When analyzing financial instruments, there are usually two schools of thought. The more traditional approach is to focus on a company’s fundamentals. One can study the earnings growth potential, price/earnings ratio compared to peers, or more precisely, the company’s annual report figures. All this attempts to assist the investor in forecasting the future price behavior of the company’s stock. In broader markets such as foreign exchange rates and interest rates, it would be the economic performances of the country versus another, or where the country is at in terms of the economic cycle that would be focused upon.
Moreover, due to rapid proliferation of information technology, such type of information are not only readily available, but in fact so much so that the amount of information can overwhelm any individual’s attempt to make a meaningful study without undue time delay because of the sheer volume of work involved, thus rendering the derived results often useless.
In the other spectrum, however, lies the development of collective investment schemes such as funds that employ asset managers and their specialized analysts, whose main focus is to concentrate their efforts in one or two selected industry sectors or companies. For any individual trying to compete with these analysts and be one step ahead, it would be extremely difficult.
Even assuming that we are sufficiently competent in our ability to analyze information, it still does not stop the likes of Enron to doctor their results and therefore finding genuine fundamental information is itself already a great hurdle to overcome.
Perhaps the most important aspect of all is the fact that all the study and work involved would only end in a decision to buy, hold or sell, effectively translating the work into the price behavior of the instrument. How much the market has discounted the information, how much expectation is build into the price, and how would sentiments change when a new set of figures come out are all things that can not be effectively studied based on the underlying fundamental data. Thus, this is where we can turn our attention to the second school of thought when analyzing financial instruments: Technical Analysis.
What is Technical Analysis?
Technical analysis can be defined as the study of historical price movements in an effort to forecast future price movements with the primary tool for technicians, as they are often referred to as, being the price chart. Technical analysis is applicable to all securities such as stocks, futures, commodities, indices, and currencies where the price is influenced by the forces of supply and demand.
The history of technical analysis stems from the Dow Theory which was developed in the early 1900s by Charles Dow. The main principles of the theory include: 1) price discounts all known information, 2) price movements follow trends and are not completely random, and 3) history repeats itself. A direct consequence of the Dow Theory is the widely followed Dow Jones Industrial Average.
Technical analysts believe that the current price fully reflects all available information. Because all information is already reflected in the price, it represents the fair value and should form the basis for analysis.
Technicians believe that the markets may experience extended periods of random fluctuation whereby the price is unpredictable but most technicians would also agree that there exists shorter periods of non-random price movements that can be analyzed and forecasts can be derived. Technicians believe that it is possible to recognize a trending market, invest or trade based on the trend, and come out on top as the trend unfolds. Because technical analysis can be applied to many different timeframes, as explained in the Chart Analysis section, it is possible to spot both short-term and long-term trends.
In general, technical analysis is performed by comparing the current price action of a security with its historical price action to predict future movements. It follows then that this process can be defined as the fact that history repeats itself.
Market technicians, technical analysts, and chartists use charts to analyze a security’s price action and attempts to forecast future price movements. But charts are not limited to only charting experts. Fundamental analysts can also make use of charts since a graphical historical record makes it easier for fundamentalists to spot the effect key events have on a security’s price (e.g. earnings, dividend payout, etc.) and checking a security’s performance over time is made a lot easier as well.
The appearance of a chart can come in a variety of forms and can display intra-day, daily, weekly, or monthly data. Daily data is made up of intra-day data that has been compressed to show each day as a single data point. Weekly data is made up of daily data that has been compressed to show each week as a single data point while monthly data is made up of weekly data that has been compressed to show each month as a single data point. The choice of data compression and timeframe depends on the data available and one’s trading or investing style.
Traders usually focus on daily and intra-day charts to attempt to forecast short-term price action. Short-term charts are very detailed and informative but can also be very volatile at times due to large sudden price movements, a wide high/low range, and gapping prices.
In contrast, investors usually concentrate on weekly and monthly charts to identify long-term trends for forecasting long-term price movements. Because long-term charts cover a longer timeframe, price movements are more smoothed out with less noise.
A combination strategy is also available. Investors can use long-term charts for analyzing the broader perspective, or trend, of the price action while short-term charts can be used for entry and exit points.
There are a few types of charts that technicians, technical analysts, and chartists rely on and the line chart is one of the simpler ones. It can be produced by plotting one price point, usually the close, of a security over a period of time. Connecting all of the price points creates the line. Due to the, sometimes volatile, intra-day action, the close is the preferred price of many for creating a line chart, rather than the open, high, or low.
