Technical Indicators Simplified

Till now we have understood Fundamental and Technical Analysis. If you have not seen that post you can read about it here. Have you ever thought about how technical analysis is performed? The answer to this is the tools called Technical Indicators.

Technical analysis focuses on patterns, trading signals, and charting tools to evaluate a security’s strength or weakness, rather than intrinsic business fundamentals like earnings or revenue. We will be discussing patterns in one of the upcoming posts. In this post, we will be learning about technical indicators.

What are Technical Indicators?

Technical Indicators are mathematical calculations based on historic price, volume, or open interest data of a financial asset. Traders and investors use them to analyze markets and make informed decisions about buying or selling specific assets.

1. Overlay Indicators

These indicators are technical analysis tools plotted directly on top of price charts. They use the same scale as prices. They provide additional information about price trends, volatility, and potential reversal points. A few common overlay indicators are:

Moving Averages (MA):

These smooth out price data by calculating the average price over a specific period. So instead of the candlesticks with highs and lows, you can just visualize the price trend easily. The two main types are:

Simple Moving Average (SMA): SMA gives equal weightage to all data points in the period by dividing the sum of the prices by the total number of prices in the series. Due to this, it is less reactive to recent price changes.
Exponential Moving Average (EMA): EMA gives more weight to recent data points. It uses a smoothing factor (multiplier) to emphasize recent data. It is calculated according to the following formula: EMA = Closing price x multiplier + EMA (previous day) x (1- multiplier). Due to this EMA reacts quicker to price movements as compared to SMA.

The significance of moving averages is summarized in the points below:

By matching the moving average period to cyclic movements in the series, oscillatory movements can be removed, thus simplifying the chart for study.
Additional observations can be added to the data without changing the predetermined trend values. This flexibility makes moving averages versatile.
Unlike freehand curve methods, moving averages are objective. The periodic motions in the data define the period of the moving average, eliminating subjective judgment.

However, moving averages have some limitations as stated below:

We can’t obtain trend values for all observations, especially at extremes.
Moving averages aren’t suitable for predicting future values; their primary purpose is trend analysis.
Selecting the right moving average period can be challenging, especially when the series lacks regular cycles.
Non-linear trends can skew the trend values provided by moving averages. Moving Averages don’t correct for seasonal variation.

Bollinger Bands:

Bollinger Bands are another type of overlay indicator. It is composed of 3 lines as described below:

The middle line represents the SMA or EMA.
The upper and lower bands represent standard deviations from the middle line. They expand during high volatility and contract during low volatility.

Bollinger Bands are straightforward and intuitive. Traders can quickly identify overbought and oversold conditions, as well as trends and volatility levels. These bands can be applied to any asset class, including stocks, commodities, and currencies.

Remember that Bollinger Bands don’t provide standalone buy or sell signals. Instead, they help you assess market conditions and potential reversals. When using them, consider chart patterns like the “double bottom” or other formations for more informed decisions.

Some important points that need to be point about the Bollinger Bands are described below:

Bollinger Bands react to price changes rather than predicting them, therefore it is a lagging indicator.
They offer a retrospective view of recent price events, which can be limiting.
Bollinger Bands should not be used in isolation. Combining them with other non-correlated indicators provides more direct market signals. Complementary indicators that can be used with Bollinger Bands are RSI, MACD, and Stochastic Oscillator.

Parabolic SAR (Stop and Reverse):

Parabolic SAR is an overlay indicator that helps determine trend direction. Here SAR stands for Stop and Reverse. It places dots above or below the price bars, indicating whether the price is trending upward or downward.

It provides potential entry and exit signals. When the dots flip direction, it suggests a potential change in price movement, providing potential entry and exit points. Parabolic SAR works well in robust, trending markets and adapts to various timeframes and asset classes.

Apart from the positive characteristics mentioned above

The position of the dot changes with each price movement. A single substantial price shift can suddenly alter the dot’s position, leading to potential confusion for traders.
While it creates numerous trade opportunities, not all of them are reliable. Traders need to exercise caution and consider other factors before acting on these signals.
Parabolic SAR doesn’t perform well in sideways markets, often providing false signals. It’s essential to use additional indicators to filter out noise during such conditions.
The indicator doesn’t provide direct information on market volume, although it indirectly reflects momentum. Incorporating volume data can enhance the analysis.

