An Introduction to Technical Analysis

1. General Overview

Portfolio Management is the process of choosing investments that are suitable for an account, bearing in mind an identified objective for the account but operating within defined risk parameters. A Portfolio manager should design a portfolio that will achieve the desired rate of return while keeping the risk within an acceptable level. There are two main types of methods used to analyse and predict the performance of stock. These types fall into two categories: Fundamental Analysis and Technical Analysis. In this paper we will focus solely on Technical Analysis.

Technical Analysis is the forecasting of future stock movements by using numerical series generated by market activity to look for peaks, bottoms, trends, patterns and other factors affecting a stock's price movement in order to make buy/sell/HOLD decisions. It can be applied to stocks, indices, commodities, futures or any tradable instrument for which price is influenced by the forces of supply and demand. In this case, the prices refer to combinations of the open, high, low or close for a given security in a specific time frame.

Technical Analysis does not result in absolute predictions about the future, but it can help investors anticipate what is "likely" to happen to prices over time. It is primarily, though not solely conducted by studying charts that show the price movement of a stock over time. There are hundreds of different patterns and indicators used by investors, this paper will close up on some of them.

example of bar chart

Technical analysis does not mean to analyse the reasons why there has been a price movement in a certain stock. Instead, it focuses in whether it has moved in a particular direction and tries to find a chart pattern that can be useful for forecasting. Followers of this method believe that you can take advantage of the market and make profit by what they call “trend following”, meaning that if the price rises, they expect it to continue rising and vice versa.

Once a trend is identified, it is believed that it will continue until something happens to change the trend, and until this change occurs, price levels are predictable.

3. Basis of Technical Analysis[1]
The Dow Theory, which is a theory based on the writings of the co-founder and editor of Dow Jones, Charles Dow, laid the foundations of what later became modern technical analysis.

Ralph Nelson Elliott based his studies on the Dow Theory and in the late 1920s came up with The Elliott Wave principle. He discovered that stock markets do not behave in a chaotic manner, but that markets move in repetitive cycles, which reflect the actions and emotions of humans caused by exterior influences or mass psychology. The patterns that Elliott discovered are built in the same way. An impulsive wave, which goes with the main trend, always shows five waves in its pattern. On a smaller scale, within each of the impulsive waves of the before mentioned impulse, again five waves will be found. In this smaller pattern, the same pattern repeats itself ad infinitum.

Example of an impulsive wave in an uptrend

Source: “Elliott Wave Theory”, Prognosis software development, p. 5

Studying the patterns is very important in order to apply the Elliott Wave Principle correctly. The pattern of the market action, if correctly determined, not only tells an investor to what price levels the market will rise or decline, but also in which way (or pattern) this will happen. When an investor is able to recognize the patterns, and apply these patterns correctly, he can trade the Elliott Wave Principle. However this is not easy to accomplish due to the fact that the theory itself is very complicated as it consists of many patterns, which incorporate Fibonacci ratios. That is also a reason why explaining it in detail cannot become a part of this essay.

In the 70s, the Wave Principle gained popularity through the work of Frost and Prechter. At present there can be found a lot of software on the market which uses different engines to perform wave count according to Elliott Wave Theory, or a neo/modern version of it.

Obviously the Elliott Wave Principle can get very complex – especially in corrective waves – since the person applying it will have to look for patterns, which contain patterns, which contain patterns etc. etc. The problem is that sometimes several alternative counts can be found pointing not in the same direction. That is why the key to forecasting markets with Elliott Wave Theory lies in determining the probabilities of alternative scenarios, assessing their probabilities by studying their compliance with the permitted internal wave structure, and supporting the analysis with other indicators.

4. Trading the Elliott Wave (example)
An investor willing to use Elliott Wave Theory should first of all determine which patterns and alternative wave counts give the best trading opportunities, such as when several alternatives all produce a price movement in the same direction. Afterwards we should determine objective entry points based on patterns (a point at which we are sure the pattern is valid) as well as objective exit points, also based on patterns. You should for example exit a trade when a price movement makes your preferred wave count invalid or when a price movement reaches its target.

