What are Stock Market Indicators, their purpose and their types?

Basically, stock market indicators are used to identify inherent strength or weakness in the stock prices. Indicators have fascinated traders and technical analysts since the beginning. In this chapter, we will learn about the construction and proper application of oscillators and various overlay indicators to help better forecast potential reversals and breakouts in the markets.


Defining Indicators & Oscillators

Classification of Oscillators and Indicators

Indicators are subdivided into two categories:

  1. Overlay Indicators: Overlay indicators are plotted on the same price chart as price action, as well as window oscillator action. They provide various support and resistance at various price and oscillator levels. Please make a note that the window oscillator when plotted on the price chart does not provide support and resistance. For example, a standard Moving Average Convergence-Divergence(MACD) or Relative Strength Index(RSI) oscillator plotted on the price chart itself will not interact with price in any meaningful way. Whereas overlay indicators plotted on window oscillator action do represent a valid and meaningful overlay indicator and as such provide a valid barrier to oscillator action. For example, an overlay indicator like Bollinger Band plotted on an RSI window-based oscillator would indicate levels of overbought and oversold in the RSI. There are four types of overlay indicators, namely:
  • Numerically Based Overlay: These overlays forecast future price barrier levels mathematically. For example, when we apply Fibonacci projection upside price target of 161.8% for the range of Price A to Price B from C, then we add 1.618% of the AB range to the price point C for target calculation.
  • Horizontally Based Overlays: These overlays forecast future price barrier levels based on prior resistance and support levels. In this case, the forecast is independent of time. Price gaps are also horizontal overlay indicators because they provide us with potential future support and resistance. It should be noted that some numerically based indicators such as the Fibonacci ratio and Gann’s Square of Nine price projections may also be classified as horizontally based overlays, unlike numerically based indicators such as moving averages and Bollinger bands.
  • Geometrically Based Overlays: These overlays forecast future price barrier levels via the drawing of trendlines or lines that are projected from particular peaks and troughs, also referred to as price inflexion points. Since they are diagonal, forecasts of potential barrier levels based on these overlays will vary over time, and the forecast of potential barrier levels will depend on when price tests these overlays. In other words, the forecasts of potential future price barrier levels depend on the geometry of the barrier created.
  • Algorithmically Based Overlays: These overlays forecast future price barrier or breakout levels based on a specific sequence of bar or candlestick action. Some examples include two‐bar breakouts.

2. Window Oscillators: These indicators are mathematically derived from the data like Open, High, Low and Close, volume & open interest. Basically there are two types of window oscillators:

  • Bounded Oscillators: Window oscillators whose readings range from 0 to 100 are termed bounded oscillator. It provides a meaningful way of relative levels of overbought and oversold, between different stocks or markets over the same number of periods. The disadvantage is that during strong trend action, the readings tend to remain at overbought or oversold for extended periods and such provide little information during the trending market.
  • Unbounded Oscillators: The readings of unbounded oscillators have no upper or lower limit. Note that although unbounded window oscillators have no theoretical upper or lower limit, some unbounded window oscillators do have a lower limit of zero, such as volume, ADX, Bollinger Bandwidth, and average true range (ATR). These window oscillators are therefore referred to as being semi‐bounded. The main advantage of employing an unbounded oscillator is that it provides historical levels of overbought and oversold. These historical levels of overbought and oversold are specific to a particular stock or market at a selected timeframe, and care should be taken when used to compare the degree of overextension between different stocks or markets. See Figure 1.1 for comparisons between bounded and unbounded window oscillators. Notice that overlays may be applied to window oscillators as well.
Indicator Types
Figure 1.1 - Overlay, Bounded, and Unbounded Technical Indicators

Classification of Oscillators and Indicators

Chart scaling only affects indicators that are geometrically based. I does not affect mathematically calculated window oscillators. For example if a moving average is plotted of Nth data on linear scale its value will remain same on the algorithmic scale too. Refer Figure 1.2 for classification of technical indicators.

Figure 1.2 - Classifiction of Technical Indicators

Horizontal based support & resistance are scale-invariant as there is no time element involved in the forecast. Whereas, unlike support and resistance, trendline forecast of potential future barrier levels are time-dependent. The potential support provided by an uptrend line depends on when the price tests it. The more time has elapsed, the higher will be the trendline support level when tested by price. Trendlines are a form of geometrically based overlay indicators. Unfortunately, geometrically based overlays are the only group of indicators that are not scale-invariant. Forecasted prices vary with the scaling employed. For example, two trendlines based on different scaling would forecast different future support and resistance levels. In figure 1.3 we can clearly see the difference of trendline on two different scales.

