Technical analysis is a very old discipline in market analysis. Created for the most part, by pure practitioners, it has most of the time been questioned, rejected or ignored by academic circles. However, technical analysis has developed over the centuries from clear chart reading into a state where many varying toolsets are used. The used charts, trading models and analyses are very different in nature but do have a common denominator. They use pure market data as input and therefore they are classified as technical analysis. The body of knowledge of technical analysis has grown rapidly by borrowing from other disciplines.
With the growth of computer power, technicians have integrated elements from statistics, information theory, physics, time series analysis and econometrics – just to name a few. While the toolset has become more academic and sophisticated; practitioners’ intention is still driven by market returns. Academic interest in technical analysis started in the late 1950s. Ever since the first paper on the subject was written, researchers from universities and institutions, such as central banks, have tried to prove whether technical analysis is worthwhile or whether it is just pure nonsense.
For decades, the prevalent regime was the efficient market hypothesis” i. e. the idea that market prices discount available information instantly and therefore, not only technical analysis but virtually every kind of analysis is useless. This quarrel has not yet been solved, but for over 20 years there has been a growing body of evidence that technical analysis can be profitable. Whereas technicians are only interested in the question: “Does it work? ”, academics prefer to ask: “Why does it work? ”. ”
This paper provides a brief explanation of some of the underlying theories of technical analysis and some of the most popular indicators. The paper starts with a definition of technical analysis and its basic assumptions. Then follows an overview of the Dow Theory, the first pillar of technical analysis, and its implications it the process of technical trading until now. The paper skips the topics about the process of charting stocks and the major chart patterns. It goes directly to the most popular indicators used in technical analysis – those of moving averages and oscillators.
All indicators are explained in theory and in practice using the data of the Dow Jones Industrial Average index as one of the barometers of the economy. Lately, the paper presents another theory – Elliot Wave Principle as a complement of the Dow Theory and a new view of the predominant psychological influence over the stock markets. Definition Technical analysis is the study of market action for the purpose of forecasting of future price trends. The term market action includes the three main sources of information: price, volume and open interest (only for futures and options).
Technical analysis is in its essence a set of forecasting methods used for taking trading decisions. Technical analysis is the study of how securities prices behave and how to exploit that information to make money while avoiding losses. The technical style of trading is opportunistic. The goal is to forecast the price of the security over some future time horizon in order to buy and sell the security to make a cash profit. The emphasis in technical analysis is to make profits from trading, not to consider owning a security as some kind of savings vehicle.
The preconceived notion is that because technical analysis entails an active trading style, it is riskier. In fact, executing the one-hour trade has less inherent risk of loss than buying and holding a security indefinitely without an exit plan. The existence of an exit plan is what defines and limits the risk. Preventing and controlling losses is more important than outright profit seeking to practically every technical trader. The technical analysis approach is demonstrably more risk averse than the value-investing approach. To embrace technical analysis is to embrace a way of thinking that’s always sensitive to risk.
Technical trading means to trade with a plan that identifies the potential gain and the potential loss of every trade ahead of time. The timing of entry and exit from the market is critical to making money and controlling losses. This chart, from Barron’s, shows the benefit of being smart enough to miss the worst 5 days of the year between February 1966 and October 2001. Source: “The Truth About Timing,” by Jacqueline Doherty, Barron’s (November 5, 2001)
The first cornerstone of technical analysis is prices. Technicians believe that anything that can possibly affect the price – fundamentally, psychologically, politically or otherwise – is already reflected in the price. Hence, the study of price action is all that is required. Securities prices are the product of the collective decision making of buyers and sellers. Prices incorporate all known information about the security. All known information consists of hundreds of factors ranging from accurate facts to opinions, guesses, emotions, and previous prices.
They all go into the supply and demand for a security and result in its price. However, the prices on a chart don’t tell you anything about the underlying value of the security. Where the price “should” be is a totally different subject, and is explored by fundamental analysis. Moreover, technicians don’t concern themselves with the reasons why prices rise or fall. They don’t think that knowing what those reasons are is necessary in the forecasting process. Nevertheless, technical and fundamental analysis are compatible and can be used together, not controversial as some critics think.