Arguably the most popular chart in use today is the bar chart. The open, high, low and close prices are all required to form the price plot for each period of a bar chart. The high and low are represented by the top and bottom of the vertical bar while the open is the short horizontal line on the left of the vertical bar and the close is represented by the short horizontal line on the right of the vertical bar. The primary reason for the bar chart’s popularity over the years is that its skinny appearance allows for more data to be plotted on a chart. Unlike the line chart, the bar chart is more informative by presenting not only the close but the open, high, and low prices as well. Occasionally, some bar chart users will prefer to omit the open price from the plot so that the chart will be less cluttered and easier to analyze.
Used in Japan for over 300 years, the Japanese candlestick charts have become quite popular in recent years. The open, high, low and close are all required to produce the chart. As shown above, the difference between a candlestick and a bar is the area between the open and the close. A white, or clear, body is formed when the close is higher than the open. Alternatively, a black, or dark, body is formed when the close is lower than the open. The lines above and below the body, if any, are referred to as shadows and represent the high and low. The recent surge in enthusiasm of the candlestick charts is primarily due to the chart’s easy to read appearance and the easily recognizable relationship between the open and the close.
Over the years, technicians have become accustomed with two techniques for displaying the price scale of a chart: absolute and logarithmic. An absolute scale displays the same vertical distance between every price. Each unit of measure is the same throughout the entire scale.
On the other hand, a logarithmic scale measures price movements in terms of percentage move. For example, as illustrated below, a gain from 1 to 2 would represent an increase of 100 percent. Similarly, a move from 2 to 4 would also be a gain of 100 percent. However, both of these advances would be displayed on a logarithmic scale the same in terms of vertical distance. On an absolute scale, the move from 2 to 4 would be twice that of the 1 to 2 move.
So which scale should one use? Absolute scales are most useful when the price is trading in a tight range. Hence, absolute scales can be particularly useful for short-term charts and traders. Conversely, logarithmic scales are best suited for long-term charts and when the price had made a significant move (e.g. technology boom and bust in late 1990s).
Forecasting With Charts
Even though many different charting techniques are available, one method is not necessarily better than the other. Each has its own benefits and drawbacks. One should always keep in mind that the data and price action are the same for all methods. Thus, the choice of which charting method to use will depend on one’s preference and trading or investing style. A successful technician will be one that can successfully transform one’s own charting preferences to an accurate interpretation of the underlying strength of the security under analysis.
An indicator can be defined as a set of data points that are derived by applying a formula to the underlying price data of a security. Price data includes any combination of the open, high, low or close price over a particular time interval. Certain indicators use only the closing prices, while others may incorporate such elements as time and volume into their calculation.
By creating a time series of data points, comparisons and analyses can be performed between current and historical levels. For analyses, indicators are usuallyplotted above or below, or even overlaying, a security’s price chart. Once portrayed in this graphical form, comparisons can then be made more easily with the corresponding price chart of the financial instrument.
Indicators, in fact, can help one identify the underlying strength and direction of a security’s price action. Having this in mind, one should also take into consideration that indicators are signals, and not direct reflections, of a security’s price action.
Indicators are primarily used for three reasons: 1. alert, 2. validate, and 3. forecast.
- An indicator can help alert one to study closely the price action of a security. If momentum is fading, it may be an early sign of a break of support. On the other hand, if there is a growing positive divergence, it may be an alert to monitor closely the price action of the security as a possible resistance breakout may be on the horizon.
- Indicators can help validate the results of other technical analysis tools. If a breakout to the upside occurs, a corresponding moving average crossover may act as a confirmation of the strength in the price action. Alternatively, if a stock pierces through a support level, a corresponding low in the Relative Strength Index (RSI) may confirm that the sellers have overwhelmed the buyers.
- Indicators can also be used to help investors and traders forecast when to buy and when to sell. However, one should always keep in mind that indicators dogenerate false buy/sell signals from time to time. Hence, one should always use other technical analysis tools to confirm other indicator’s signals.
As always in technical analysis, learning how to read indicators is more of an art than a science. Indicators that work well for certain stocks may not work as well for others. Expertise will develop with experience, which in turn will provide the basis for effective recognition of false signals.
