back start next


[start] [1] [2] [3] [4] [5] [6] [7] [8] [ 9 ] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72]


9

1. October 9 high-364.50

2. Immediately preceding sell-off low-349.85; the probable reward point.

3. Potential support on the way down; resistance on the way back up.

4. August 27 high-359.85; the level to watch for a break.

5. Support established in the sell-off prior to August 27; a potentially good place to set stops when prices broke through it.

6. Another tangible support point.

7. The likely reward point if trading October 13 through the 16th. Once prices broke through this level, it would become a good place to set stops.

PURSUIT OF SUPERIOR RETURNS

As profits accrue, I apply the same reasoning but take the process a step further to the pursuit of superior retums. If, and only if, a level of profits exists to justify aggressive risk, then I will take on a higher risk to produce greater percentage retums on capital. This does not mean that I change my risVreward criteria; it means that I increase the size of my positions.

A good example occurred in July and August 1974 when I was mnning the inventory at Ragnar Options Corporation. Our fiscal year ended in June, and I began every fiscal year with $250,000 of risk capital allotted for trading. In July, I made about $104,000, bringing me to over a 40% retum for the quarter. I was a strong bear at the time, so I decided to take half of my profits and go short big the next month. No puts were traded on the (Chicago Board of Exchange) back then, so I went short by taking a position in what is called synthetic puts. Risking about $50,000,1 shorted 3500 shares each of Texas Instmments, Kodak, McDonalds, and IBM and bought 35 calls of each. In net effect, the only money at risk was what I paid for the calls; each 100 shares of stock sold short was perfectly hedged with a call-thus, a synthetic put.

I took the position when the Dow Industrials average broke 750-the previous low established in July-and the market began to sell off as I expected. Then on August 8, Nixon resigned and the market crashed, accelerating the down move. I closed out the month up over $269,000 in my acc ount, more than doubling the initial capital for the fiscal year in a single month. That is what I mean by aggressive risk taking; the odds are in my favor, but I put more money on the line. Even if I had been totally wrong, I would have lost only about half of my previous profits, with plenty of money left to take lower risk positions.

CONCLUSION

Preservation of capital, consistent profitability, and the pursuit of superior retums are three simple principles that, if properly understood, will guide you toward making profits in the markets. But to put these ideas into practice, much more informatio n is needed. The best starting point is to understand the nature of market movements. And I know of no better way to discuss these ideas than to introduce a body of knowledge that I consider indispensable if one is to tmly understand market behavior: Dow Theory.



There is a new theory in science-the theory of chaos-that postulates that certain types of natural activity are chaotic and unpredictable except in terms of probabilities. For example, doctors can monitor and chart a heartbeat on highly sensitive equipment, but given certain conditions, a heart will go into random fibrillation (random chaotic beating that can be deadly) during which the heartbeat cannot be predicted or modeled mathematically. This kind of chaos is life -threatening, but ironically, researchers have found that the brain waves of a healthy mind in a state of intense concentration are chaotic, whereas those of an epileptic during seizure or a drug addict on a "high" are regular and predictable.

Weather forecasting is another area where many scientists think that chaos theory applies. The unpredictability of weather comes from what is called sensith-itv to initial conditions. Mathematical models fail in weather forecasting because the slightest divergence between simulated and actual conditions multiplies in a complex chain of cause and effect relationships, giving rise to resul ts in the model totally different than in nature. The best, chaos theory says, that meteorologists can ever do is forecast the weather within the limits of probability.

If this seems like a hopeless and futile theory, it is only because I dont do it justice. By studying what gives rise to chaotic behavior, scientists believe they will find the means to prevent it in some instances and to induce it in others. The potential applications are unlimited: medical, biochemical, psychiatric, meteorological, computer, and many more. So, while admitting that certain events in nature dont follow a perfect mathematical and predictable order, chaos theory says that they can still be understood and in some cases predicted and controlled.

So it is with the financial markets. People are not machines ordered and structured by mathematics; they are beings of choice. And people are the markers.

Literally millions of market decisions are made each day, and the results of each one has its effect on price movements. The idea that such a complex set of components, which includes free will, can be modeled and predicted with mathematical exactness is laughable. You can never predict with abso lute certainty how the collection of individuals that make up the markets will react to events nor what new conditions will arise. But there is order to the chaos, and it is the speculators job to find it.

Market forecasting is a matter of probabilities; the risk of being wrong is always present. The best you can do is minimize risk by maximizing knowledgeby understanding the original conditions that give rise to probable future events. That way, it is possible to keep the odds in your favor and to be righ t more often than not in making market decisions. The first step in obtaining this knowledge is to find a way to monitor the pulse of market behavior.

Dow Theory, if properly understood, is like the physicians highly sensitive heart monitor or the weather forecasters barometer; it is one tool to be used as an aid in forecasting future events within the bounds of probability. It wont tell you the causes of change, but it will indicate the symptoms that lead to change. It wont tell you exactly what is going to happen, but it will give you a general overview of what is likely to happen. As William Peter Hamilton put it, "Dow theory is a commonsense method of drawing useful inferences as to future market movements from the recorded daily price fluctuations of the ... [market] averages."

