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
[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
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