Suppose the market has experienced a big sell off. From the low it starts to rise. Wave 1 (or A) and waves 2 (or B) have been completed and the market starts to rise again. The first picture shows two scenarios possible, either an impulse (1,2,3) or an A, B, C correction.

Forming of a pattern

Source: “Elliott Wave Theory”, Prognosis software development, p.39

The pattern can be an impulse only if the 4th wave does not overlap the first, a level indicated by the horizontal “stop” line. If it does we might be dealing with a correction. This correction will be confirmed when the price drops under the origin of wave C, which is the end of wave B. Provided it doesn’t drop under the “confirmation” line, it cannot be assumed that the market will go down.

Scenario number one Scenario number two

Source: “Elliott Wave Theory”, Prognosis software development, p.39

In the first scenario we might want the pattern to confirm itself therefore we might want to wait for the price to come near the stop line and enter the trade, which is quite hazardous, as it would require exiting it with a loss when it turns out that we are in a correction. We could also wait for the trend to turn. However, we then lose part of the move, which is part of the profit. The best way to deal with this problem is to combine the wave count with other indicators.

When analysing the second scenario it becomes obvious at a certain point in time that we are dealing with a downtrend. That situation would require from us to wait for the confirmation and during that time we lose part of the profit just as in the situation described above.

After entering the trade we will know the exit point (stop line) and the take profit point, meaning that we know how much we can lose (risk, amount of money lost by the time we can clearly state that we were on the wrong side of the market) and how much we can gain (return, amount of money that we receive when the prices hit the take-profit level). That makes exactly this type of analysis very useful in portfolio management, as we receive a tool that is able to objectively measure risk/return ratio on the basis of which we can evaluate our next move. After each trading day we can perform an update of our positions not only on a guess basis, but taking into account the before mentioned risk/return ratio and the changes in prices. What is more, advanced forms of Fibonacci ratios enable us to calculate time clusters, meaning that we can expect how long will it take for a pattern to form and when can we expect a given trend to come to an end. We should not, however, rely on risk that is small. It means in practice, that we might be easily wiped of the market in a short term opposite movement, as our stop will be close to the entry point. Also, a small number in the nominator would dilute the risk/reward ratio.

5. Indicators[2]
In general, an indicator is a result of mathematical calculation (formula), based on prices and/or volume. The received figures are important because they act as an alert to study price action a little more closely. Furthermore, they can be used to confirm other technical analysis tools and finally, indicators can be used to predict the direction of future prices. Unfortunately there are hundreds of indicators. Which should we choose then? If we have a closer look at the indicators, it could be said that they can be divided into two main categories; moving averages and oscillators. These two measurements can be used in several ways as they might be: presenting strength of a trend, support and resistance levels; divergences that occur between indicators and price, suggesting a possible future trend reversal; confirming trend reversals.

Moving averages are one of the oldest and most popular technical analysis tools. A moving average is the average price of a security at a given time. When calculating a moving average, you specify the time span to calculate the average price (e.g., 25 days). If the security's price is above its moving average, it means that investor's current expectations (i.e., the current price) are higher than their average expectations over the last 25 days, and that investors are becoming increasingly bullish on the security. Conversely, if today's price is below its moving average, it shows that current expectations are below average expectations over the last 25 days.

The classic interpretation of a moving average is to use it to observe changes in prices. Investors typically buy when a security's price rises above its moving average and sell when the price falls below its moving average. However the disadvantage is that you will always buy and sell late. If the trend doesn't last for a significant period of time, typically twice the length of the moving average, you'll lose money. That is why MACD gained more importance.