Up-Trendline Breakout Variance Depending upon the Type of Scale
Figure 1.3 - Geometrically Based Overlays Displaying Non‐Scale Invariance

Static and Dynamic Overlay Indicators

Finally, a distinction has to be made between static and dynamic overlay indicators and their relationship with numerically, horizontally, geometrically, and algorithmically based overlay indicators. Static overlay indicator forecasts are not dependent on the time element, and as such include all horizontally and algorithmically based overlays, as well as many numerically based overlays. The forecasted price reaction level does not change over time unless it is invalidated and a new forecast is required. Hence all horizontal overlay indicators like support and resistance are clearly static overlay indicators. Static overlays include:

  • Prior support and resistance levels.
  • Fibonacci projection, retracement, extension, and expansion levels.
  • Gann Square of Nine price projection levels.
  • Floor Trader’s Pivot Points support and resistance levels.
  • The risk to reward ratio price target levels (price targets often represent levels of potential support and resistance)
  • Parabolic SAR levels.
  • Chandelier Exit based price levels.
  • Horizontal Channel-based price levels.

Dynamic overlay indicator forecasts are dependent on the time element and as such include all geometrically based overlay indicators and some numerically based overlays. The forecasted price level varies over time. The exact forecasted price reaction level is only known once price tests or is in proximity to the overlay. Some dynamic overlays include:

  • Bollinger Bands.
  • Moving Averages.
  • Moving Average Bands.
  • Keltner Bands.
  • Ichimoku Overlays.
  • Linear Regression Bands.
  • Andrew’s Pitchfork.
  • Trendlines.
  • Rising and Falling Channels.
  • Chart Patterns.

Eight Ways to Analyze an Oscillator

There are eight basic ways to use a window oscillator to indicate potential buy (bullish) and sell(bearish) signals:

  1. OBOS Overextensions.
  2. Equilibrium & Zero Line Crossover.
  3. Signal line Crossover.
  4. Price Oscillator and Oscillator – Oscillator Divergence.
  5. Geometrically Based Oscillator Pattern Analysis.
  6. Numerically Based Oscillator Pattern Analysis.
  7. Horizontally Based Oscillator Pattern Analysis.
  8. Oscillator on Oscillator Analysis.

It should be noted that many practitioners require that buy and sell reversal signals based on window oscillators require price confirmation, that is, price is required to breach an overlay indicator. Just because an indicator issues a bearish or bullish reversal signal does not necessarily mean that prices have reversed or broken through a barrier. The signals may be based on oscillator action, but the trigger for entry or exit must always be based on price action. Oscillator values breaching overlays do not represent price confirmation but are regarded as merely a signal of potential bullishness or bearishness. For a valid price confirmation, the price may breach any of the following overlays:

  • Numerically based overlays.
  • Horizontally based overlays.
  • Geometrically based overlays.

Nevertheless, the most reliable and popular overlays used for price confirmation are prior support and resistance levels, simple trendlines, moving averages, and chart pattern breakouts or reactions.

OBOS Overextended Levels

Overbought and oversold (OBOS) levels are indicative of overextensions in price, where a potential reversal in price is expected. It should be noted that an overbought signal is first and foremost an indication of a strong uptrend in effect, with a high probability of a potential bearish reversal. Similarly, an oversold signal is first and foremost an indication of a strong downtrend in effect, with a high probability of a potential bullish reversal. As such, price confirmation is required when trying to identify reversals. These overextensions may occur at expected percentage levels or may be formed at levels specific to the stock or market itself. Overextensions may be identified as follows:

For Bounded Oscillators:

  • Overbought is represented as relatively high percentage readings, usually at or above 70 or 80 per cent (depending on the oscillator employed).
  • Oversold is represented as relatively low percentage readings, usually at or below 20 or 30 per cent (depending on the oscillator employed).

For Unbounded Oscillators:

  • Overbought is represented as historical or significant peaks in the oscillator.
  • Oversold is represented as historical or significant troughs in the oscillator.