It is also best to focus on two or three indicators at one time. Attempts to analyze a security with five or more indicators are usually ineffective and frustrating. Try to choose indicators that complement each other, instead of those that generate the same signals. For example, it would be meaningless to analyze two indicators that are both good at providing signals for overbought and oversold conditions, such as the RSI and Williams %R. Most of the time, the results will leave you scratching your head.
Leading Versus Lagging Indicators
Indicators also come in two varieties: leading and lagging.
Leading indicators are designed to help one forecast what the price will do next and can provide a greater return at the expense of increased risk. Hence, false signals and whipsaws tend to occur, more often than not, with these types of indicators. Leading indicators measure how overbought or oversold a security is. This is done with the assumption that overbought securities will retrace and vice-versa for oversold ones. Some of the more popular leading indicators include Commodity Channel Index (CCI), Momentum, Relative Strength Index (RSI), Stochastic Oscillator, and Williams %R.
Conversely, lagging indicators are what technical analysts refer to as trend following indicators. These indicators are best when prices move in relatively long trends. They simply inform the technician what the price is doing at the current moment and are not good at predicting into the future. As such, lagging indicators are not effective in trading the bounce back or retracement (i.e. when the market is in a trading range). It follows then that these types of indicators provide signals that are somewhat late, with a significant portion of the move having already occurred. But having said that, investors can still benefit tremendously from relatively long trends by following these types of indicators. Some of the more popular lagging indicators include moving averages (exponential, simple) and the Moving Average Convergence Divergence (MACD) indicator.
An oscillator is a type of indicator that fluctuates above and below a centerline or within a set range over a period of time. However, oscillators can often linger around the upper or lower boundary of the range (overbought or oversold) for an extended period of time, but they cannot trend persistently. In contrast, indicators that do not fluctuate around a centerline or remain in a range, such as the On Balance Volume (OBV) indicator, can trend continuously for a sustained period of time.
In general, there are two different types of oscillators: 1) centered oscillators, which fluctuate above and below a centerline and 2) banded oscillators, which fluctuate between overbought and oversold levels.
An example of a centered oscillator is the MACD indicator (below). MACD is the difference between the 12-day and 26-day Exponential Moving Averages (EMA). The higher the difference between the two, the higher the indicator reading. Although there is no bound as to how high or low the MACD value can be, large differences between the two moving averages are unlikely to persist for a long period of time.
On the other hand, the Relative Strength Index (RSI) is an example of a banded oscillator. Readings in the lower range of the indicator represent an oversold condition while readings at the higher end indicate an overbought condition.
So which types of oscillators should one use? In general, centered oscillators are best suited for identifying the underlying strength and direction of the price action. Usually, readings above the centerline indicate a bullish presence for the security while readings below it represent a bearish mood. A centerline crossover can also act as validation of a previous signal. For example, if there were a previous buy signal then a subsequent move above the center line would confirm the previous signal.
In contrast, banded oscillators are best suited for the trader, or short-term investor. These types of oscillators are best suited for identifying extreme overbought and oversold conditions in a sideways market and should not be used for trending issues. In a trending environment, many false signals may occur because banded oscillators can remain near overbought or oversold levels for an extended period of time. An overbought condition does not necessarily mean it is a time to sell and vice-versa for an oversold condition. For example, if a security is in a strong uptrend, buying at oversold levels will be much more profitable than selling at overbought conditions. Overbought and oversold situations are best used as a warning that close attention should be paid to the price action as conditions are reaching extreme levels.
One of the most powerful and widely believed concepts in technical analysis is divergence. It is a key concept behind many indicator buy/sell signals. Divergences can help one identify changes to a trend and also, it can help solidify a buy or a sell signal from other indicators.
There are two types of divergences: positive and negative. In general, a positive divergence occurs when the indicator advances and the underlying security price declines (below). A negative divergence occurs when an indicator declines while the price advances.
To be successful when trading with oscillator signals, trading strategies and analysis should be based from the results of multiple signals. The criteria for a buy or sell signal could depend on, for example, three separate yet confirming signals. For example, a buy signal might be generated with an oversold reading from the RSI, positive divergence, and a bullish moving average crossover. By following a certain set of rules, the trader will be more confident when making the final buy/sell decision while at the same time, reduce the risk of false signals from individual oscillators.
Oscillators are also most effective when used in conjunction with chart pattern analysis, support/resistance identification, trend identification, and other technical analysis tools. Interpreting oscillator values and signals vary from situation to situation and thus, by using other analysis techniques in conjunction with oscillator readings, the chances of success can be greatly enhanced.