Introduction 2

I have been in the financial industry for a number of years.  I have seen lots of traders using the most simple ways of charting (hand plotted) to the most complex (using servers) to pump out the data as the market are traded.  In 2007, I was recruited by a hedge fund to do their stock indices hedging.  At one stage, there are 27 computer servers helping me to hedge out my portfolio and indicating which direction the markets are heading. But I still prefer, the easier way of using some of the indicators to point the direction of the market.  I shall discuss the some of the indicators here:

Moving Averages

Types of Moving Averages
There are a number of different types of moving averages that vary in the way they are calculated, but how each average is interpreted remains the same. The calculations only differ in regards to the weighting that they place on the price data, shifting from equal weighting of each price point to more weight being placed on recent data. The three most common types of moving averages are Simple, Linear and Exponential.

Simple Moving Average (SMA)
This is the most common method used to calculate the moving average of prices. It simply takes the sum of all of the past closing prices over the time period and divides the result by the number of prices used in the calculation. For example, in a 10-day moving average, the last 10 closing prices are added together and then divided by 10. As you can see in Figure 1, a trader is able to make the average less responsive to changing prices by increasing the number of periods used in the calculation. Increasing the number of time periods in the calculation is one of the best ways to gauge the strength of the long-term trend and the likelihood that it will reverse.

Figure 1

Many individuals argue that the usefulness of this type of average is limited because each point in the data series has the same impact on the result regardless of where it occurs in the sequence. The critics argue that the most recent data is more important and, therefore, it should also have a higher weighting. This type of criticism has been one of the main factors leading to the invention of other forms of moving averages.

Linear Weighted Average
This moving average indicator is the least common out of the three and is used to address the problem of the equal weighting. The linear weighted moving average is calculated by taking the sum of all the closing prices over a certain time period and multiplying them by the position of the data point and then dividing by the sum of the number of periods. For example, in a five-day linear weighted average, today’s closing price is multiplied by five, yesterday’s by four and so on until the first day in the period range is reached. These numbers are then added together and divided by the sum of the multipliers.

Exponential Moving Average (EMA)
This moving average calculation uses a smoothing factor to place a higher weight on recent data points and is regarded as much more efficient than the linear weighted average. Having an understanding of the calculation is not generally required for most traders because most charting packages do the calculation for you. The most important thing to remember about the exponential moving average is that it is more responsive to new information relative to the simple moving average. This responsiveness is one of the key factors of why this is the moving average of choice among many technical traders. As you can see in Figure 2, a 15-period EMA rises and falls faster than a 15-period SMA. This slight difference doesn’t seem like much, but it is an important factor to be aware of since it can affect returns.

Figure 2

Major Uses of Moving Averages
Moving averages are used to identify current trends and trend reversals as well as to set up support and resistance levels.

Moving averages can be used to quickly identify whether a security is moving in an uptrend or a downtrend depending on the direction of the moving average. As you can see in Figure 3, when a moving average is heading upward and the price is above it, the security is in an uptrend. Conversely, a downward sloping moving average with the price below can be used to signal a downtrend.

         Figure 3

Another method of determining momentum is to look at the order of a pair of moving averages. When a short-term average is above a longer-term average, the trend is up. On the other hand, a long-term average above a shorter-term average signals a downward movement in the trend.

Moving average trend reversals are formed in two main ways: when the price moves through a moving average and when it moves through moving average crossovers. The first common signal is when the price moves through an important moving average. For example, when the price of a security that was in an uptrend falls below a 50-period moving average, like in Figure 4, it is a sign that the uptrend may be reversing.

Figure 4

 
The other signal of a trend reversal is when one moving average crosses through another. For example, as you can see in Figure 5, if the 15-day moving average crosses above the 50-day moving average, it is a positive sign that the price will start to increase.
 

 Figure 5

If the periods used in the calculation are relatively short, for example 15 and 35, this could signal a short-term trend reversal. On the other hand, when two averages with relatively long time frames cross over (50 and 200, for example), this is used to suggest a long-term shift in trend.

Another major way moving averages are used is to identify support and resistance levels. It is not uncommon to see a stock that has been falling stop its decline and reverse direction once it hits the support of a major moving average. A move through a major moving average is often used as a signal by technical traders that the trend is reversing. For example, if the price breaks through the 200-day moving average in a downward direction, it is a signal that the uptrend is reversing.

          Figure 6

Moving averages are a powerful tool for analyzing the trend in a security. They provide useful support and resistance points and are very easy to use. The most common time frames that are used when creating moving averages are the 200-day, 100-day, 50-day, 20-day and 10-day. The 200-day average is thought to be a good measure of a trading year, a 100-day average of a half a year, a 50-day average of a quarter of a year, a 20-day average of a month and 10-day average of two weeks.

Moving averages help technical traders smooth out some of the noise that is found in day-to-day price movements, giving traders a clearer view of the price trend. So far we have been focused on price movement, through charts and averages. In the next section, we’ll look at some other techniques used to confirm price movement and patterns.

Relative Strength Index (RSI)

Introduction

The relative strength index (RSI) is another one of the most used and well-known momentum indicators in technical analysis. RSI helps to signal overbought and oversold conditions in a security. The indicator is plotted in a range between zero and 100. A reading above 70 is used to suggest that a security is overbought, while a reading below 30 is used to suggest that it is oversold. This indicator helps traders to identify whether a security’s price has been unreasonably pushed to current levels and whether a reversal may be on the way.
Use

Overbought/Oversold

Wilder recommended using 70 and 30 and overbought and oversold levels respectively. Generally, if the RSI rises above 30 it is considered bullish for the underlying stock. Conversely, if the RSI falls below 70, it is a bearish signal. Some traders identify the long-term trend and then use extreme readings for entry points. If the long-term trend is bullish, then oversold readings could mark potential entry points.