The overbought(OB) and oversold(OS) levels for two popular bounded oscillators are defaulted at:

  • Stochastic: OB(80 percent) OS(20 Percent)
  • RSI: OB(70 percent) OS(30 Percent)
Various Signals generated by oscillator
Figure 1.4 - Various Buy (Bullish) and Sell (Bearish) Signals Generated by Divergence,  Signal Crossovers, Chart Patterns, and Overextensions.

The OB and OS levels for unbounded oscillators are:

  • CCI Oscillator: OB (+100) OS (−100)—note that these values are measures of volatility. This oscillator coincides well with the Bollinger band 1 standard deviation values. The ± 200 levels also match the Bollinger band ± 2 standard deviations (or sigma) bands.
  • Standard Deviation Oscillator: OB (+1 or +2 Sigma) OS (−1 or −2 Sigma).
  • Most unbounded oscillators do not have widely accepted levels of overextension. This is because such levels are specific to a particular stock or market historical oscillator action.

Figure 1.4 depicts various signals being generated by oscillator divergence, chart patterns, overextensions, and signal crossovers.

Figure 1.5 depicts a historically significant overbought level on the MACD unbounded oscillator, on the daily chart of Zee Entertainment Ltd. Notice that every time the MACD tests or exceeds the overbought level, this is was followed by a reversal or correction in price, as seen at timelines 1 to 3. These overextension levels are best determined via visual inspection.

MACD Overbought Region
Figure 1.5 - Overbought at Historically Significant MACD Levels on the Daily Chart  of Zee Entertainment Ltd.

Equilibrium and Zero Line Crossovers

Another way a window oscillator can indicate buy or sell signals is via the crossing of the equilibrium value, which is represented by any of the following penetrations:

  • Fifty percent level crossing in bounded oscillators.
  • Zero Line crossing in unbounded oscillators.
Support According to Oversold Levels of Stochastic Oscillator
Figure 1.6 - Oversold on the Stochastic Oscillator on the Daily Chart of ACC.

Bounded oscillators fluctuate between 0 and 100 percent and hence their central or equilibrium value would be at the 50 percent level. Unbounded oscillators have no upper and lower limits, and as such the zero levels would best represent the central or equilibrium level. Signals are indicated as follows:

  • Oscillator crossing above its equilibrium level is a buy (bullish) signal.
  • Oscillator crossing below its equilibrium level is a sell (bearish) signal.

It must be noted that these only represent signals and should not be regarded as triggers for entry. The main reason why oscillator signals should be regarded as mere indications of potential sentiment and not actionable signals is mainly due to the possibility of misrepresentation resulting from a phenomenon referred to as divergence. With divergence, higher highs in price may be accompanied by lower highs in the oscillator, causing market participants to initiate shorts or liquidate positions in the market without evidence that the price is actually reversing. Figure 1.7 depicts the bounded RSI 50 percent equilibrium level crossovers generating buy and sell signals on the daily chart of ACC. Notice that, using the defaulted lookback periods for the RSI and the commodity channel index (CCI), the buy and sell signals generated by both oscillators are nearly identical. The unbounded CCI generated signals via its zero-level crossings.

Figure 1.7 - RSI 50 Percent Level Crossovers Generating Buy and Sell Signals on the Weekly Chart of ACC.

Signal Line Crossovers

Buy and sell signals may also be generated via signal line crossovers. A signal line is a smoothed version of the original oscillator, that is, it is a moving average of the original oscillator values. As such, it will lag the original oscillator action. Signals are indicated as follows:

  • Oscillator crossing above its signal line is a buy (bullish) signal.
  • Oscillator crossing below its signal line is a sell (bearish) signal.

It is important to note that many practitioners consider an upside crossover (oscillator crossing above its signal line) to be significantly more bullish if it occurs in proximity to an oversold level. Similarly, a downside crossover (oscillator crossing below its signal line) would be regarded as significantly more bearish if it occurs around an overbought level. The defaulted signal line for the MACD is usually a nine‐period exponential moving average of the MACD. Figure 1.8 depicts MACD signal line crossovers generating buy and sell signals on the daily chart of ACC, as seen at the vertical timelines. We see that the MACD signal line crossovers are fairly effective in forecasting tops and bottoms in the stock.

MACD Buy Sell Signal
Figure 1.8 - MACD Signal Line Crossovers Generating Buy and Sell Signals on the  Weekly Chart of ACC.