The MACD ("Moving Average Convergence/Divergence") is a trend following momentum indicator that shows the relationship between two moving averages of prices. The MACD is the difference between a 26-day and 12-day exponential moving average. A 9-day exponential moving average, called the "signal" (or "trigger") line, is plotted on top of the MACD to show buy/sell opportunities. The basic MACD trading rule is to sell when the MACD falls below its signal line. Similarly, a buy signal occurs when the MACD rises above its signal line. It is also popular to buy/sell when the MACD goes above/below zero. The MACD is also useful as an overbought/oversold indicator. When the shorter moving average pulls away dramatically from the longer moving average (i.e., the MACD rises), it is likely that the security price is overextending and will soon return to more realistic levels. On the other hand, however, when shorter moving averages reaches high levels we can be almost sure that the prices, after declining slightly, shall almost come back to their previous levels in order to establish a divergence. This is a strong indication that an end to the current trend may be near. A bearish divergence occurs when the MACD is making new lows while prices fail to reach new lows. A bullish divergence occurs when the MACD is making new highs while prices fail to reach new highs.

Another indicator that offers a wide range of trading signals is RSI, which is a price-following oscillator that ranges between 0 and 100. A popular method of analyzing the RSI is to look for a divergence in which the security is making a new high, but the RSI is failing to surpass its previous high. This divergence is an indication of an impending reversal. When the RSI then turns down and falls below its most recent trough, it is said to have completed a "failure swing." The failure swing is considered a confirmation of the impending reversal. Apart from that the RSI usually tops above 70 and bottoms below 30. It usually forms these tops and bottoms before the underlying price chart. It often forms chart patterns such as head and shoulders or triangles that may or may not be visible on the price chart. The same applies for support and resistance levels, Gann fans.

The Guru Index

In the portfolio management sense Gurus are people who write for newsletters and publications on matters of business and the economy. The Guru Index is a measure of their levels of optimism (expecting a bull run) or pessimism (expecting a bear run). This is then noted as a percentage of bullish / bearish sentiment.

Below a table details the ratio and frequencies of bearish sentiment in the market and the performance of the Dow Industrial Index 6 months later.

The data seems to confirm the logic of the Rule of Contrary Opinion, a belief that there are gains to go against popular opinion, as often people work each other into frenzy when there is nothing quantifiable to back up such enthusiasm. This is because the data shows that experts’ strong opinions tend to correlate inversely with stock market movements. For example, high bullish opinions of experts normally correlate with a decrease in the marketplace, and high bearish opinion correlates with a large increase in the marketplace.

The Rydex Ratios
Among the Rydex Mutual portfolio of funds there exists the Rydex Nova Fund and the Rydex Ursa Fund. The Nova Fund is leveraged to cover 150% of the S&P 500 market, i.e. earn larger or smaller losses than possible with simple investing. On the other hand, the Ursa Fund works in the opposite way, being an inverse to the markets movements.

The amount invested for each of these funds is then measured and turned into a ratio, with the bearish Ursa fund being divided in value by the bullish Nova funds value for a ratio.

The diagram below highlights a strong correlation, with similar movements in the data to the movements of the Ursa / Nova indexes.

Similarly, the theory of Contrary Opinion highlights how extremes in opinion, such as Ursa : Nova ratios being higher than 3 preceding an increase in the S & P, or a ratio below 0.3 signalling a decrease in the S & P 500. However. These funds are recent and as a result there has not been enough data to fully substantiate how useful an indicator the Rydex Ratio is.

Even if we are happy with the above mentioned indicators, or with any other taken from a long list of trading tools there is always a way to make it even better. All of this can be accomplished with neural networks. We can take a number of different length RSI oscillators, pass them to the neural network, and ask it to use those inputs to improve our original RSI oscillator. In that way we would receive trading signals at least 2-3 days earlier, which is a big advantage. What is more we can combine several indicators when performing the calculations, which can also give us interesting results in a form of an indicator that incorporates several others and performs in a completely new way.

6. Trading strategy

All in all technical analysis is a broad area of study, offering many trading methods. That is why some of them will always be contrary towards each other, giving opposite signals. Therefore each investor should establish his trading strategy. In order to stay on the right side of the market we should follow the Elliott Wave Theory, which may be supported by moving averages. That will enable us to “trade with the trend”, manage our portfolio most efficiently with risk/return ratio. However for timing the trade we should take into account other indicators, most preferably few of them, augmented by neural networks. They would be helpful in entering and exiting a trade in the most proper moment.