Properly .considered, Dow Theory provides the key starting point with which to analyze stock market behavior. Many of its definitions and principles apply not only to the stock market but to all financial markets as well.

GOOD IDEAS OFTEN MISUNDERSTOOD

The body of ideas known as Dow Theory is a composite of the work of Charles Dow, William Peter Hamilton, and Robert Rhea. Charles Dow was the founder of Dow Jones & Company and -founder

Finding Order i n Market Chaos: An Introduction to Dow Theory



and editor of the Wall Street Joumal until his death in 1902. He originated the idea of an index of stock averages with the Dow Jones Industrial average in 1895. In 1897, he created an average index for railroad stocks on the premise that the industrial and rails indexes would be indicators for the two basic economic sectors, production and distribution.

Dow intended the indexes to be an indicator of business activity and never himself employed them to forecast stock price movements. Although he had only five years of data to work with unti 1 his death, his observations were nevertheless remarkable in both scope and accuracy.

Dow himself never organized and formalized his ideas into a theory of economic forecasting, but a friend of his named A. J. Nelson attempted such a formalization in The ABC of Stock Speculation, published in 1902. It was Nelson who dubbed Dows methods Dow Theory.

William Peter Hamilton, who worked under Dow, was the most articulate Dow Theory advocate of his day. After Dows death in 1902, Hamilton continued to expound upon and refine Dows ideas primarily through editorials in the Wall Street Joumal from 1903 until his death in 1929. In addition, he wrote a book called The Stock Market Barometer in 1922 in which he gave Dow Theory a somewhat more detailed and formal structure beyond the scope of what was permissible in an editorial format.

Robert Rhea, forced through injury to work from his bed from 1922 until his death in 1939, was an admirer of both Hamilton and Dow and profited handsomely by applying their principles to stock price forecasting. Through detailed study, Rhea better defined the principles and methodology of the theory and developed the first set of publicly available charts of the daily closings of the Dow Jones Industrial and Railroad averages with volume included.

Among the many contributions Rhea made to the theory were his observations characterizing volume relationships as a further indication of the future of price movements. In addition, although he didnt coin the name, he discovered the concept of relative strength, which will be discussed in Chapter 8. His book. The Dots, Theory, published by Barrons in 1932 and now out of print, synopsizes Hamil -tons work and provides an excellent reference for understanding the principles of Dow Theory. In a later book, Dow Theory Applied to Business and Banking, Rhea demonstrated the consistency with which Dow Theory accurately predicted the future course of business activity.

In all his writings, Rhea emphasized that Dow Theory was designed as an aid or tool to enhance the speculators or investors knowledge, not as an all encompassing, rigorous, technical theory that could be divorced from knowledge of fundamental market and economic conditions. Dow Theory is, by definition, a technical theory; that is, it is a method of forecasting which relies on the study of pattems of price movements to infer future price behavior. In this sense, it is the father of modem technical analysis.

After Rheas death, Dow Theory fell into less competent hands. Men who failed to grasp the essential principles of the theory misapplied and misinterpreted it, to the point that it is now generally considered dated and of little use as a technical tool in the modem markets. This is simply not t me. I performed a study applying Dow Theorys principles to the Industrial and Railroad (later Transportation) averages from 1896 to 1985 and found that Dow Theory tactics accurately captured an average of 74.5% of business expansion price movements and 62% of recession price declines from confirmation date to market peaks or bottoms, respectively.

In addition, the study shows that, except for periods of World War, the stock market accurately predicted changes in the business trend with a median lead time of six months and anticipated the peaks and troughs of business cycles with a median lead time of one month. The average theoretical rate of retum attained by buying and selling the Industrial and Transportation indexes according to a strict interpretation of Dow Theory from 1949 to 1985 is a 20.1 % uncompounded average annual retum. 1 To this it should be added that Dow Theory would have had an investor short through the 1987 crash (as I was). No other forecasting method can boast such a consistent and e nduring record of success. Dow Theory therefore warrants significant investigation by any serious speculator or investor.

THE "HYPOTHESES" OE DOW THEORY

In his book. The Dow Theory, Rhea listed what he called the "hypotheses" and "theorems" of Dow Theory. Actually, they should be termed principles and definitions, because Dow Theory isnt a strict system like mathematics or the physical sciences. That aside, since so many interpretations of Dow Theory are wrong. Im going to go right to the source. Ill present Rheas observations in the order he



[start] [1] [2] [3] [4] [5] [6] [7] [8] [ 9 ] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] [36] [37] [38] [39] [40] [41] [42] [43] [44] [45] [46] [47] [48] [49] [50] [51] [52] [53] [54] [55] [56] [57] [58] [59] [60] [61] [62] [63] [64] [65] [66] [67] [68] [69] [70] [71] [72]