Price‐Oscillator Divergence

The divergence between price and the oscillator indicates potential bearish or bullish reversals. Signals are indicated as follows:

  • Standard bullish divergence between price and the oscillator is a bullish setup awaiting price confirmation. It is represented by lower troughs in price being accompanied by higher troughs in the oscillator. A potential upside reversal is expected.
  • A standard bearish divergence between price and the oscillator is a bearish setup awaiting price confirmation. It is represented by higher peaks in price being accompanied by lower peaks in the oscillator. A potential downside reversal is expected.
  • Reverse bullish divergence between price and the oscillator is a bullish setup awaiting price confirmation. It is represented by higher troughs in price being accompanied by lower troughs in the oscillator. A potential upside continuation is expected.
  • A reverse bearish divergence between price and the oscillator is a bearish setup awaiting price confirmation. It is represented by lower peaks in price being accompanied by higher peaks in the oscillator. A potential downside continuation is expected.
Standard Divergence Example
Figure 1.9 - Example of Standard Bullish & Bearish Divergence on Daily Chart of Tatamotors.

In Figure 1.9, we observe bullish and bearish divergences forecasting potential reversals with uncanny accuracy on the daily Tata motor chart. Please refer to the next technical post for more on divergence. Note that although divergence can also be identified between oscillators, it is the divergence between price and an oscillator that is regarded as more pertinent. Figure 2.0 shows the example of Reverse Bullish Diveregence.

Figure 2.0 - Example of Reverse Bullish Divergence

Geometrically Based Oscillator Pattern Analysis

Buy and sell signals may be derived from applying geometrically based overlay indicators to window oscillators. Overlays that are usually employed include:

  • Trendlines
  • Channels
  • Chart Patterns
  • Apex Reactions

Signals are indicated as follows:

  • An oscillator breaching a geometrically based overlay to the upside is a buy (bullish) signal.
  • Oscillator testing a geometrically based overlay from below is a sell (bearish) signal.
  • An oscillator breaching a geometrically based overlay to the downside is a sell (bearish) signal.
  • Oscillator testing a geometrically based overlay from above is a buy (bullish) signal.

See Figure 2.1, We see the geometrical overlays, on the momentum oscillator (MOM), generating buy and sell signals upon violation of trendlines and chart patterns on the Daily Chart of the LICHSGFIN.

Figure 2.1 - Oscillator Chart Pattern‐Based Buy and Sell Signals

Numerically Based Oscillator Pattern Analysis

Just as for geometrically based overlays, buy and sell signals may also be derived from applying numerically based overlay indicators to window oscillators. Overlays that are usually employed include:

  • Bollinger Bands
  • Moving Averages
  • Moving Average Band
  • Fibonacci Levels
  • Linear Regression Bands

Signals are indicated as follows:

  • An oscillator breaching a numerically based overlay to the upside is a buy (bullish) signal.
  • Oscillator testing a numerically based overlay from below is a sell (bearish) signal.
  • An oscillator breaching a numerically based overlay to the downside is a sell (bearish) signal.
  • Oscillator testing a numerically based overlay from above is a buy (bullish) signal.

See Figure 2.2, we observe that the RSI is finding support at the lower Bollinger band. Prices also bottomed every time the RSI found support at the lower band. Notice that the actual oversold was a fair distance below the Bollinger band oversold levels. This method effectively catches bottoms in a rapidly rising market, without requiring the RSI to decline all the way down to test the 30 percent oversold line.

Buy Sell Signal of Bollinger Band when overlap with RSI
Figure 2.2 - Oscillator Chart Pattern‐Based Buy and Sell Signals on the Daily Chart of LICHSGFIN.

Horizontally Based Oscillator Pattern Analysis

Buy and sell signals may also be derived from applying horizontally based overlay indicators to window oscillators. Hence, practitioners look for prior support and resistance in the oscillators for potential bullish and bearish indications. Signals are indicated as follows:

  • An oscillator breaching a resistance level is a buy (bullish) signal.
  • An oscillator displaying resistance at a prior oscillator resistance level is a sell (bearish) signal.
  • An oscillator breaching a support level is a sell (bearish) signal.
  • The oscillator displaying support at a prior oscillator support level is a buy (bullish) signal.

See figure 2.3 for example.

