P age 1 GUIDE TO STOCK trading tools VI. TECHNICAL INDICATORS AND OSCILLATORS I. Introduction to Indicators and Oscillators Technical indicators, to start, are data points derived from a specific formula. Basically speaking, a technical indicator consists of a set of points (much like a price chart) but is instead based on a series of data based on a formula with the security s price as one of its variables. For the mathematically inclined, a technical indicator is a function of several variables, primarily stock prices. Why use a technical indicator? Technical indicators offer a different outlook based on the formula given for the indicator. Technical indicators are based on stock prices to start with, with the aim of providing markers, or signals as points of analysis. Using mathematical analysis, formulas involving prices are created, inputting stock prices to provide points (and eventually, lines) on which to analyze the price action of a security. Indicators basically serve three broad functions: 1) As an alert mechanism Indicators are basically a method to alert analysts and investors for any price action that may potentially be strategic to their goals. An indicator serves to warn analysts and investors to watch out closer for any movement in the price of a security. Indicators may serve to alert or confirm (read below) certain price chart patterns (as discussed before) and may spell the difference between a true price breakout and a deceptively similar but false price movement. 2) As a method of confirmation Indicators can also serve to confirm the results or alerts of other technical indicators. While no technical indicator can single-handedly warn any analyst or investor of profitable positions to grab and let go, the use of other technical indicators can narrow down (or at least help to do so) the accuracy of what one indicator says. For example, a confirmation of a price breakout (after a period of stagnation) may help investors and traders decide whether or not to believe a single technical signal. The use of more tools may supplement and/or complement other tools, and the same goes with technical signals. A caveat, though, is that too much confirmation may also lead to confusion and possibly riskier trading/investing. 3) As a tool for prediction Finally, indicators serve to help analysts, investors and traders predict (with a certain degree of accuracy) what prices will tend to lean towards. A technical indicator cannot predict an exact number, but technical indicators can help analysts predict as to the direction of the movement of stock prices.
P age 2 Leading vs. Lagging Indicators Leading Indicators are designed to create a lead as to where prices will move in the future. Leading indicators usually signals changes in trends before these are reflected in the market. While leading indicators predict as to where the trend will be in the future, it is not 100% accurate. Leading indicators therefore provide good entry and exit points as these indicators generate signals for trading opportunities, as well as warnings against potential strength or weakness. Early signals therefore can provide greater returns, with greater risks, of course. False signals also exist in leading indicators and potentially cause losses. Common leading indicators used include Momentum Oscillators, Stochastic Oscillators, the Commodity Channel Index and the Relative Strength Index or RSI. Lagging indicators, on the other hand, follow an already existing trend in price movement. These indicators confirm trends already existing in the market, unlike leading indicators which try to predict where a trend will go. Lagging indicators, therefore, signal a continuation of an existing trend, and therefore work best when strong price trends are developed by the stock. As long as a trend exists, traders and investors can follow it, and strategize again when the trends end. Common lagging indicators used include Moving Averages (exponential, simple, weighted, or variable) and Moving Average Convergence-Divergence or MACD. II. An example of Technical Indicators - Simple and Exponential Moving Averages Moving averages are overlays (meaning, they are usually put alongside price charts) that show the current direction of a trend, albeit with a lag. Moving averages are built to smooth out the sharp kinks and filter sudden movements of stock prices to show how prices tend to move on average. Also, moving averages can also be used as possible bases for support and resistance levels. There are two commonly-used types of moving averages Simple and Exponential moving averages. Moving averages also vary on how many days worth of prices are calculated to make a data point of averaged stock prices. For example, short-term moving averages usually last for 5-20 days or periods, while medium-term averages last around 20-60 periods. Long-term moving averages usually calculate 100 to as much as 200 periods worth of prices to get data points. Again, depending on the goals of investors and traders, moving averages can be adjusted to suit one s analysis needs. Simple Moving Averages Simple Moving Averages are calculated as follows: if daily closing prices for 15 days are: P 1, P 2, P 3, P 4, P 5 P n where n = number of days: For 5-day SMA:
P age 3 1 st day SMA (5) = (P 1 + P 2 + P 3 + P 4 + P 5 ) / 5 2 nd day SMA (5) = (P 2 + P 3 + P 4 + P 5 + P 6 ) / 5 3 rd day SMA (5) = (P 3 + P 4 + P 5 + P 6 + P 7 ) / 5 For n-day SMA: (where s = starting period) 1 st day SMA (n) = (P s + P s+1 + P s+2 + P n ) / n 2 nd day SMA (n) = (P s+1 + P s+2 + P s+3 + P n ) / n 3 rd day SMA (n) = (P s+2 + P s+3 + P s+4 + P n ) / n The SMA is calculated using simple arithmetic averaging, covering the last n days of the price chart, hence the name. Equal weight is given to each price. The SMA absorbs all kinds of fluctuations equally and captures all fluctuations equally, and represents a true average of prices, as the SMA does not take any other factors or weights in other than the price for the past n days. Therefore, SMAs may be better suited to provide possible support or resistance points when overlaid together with prices. However, SMAs may tend to not reflect more recent price movements. Since all price values are given equal weight, recent price shocks or trends may be muted (or exaggerated) by previous price trends. This problem does not pose problems with short-term SMAs, but with medium-to-long-term SMA this may cause a bit of a problem, especially if the stock changes volatility every now and then. Exponential Moving Averages Exponential Moving Averages, on the other hand, are calculated are as follows: P = price, t=current time, t-1 = previous day N=number of days in EMA Multiplier = 2 / (N+1) (e.g. if N=10 days, Multiplier = 0.1818) EMA = [P(t) * Multiplier] + [EMA(t-1) * (1-Multiplier)] The first point of the chart of the exponential moving average chart starts with a N-period SMA point, and then calculate the multiplier, which is a constant number that will smooth the EMA curve. The following points can use the EMA formula (with the second point using EMA(t-1) = SMA, and going afterward with previous day s EMAs on subsequent points). Exponential moving averages, as seen above, are more complicated to calculate, but at the same time it reduces the lag associated with SMAs. EMAs do so by applying more weight to recent prices, depending on the number of periods in the moving average. This makes EMAs more sensitive to recent price changes, which means that recent volatility is captured by EMAs better than SMAs can. Furthermore, since more recent price changes are taken into consideration, the EMA is more attuned to capture trends happening in more recent periods.
