG. Of course, KPMG follows regular accounting standards, so it had no way of accounting for this.

At any rate, the high level of volatility in a trendless market exhausted many traders. It was not until October that the market resumed its uptrend in earnest. I'm glad to say that periods such as the second and third quarters of 1999 are rare.

That said, it is important to stick with a winning strategy, in good times and bad. I have lived with my strategy since 1991. This gave me the confidence to stick with it even during the treacherous second and third quarters of 1999. I never lost sleep during this period, nor have I ever lost sleep over the market. The key is to always understand why one is making or losing money. My timing model sheds much light on the character of the market. If the model is struggling to make profits, such as it did during the second and third quarters of 1999, it helps me realize that we are in an unusual environment. In this case, the market was both volatile and relatively trendless, the Achilles' heel of trend following. Fortunately, as demonstrated clearly in Michael Covel's book Trend Following, which I highly recommend to any investor, markets tend to trend more often than not; thus highly successful portfolio managers such as Bill Dunn and John Henry can remain successfully in business with exemplary 25+ year long-term track records and continue to thrive to this day. That said, periods of steep drawdowns are part and parcel of trend following. It is critical to stick with the strategy in both good times and bad. As shown by Dunn, Henry, O'Neil, and other successful trend followers, the profits made during the good times more than make up for the losses during difficult, trendless periods.



Celera Genomics (CRA), shown in Figure 2.12, had made a critical announcement about their mapping of the human genome in late 1999, sending biotechnology stocks soaring. The group continued to make huge price advances in early 2000. As with the Internet sector, many of which had no earnings, market perception played an important role in the bio-techs, many of which not only had no earnings but also had no revenues. So, with none of the classic fundamental variables on which to measure the company, I applied to the biotechnology sector what I had learned about market perception with the Internet sector. If market perception was highly positive due to a belief held by institutional funds that the company had huge potential, this could be seen in the price/volume action of the stock, as it was the signature of significant, big money institutional buying. This was key to my making a triple-digit return in 2000 on the long side, a year when the market averages such as the NASDAQ Composite were down nearly -40 percent.

The biotechnology sector topped in late February, shortly before the general market topped. The general market then put in a top on March 10 as shown in Figure 2.13. I was quick to take my account off margin and move into cash as each one of my stocks hit its sell alert in the ensuing days. For

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FIGURE 2.12 Celera Corp (CRA) daily chart, 1999-2000.  Chart courtesy of eSignal, Copyright 2010.


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FIGURE 2.13 NASDAQ Composite Index daily chart, 2000. Chart courtesy of eSignal, Copyright 2010.

the rest of the year, I did some infrequent, light buying, and so I was able to preserve most of the profits I had made that first quarter. It is critical not to overtrade, and perhaps it is often best to do nothing, and just sit in cash when the market is not acting right. That said, overtrading is one of the most difficult issues to overcome even for the most seasoned investors.The market will tempt the trader to jump back in by making things look almost right. And most traders would rather remain active than dormant. But it is often best just to sit and do nothing if the market is not acting just right. In my experience, I have observed that this is easier said than done.

Here is another argument for staying on the sidelines if the market is not acting just right. If one only trades 10 optimal buy situations in a given year, and makes an average of 10 percent on each trade, one's entire account would be up 159 percent in that year if one invested one's whole account each time such an optimal buy point arose. In practice, due to risk management reasons, even if one invested 25 percent of one's account in each trade, one's whole account would still be up about 40 percent for the year. Of course, ample experience is required to know that the odds are greatly on your side, and that there are no guarantees. However, if we take the period of 2006-2009 as one example, the latter part of 2006 and 2007 were just right for buying, and big money could be made during such windows of opportunity. Then in early September 2009, GLD had a perfect set up and gold stocks could be bought, as they correlate highly with GLD.Of course, there were other picture-perfect plays during these years, giving one further opportunity to do well. I am not saying this in hindsight but am basing this on my actual profits during these picture-perfect, albeit brief,periods. My mistake was overtrading during the less optimal periods.

Incidentally, I noticed that O'Neil does little when the market is not acting right. You can make a fortune just by being long the right stocks at the right times when the window of opportunity is open. My market direction model is almost always on a buy signal during such times, and, if not, it has always switched to a buy signal within days after the first few leading stocks break out of sound bases. You can further enhance your performance by learning short selling techniques, which are discussed in Chapter 6.



In February, I pyramided a short position in the Powershares QQQ Trust(QQQQ). I remember as profits were building, I started calling this my "Modena trade." A Ferrari Modena back then was the hottest new model and cost about $250,000 with the mark-up. Thus, a profit of $500,000 on a trade would pay for the car, after federal, state, and miscellaneous taxes were paid. I finished the trade at a profit of over $600,000, but I never bought the car. I learned that even though I had always wanted to own a Ferrari, I did not buy it because it was not the act of possessing the car that was important. Psychologically, it was the idea that I could easily possess it. So buying it became unnecessary. It brought me greater pleasure to keep the capital on hand to invest in the markets. As I learned from O'Neil in the years I worked with him, one should never make the market pay for one's luxuries.