Oscillator Based Support and Resistance
Figure 2.3 - Oscillator Support- and Resistance‐Based Buy and Sell Signals on the Daily Chart of JSWSTEEL

Oscillator‐on‐Oscillator Analysis

Buy and sell signals may also be derived from the interaction between window-based oscillators. We have already seen an example of indicator‐on‐oscillator analysis in Figure 2.2 where the RSI reacted at the upper and lower Bollinger bands. Similarly, oscillator‐on‐oscillator analysis may also render useful information. One such example is the Stochastic RSI, where the stochastic of RSI values are calculated and plotted as a window oscillator. Practitioners look for potential bullish and bearish indications via any of the previous seven approaches to analyzing an oscillator. In Figure 2.4, notice that the stochastic RSI pinpoints potential buying dips (indicated at the dotted time lines) in an uptrend on the daily chart of Nifty Futures.

Figure 2.4 - Oscillator‐on‐Oscillator Analysis on the Daily Chart of Nifty Future.

Cycle Period, Multiple Timeframes, And Lagging Indicators

Optimization of the Oscillator Using the Dominant Half-Cycle Duration:

When oscillators and most overlays are tuned to the dominant half-cycle time, they produce more efficient buy and sell signals. This means the oscillator will issue buy and sell signals based on the wave cycle of interest rather than its default lookback time, which can generate too few or too many signals depending on the wave cycle exchanged.

The half-cycle lookback period can be calculated in three ways, using any of the following formulas, where N is the period of the dominant cycle.

  • (N+1)/2, and round up if N is an even number;
  • (N/2) + 1, and round down if N is an odd number;
  • (2N+3)/4, round to the nearest integer.

Assume, for example, that we want to use stochastic to generate buy and sell signals. According to Figure 2.5, the average dominant cycle period on the daily JSWSTEEL chart in 2020 was 53 days (where a new cycle trough was formed at the same wave degree). Using the second formula above, the half-cycle would be (53/2) + 1 = 27.5 days. As a result, we set our stochastic lookback period to 26 periods. We can see that it perfectly tracked and forecasted cycle troughs, including troughs that occurred after the sample period was taken (out of sample data). When compared to the cycle tuned oscillator, the standard 14-period default setting produced far too many oversold signals.

Figure 2.5 - Cycle‐Tuned Stochastic Tracking the Cycle Troughs Effectively On The Daily JSWSTEEL Chart.

Oscillator Analysis on Multiple Timeframes (MTF):

Oscillators and overlays from different timeframes can be plotted on the same chart for a more accurate comparison of oscillator action and its relationship to price action. Assume we want to create a chart that shows the 5minute, 15minute, and 1hour RSI. As a starting point, we use a 5-minute interval chart. To calculate the lookback periods of the higher timeframe RSIs, we must first determine the multiplying factor (MF).

  • MF (for a 15 mins interval chart) = 15 min/5 min = 3
  • MF (for a 60 mins interval chart) = 60 min/5 min = 12

So, we get our 15min RSI by multiplying the RSI standard default lookback period by 3, yielding 14 X 3 = 42 periods. As a result, a 42 period RSI on a 5min chart represents a 15min RSI. Similarly, an hourly RSI is displayed on a 5min chart if the lookback period is increased to 14 12 = 168 periods. For oscillators such as the MACD, we must increase all variables using the MF. The same method is used to overlay multiple timeframes moving averages and other overlays on charts. To display an hourly 20period moving average on a 5min chart, for example, we must plot a 20 12 = 240 period moving average. On the hourly chart, this would be a 20-period moving average. Although they both essentially track the same average, there will be very small differences between an actual 20period moving average on an hourly chart and a 240period moving average on a 5min chart.

Lagging Indicators:

Oscillators, which are derived primarily from price, typically lag price action. However, this does not rule out the possibility of early warning signs. Divergence is a type of oscillator analysis that is thought to be a leading indicator. Another example of a leading indicator is the early reversals that occur in momentum oscillators, which usually reverse or slow down before the price. Overlays that are horizontally or geometrically based are also types of leading indicators. Not all numerically based overlays are predictive. Moving averages, for example, are not a type of leading indicator, but Fibonacci projection, extension, expansion, and retracement are.


Trend Trading Using Oscillators

Oscillators can be used to time continuations and breakouts in the direction of the current trend. It is always preferable to trade in the direction of the larger current trend. Using oscillators, we look for the following signals to join and trade in the direction of the larger existing or dominant trend:

In an existing uptrend, a buy signal is represented as:

  • Oscillator crossing above the equilibrium line.
  • Oscillator crossing above its signal line.
  • Oscillator is at oversold or rising back above oversold levels.
  • Oscillator displaying bullish standard or reverse divergence with price.
  • Oscillator violating a chart pattern or trendline to the upside.