The second cornerstone of technical analysis is trends. The whole purpose of charting the market action is to identify trends in the early stages of their development and to trade in the direction of those trends. Trend is such a wide and flexible concept that a large variety of definitions is possible. In fact, some securities are frequently in a trending mode, others seldom trend, or their trends are short lived. Only one thing is certain: No security trends all the time. Even the bestbehaved security spends some time going sideways (nontrending), which can be considered a trend in its own right.
It is very important to consider the time period of the analyzed data. For example, the view of trendedness is different when looking at ten years of daily prices and when looking at only two years of data. In other words, trends are reasonable and useful only in a specified time frame. Basic observations:
- Securities prices move in trends much of the time.
- Trends can be identified with patterns that are seen repeatedly and with support and resistance trendlines.
- Primary trends (lasting months or years) are punctuated by secondary movements (lasting weeks or months) in the opposite direction of the primary trend.
Trends remain in place until some major event comes along to stop them. The third cornerstone of technical analysis is the belief that understanding the future lies in the study of the past. This is because much of the body of technical analysis and the study of market action has to do with the study of human psychology. In fact, technical analysis works because people consistently repeat behaviors under similar circumstances. Much of the time there is order in the way securities prices evolve, even though they develop in an infinite variety of configurations and each chart is literally unique.
Technical traders attribute that orderliness to the swings of market sentiment. Prices form patterns because the traders in the market behave in regular and repetitive ways. They can identify, measure, and project prices because they can identify, measure, and project human behavior. However, experienced technical traders know that no technique works all the time and no technique works on every security. In fact, many techniques work only when the majority of market participants believe that they will work, forming a self-fulfilling prophecy.
The most discussed question is how reliable is technical analysis for making profits. Every day, hundreds of thousands of traders all over the world beat the market. To beat the market means to earn a return higher than the benchmark in that market, such as making more from trading a single stock included in the Dow Industrial Average than the Dow Industrial Average index returned in the same period. Beating the market can also mean to earn a return greater than the return on the return on a risk-free investment, usually defined as the three-month U. S. Treasury bill. There is no doubt that technical analysis tools and methods can make money for the traders at one time or another.
The real question is, though, can they do it consistently. Dow Theory Much of what we call technical analysis today has its origins in the theories proposed by Charles Dow in his publications for the Wall Street Journal at the turn of the 20th century. “As co-founder of the Wall Street Journal and the Dow Jones Indexes, he developed the framework for monitoring market movement that we have been using for the last century. It is interesting to notice that his theory was at first an economic theory.
In 1884 Dow created the first stock market average composed of the closing prices of eleven stocks. In 1987 he determined that two separate indices would better represent the health of the economy and created a 12-stock industrial and 20-stock rail index. “Dow’s theory was simple: if goods were being produced and moving through the economy, then it should show up in the action of both the Industrials and Transports, the makers and transporters of raw and finished products.
If either the Industrials or the Transports weren’t confirming the direction of the other, then it was a warning that conditions might be about to change. ” Dow Theory lies on six basic tenets that fit into the modern technical analysis: 1. The averages discount everything As stated above, the market reflects every possible knowledge factor that can affect supply and demand. The theory applies to market averages, as well. That is why there is no need to add to the averages any other elaborate statistical indexes or numbers such as fluctuations in exchange, volumes of trade etc. Wall Street considers all these things. ”
The market has three trends Dow defined an upward trend as a situation in which each successive rally closes higher than the previous rally high and each successive rally low closes higher than the previous rally low. In other words, an upward trend has a pattern of rising peaks and troughs. On the opposite, a downtrend is defined by successively lower peaks and troughs. Dow’s definition has withstood the test of time and still forms the cornerstone of trend analysis.
Dow considered each trend to have three parts – primary, secondary and minor – which he compared to the sea tides, waves and ripples, respectively. Accordingly, he considered the primary trends to last for more than a year, the secondary trends that represent corrections to the primary – for a period between three weeks and three months, and the minor trends – for usually less than three weeks.