Conclusion

Technical analysis is the attempt to understand the seemingly random stock market and enable investors to make better informed decisions about how to speculate their money effectively. However, it has to be remembered that there will never be a golden rule to understanding the stock market. Tools such as the Elliot wave, although highly useful at forming a more quantifiable approach to investing have their limitations. Like all models, the Elliot wave is built upon certain inferences and assumptions. Sometimes models put too much or too little emphasis on particular information. Often tools become less useful over time, as the factors explaining the tool’s reliability become outdated and less important to business and the economy. Unfortunately, it (just as every other form of analysis) has its limitations, as the stock markets movements are too complex for one set of guidelines.

This does not mean that they should never be used but merely employed in moderation. The use of a carefully chosen group of technical tools to complement your knowledge is a sensible option. However, overburdening yourself with models, no matter what their potential use is can be dangerous and highly misleading. For example, just as somebody having a studios worth of musical equipment does not guarantee any musical chart success (even though it may help) an investor is not necessarily going to become wealthy by hoarding stock market models. Ultimately, technical tools are indispensable for an investor keen to anticipate the correct time to invest and the correct time to sell. It is just necessary to remember that a balance needs to be maintained between a collection of tools correctly tested and understood in terms of their benefits and limits of analysis and an investor’s gut feeling, which being formed from life experience is probably the most important tool an investor has.

Report written by Marisa Ahuja, Cristina Obando, Rafal Szymczak, Jonathan McHugh and Audrey Mailott in April 2006

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[1] “Elliott Wave Theory”, Prognosis software development, www.prognosis.nl

„Elliott Wave Theory”, Frost, Prechter

[2] “Technical Analysis from A to Z”, Achelis

„Technical Analysis Explained”, Pring

“Technical Analysis of the Financial Markets”, Murphy

Book Review of Cultures and Organizations: Software of the Mind.

Authors: Geert and Gert Jan Hofstede 2005 McGraw Hill

Geert and Gert Hofstede’s revised book, Cultures and Organizations: Software of the Mind contains three different approaches to understanding cultures and management throughout the world and thus need to be examined separately. The first reintroduces and builds upon Geert’s work in the 1970s on cross cultural differences among IBM’s global network of employees using his five dimensions of High vs Low Power Distance, Individualism vs Collectivism, Masculinity vs Feminism, High vs Low Uncertainty and Long vs Short Term orientation in order to help differentiate national characteristics. Part Two is an attempt to create a similar language for different business cultures in organizations. This is done through documenting similar methods to Geert’s IBM research, measuring the differences between employees within an organization, differing company goals and attempting to show how nationality can influence the value held. Part Three is intended to be a practical guide for recognizing and dealing with cultural differences and shocks and advice for differing groups to use, such as multinationals, politicians, media groups and parents. Its methodology, particularly in the first half of the book is to start from a statistical framework for highlighting differences and then justifying it with real world experience and academic research. This is where its success lies. However, as the book develops it becomes too general and as a consequence holds less authority, as it becomes less scientific, too broad and more effectively covered by other textbooks.

Introductionary Section

The backbone of Hofstedes’ book is that culture mentally programs everybody, both consciously and unconsciously, with society forming peoples values as a result of symbols (words, gestures, pictures, or objects), heroes (people living or not highly prized in a culture) and rituals (unnecessary collective activities carried out for their own sake. Presented in the form of an “Onion” (below), which shows the interrelationship and the steps that form values and how each group is visible (the furthest away from the centre).

Geert’s work considers this to be self replicating, with one generation passing down its fundamental beliefs, which although slightly changing as a result of individual personality and contemporary developments in the world will still continue.

This notion is even stretched into the context of social Darwinism, with a belief that differing cultural patterns exists for different groups of apes and chimpanzees. The differing forces put on man, it is explained forced man to live with differing values to others, as climate and differing challenges forced communities across the world to employ different priorities in order to be more successful. Gradually developing throughout the periods of man, Darwinism sits comfortably with Hoftedes’ cultural reasons as to why some people took on certain characteristics, even explaining why some races disappeared, declined in influence and why there were some major events in history, such as the reformation. This is obviously creates a form of analytical bias, which forms a more of an social evolutionary framework than political, economic or even religious (often too heavily criticized, possibly from a scientific bias) analysis of world events and development.