Divergences

Buy and sell signals can also be generated by looking for positive and negative divergences between the RSI and the underlying stock. For example, consider a falling stock whose RSI rises from a low point of (for example) 15 back up to say, 55. Because of how the RSI is constructed, the underlying stock will often reverse its direction soon after such a divergence. As in that example, divergences that occur after an overbought or oversold reading usually provide more reliable signals.

Centerline Crossover

The centerline for RSI is 50. Readings above and below can give the indicator a bullish or bearish tilt. On the whole, a reading above 50 indicates that average gains are higher than average losses and a reading below 50 indicates that losses are winning the battle. Some traders look for a move above 50 to confirm bullish signals or a move below 50 to confirm bearish signals.

Example

The standard calculation for RSI uses 14 trading days as the basis, which can be adjusted to meet the needs of the user. If the trading period is adjusted to use fewer days, the RSI will be more volatile and will be used for shorter term trades.
Stochastic Oscillator (Fast and Slow)

The stochastic oscillator is one of the most recognized momentum indicators used in technical analysis. The idea behind this indicator is that in an uptrend, the price should be closing near the highs of the trading range, signaling upward momentum in the security. In downtrends, the price should be closing near the lows of the trading range, signaling downward momentum.

The stochastic oscillator is plotted within a range of zero and 100 and signals overbought conditions above 80 and oversold conditions below 20. The stochastic oscillator contains two lines. The first line is the %K, which is essentially the raw measure used to formulate the idea of momentum behind the oscillator. The second line is the %D, which is simply a moving average of the %K. The %D line is considered to be the more important of the two lines as it is seen to produce better signals. The stochastic oscillator generally uses the past 14 trading periods in its calculation but can be adjusted to meet the needs of the user.

 
Slow versus Fast

There are three types of Stochastic Oscillators: Fast, Slow, and Full. The Full Stochastic is discussed later. For now, let’s look at Fast versus Slow. As shown above, the Fast Stochastic Oscillator is made up of %K and %D. In order to avoid confusion between the two, I’ll use %K (fast) and %D (fast) to refer to those used in the Fast Stochastic Oscillator, and %K (slow) and %D (slow) to refer to those used in the Slow Stochastic Oscillator. The driving force behind both Stochastic Oscillators is %K (fast), which is found using the formula provided above.

The Slow Stochastic Oscillator is plotted in the lower box: the thick black line represents %K (slow) and the thin red line represents %D (slow). To find %K (slow) in the Slow Stochastic Oscillator, a 3-day SMA was applied to %K (fast). This 3-day SMA slowed (or smoothed) the data to form a slower version of %K (fast). A close examination would reveal that %D (Fast), the thin red line in the Fast Stochastic Oscillator, is identical to %K (Slow), the thick black line in the Slow Stochastic Oscillator. To form the trigger line, or %D (slow) in the Slow Stochastic Oscillator, a 3-day SMA was applied to %K (Slow).

Use

Readings below 20 are considered oversold and readings above 80 are considered overbought. However, Lane did not believe that a reading above 80 was necessarily bearish or a reading below 20 bullish. A security can continue to rise after the Stochastic Oscillator has reached 80 and continue to fall after the Stochastic Oscillator has reached 20. Lane believed that some of the best signals occurred when the oscillator moved from overbought territory back below 80 and from oversold territory back above 20.

Buy and sell signals can also be given when %K crosses above or below %D. However, crossover signals are quite frequent and can result in a lot of whipsaws.
One of the most reliable signals is to wait for a divergence to develop from overbought or oversold levels. Once the oscillator reaches overbought levels, wait for a negative divergence to develop and then a cross below 80. This usually requires a double dip below 80 and the second dip results in the sell signal. For a buy signal, wait for a positive divergence to develop after the indicator moves below 20. This will usually require a trader to disregard the first break above 20. After the positive divergence forms, the second break above 20 confirms the divergence and a buy signal is given.

Example

Moving Average Convergence/Divergence (MACD)

Introduction

The moving average convergence divergence (MACD) is one of the most well known and used indicators in technical analysis. This indicator is comprised of two exponential moving averages, which help to measure momentum in the security. The MACD is simply the difference between these two moving averages plotted against a centerline. The centerline is the point at which the two moving averages are equal. Along with the MACD and the centerline, an exponential moving average of the MACD itself is plotted on the chart. The idea behind this momentum indicator is to measure short-term momentum compared to longer term momentum to help signal the current direction of momentum.

MACD= shorter term moving average – longer term moving average

When the MACD is positive, it signals that the shorter term moving average is above the longer term moving average and suggests upward momentum. The opposite holds true when the MACD is negative – this signals that the shorter term is below the longer and suggest downward momentum. When the MACD line crosses over the centerline, it signals a crossing in the moving averages. The most common moving average values used in the calculation are the 26-day and 12-day exponential moving averages. The signal line is commonly created by using a nine-day exponential moving average of the MACD values. These values can be adjusted to meet the needs of the technician and the security. For more volatile securities, shorter term averages are used while less volatile securities should have longer averages.

Another aspect to the MACD indicator that is often found on charts is the MACD histogram. The histogram is plotted on the centerline and represented by bars. Each bar is the difference between the MACD and the signal line or, in most cases, the nine-day exponential moving average. The higher the bars are in either direction, the more momentum behind the direction in which the bars point.

As you can see in Figure 10, one of the most common buy signals is generated when the MACD crosses above the signal line (blue dotted line), while sell signals often occur when the MACD crosses below the signal.

Figure 10