The speculation was much greater in the housing market—particularly in risky subprime mortgages and myriad ways they were repackaged and leveraged. ” “The theory assumes that majority of the stocks follow the prevailing trend of the market majority of the time. ”“Since the Dow Theory has no forecasting values regarding the duration of the trend, it only takes into account the direction of trend. ”Nevertheless, its applications and usefulness in capturing the major market movements cannot be denied.
The moving average is one of the most popular and versatile technical indicators. Because of the way it is constructed and the fact that it can be so easily quantified and tested, it is the basis of many trend-following systems used today. Unlike chart analysis, which is highly subjective and difficult to test, moving averages can easily be computer-programmed and give precise buy and sell signals. A moving average is essentially a trend following device. Its purpose is to signal that a new trend has begun or that an old trend has ended. Its purpose is to track the progress of the trend and it does not predict market action as the chart analysis attempts to do.
The moving average is a follower, not a leader; it doesn’t anticipate, only reacts. The moving average is a smoothing device. By averaging the price data, a smoother line is produced, making it easier to view the underlying trend. By its nature, however, the moving average line lags the market action. A shorter moving average (e. g. 20 days’ average) would represent the price action more closely than a longer one (e. g. 200 days’ average). The time lag is reduced with the shorter averages but cannot be completely eliminated.
The most common price used in the moving average construction is the closing price because it is, usually, considered to be the most important price of the trading day. Nevertheless, some technicians prefer to use other prices. Some prefer to use a midpoint value, which is derived by dividing the day’s range by two. Others add the high, low and closing prices and divide the sum by three. Still others prefer to construct price bands by averaging low and high prices separately.
Simple moving average The simple moving average, or the arithmetic mean, is the type of moving average used by most technical analysts. But there are some people who question its use on two major topics. First, only the period covered by the average is taken into account. Second, the simple oving average gives equal weight to each day’s price. For example, in a 10-day average, the prices of each day take 10% weighting. Some analysts believe that a heavier weight should be given to the more recent price action.
Linearly weighted moving average In an attempt to correct the weighting problems, some analysts employ the linearly weighted moving average. In its calculation the greatest weight is given to the last day’s price and is decreased with every previous day. For example, for a 10-day average, the closing price of the 10th day is multiplied by 10, of the 9th day – by 9 and so on. The total is then divided by the sum of the multipliers (for a 10-day moving average, the sum is 55 = 10+9+8+7+6+5+4+3+2+1). However, the linearly weighted average still doesn’t address the problem of including only the price action covered by the length of the average itself.
Exponentially smoothed moving average This type of average addresses both of the problems associated with the simple moving average. The exponentially smoothed moving average assigns a greater weight to the more recent data and meanwhile it includes in its calculation all of the data of the life of the instrument. In addition, the user is able to adjust the weighting to give a greater or lesser weight to the last day’s price. Yet, the simple moving average is the one most widely used by technicians and the following analysis will be concentrated on it. To generate trade signals the simple moving average is plotted on the bar chart in its appropriate trading day along with that day’s price.
When the closing price moves above the moving average, a buy signal is generated. A sell signal is given when the price moves below the moving average. For added confirmation, some technicians also wait to see the moving average line itself turn into the direction of the price crossing. The chart below takes for example the price movements the Dow Jones Industrial Average index and the respective 200-day simple moving average. Source: http://buyupside. com/ It can be noticed how the moving average lines crosses the price line at the end of 2007.
This is a signal that the trend will end or reverse. The stronger confirmation comes when the moving average line itself turns downwards at the beginning of 2008. On the contrary, the crossing point in 2009 signals the beginning of an uptrend. However, one should be aware that there is always a time lag in using simple moving averages and this one especially is a 200-day moving average, which means it isn’t sensitive enough of price action changes but gives a summarized view of the trends. If a shorter term moving average is used, it tracks prices more closely and more crossings occur.
The use of a very sensitive average means that more trades will occur (with higher commission costs) and some of the short-term random price movement may activate false trade signals. On the other hand, the more sensitive moving average has the advantage of giving trade signals earlier in the move. The 50-day moving average of Dow Jones Industrial Average below can be taken as an example, in comparison to the 200-day average. It is obvious from the comparison that the longer average performs better when the trend remains in motion.
