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Chapter 8 Trading with Technical Indicators

Technical Indicators tell you when to buy or sell

A Technical Indicator is a mathematical formula applied to the security’s price, volume or open interest. The result is a value that is used to anticipate future changes in prices.

A Technical Indicator is a series of data points derived by applying a formula to the price data of a security. Price data includes any combination of the open, high, low or close over a period of time. Some indicators may use only the closing prices, while others incorporate volume and open interest into their formulas. The price data is entered into the formula and a data point for buy and sell is produced.

Using Technical Indicators

Technical Indicators broadly serve three functions: to alert, to confirm and to predict. An Indicator acts as an alert to study price action. Sometimes, Indicators signal to watch for a break of support. A large positive divergence can act as an alert to watch for a Resistance breakout.

Technical Indicators can be used in combination with other Technical Analysis tools. Investors use indicators to predict the direction of future prices.

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Leading Indicators

These are designed to lead price movements. Benefits of leading indicators are: early signaling for entry and exit points, generating signals and allowing opportunities to trade. Some of the popular leading indicators include Commodity Channel Index (CCI), Momentum, Relative Strength Index (RSI), Stochastic Oscillator and William’s % R.

Price Discounts Everything

Technical Analysis assumes that the company’s fundamentals, along with broader economic factors and market psychology, are all priced into the stock, removing the need to actually consider these factors separately. This only leaves the analysis of price movement, which technical theory views as a product of the supply and demand for a particular stock in the market.

Lagging Indicators

These are the indicators that would follow a trend rather than predicting a reversal. A Lagging Indicator follows an event. These indicators work well when prices move in relatively long trends. They don’t warn you of upcoming changes in prices; they simply tell you what prices are doing (i.e. rising or falling), so that you can invest accordingly. These trends following indicators make you buy and sell late and, in exchange for missing the early opportunities, they greatly reduce your risk by keeping you on the right side of the market. Moving averages and the MACD are examples of trend following, or lagging indicators.

Moving Averages

Moving Average is a widely used Technical Indicator of stock prices that helps to smooth out the volatility in the price action by filtering out the noise from random price fluctuations. A Moving Average is a trend-follow Lagging Indicator as it is calculated taking past data into consideration.  As its name suggests, a Moving Average is an average that moves as old values are dropped out as new values become available. Moving Averages can be employed to identify the current trend in a stock.

Types of Moving Averages

There are 3 types of Moving Averages

a) Simple Moving Average (SMA)

It is obtained by computing the simple average of price data over a defined period of time. In general, we compute the Simple Moving Average based on the closing price of the security as it is considered to have more significance as compared to the rest of price points (Namely open/high/low price for the day). Thus, a 5-day SMA is calculated by adding the closing price of 5 days and dividing this sum by the total number of days (in this case, five).

For example, the 5 days SMA of ITC is calculated as follows:

While calculating the Moving Average after the close of the trading session on July 7, 2017, we can compute the SMA value by taking the closing price of the last 5 trading session, including July 7, 2017, and dividing the same by 5. At close of the next trading session on July 10, 2017, SMA is calculated by excluding the Closing Price of July 3, 2017 by adding the new data point. (Closing Price of July 10, 2017).

As illustrated in the example below, prices gradually decreases from 342.5 to 328.85 over a period of eight days in the same timeframe the 5 Period SMA decreases from 336.44 to 332.79, indicating a lag associated with the Moving Averages. Hence, larger the time period, larger is the lag.

Date Close Price 5 Period SMA
03-Jul-17 342.5
04-Jul-17 337.25
05-Jul-17 331.05
06-Jul-17 337.10
07-Jul-17 334.30 336.44
10-Jul-17 333.30 334.60
11-Jul-17 330.40 333.23
12-Jul-17 328.85 332.89
7tH July SMA = 336.44 = (342.50+337.25+331.05+337.10+334.30)
10th July SMA = 334.6 = (337.25+331.05+337.10+334.30+333.30)
11th July SMA = 334.6 = (331.05+337.10+334.30+333.30+330.40)
12th July SMA = 332.89 = (337.10+334.30+333.30+330.40+328.85)

b) Weighted Moving Average (WMA)

Weighted Moving Average moves a step ahead from Simple Moving Average. Here, we assign a weight to each value, with a bigger weight assigned to the most recent data points as they are more relevant than historical data points. The sum of weights should add up to 1 (or 100%). As new data points are added, the new weights will align accordingly. In contrast, in Simple Moving Average, each value is assigned the same weight. Ideally, traders calculate WMA on the basis of closing price.

The Weighted Moving Average is calculated by multiplying the given price by its assigned weight and then dividing the sum by total number of days. The weights assigned are subjective in nature, and it is based on the discretion of the trader. Because of its calculation methodology, WMA will follow prices more closely than a corresponding SMA. The WMA reduces the lag effect to an extent.