Then in March, I re-shorted my QQQQ position. I pyramided the position as before, and profits eventually amounted to over $1,000,000. The problem was that greed got the best of me and I thought the market was going to crack wide open, and my profit of over $1,000,000 would turn into $2,000,000 or more in the event of a market crash. I was heavily leveraged on the short side and failed to consider the more likely outcome that the market could bounce big after having sold off so hard. On April 5, the market gapped up fiercely and rallied the rest of the day (Figure 2.14). I finally closed my position at the end of the day. I lost just over a cool million in one day. My profits on the trade shrunk from over $1,000,000 to about $100,000.  Gil Morales came into my office, shook my hand, and told me "that's one hell of a ride," and that he had enjoyed the

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FIGURE 2.14 NASDAQ Composite Index daily chart, 2001. The "Modena Trade"goes awry! Chart courtesy of eSignal, Copyright 2010.

vicarious thrill by watching me make the trade. I then recalled the Victor Sperandeo interview in Jack Schwager's book, "Market Wizards," where he talks about going into a bar and telling the bartender, "I just made $100,000 today. I really need a drink."So the bartender asks, "Why the down face? Shouldn't you be celebrating?" Sperandeo replied, "The problem is, I was up $800,000 earlier today."

The rest of 2001 was uneventful with just a few losing trades. The window of opportunity was clearly shut, so I stayed mostly on the sidelines as my timing model was usually either on a sell or a neutral signal.



The year 2002 was also uneventful, and I stayed mostly in cash. I remember many funds closing their doors. While 2001 was a massacre, 2002 was equally brutal. Few were left standing. Once the NASDAQ Composite was off more than 70 percent, the market seemed to be excessively oversold. So I decided to take a small position in the QQQQs for a long-term play. I reasoned that the market could go lower but historically, had always resumed a strong rally after being so oversold. This was true after the panic of 1907, after the Great Depression when the market lost almost 90 percent of its value, and after other serious market setbacks dating back to the nineteenth century.

So 2002 was profitable by a hair due to this one trade, which reversed my small losses. My losses had been small because I remained mostly on the sidelines, safely in cash. That said, I would have been nicely profitable had I shorted indices on any sell signals issued by my timing model. This was also true in other years. Thus, this bias I had toward staying in cash during bear markets was replaced starting in 2009 with the action of shorting major indices on sell signals; 2008 was a wake-up call to start shorting the major indices as 2008 was a good year for my timing model, as shown in Figure 2.15, due to the collapse in the general markets. The return of +31.1 percent is good, but under the model's long-term average annualized returns of +33.1 percent. But when accounting for optimization of the follow-through day threshold, which I discuss in Chapter 7, the return increases to 38.8 percent for 2008. I prefer to err on the side of absolute caution, so I show the "worst-case" situation of +31.1 percent.

Note, the timing model's back-tested historical average of +33.1 percent/year from 1974 to 2006 was achieved by going 100 percent long the NASDAQ Composite on a buy signal (B), 100 percent short the NASDAQ Composite on a

figure 2-15

FIGURE 2.15 NASDAQ Composite Index daily chart, 2008. The "Slow MotionCrash" of late 2008. Chart courtesy of eSignal, Copyright 2010.

sell signal (S), and 100 percent cash on a neutral signal(N). In working with my model in real time since 1991, the returns in my personal and institutional accounts were larger because I was buying individual stocks during periods when my model was on a buy signal.

The toughest year for my model was 2007, as it was one of the only two years when the model was down in its entire 36-year run. Its negative return of 10.9 percent was due to a large number of false price/volume signals. That year, distribution day clusters often did not lead to a falling market, as the market continued to grind higher. This may have been due to the many one-time confluences of cross-currents including the end of the housing bubble, the early stages of a breakdown of financials as seen in the XLF index, and the beginning of the recession. Fortunately, years such as 2007 are extremely rare. On balance, my timing model continues to keep me on the right side of the market cycle after cycle. For historical interest, Figure 2.16 shows my timing model in action during the crash of 1987 and its aftermath.

In the current decade, the compressed, sideways markets observed from January 2004 to August 2006 brought new trading challenges, as shown in Figure 2.17, and my market direction model's returns, while still ahead of the major averages, have been under its historical returns of +33.1 percent/year.

figure 2-16

FIGURE 2.16 The timing model during the 1987 market crash. Chart courtesy of eSignal, Copyright 2010.


figure 2-17

FIGURE 2.17 S&P 500 weekly chart. Three years of difficulty.Chart courtesy of eSignal, Copyright 2010.


But whatever doesn't kill you makes you stronger. In late 2005, I came up with a major refinement to my strategy, which enabled me to make my initial buy in a stock's base just before it broke out, a method I call buying "in the pocket," which will be discussed in detail in Chapter 6. Not only does this refinement work today but also worked beautifully in prior 1970s, 1980s, and 1990s markets. Those of you who subscribe to the Gilmo Report will note that we have discussed them in some detail in prior reports ,which can be found at This technique will improve your investment performance should the market encounter choppy, sideways action that grinds higher, such as during much of 2004-2007 or during windows of opportunity such as the brief uptrends of September to November 2006 and September to October 2007.

Looking back, as the saying goes, if I only had known in the 1990s what I know now, my returns would have been higher. We are all students of the market, always learning, always optimizing, and hopefully always evolving. It certainly keeps the journey alive and well.

By Dr. Chris Kacher and Gil Morales


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