Ichimoku Cloud:

The Ichimoku Cloud considers multiple factors, including trend direction, support and resistance levels, and momentum. This holistic approach allows traders to gain a deeper understanding of market dynamics and make more accurate predictions. The visual nature of the cloud makes it easy for traders to assess market conditions and identify potential trading opportunities quickly. This indicator includes the following lines:

Tenkan-sen: The conversion line
Kijun-sen: The baseline
Senkou Span A and B: The cloud boundaries
Chikou Span: The lagging line

The Ichimoku Cloud works well in varying market conditions, offering an all-in-one system that accounts for time, price action, and market sentiment. It enables informed decisions with a clear understanding of market dynamics.

While the Ichimoku Cloud excels in trending markets, its effectiveness diminishes in sideways or ranging markets. During such periods, signals can become less reliable, and the cloud may not accurately represent support and resistance levels.

The Ichimoku Cloud relies on historical data. While past tendencies can provide insights, they may not always repeat in the future as traders expect. Like any technical indicator, the Ichimoku Cloud can produce false signals. Traders should exercise caution and consider other factors before making decisions based solely on its signals. Depending on the time frame the indicator is applied to, it may not account for larger trends. Traders should adjust their settings accordingly.

Volume-Weighted Average Price (VWAP):

VWAP is an intraday indicator based on the total currency value of all trades divided by the total trading volume for the day. it is given by the formula:

VWAP = (Cumulative Typical price x volume) / Cumulative Volume

here cumulative typical price is given by the formula (High Price+ Low Price + Closing Price)/3

Cumulative is the total trade since the trading session opened.

VWAP serves as a benchmark for trading execution, helping traders aim for average prices during their trades. It confirms liquidity levels, allowing traders to gauge where most trading occurs in a stock. By executing trades near the market average, VWAP helps reduce market impact, especially for large orders.

VWAP provides transparency, which is invaluable for understanding market dynamics. Traders use VWAP for intraday strategies, identifying optimal entry and exit points. It minimizes adverse selection risk by aligning trades with prevailing market conditions. VWAP helps traders achieve cost-effective executions by considering both price and volume.

However, apart from the above points caution has to be taken as VWAP calculations are based on intraday data, which means they may not accurately represent longer-term trends or overnight gaps. Also during high volatility, VWAP is less reliable during rapid price fluctuations. Also, it assumes uniform volume distribution throughout the day, which may not always hold true. Late-day volume spikes can disproportionately affect VWAP, potentially misleading traders.

2. Oscillators

An oscillator is a technical analysis tool that varies over time within a band, oscillating above and below a center line or within predefined upper and lower bounds. Oscillators help traders discover short-term overbought or oversold conditions in an asset.

Stochastic Oscillator:

Stochastic Oscillator is a popular momentum indicator. It compares a security’s closing price to a range of its prices over a specific time period. It helps identify overbought and oversold conditions.

The oscillator value always falls between 0 and 100. Readings above 80 are considered overbought, while readings below 20 indicate oversold conditions. When the stochastic oscillator is above 80, it suggests the asset is overbought, and a reversal may be imminent. Readings below 20 indicate oversold conditions, potentially signaling a bullish reversal.

Stochastic oscillator charts typically include two lines:

The actual oscillator value for each session.
A three-day simple moving average of the oscillator.

Look for divergence between the oscillator and price action. For example, if a bearish trend makes a lower low but the oscillator prints a higher low, it could signal a bullish reversal.

The formula for the stochastic oscillator:

%K=(H14−L14C−L14)×100

Where:

(C) = Most recent closing price
(L14) = Lowest price traded in the previous 14 sessions
(H14) = Highest price traded during the same 14-day period
(%K) = Current value of the stochastic indicator

But as with other indicators, this indicator has its own limitations. Stochastics provide signals after the market has already moved, that is it is a lagging indicator. They lag behind price action, which can impact timely decision-making. The oscillations can be choppy and may not proportionately reflect price movements. Remember, stochastics measure momentum, not price directly.

Relative Strength Index (RSI):

It is a momentum indicator used in technical analysis, that compares recent gains to recent losses. It measures the magnitude of recent price changes to evaluate overvalued or undervalued conditions in a security’s price.

RSI is displayed as an oscillator (a line graph) on a scale of 0 to 100. It helps traders identify bullish and bearish price momentum. RSi has two major indications as described below:

Overbought: Traditionally RSI above 70 indicates an overbought condition and may signal a potential reversal or corrective pullback.
Oversold: Traditionally RSI below 30 indicates an oversold condition and could indicate a bullish reversal.

The initial RSI value is calculated using a 14-day look-back period. The formula involves average gains and losses during that period. Remember, RSI works best in trading ranges rather than trending markets.