The attempts to highlight the methods of research draw an interesting insight into the process of analysis. The procedure of validating, i.e. drawing assumptions from the real world in order to justify statistics can be dangerous, as it can result in people seeing validation everywhere, despite having misleading information. However, the text is well research is well balanced, with views from Europe (particularly French), S.E Asia (particularly China) and America clearly represented and balanced satisfactorily.

Part One: Dimensions of National Cultures

Geert Hofstead’s research into IBM employees from around the world was an attempt to understand the differing values that people hold and to create some language or tools for understanding why this exists and how this can effect future actions. The aforementioned dimensions of High vs Low Power Distance, Individualism vs Collectivism, Masculinity vs Feminism, High vs Low Uncertainty and Long vs Short Term provide highly interesting conclusions to different thinking patterns.

The dimension of High vs Low Power Distance has been able to differentiate between countries desire for either highly regarded figures, whether private, public or communal or the ability to question authority and expect more from them. This method was able to differentiate between groups of countries, such as the Scandinavian block, which favored a more democratic process and more authoritarian countries such as China, which preferred leaders to exercise more authority

Individualism vs Collectivism highlights how people and groupings prioritize themselves, with individualist countries favoring personal ambition, whereas collectivists put a greater emphasis on group priority. This enables analysis as to why America is more individualist compared to Japan and offer ways to deal with this.

Masculinity is described as a method of achieving results no matter what the costs, whereas Femininity is the belief in allowing other things to be prioritized in society than material gain. With this tool the book was able to detail why masculine countries such as the USA had such an aggressive form of capitalism and countries such as Sweden prefer a more caring welfare state.

High verses Low uncertainty countries responses to events and groups of people were considered to be highly different as a result of differing needs for stability and fear of unknown groups or events. The data collection was used to justify why it may have been possible for racism in Germany in the 1930s and a low amount of laws in relaxed countries such as Australia.

The fifth dimension, Short vs Long Term Orientation describes how and why some cultures have their eye on the future, such as China, whereas countries such as the United States are very much focused on the now. This assumption is used to justify policies ranging from why Americans do not save enough to factors underlining what people desire from relationships.

The success of this strain of analysis is to highlight not only differences more obvious between continental cultures but also subsets, highlighting differences between (for example) North European and Southern European as a result of different climates, resources, history forming habits. As a result conclusions as to the similarities between Austria and Germany and Spain and Portugal both using statistics of IBMs employees and analysis appears highly insightful.

The method of analysis using validation from an evolutionary perspective has been very well used. However, many assumptions, although appearing correct become misleading after detailed analysis. For example, bracketing the growth of Protestantism in England and Germany together as a cultural movement is misleading, as it was politically top down (ie Henry VIII) in England and bottom up (as a result of the Gettysburg Press). So much emphasis is put on culture by the authors that it forgets that there are moments in history where cultures are formed as a result of institutions (such as the growth of English Protestantism) or from major events that cause shifts in cultures (although briefly mentioned more could have been made on the potential effects of the September 11^th attacks on America’s uncertainty avoidance for example.

Part Two: Cultures in Organizations

Satisfied by the analysis of why different cultures have alternative beliefs and habits, Part Two attempts to do the same in terms of work culture and management. However, its emphasis on summarizing other works and integrating them into the authors’ own viewpoint shows a lack of confidence and less of a coherent method of cutting across the thinking and processes of individual companies than in Part One.

Highlighting works such as Mintzberg’s Cultural and Organizational Structure help to understand organizations, such as the five configurations (The Simple Structure, The Machine Bureaucracy, The Professional Bureaucracy, The Divisionalized Form and the Adhocracy). This can help highlight how an organization coordinates, standardizes and monitors processes. Again, there is felt to be some sort of correlation between his conclusions and that of the IBM inter country research, with the idea that certain countries would hold preferences for certain structures, such as the United States preferring the Divisionized form and France the Bureaucracy as a result of certain cultural preferences.