In an existing downtrend, a sell signal is represented as:

  • Oscillator crossing below the equilibrium line.
  • Oscillator crossing below its signal line.
  • Oscillator is at overbought or declining back below overbought levels.
  • Oscillator displaying bearish standard or reverse divergence with price.
  • Oscillator violating a chart pattern or trendline to the downside.

Window Oscillators

We’ll now look at some popular indicators like the MOM, ROC, MACD, Stochastics, and so on. Because they track the underlying acceleration and deceleration of price action, these oscillators are known as momentum oscillators. Momentum has a tendency to weaken and strengthen ahead of price. It is because of this quality that such oscillators are effective at forecasting potential trend changes.

Unfortunately, momentum oscillators are ineffective during a strong and prolonged up- or downtrend because they tend to remain overbought or oversold for extended periods of time. During such times, price overlay indicators such as support and resistance, trendlines, moving averages, channels, envelopes, and volatility bands should be used to signal any potential trend change. A trend change indicator, such as the average directional index (ADX), may also be useful in determining the start and end of a trend.

Finally, it is always preferable to fully master the use and interpretation of a single oscillator rather than using multiple oscillators and being unfamiliar with any of them. Each oscillator has unique characteristics that require time to become acquainted with. However, the trader must understand that oscillators only generate trade signals and not trade triggers.

ROC (Tracking Momentum via the Ratio Method):

The rate of change oscillator (ROC) measures the price change as a percentage or as a ratio over N periods. It’s worth noting that some practitioners use a smoothed version of the ROC to better visualize price behavior, especially when there’s a lot of volatility. Although closing prices are typically used in the ROC, some practitioners also use typical prices, midprice, and weighted close prices.

When prices are flat or starting to flatten, the ROC falls to zero. Price must rise steadily in order for the ROC to remain flat. If the ROC increases, it means that prices are increasing faster than they were N periods ago.

The ROC, like any oscillator, can be analyzed for buy (bullish) and sell (bearish) signals using any of the eight oscillator analysis methods described in the previous section. Figure 2.6 shows an example of this. As expected, the ROC remains flat during a constant rate of price ascent. We also expect the ROC to fall as prices begin to fluctuate. On the daily chart of DLF, the zero line crossovers indicate buy and sell signals, and the historically overbought levels, at Points 1 to 2, accurately forecast tops and bottoms. At Points 1–2, notice how the ROC momentum oscillator reverses before the price. This is the most important and practical feature of momentum oscillators.

Figure 2.6 - ROC Action of the Daily Chart DLF

MOM (Tracking Momentum via the Difference Method):

The difference method can also be used to track momentum. The MOM tracks the price difference over the last N periods rather than the ratio as in a ROC oscillator. Although the MOM typically employs closing prices, some practitioners do as well. Use the typical price, the midprice, and the weighted close price. The general MOM formula is as follows:

MOM = Most Recent Price  – Price N periods ago

The MOM oscillator does not exhibit the nonlinearity that ROC oscillators do. When prices are flat or starting to flatten, the MOM falls to zero. The price must rise steadily in order for the MOM to remain flat. If the MOM is rising, it means that prices are increasing faster than they were N periods ago. Any of the eight types of oscillator analysis described in the previous section can be used to analyze the MOM for buy (bullish) and sell (bearish) signals. In most ways, it is the same as ROC action.

MACD and MACD Histogram:

Gerald Appel invented the MACD, which stands for moving average convergence divergence. The MACD is calculated by detrending two moving averages and plotting the difference as a window oscillator. Detrending removes the trend component, leaving only the value difference. Detrending the MACD is simply subtracting the values of the 26period exponential moving average from the 12period exponential moving average.

MACD = = 12-periodEMA − 26-periodEMA

We can see in Figure 2.7 that whenever the 12day EMA tests or crosses the 26day EMA, the MACD line tests the zero level (refer to the solid vertical arrows).
This is due to the fact that the difference between the two EMAs is zero. When the two EMAs begin to diverge, the MACD begins to move away from the zero levels, and when they converge, the MACD returns to zero. When the 12period EMA crosses above the 26period EMA, the MACD rises above zero, and when the 12period EMA crosses below the 26period EMA, the MACD falls below zero.