ITC

Date Close Price Weights WMA
03-Jul-17 342.5 0.07
04-Jul-17 337.25 0.13
05-Jul-17 331.05 0.20
06-Jul-17 337.10 0.27
07-Jul-17 334.30 0.33 335.34
10-Jul-17 333.30
11-Jul-17 330.40 332.89
12-Jul-17 328.85 332.89
7tH July SMA = 335.34 = (342.50*0.07+337.25*0.13+331.05*0.20+337.10*0.27+334.3*0.33)
10th July SMA = 334.29 = (337.25*0.07+331.05*0.13+337.10*0.20+334.3*0.27+333.3*0.33)
11th July SMA = 332.89 = (331.05*0.07+337.10*0.13+334.30*0.20+333.3*0.27+330.4*0.33)
12th July SMA = 331.43 = (337.1*0.07+334.30*0.13+333.30*0.20+330.4*0.27+328.85*0.33)

c) Exponential Moving Average (EMA)

Exponential Moving Average differs from the simple and weighted moving average as an EMA is calculated by taking all the historical data points since the inception of the stock. Ideally, to calculate 100% accurate EMA, we should make use of all the closing prices right from the time of the listing of stock.

Calculation of the EMA is a 3 step process

Step 1: Since it is not practical to calculate historical data right from the inception of the stock, we use the SMA value as the initial EMA value. So, a Simple Moving Average is used as the previous period's EMA in the first calculation.

Step 2: We calculate the weighting multiplier by dividing 2 by the sum of total periods and 1.

Step 3: We subtract the EMA of the previous day from the current closing price, and multiply this number by the multiplier. We then add this product with its previous period EMA to find out the final EMA value.

Therefore, the current EMA value will change depending on how much past data we use in our EMA calculation. The more data points we use, the more accurate our EMA will be. The goal is to maximize accuracy while minimizing calculation time.

Initial EMA value = 5-period SMA

Weighting Multiplier= (2 / (Time periods + 1)) = (2 / (5 + 1) ) = 0.3333 (33.33%)

EMA = {Close – EMA of previous day} x multiplier + EMA (previous day).

A 5-period EMA applies a 33.33% weighting to the most recent prices. A 10-period EMA has a weighting multiplier of 18.18%. The shorter the time period, larger the weighting multiplier will be. We notice that as the time period doubles, the weighting multiplier drops ~50%.

Date Close Price 5 Period SMA Weighting factor 5 Period EMA
03-Jul-17 342.5
04-Jul-17 337.25
05-Jul-17 331.05
06-Jul-17 337.10
07-Jul-17 334.30 336.44 336.44
10-Jul-17 333.30 334.60 0.3333 335.39
11-Jul-17 330.40 333.23 0.3333 333.73
12-Jul-17 328.85 332.793 0.3333 332.10
7tH July SMA = 336.44 = 5 Period SMA = 336.44
10tH July SMA= 335.39 = (333.30-336.44) x0.33 + 336.44
11tH July SMA = 333.73 = (330.40-335.39) x0.33 + 335.39
12tH July SMA = 336.44 = 5 Period SMA = 336.44

Comparison of the 3 Moving Averages

As we see by comparing the computation methodology of the 3 Moving Averages, different values are generated. EMA is most commonly used by traders.

Moving Averages SMA WMA EMA
Advantages
  • 1) Smoothened Average
  • 2) Less prone to whipsaw
  • 3) Best average to consider for support & resistance
1)Reduction in price lag, so can be implemented for short term trading
  • 1) Reduction in price lag, hence can be used for short term trading
  • 2) No omission in price data points
Disadvantages
  • 1) Has maximum price lag
  • 2) Assigns same weight to all price data.
  • 3) Omission of previous data points leading to all price data not made use of
  • 1) Omission of previous data points leading to all price data not made use of
  • 2) Chance of whipsaw
1)Chance of whipsaw

Moving Average Value comparison – The following table represents a comparison between the different values of the 3 types of Moving Averages over the same period of time

Date Close Price 5 Period SMA 5 Period WMA 5 Period EMA
03-Jul-17 342.5
04-Jul-17 337.25
05-Jul-17 331.05
06-Jul-17 337.10
07-Jul-17 334.30 336.44 335.34 336.44
10-Jul-17 333.30 334.60 334.29 335.39
11-Jul-17 330.40 333.23 332.89 333.73
12-Jul-17 328.85 332.89 331.43 332.10

Graphical comparison on the 3 moving averages.