As seen above, the 200-day moving average crosses the price chart only once between 2008 – 2009 while the 50-day moving average crosses the price chart several times, thus creating false signals, when the reality shows that the prices continued to fall. On the other hand, the fact that a longer moving average trails the trend from a greater distance works against the trader when the trend actually reverses. It can be seen that the 50-day average line crosses the price chart much sooner in 2009 than the 200-day, showing the beginning of the upward trend.
Therefore, it is recommended to use longer averages while the trend remains in force and shorter averages when the trend is in the process of reversing. Moving Average Envelopes and Bollinger Bands The usefulness of a single moving average can be enhanced by surrounding it with envelopes. Percentage envelopes can be used to determine when the market has become overextended in either direction. In other word, they show when the prices have extended too far from their moving average line. The envelopes are put at fixed percentages below and above the average.
Shorter term traders, for example, often use 3% envelopes around a 21-day moving average. When prices reach on of the envelopes the short-term trend is considered overextended. For long-range analysis some possible combinations include 5% envelopes around a 10-week average or 10% envelopes around a 40-week average. Similar to moving average envelopes is the Bollinger Bands technique, developed by the professional technical analyst John Bollinger. Again two trading bands are placed around the moving average, except that Bollinger Bands are placed two standard deviations above and below the moving average, which is usually 20 days.
Using two standard deviations as a measure ensures that 95% of the trading data will fall between the bands. As a rule, prices are considered to be overbought when they touch the upper band and oversold when they touch the lower band. Bollinger Bands differ from envelopes in one major way: While the envelopes stay a constant percentage apart from the moving average, Bollinger Bands expand and contract based on the volatilityof prices. So wide swings in prices result in wide distances between the upper and lower bands and relatively stable prices result in a narrow ranges.
There is also a tendency for the bands to alternate between expansion and contraction. When the bands are unusually far apart, that is often a sign that the current trend may be ending. When the distance between the two bands has narrowed significantly, that is often a sign that the market is about to initiate a new trend.
One technical measure of market performance is the number of stocks above their moving averages. A high number of stocks above their moving averages tends to be a bullish indicator – prices are moving up or they are already on the price upside. Currently, about 50% of the stocks comprising the DJIA index have closing prices above their 50-day moving average; about 93% of them are above their 200-day moving average. In conclusion, the moving averages can be applied to virtually any technical data or indicator. They can be used on open interest or volume figures, as well.
However, moving averages don’t work all of the time. They do their best work when the market is in a trending phase but they are not very helpful when the market is in a trendless period and prices move sideways. Fortunatelly, there is another class of indicators that performs much better than the moving average during those frustrating trading periods. Oscillators The oscillator is extremely useful indicator for non-trending markets where prices fluctuate in a horizontal price band, or trading range, creating a market situation where most trend-following systems simply don’t work that well.
The oscillator provides technical traders with a tool that can enable them to profit from these periodic sideways and trendless market environments. Used in conjunction with price charts even during trending phases, the oscillator becomes extremely valuable for alerting the trader to short-term extremes i. e. overbought or oversold conditions. The oscillator can also warn that a trend is losing momentum before that situation becomes evident in the price action. Oscillators can signal that a trend may be nearing completion by displaying certain divergences.
The oscillator is only a secondary indicator because it must be subordinate to the basic trend analysis. Most oscillators look very much alike and their interpretation differs very little. The oscillators are plotted along the bottom of the price chart and resemble a flat horizontal band. The oscillator band is basically flat whereas prices may be going up, down or sideways. However, the peaks and troughs of the oscillator coincide with those of the price chart. Some oscillators have a midpoint value that divides the horizontal range into two halves.
Depending on the formula used, this midpoint is usually a zero line. Some oscillators have an upper and a lower boundary ranging from 0 to 100. As a general rule, when the oscillator reaches an extreme value in either the upper or lower end of the band, this suggests that the current price move may have gone too far too fast and is due for a correction of some type. As another general rule, the trader should be buying when the oscillator line is in the lower end of the band and selling in the upper band. The crossing of the midpoint line is used to generate buy or sell signals.
