Popular Theories of Technical Analysis

There are certain important theories of technical analysis that are helpful in conducting technical analysis of the market. These include

1. Dow Theory
2. Fibonacci Numbers
3. Kondratev Wave Theory
4. Chaos Theory
5. Neural Networks

Technical Analysis Theories

1. Dow Theory

One of the founders of Dow Jones & Co. was Charles Dow. He is also sometimes considered as the inventor of point & figure chart. According to Dow Theory, movement of stock prices includes three components. The most important one is the primary trend which represents the long term direction of the market. This primary trend indicates the terms bull & bear. The temporary reversal in the primary trend is referred to as secondary trend. The secondary trend does not continue for a long term and due to this reason it cannot become primary trend. The third component includes daily fluctuations in the prices of stock which does not contain any useful information and are meaningless.

Ocean analogy is mostly used as an illustration for the Dow Theory. The tide in the ocean is either coming in or going out which reflect the primary trend. When there tide going out, the waves still wash ashore which is representation of secondary trend. In certain situation ripples are produced from the waves that reach the sand with no apparent reason and soak the things on the sand. 

The price movements of Dow Jones Industrial Average provide the basis for Dow Theory. Dow Jones Transportation Average confirms the changes in the primary trend of the DJIA. The logic is that the products are manufactured by industrial companies & shipped by transportation companies. The economy is in good shape when both averages are advancing. The technical points of this famous market technique are better explained in the books in most public libraries.

The Dow Theory was not much developed by the Charles Dow. It is suggested by the Wall Street Journal that distortion & selective editing of ideas of Mr. Dow provides the basis for the entire field of the technical analysis. It is argued by another financial historian that Dow Theory only explains the statistical nature of trends from the averages. Also the Dow did not suggest the prediction of price through interpretation of charts.

2. Fibonacci Numbers

For hundreds of years Fibonacci Numbers have intrigued mathematics and scientists. Fibonacci Numbers were discovered by medieval mathematician named Leonard Fibonacci (1170-1240) from the study of the reproductive behavior of rabbits. The Fibonacci series is given below from its beginning.

1, 1, 2, 3, 5, 8, 5, 13, 21, 34, 55, 89, 144, 233 . . . . . . . .

After the first two numbers of 1, the sum of the two adjacent numbers provides the next following number.

The frequency with which the Fibonacci Numbers appear in the environment is significant. Around the center of plant, sunflowers have seeds spirals. Some spirals have seeds with counterclockwise tendency along with other spirals that have different arrangements. Most of sunflowers contain adjacent Fibonacci Numbers of the numbers of counterclockwise spirals and number of clockwise spirals. There might are 34 counterclockwise spirals and 55 clockwise spirals in a blossom. Fibonacci Numbers are revealed in the number of chambers in nautilus seashell, the structure of pine cones, the ancestry of bees and the topology spiraling galaxies. The study of this series of numbers is explained in a separate professional journal called the Fibonacci quarterly.

The number 1.618 is generally used by the technical analysts who follow Fibonacci Numbers. The number appears in ancient writings & architecture and is called golden mean. In the series, every Fibonacci number, after the first ten numbers, divided by its immediate predecessor equals 1.618. For example 144/89 = 1.618, 233/144 = 1.618 and so on. Fibonacci ratios are calculated with this magic number.

The retrenchment levels of previous move are computed by the use of first two ratios, 0.382 and 0.618, by many Fibonacci advocates in the investment business. For example a 30% decline in the stock price from $50 to $35 will encounter resistance to further advances after stock price rises to $40.7 (or after regaining of 38.2% of its loss).

Close tab is kept by some technical analysts on support & resistance levels as forecasted by the Fibonacci ratios. It is cleared to those people also who are not in involved in making investments in stocks that unusual things can occur when stock prices approach significant Fibonacci Numbers.

3. Kondratev Wave Theory

Nikolay Kondratev was born in 1892 and he was a Russian economist & statistician. The first soviet five year plan was made with his assistance. He was Director of the study of business activity from 1920 to 1928 at the Timiriazev Agriculture Academy. He studied the Western capitalist economies during his service at agriculture academy. He pointed out the long term business cycles with duration of 50 to 60 years in the economies of Great Britain and United States. After the US crash of 1870, he became well known. He proposed the long term business cycle of 50 to 60 years hypothesis which is referred to as Kondratev Wave Theory.

Kondratev theory is obvious from the real example of crash of 1987, which happened after 58 years from the crash of 1929. Some modern economists have consider that important macroeconomic changes make the business cycle less predictable like floating exchange rates, the reduction of barriers to free trade, the elimination of gold standard etc. In spite of this modern view, there are many market analysts who access the stock market & its risks with the help of Kondratev Wave Theory.

4. Chaos Theory

One of important theories of technical analysis is chaos theory. Few researchers have provided material on Chaos Theory and its application to the stock market at recent finance conferences. Chaos Theory is an emerging field of study in Physics in which apparently random behavior in instances is quite systematic or even deterministic. Scientists apply this theory to population growth estimates, prediction of weather and fisheries biology.

For example if there is a given volume of ocean water where no human interferes. The population of different species living there will not surely reach an equilibrium population. The growing fishes greatly eat the little fishes or other smaller species. Less number of young fishes grows and the older ones will die naturally which result in the sudden severe reduction in the population of fishes. This created excitement in local media and dismay the fisherman. At the same time the predation & food competition is reduced in the surviving fishes which further result in the dramatic growth in the population and the cycle continues. The process becomes more complex by the interaction between species.

Patterns in the behavior of the stock market are sought out by the investment analysts since the origin of the exchanges. Some of patterns are effectively explained by the Chaos Theory while some patterns remain unknown. Much of this theory needs revision if apparent randomness of the change in the stock price can be shown to be non-random.

5. Neural Networks

A trading system in which anticipating model is trained to ascertain a desired output from the past trading data is referred to as neural network. The neural network eventually learns the pattern that generates the required output by repeatedly cycling through the data. When the pattern of the desired output is not found, additional data is put until a pattern is formed. There is also a feedback mechanism in the neural network by which the network gains experience from the past errors.

In the investment community, this topic is quite hot. Many articles have been published on this topic and National Conferences are held that considered only this topic. It is fact that stock market is rarely deterministic which cause the problem for concept of neural network. There is constant change in the situations and many previously true facts are now seem to be false in current period. Financial academics are particularly suspicious about the research that verifies a hypothesis using past data. The analysis of the data provides apparent cause & effect between stock market performance & past data. That research is much more useful which uses a subsequent data to test a hypothesis. The Wall Street’s response to this criticism is described in an article in popular press.

Building of genetic algorithm into neural network is way to get from this hazard. A sexiest term is employed in the neural network that makes the scientists of the Wall Street to surprise that neural nets are adapted to the future by the use of genetic algorithms. The schools of baby newts are spawning and each one is allowed to swim against the altering flow of data and the role of mother among them is taken by the one which is the fittest survival.

The investment analysts need effective mousetrap that enables them to make good investments in the stock market. Whatever theory they are considering it is useful for them to ascertain modifications in their security selection methodology because none of the above theories are perfect in making profitable investment every time.