(Blue-5 Period EMA, Green-5 Period WMA, Pink-5 Period SMA)

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As we seen in the above graph, when there is a sharp correction in price as in the case of ITC, EMA and WMA reacted the most since they are assigned a higher weight to the most recent prices as compared to the SMA.

Applications of Moving Average

Trend Identification

Traders use moving averages to identify the trend in a stock. A rising 200day Moving Average reflects that the long term trend is up and stock can be traded with a positive bias. Similarly, a falling 200day Moving Average reflects a long term downtrend and hence we can consider shorting the stock or refraining from investing in it.

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(Blue-10 Period EMA, Green -89 Period EMA, Pink 200 Period EMA)

From the above graph, we can clearly see that L&T Fin is in a long term uptrend, the short term and medium term averages are trading above its long term, 200day Moving Average which is also showing an upward momentum. A price dip towards its medium term average can be considered as a buying opportunity.

Buy/Sell signals based on crossover

A buy signal is generated when a bullish crossover occurs i.e. the short term Moving Average crosses the long term Moving Average, popularly referred to as a golden cross. For example, when the 89day EMA crosses above the 200day EMA, a bullish trade can be initiated. On the other hand, a bearish dead cross occurs when the short term Moving Average crosses below the long term moving average. The signals generated tend to occur with a lag as we make use of 2 Lagging Indicators. The best trading opportunities are obtained in a trending market as compared to the sideways market wherein whipsaws or false signals are generated.

Price 89 Period EMA Action /View Technical Term
Trading Above 200EMA Crosses above 200EMA Bullish Golden cross
Trading Below 200EMA Crosses below 200EMA Bearish Dead cross
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From the above graph we see how moving averages can be used to generate trading signals

Moving Averages can also be used to generate signals with simple price crossovers. A bullish signal is generated when prices move above the Moving Average. A bearish signal is generated when prices move below the Moving Average. Advantage of price signals is that the time lag is reduced and traders are able to react at an early stage.

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As in the Fortis Ltd case shown above, traders could have initiated a short position or could have closed their long positions when the stock price closed below its 200day EMA. Consequently, a huge surge in trading volumes with MACD Histogram getting into the negative territory indicated a change in momentum which gave added information to traders to take a bearish view, resulting in a fall in stock price by 18%.

Support & Resistance Levels

Moving Averages also tend to act as support and resistance levels. A stock in a long term uptrend could find support near its medium term EMA during a pullback, similarly a stock in a long term downtrend could face resistance near is medium term moving average during any bounce back. In fact, some moving averages may offer support or resistance simply because it is widely used by many traders. As an example, a trader may not short a stock if it is trading near its 200day EMA because of the fear that other traders may be using it as a buying zone.

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In the above example of JSW Steel, we see how the stock has taken support along its medium term 89day EMA on multiple occasions and has acted as a good support level to purchase the stock.

Moving Averages in sync with Candlestick pattern

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Moving averages can also be traded in tandem with candlestick patterns. In the above chart of Bata India Ltd, the bullish candlestick pattern can be traded with added confidence as it coincides with the support of 200day EMA.

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In the above chart of United Spirits Ltd, the buy signal generated by the bullish crossover coincides with a cup and handle breakout on the daily chart, affirming a bullish bias in the stock.

Difference between technical and fundamental analysis

Moving averages are used based on trading horizon.

Moving Average Trading Time frame
5 period MA Short term
13 period MA Short term
50 period MA Medium Term
89period MA Medium Term
200 period MA Long Term

Observations on Moving Average

  • It is used in a trending market to give clear trend direction by eliminating the noise.

  • In case of a sideways market, Moving Average would lead to whipsaws making the use of other indicators like RSI and Stochastic more helpful.

  • Signals generated by moving averages tend to have a lag.

  • It is used best when combined with technical indicators and price patterns.

Bollinger Bands

Bollinger bands, created by John Bollinger, are a Trending Indicator that can show you not only in what direction the stock price is going, but also how volatile the price movement of the stock is. Bollinger bands consist of two bands—an upper band and a lower band—and a Moving Average and are generally plotted on top of the price movement of a chart.

How Bollinger bands are constructed?

Bollinger bands are typically based on a 20-period Moving Average. This Moving Average runs through the middle of the two bands. The upper band is plotted two standard deviations above the 20-period moving average. The lower band is plotted two standard deviations below the 20-period moving average.

A standard deviation is a statistical term that measures how far various closing prices diverge from the average closing price. Therefore 20-period Bollinger bands tell you how wide, or volatile, the range of closing prices has been. The more volatile the stock price, the wider the bands will be. The less volatile the stock price, the narrower the bands will be.

Bollinger band trading signal

Entry signal—when the bands widen and begin moving in opposite directions after a period of consolidation, you can enter the trade in the direction the price was moving when the bands began to widen.