Measuring Momentum The concept of momentum is the most basic application of oscillator analysis. Momentum measures the velocity of price changes as opposed to the actual price levels themselves. Market momentum is measured by continually taking price differences for a fixed time interval. The formula of momentum is M = V – VX, where V is the latest closing price and VX is the price X days ago. If the latest price is higher than that of X days ago, a positive value would be plotted above the zero line and vise versa.
By plotting the price differences for a set period of time the chartist is studying rates of ascent and descent. If prices are rising and the momentum line is above the zero line and is rising, this means that the uptrend is accelerating. If the momentum line begins to flatten out, this means that the new gains received by the latest closes are getting the same as those X days ago. While prices may still be advancing, the rate of ascent (velocity) has leveled off. When the momentum line begins to drop towards the zero line, the uptrend in prices is still in force, but at a decelerating rate.
When the momentum line moves below the zero line, the latest closing price is now under the price of X days earlier and near-term downtrend is in effect. Because of the way it is constructed the momentum line is always a step ahead of the price movement. It leads the advance or decline in prices, then levels off when the current price trend is still in effect. It begins to move in the opposite direction as prices begin to level off. The chart below presents an example of a momentum line again of the Dow Jones Industrial Average prices. The green curve represents the 20-day momentum.
It can be seen that the momentum line in the period from the middle of 2010 until now is positioned above the zero line, which indicates the closing prices of the index were rising. The steep momentum line in October 2011, for example, forecasts the uptrend of prices during the following month. Currently, the momentum is beginning to flatten out, which means that the gains are becoming closer to each other today and 20 days ago. And the momentum line is sloping downwards, which predicts a slower rate of price increases. The Relative Strength Index (RSI) The Relative Strength Index was developed by J. Welles Wilder and presented in his book New Concepts of Technical Trading Systems, 1978.
The RSI has become a very popular oscillator among traders. As Wilder points out, one of the two main problems of constructing a momentum chart is the unstable movement often caused by the sharp changes in the values used. A sharp advance or decline 10 days ago can cause sudden shifts in the momentum line even if the current prices change only a little. Therefore, some smoothing is necessary to minimize the distortions. The second problem is that there is a need of a constant range for comparison purposes.
The RSI formula not only provides the necessary smoothing, but also creates a vertical range from 0 to 100. The actual formula is calculated as follows: Usually 14 days are used in the calculation. To find the average up value one must add the total points gained on up days and divide the sum by 14. To find the average down value, one must do the same with the points lost during the down days.
To determine the %K line, which is the more sensitive, the following formula is used: %K = 100[(C – L14) / (H14 – L14)], where C is the latest closing price, L14 is the lowest low for the last 14 days and H14 is the highest high for the same 14 days. The second line, %D is a 3-day moving average of the %K line. This formula produces a version called fast stochastics. By taking another 3-day moving average of %D line a smoother version called slow stochastics is computed. Most traders use the slow stochastics because of its more reliable signals.
These formulas produce two lines that oscillate in the range between 0 and 100. The %K is a faster line, while the %D line is slower. The major signal to watch for is a divergence between the %D line and the price when the %D line is in an overbought (above 80) or oversold (below 20) area. A bearish divergence occurs when the %D line is over 80 and forms two declining peaks as the prices continue to move higher. A bullish divergence is present when the %D line is under 20 and forms two rising bottoms while prices continue to move lower.
Assuming all of these factors are in place, the actual buy or sell signal is triggered when the faster K line crosses the slower D line. To illustrate the use of the stochastic oscillator a graph of DJIA index is taken. For the period June 2011 – May 2012, it seems that only in the middle of June 2011, the oscillator provided a buy signal according to the requirements listed above. Source: Yahoo! Finance Moving Average Convergence / Divergence (MACD) The Moving Average Convergence / Divergence is a useful indicator because it combines some of the oscillator principles with a dual moving average crossover approach.
It consists of two lines: The faster line, called MACD line, is the difference between two exponentially smoothed moving averages of closing prices (usually the last 12 and 26 days). The slower line, called signal line, is usually a 9-period exponentially smoothed moving average of the MACD line. The actual buy and sell signals are given when the two lines cross. A crossing by the MACD line above the signal line is a buy signal. A crossing by the MACD line below the signal line is a sell signal. On the other hand, MACD resembles an oscillator because its values also fluctuate above and below a zero line.