Similarly, the summary of the different Corporate Goals of national companies similarly offers an interesting look as to how companies govern themselves. The rankings of the six greatest priorities of businessmen also seem to correlate well with Geert Hofstede’s Five Dimensions Theory.

Hofstedes’ conclusions over risk and accountancy practices seem to fit rather well, with differences in Power Distances and Uncertainty enabling for a suitable point of discussion for differing accounting practices. The notion of symbols is also used well as a tool to differentiate the differences in the value of money and the conventions held between bankers and accountants.

In their analysis, Geert and Gert Jan reference American management theories very rarely. Whilst discussing leadership and motivation they feel the need to mention it but as European academics are keen to distance themselves, with only one American quotation in the whole text. Their cynicism is seen when highlighting the situations which enable American models to be successful but also showing how the differences that exist between countries (as shown in the 5 dimensions) highlight a poor fit of cultural styles. Later they back this up, citing the failure of organizational culture theories when adapted to France. This is well reasoned, with their philosophy of cultural inclusiveness giving clues but beneficially offering no concrete answers, in order to foster personal customization, suggesting that there is no single formula for developing successful managers that can be used in all cultures.

The more original research into organizational cultures find six dimensions, namely Handling People vs Handling Things (comparing the roles or nurses and engineers in who or what they deal with); Specialist vs Generalist (a psychologist would be more specialist than a politician, say); Disciplined vs Independent (a police officer would have less discretion than a shopkeeper); Structured vs Unstructured (a systems analyst would have more of a defined role than a fashion designer); Theoretical vs Practical (a professor would be more academic than a salesman) and Formative vs Pragmatic (where procedures were more important than results, such as in the public sector).

This is built upon when these results were used to distinguish between Elephants, slow bulky but self confident companies and Storks, reliable, caring and transporting companies. Subcultures are more easily understood when tied in with further theories on Alienation, Commitment to work, a personal need for achievement, personal masculinity, orderliness and authoritarianism.

Similar to Geert Hofstead’s 5 dimensions of national cultures the 6 dimensions of organizations are non discriminatory, merely being tools to analyze the differences between companies and possibly help judge the possible suitability. Although useful as a result of not focusing entirely on cultural issues the topic feels like a shoe-in of new management theories into Geert Hofstede’s cultural dynamics philosophy covered in Part One. As a result the theory is useful, although not revolutionary.

Part Three: Implications

The third part offers a range of situations, such as diplomacy or in business, which helps to highlight flaws in cross cultural misunderstanding. For example, dangers to international mergers and acquisitions have been highlighted in situations such recognizing both areas for at least an interim period and the necessity of charasmatic leadership

Problems of culture shock are summarized well in the Acculturation Curve (below), which summarize a tourist or expatriate worker over time. This is divided into Euphoria (A), the positive experience of finding something new, Culture Shock (B) the readjusting to new norms, Acculturation (C), the coming to terms with a new environment and A Stable Set (D), where the experience settles and is either positive, neutral or negative.

Time

The book suggests that failures from cultural shocks are overestimated, with statistics quoted usually being echoed from unreliable sources. It also appears correct in addressing that problems that do occur and suggests useful methods to limit this. In the case of businesses the advice of forcing expats to integrate more and give them adequate cultural teaching (if language training is too difficult given the time) is helpful but not too illuminating.

Conclusion

This book is an interesting and broad introduction to the challenges of organization and individuals dealing with other beliefs and processes. The development of cross cultural understanding using the language of Hofstede’s five dimensions mentioned in Part One can be a highly powerful tool for analysis. The management advice in Part Two for looking at organizations and comparing is useful, although not revolutionary. Similarly, the Third Part creates a useful insight into the challenges created from dealing with other cultures, although it is not as distinct as the advice offered in other texts. Ultimately the three part approach to cross culture is interesting but flawed. The quality of writing at the beginning was so much more thought out than the final two parts that the authors would have benefited from more of an integration of ideas or treated as three separate topics in different books.

This review was written by Jonathan McHugh in April 2006