However, there are some precautions that traders need to take with RSI as described below:

It can generate false signals during sideways markets. Traders may act on these signals, leading to losses.
Like many oscillators, RSI lags behind price movements. It reacts after the market has already shifted, affecting timely decision-making.
RSI can stay in overbought or oversold territory for extended periods. Relying solely on these levels may result in missed opportunities.

Remember, combining RSI with other indicators and price patterns can enhance its effectiveness.

Rate of Change (ROC):

The Rate of Change indicator, also known as momentum, measures the percentage change in price over a specific time frame. The ROC is calculated as follows:

ROC = (Closing Price_p-Closing Price_p-n)x 100

Here:

Closing Price_p represents the closing price of the most recent period.
Closing Price}_p-n represents the closing price (n) periods before the most recent period.

Remember to choose an appropriate (n) value based on your trading style (short-term or long-term). Smaller values react more quickly but may yield more false signals, while larger values provide more meaningful signals but react slower.

A positive ROC indicates prices are increasing whereas a negative ROC suggests prices are declining ROC helps confirm trends, spot divergences, identify overbought/oversold conditions, and detect centerline crossovers.

There are certain limitations of ROC as described below:

ROC can produce false signals, especially when the price oscillates around the zero line. These whipsaws can lead to incorrect trading decisions.
ROC considers both the ‘n’ price and the last closing price equally. This equal weighting may make it less effective in capturing meaningful price changes.
Even after a divergence signal, the price may continue moving in the same direction, limiting the effectiveness of ROC as a standalone indicator.

Money Flow Index (MFI):

The Money Flow Index (MFI) is a momentum indicator that measures the flow of money into and out of a security over a specified period of time. It’s related to the Relative Strength Index (RSI), but with an important difference: the MFI incorporates both price and volume data, whereas the RSI only considers the price. This helps assess buying and selling pressure.

The MFI identifies overbought or oversold signals and can also spot divergences that warn of potential trend changes in price. The MFI oscillates between 0 and 100.

An MFI reading above 80 is considered overbought.
An MFI reading below 20 is considered oversold.

Some analysts also use levels of 90 and 10 as additional thresholds. The following steps are involved in the background of Money Flow Index:

Calculate the typical price for each of the last 14 periods (average of high, low, and close prices).
Determine whether the typical price was higher or lower than the prior period to determine raw money flow (positive or negative).
Multiply the typical price by volume to get the raw money flow.
Calculate the money flow ratio by dividing the sum of positive money flows by the sum of negative money flows over the last 14 periods.
Finally, compute the MFI using the ratio.

Money Flow index has the following limitations:

Like all technical analysis indicators, the MFI can generate false signals. It’s best used alongside other forms of analysis or indicators to confirm trading signals. These false signals may occur during large price swings or periods of high market volatility.
The MFI relies on historical price and volume data. Consequently, it may not accurately reflect current market conditions, especially during rapid changes.
Overbought and oversold zones don’t always signal the end of a trend; further trend continuation can occur.

Moving Average Convergence Divergence (MACD):

The Moving Average Convergence/Divergence (MACD) is a trend-following momentum indicator that helps investors identify price trends, measure trend momentum, and determine market entry points for buying or selling. It consists of the following components:

MACD Line: Calculated as the difference between the 12-period Exponential Moving Average (EMA) and the 26-period EMA.
Signal Line: A 9-period EMA of the MACD line.
MACD Histogram: Represents the difference between the MACD and the Signal Line.

The following inferences can be drawn from MACD:

Moving Average Crossovers: When the shorter-term 12-period EMA crosses above the longer-term 26-period EMA, it generates a potential buy signal. Conversely, when the 12-period EMA crosses below the 26-period EMA, it generates a potential sell signal.
MACD Histogram: Traders use this to anticipate changes in market momentum. Positive histogram bars indicate bullish momentum, while negative bars suggest bearish momentum.

Therefore we have to use MACD crossovers and histogram patterns to make informed trading decisions by identifying oversold and overbought conditions and potential price reversals.

The limitations of MACD are as described below:

The MACD relies on historical price data, making it a lagging indicator.
It may not always predict future price movements accurately. In sideways markets, the MACD can generate false signals, leading to potential losses. While effective for identifying trends and momentum, the MACD may be less useful in other market conditions, such as sideways or range-bound markets. Signals from the MACD should be confirmed before making trading decisions.

So to summarise the Oscillators are often used alongside other technical indicators to signal trend breakouts or reversals.

This is all for this post. Tell me your thoughts in the comments section. Don’t forget to follow my Facebook and Instagram Page for regular updates. See you all in the next post. Till then keep learning.