An overbought condition is present when the lines are too far above from the zero line. Crossings above and below the zero line are another way to generate buy or sell signals, respectively. Divergences appear between the trend of MACD lines and the price line. A negative (bearish) divergence exists when MACD lines are well above the zero line and start to weaken as prices continue to trend higher. A positive (bullish) divergence exists when MACD lines are well below the zero line and start to move up ahead of the price line.
The graph below shows the several buy and sell signals when the MACD line crossed the signal line. However, divergences of the MACD lines from the price char are not present in the observed period. Source: http://www. stockta. com It was noted above that there are times when oscillators are more useful than at others. At uncertain market periods, as prices move sideways for several weeks or months, oscillators track the price movements very closely. The peaks and troughs on the price chart coincide almost exactly with the peaks and troughs on the oscillator.
On the chart above, this is quite visible for both the RSI and Stochastics. At some point of time, however, a price breakout occurs and a new uptrend or downtrend begins. By its very nature, the oscillator is already in an extreme position just as the breakout is taking place. If the breakout is to the upside, the oscillator is already overbought and the opposite. In an early stage of a new trend, following an important breakout, oscillators often reach extremes very quickly and stay there for a while. That’s why at such a period the oscillator is better ignored for the time being.
Later on, as the trend begins to mature, the oscillator should be given greater weight. Elliot Wave Theory In 1938 a monograph entitled the Wave Principle was the first published reference to what is known today as the Elliot Wave Principle. Elliot was very much influenced by the Dow Theory and even said that the Wave Principle was “a much needed complement to the Dow Theory”. Brought to the mainstream through Frost and Prechter’s publication in 1978, wave analysis is now a very popular form of technical analysis that can be applied to stock charts to forecast the future direction of prices.
There are three important of the wave theory – pattern, ratio and time – in that order of importance. Pattern refers to the wave patterns or formations that comprise the most important element of the theory. Ratio analysis is useful for determination of retracement points and price objectives by measuring the relationships between different waves. Time relationship[s are used to confirm the wave patterns and ratios but are considered to be less reliable in forecasting of the market. Elliot Wave Theory was originally applied to the major stock market averages, especially the Dow Jones Industrial Average.
In its most basic form, the theory states that the stock market follows a repetitive rhythm of a five waves advance and three waves decline. In the advance part, the waves going in the upper direction are called impulse waves (number 1,3,5), while the downwards waves are called corrective waves (2, 4). After the advance part a three waves correction begins (labeled a, b, c). Along with the constant form of the waves, there is an important consideration of degree. Elliot categorized 9 different degrees of a trend – from a Grand Supercycle (around 200 years long) to a subminuette (covering only a few hours).
Each wave subdivides into waves of lesser degree that, in turn, subdivide into waves of even lesser degree. It also follows then that each wave is part of the wave of the next higher degree. Whether a given wave subdivides into 5 or 3 waves is determined of the direction of the next larger wave. One of the most important rules to remember is that a correction can never take place in 5 waves. In a bull market, for instance, if a five wave decline is seen, this means that it is probably only the first wave of three wave (a, b, c) decline and there’s more to come on the downside.
In a bear market a three wave advance should be followed by resumption of the downtrend. Impulse Waves Impulse waves are powerful moves composed of 5 subwaves that drive the market in the direction of the larger trend. Within the larger impulse wave the 5 waves subdivide into 5, 3, 5, 3, 5 formations and are labeled 1, 2, 3, 4, 5. Waves 1, 3, 5 are impulse waves and are powerful driving moves, which are interrupted by the waves 2 and 4 that present the corrective and consolidating phases. General description of the market phases connected with these waves: Wave 1: the smart money enters the market.
The trend has changed but the market remains uncertain. Wave 2 retraces some of the first wave back. The initial burs has lessened but the market doesn’t seem to have the energy to resume the previous trend. Wave 3: mass participation causes prices to explode in the direction of the new trend as the market accepts that the trend has reversed. Wave 4: quite often a shallow retrace of the third wave as the market consolidates its gains and investors start taking profits. Wave 5: distribution phase – Profit taking increases as the last man standing is forced into accepting that the trend has changed.