Figure 2.7 - MACD Action of the Daily Chart of Grasim.

The MACD histogram is a detrended oscillator with two components. It is the difference between the MACD and the signal line with nine periods. Again, as shown in Figure 2.7, whenever the MACD tests or crosses over its signal line, the histogram returns to zero. By reversing before the MACD, the histogram tends to react faster. Detrending removes lag from oscillators, so double detrending results in an even more responsive oscillator. The MACD and its histogram can be analyzed for buy (bullish) and sell (bearish) signals using any of the eight oscillator analysis methods described in the preceding section.

Average True Range (ATR ):

The average true range was developed by Welles Wilder to track the volatility associated with price activity. It accomplishes this by calculating the average of the true range of each bar over a specified number of periods. True range is defined as the largest of the three price ranges listed below:

  • The range of the current bar.
  • The difference between the previous close and the current high.
  • The difference between the previous close and the current low.

ATR is a simple true range moving average. It is used to determine the size of a stop-loss. Stop sizes are typically a multiple of ATR.

The ATR has the following characteristics:

  • An increase in price volatility increases the value of the ATR.
  • Falling ATR values in an uptrend is a bearish indication.
  • Rising ATR values in an uptrend is a bullish indication.
  • Falling ATR values in a downtrend is a bullish indication.
  • Rising ATR values in a downtrend is a bearish indication.
  • High or extreme values of ATR usually accompany price peaks and troughs in the market.
Figure 2.8 - True Range Analysis on Daily Chart of Nifty

Figure 2.8 depicts the daily chart of Nifty true range action. The lookback period is set to one period, indicating that we are looking at true range rather than average true range. Every time Nifty exceeds the historically overextended level, we see true range clearly indicating a correction.

The Stochastic Oscillator:

The bounded stochastic oscillator, developed by George Lane, tracks the relative position of the current price or latest close as a percentage of the price range over a specified number of periods, measured from the lowest low of the range. The stochastic oscillator can be represented in two ways: fast and slow. Each representation contains two lines: the percent K and its corresponding signal line, the percent D. We have the fast or raw percent K and fast percent D in the stochastics fast version.

The fast or raw percent K has a default lookback period of 14 periods. The fast percent D is obtained by smoothing the percent K with a simple three-period moving average. We can calculate the slow percent D by taking a three-period simple moving average of the fast percent D. In a nutshell, the fast percent D-line is a smoothed version of the raw percent K-line, while the slow percent D-line is a double smoothed version of the raw percent K-line. Overbought and oversold levels, 50 percent level crossovers, divergence, and signal line crossovers are all determined by the percent D-line. When using the raw percent K-line, the fast percent D is the signal line, and when using the slow percent K-line, the slow percent D is the signal line.

  • Whenever the fast %K line crosses above the fast %D signal line, it represents a buy (bullish) signal.
  • Whenever the fast %K crosses below the slow %D (signal line), it represents a sell (bearish) signal.
  • Whenever the slow %K crosses above the slow %D (signal line), it represents a buy (bullish) signal.
  • Whenever the slow %K crosses below the slow %D (signal line), it represents a sell (bearish) signal.

Any of the eight types of oscillator analysis described in the previous section can be used to analyze the stochastic oscillator for buy (bullish) and sell (bearish) signals. Overbought and oversold levels are set to default values of 80% and 20%, respectively.

Relative Strength Index (RSI):

The RSI, developed by Welles Wilder, measures a stock’s underlying strength in terms of its average gain and loss over the last n periods. Let G represent the average gain over the last n periods and L represent the average loss over the last n periods. The formula for relative strength, RS, is RS = |G/L|.

RSI = 100 −[100 /(1 +G/ L)]
Re-arranging,we get,RSI = 100×(G/(G+ L))

This is analogous to the stochastic normalization process, in which the maximum value in the numerator is always equal to or less than the maximum value in the denominator. Welles Wilder used a 14period lookback to smooth the RSI data using Wilder’s averaging, a type of exponential moving average. The RSI is less volatile than stochastic action and may be a good substitute for it in volatile markets. Any of the eight types of oscillator analysis described in the previous section can be used to analyse the RSI oscillator for buy (bullish) and sell (bearish) signals.