Exit Signal- when the bands narrow the price of the stock moved away from the breakout turns and starts moving back toward the current price of the stock set a trailing stop loss to take you out of the trade if the trend reverses.

Exit Signal- when the bands narrow the price of the stock moved away from the breakout turns and starts moving back toward the current price of the stock set a trailing stop loss to take you out of the trade if the trend reverses.

Bollinger band example:

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Benefits of Bollinger bands

  • They help you identify price trend.

  • They identify current market volatility.

Moving Average Convergence Divergence (MACD)

The Moving Average Convergence Divergence (MACD) is an oscillating indicator that shows you when trading momentum changes from bullish to bearish and vise versa. The MACD can also show you when traders are becoming over-extended, which usually results in a trend reversal for the stock price.

The MACD is usually plotted below the price movement on a chart.

How the MACD is constructed

The Moving Average Convergence Divergence is constructed based on a series of moving averages and how they relate to one another. The standard MACD looks at the relationship between a stock price 12-period and 26-period Exponential Moving Average. If the 12-period Moving Average is above the 26-period Moving Average, the MACD line will be positive. If the 12-period Moving Average is below the 26-period Moving Average, the MACD line will be negative.

The MACD line is accompanied by a trigger line. This line is a 9-period exponential moving average of the MACD line.

MACD trading signal

Entry signal—When the MACD crosses above the trigger line, you can buy the stock price knowing that momentum has shifted from being bearish to being bullish.

Exit signal—When the MACD crosses below the trigger line, you can sell the stock price knowing that momentum has shifted from being bullish to being bearish.

Benefits of MACD

  • They help you identify price trend.

  • They identify current market volatility.

MACD example:

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Slow Stochastic

The Slow Stochastic is an oscillating indicator developed by George Lane that can show you when investor sentiment changes from being bullish to bearish and from being bearish to bullish. The Slow Stochastic can also show you when trades are being over-extended, which usually results in a trend reversal for the stock price.

How the Slow Stochastic is constructed

The Slow Stochastic consists of two lines—%K and %D—that oscillate in a range between 0 and 100.

%K is constructed based on where the current closing price of a stock is in relation to the range of closing prices for that same stock price in the past. %D is a moving average of %K.

If the closing price of the stock price is near the top of the range of past closing prices, the %K line (followed by the %D line) will move higher.

If the closing price of the stock price is near the bottom of the range of past closing prices, the %K line (followed by the %D line) will move lower.

Slow Stochastic trading signal

The Slow Stochastic produces trading signals as it crosses in and out of its upper and lower reversal zones. The upper reversal zone is the area of the indicator that is above 80. The lower reversal zone is the area of the indicator that is below 20. When %K is above 80, it shows the stock price may be overbought and may be reversing trend shortly. When %K is below 20, it shows the stock price may be oversold and may be reversing trend shortly.

Entry signal—when %K crosses from above 80 to below 80, you can sell the stock price knowing that investor sentiment toward the stock price has shifted from being bullish to being bearish.

When %K crosses from below 20 to above 20, you can buy the stock price knowing that investor sentiment toward the stock price has shifted from being bearish to being bullish.

Exit signal—when %K reverses direction after having crossed either above 20 or below 80 and crosses over %D, you can exit your trade knowing that investor sentiment is changing direction again.

Slow Stochastic Example

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Benefits of the Slow Stochastic

  • It helps you identify when investor sentiment towards the specific stock changes

  • It helps confirm the strength of current trends

Retracement

It is the correction that occurs in the price of a share.

Market trend Retracement will be in
Falling upward direction
Rising downward direction

Normally, it is seen 38.2%, 50% and 61.8% are good retracement levels and the markets have a tendency to take support in case of an uptrend and face resistance in case of a downtrend at or around these levels.

These levels also give an indication of the current trend or a likely change in the same. Although the retracement levels work more often than not, there could be times where prices may move beyond the normal retracement levels.

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Retracement Example

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Stop Loss

Stop loss can be defined as an advance order to sell an asset when it reaches a particular price point. Stop loss is used to limit loss or gain in a trade. The concept can be used for short-term as well as long-term trading. It is used so that the trader does not suffer unlimited losses.

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Key takeaways

  • Technical Indicators broadly serve three functions: to alert, to confirm and to predict.

  • Technical Indicators are of two types leading and lagging.

  • Capital gains from equity funds and debt funds are considered long-term if the investment horizon if more than 1 year and 3 years respectively.

  • Moving Averages and the MACD are examples of lagging indicators.

  • There are 3 types of moving averages: SMA, WMA, EMA.

  • Bollinger bands expand and contract based on the volatility in a scrip

  • MACD is used to indicate change in trading momentum from bullish to bearish and vice versa.

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