P age 4 Short-Term vs. Long-Term Lag Moving averages that are set in shorter moving averages move closer to the actual price charts. As seen in the price chart at the side for PLDT [TEL], the 15-day SMA (red) moves closer to the stock price of TEL than the 50-day SMA (blue) does, which by the way moves closer than the 100-day SMA (green). This is because longer-moving moving averages take in more data into the whole equation, resulting in dilution of averages, resulting in a slower-moving curve that takes time to turn. A good metaphor for this is the difference between cars and trucks. Short-term MAs, like cars, are more sensitive to the driver s movements or price changes. As seen above, short-term MAs are more responsive to small volatility or changes, much like how a car will easily move at the slightest movement of the steering wheel. On the other hand, long-term MAs tend to be like trucks which require more movement of the driver before they turn. As seen above, the 100-day moving average (green) is still moving upward despite prices already going down. Short-term MAs have the advantage of accurately reflecting the actual movement of stock prices, so much so that it closely hugs the price curve. This is an advantage for traders, because they can make decisions based on short-term trends reflected on MAs. Since the slope of short-term MAs change quickly, a change in direction of the MA can already indicate a short-term change in trend. It is, however, harder to see long-term trends using short-term MAs. Long-term MAs can be of use in that juncture since long-term MAs reflect trends in the long run, discounting sharper price fluctuations. It then boils down to the objectives of the investor or trader whether to trade short-term or invest in the long run. Interpretation of Crossovers Moving averages, when overlaid with the price chart and other moving average charts of a different period, will tend to cross over each other. These crossovers can help analysts determine, confirm and predict trends and price movements. Double/Moving Average to Moving Average Crossovers Two moving averages having different (but relatively close) periods can be laid down together in the same axes to generate crossovers between the two MAs. This is called the Double Crossover Method, a term coined by John Murphy 1, author of Technical Analysis of the Financial Markets. Double crossovers use one relatively short moving average and another relatively long moving average. The two timeframes, 1 John Murphy s work, Technical Analysis of the Financial Markets is known as the Bible of Technical Analysis as it contains a comprehensive guide to the subject. For those who are deeply interested in using technical analysis, the book is definitely a good read.
P age 5 however, should not be too far away. For example, a short-term crossover is defined using a 5-day EMA and 35-day EMA. A medium or long-term double crossover usually uses a 50-day SMA and 200-day SMA. A bullish crossover occurs when the shorter-moving average cross above the longer-moving average. This is otherwise known as a golden cross. In the example above, when the shorter moving averages (red and green lines for short and long terms, respectively) cross the longer-moving ones (blue and purple, respectively), price trends tend to move bullishly upward. On the other hand, a bearish crossover happens when the shorter-moving average crosses below the longer-moving average, also shown above. This is called a dead cross. Portents look bearish on the earlier periods of August to September, which then reflected downward price movements. Note that, since moving averages are laggard indicators, the crossover signals also tend to predict price movements too late. This is good if there is a strong trend to support, but without a good trend to catch support on, a lot of whipsaws 2 will be produced, in essence removing the use of the crossover signals. Price Crossovers Moving averages can also be overlaid together with the price chart to also generate signals. A bullish signal is created when prices move above the moving average, while a bearish signal is created when price move below the moving average. These can then be put together with double crossovers to create confirmation for trend signals. 2 Whipsaws are defined to be a condition where a security s price that is heading in one direction is followed quickly by a drastic movement in the opposite direction.
P age 6 Support and Resistance Moving averages can finally act as support in an uptrend and resistance in a downtrend. Short-term uptrends can find support using short-term moving averages, usually 20-day simple moving averages, while a short-term downtrend can find resistance in the same. On a side note, 20-day simple moving averages are used to compute Bollinger Bands, another type of overlay indicators. To determine longterm support or resistance, a 200-day moving average is widely used. As seen above, the 15-day SMA acts as a point of reference for resistance on the downtrend, but once prices cross over the 15-day SMA, prices start becoming more bullish until the continuation of the uptrend from December 2011 onwards. After the bullish price crossover around December 2011, DMCI [DMC] prices find support in the 15-day SMA. III. Conclusion There are many other kinds of technical indicators, and this Guide only touches but a speck in the myriad tools that a technical analyst (or an investor with a knack for technical analysis) can utilize. However, no one technical tool can accurately predict how the market will move in terms of prices of stocks. The Relative Strength Index (RSI), Moving Average Convergence-Divergence (MACD) and Stochastic Oscillators %K and %D are many of the commonly-used tools to help analyze, confirm and predict price movements, but rarely are these indicators used alone. When used in conjunction with each other, two or more indicators can be used to confirm signals and provide a base to strategize positioning in stocks and other securities. Again, there is no guarantee of accuracy with regards to indicators, and indicators must be studied carefully alongside one s goal and one s appetite for risk. As always said in the business of stock trading, no (risk of) pain, no gain. Sources: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:introduction_to_tech
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