Overbought and oversold levels are set to 70% and 30% by default, respectively. Many practitioners believe that a convergence of buy and sell signals on both the stochastic and RSI oscillators is more reliable. One strategy is to look for a dip below the oversold level on both of these oscillators first. A buy signal is issued once the readings on both oscillators rise above the oversold level. For sell signals, the opposite is true. On the daily chart of JSWSTEEL, we see a buy signal as both oscillator readings rise above the oversold level in Figure 2.9.

Figure 2.9 - Buy Signal of Stochastic & RSI on Daily Chart of JSWSTEEL

Overlay Indicators

Overlays, as previously stated, are classified into four types:

  • Overlays based on numbers.
  • Overlays that are based on geometry.
  • Horizontally based overlays.
  • Algorithmically based overlays.

Price interacts with these overlays, searching for support and resistance. Resistive and supportive clusters or confluences are the most effective forms of support and resistance. A concentration of bullish and bearish indicators within a narrow price range will typically produce a strong price barrier.

Price interacts with these overlays, searching for support and resistance. Resistive and supportive clusters or confluences are the most effective forms of support and resistance. A concentration of bullish and bearish indicators within a narrow price range will typically produce a strong price barrier.

What Are Floor Trader’s Pivot Points?

The Floor Trader’s Pivot Points is volatility and trend following indicator. It’s a purely numerical overlay. It will project various levels of resistance (R1, R2, R3, etc.) and support (S1, S2, S3, etc.) for the following day based on the previous day’s range. It also shows a pivot point level, PP, around which the action of the day revolves.

To create these pivot points, first determine the previous day’s average price. This is the pivot level for the following day, PP. To create the first pivot support level, we subtract the difference between the previous day’s high and PP from the PP price. Similarly, we project the difference between the previous day’s low and PP upward from the PP price to create the first pivot resistance level. Figure 3.0 shows an example of this. It’s easy to see why it’s called the pivot point. The previous day’s volatility is incorporated into the next day’s projections around this PP. If the previous day was volatile, the range would be larger.

Figure 3.0 - Constructing the First Pivot Resistance and Support Level

We subtract the previous day’s range from the PP to create the second pivot support level, and we add the previous day’s range to create the second pivot resistance level. We can see that by incorporating yesterday’s volatility into the current day’s projections, we are incorporating yesterday’s volatility into the current day’s projections. As a result, it is essentially a predictor of potential future volatility.

We subtract the previous day’s range from the first support level to create the third pivot support level, and we add the previous day’s range to the first resistance level to create the third pivot resistance level. Similarly, the fourth support level is created by subtracting the previous day’s range from the second support level, and the fourth resistance level is created by adding the previous day’s range to the second resistance level.

Identifying whether the price has opened below or above the PP is a popular way to gauge the day’s action. If it opened below the PP, the current day’s prices are expected to fall, and if it opened above the PP, the current day’s prices are expected to rise.

The violation of the second support or resistance levels indicates the presence of a strong downtrend or uptrend, respectively, while the third resistance and support levels represent extreme overbought and oversold levels. Prices should remain within the first pivot support and resistance levels if the day is quiet and uneventful. Besides using pivot point levels for initiating entries, many practitioners use the levels as a basis for exiting a position.

Figure 3.1 - Price Reacting to Pivot Points on the Daily Chart of ACC Futures Chart

Pivot Calculations

There are several methods for calculating a market’s pivot point (P). It is most commonly the arithmetic average of the market’s high (H), low (L), and closing (C) prices in the previous trading period.

  • P = (H + L + C) / 3.
  • R1 = P + (P − L) = 2×P − L
  • S1 = P − (H − P) = 2×P − H
  • R2 = P + (H − L)
  • S2 = P − (H − L)
  • R3 = H + 2×(P − L) = R1 + (H − L)
  • S3 = L − 2×(H − P) = S1 − (H − L)

Chapter Summary

In this chapter, we looked at different types of indicators and oscillators, as well as how they relate to price and market action. It is important to note that indicators and oscillators perform best in predicting reversals when they coincide with price barriers such as support/resistance, trend lines, channel boundaries, and Floor Trader’s pivot levels.


References

Archelis, Steven B. 2001. Technical Analysis from A to Z. New York: McGraw‐Hill.
Colby, Robert W. 2003. The Encyclopedia of Technical Market Indicators. New York: McGraw‐ Hill.

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