Corrective Waves In general corrective waves are less clearly defined and are more difficult to predict. Corrective waves retrace part of the previous trend but never move beyond the origin of the previous impulse wave. In other words, wave 2 never breaks the origin of wave 1 and wave 4 never breaks the origin of wave 3. The different types of corrective waves are zigzag, flat, triangle and combined. The difference between them is how their patterns of break down into smaller waves: Zigzag is the usual three-wave correction pattern against the major trend that breaks down into a 5-3-5 sequence.
Flat correction is different from zigzag for it breaks down into a 3-3-5 pattern. In general, the flat is more of a consolidation than correction and is considered a sign of strength in a bull market. Triangles usually occur in the fourth wave and precede the final move in the direction of the major trend. Elliot classifies different types of triangles – ascending, descending, symmetrical and expanding – that are widely used patterns in technical analysis. Combination waves can occur when a corrective wave has not met its price target or needs to extend in time.
Typical combination waves are double 3s or triple 3s where a combination of zigzags or flats is joined together by an X wave. X waves are 3-wave corrective moves. The Rule of Alternation In its more general application, this rule holds that the market doesn’t act the same way two times in a row. If a certain type of top or bottom occurred the last time around, it will probably not do so again this time. The rule of alternation doesn’t tell us exactly what will happen, but tells us what probably won’t. in its more specific application, it is most generally used to tell us what type of corrective pattern to expect.
Corrective patterns tend to alternate. In other words, if corrective wave 2 was a simple a-b-c pattern, wave 4 will probably be a complex pattern such as triangle. Conversely, if wave 2 is complex, wave 4 will probably be simple. Fibonacci Numbers as the Basis of the Wave Principle Elliot stated in his work that the basis for his Wave Principle was the number sequence discovered by Leonardo Fibonacci in the 13th century. Fibonacci ratios are derived from the sequence of numbers and the most important one is of course the Golden Ratio which is 0. 18. The Golden ratio appears in many forms throughout the natural world and the importance of the Fibonacci ratios within stock analysis is very clear to see too.
One of the easiest places to see the Elliott Wave Principle at work is in the financial markets, where changing investor psychology is recorded in the form of price movements. If you can identify repeating patterns in prices, and figure out where we are in those repeating patterns today, you can predict where we are going. ” “Using the Elliott Wave Principle is an exercise in probability. An Elliottician is someone who is able to identify the markets structure and anticipate the most likely next move based on our position within those structures.
By knowing the wave patterns, you’ll know what the markets are likely to do next and (sometimes most importantly) what they will not do next. By using the Elliott Wave Principle, you identify the highest probable moves with the least risk. ” Below is shown the latest Elliot Wave analysis of the Dow Jones Industrial Average available on the Internet. Even though not very recent, the chart proves that the Elliot Wave Principle can be successfully applied to stock indexes and the rule of the eight waves holds.
What can be inferred from the chart is that a further downward trend id to be expected as the chart finishes with the A wave of the greater degree. There are times when Elliot pictures are clear and times when they are not. Trying to force unclear market action into an Elliot format and ignoring other technical tools in the process is a misuse of the theory. The key is to view Elliot Wave Theory as a partial answer to the puzzle of market forecasting. Using it in conjunction with all other technical theories will increase its value and improve the chances of success. Conclusion
Technical analysis is a method of evaluating stock prices by relying on market data, such as charts of price and volume, to help predict future market trends. Investors who rely on technical analysts strive to accurately predict the future price of a stock by looking at its historical prices and other trading variables. Technical analysis hinges on the belief that psychology influences trading in a way that enables predicting when a stock will rise or fall. In fact, every trade has two parts — the security and its technical characteristics, and the trader himself/ herself.
After having mastered a few key concepts, exactly how to apply technical methods is a matter of personal preference. No one technical method is “right” — the right method is the one that consistently makes more money than it loses. To do that, the chosen method must match up with the trader’s risk profile and also be practical i. e possible to be executed.