Creating a Unique Technical Indicator from Scratch

Coding a Technical Indicator with Pine Script

The Stochastic Oscillator is widely recognized in Technical Analysis, providing a quick insight into whether a market is overbought or oversold. In this guide, we will develop a variation known as the Stochastic Smoothing Oscillator using the Pine Script on TradingView.

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The Stochastic Smoothing Oscillator

The Stochastic Oscillator is a well-known tool in technical analysis, with a variant called the Stochastic Smoothing Oscillator that applies additional smoothing. First, let’s briefly review the original Stochastic Oscillator.

The normalization method confines values between 0 and 1 (or 0 and 100 if multiplied). It involves subtracting the minimum value within a specified lookback period from the current value and dividing it by the difference between the maximum and minimum values of that period.

The Stochastic Oscillator identifies overbought and oversold regions by applying the normalization formula, illustrated below:

An overbought area indicates that the market is very bullish and likely to consolidate, while an oversold area suggests extreme bearishness, predicting a potential bounce. Thus, the Stochastic Oscillator acts as a contrarian indicator, signaling reactions to significant market movements. Now, let’s move to TradingView and code the Stochastic Smoothing Oscillator ourselves.

Why create it ourselves if it already exists among their indicators?

The answer lies in building our foundational skills in a reputable charting platform. By mastering the fundamentals of Pine Script, we can eventually develop our own indicators and strategies.

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Developing the Stochastic Smoothing Oscillator on TradingView

Our goal is to create and display the Stochastic Smoothing Oscillator using EURGBP data on the TradingView platform. Remember, you need an account to view charts, but the good news is that it's free! Click the Chart button on the home screen and select any asset for the indicator calculation. Next, find the Pine Editor at the bottom of the screen and prepare for coding.

Begin by specifying the Pine Script version. For our purposes, we'll use version 4.

//@version=4

Next, define the indicator's name using the following syntax:

study("Stochastic Smoothing Oscillator")

After the introductory setup, we can define the oscillator's parameters. The Stochastic Smoothing Oscillator uses exponential moving averages applied to high, low, and closing prices, with the stochastic normalization function implemented. We need to establish two lookback periods: 2 and 13. The 2-period lookback corresponds to the exponential moving average applied to the HLC data, while the 13-period looks back refers to the normalization window.

lookback = 13, ema_lookback = 2

Next, we will transform and smooth the HLC data. The ema() function calculates the exponential moving average based on the closing price and our defined lookback periods.

SSO_low = ema(low, ema_lookback) SSO_high = ema(high, ema_lookback) SSO_close = ema(close, ema_lookback)

Now, we apply the SSO formula, which mirrors the Stochastic Oscillator's formula. The built-in functions highest() and lowest() will help us identify the highest and lowest values for a specified lookback period.

SSO = (SSO_close - lowest(SSO_low, lookback)) / (highest(SSO_high, lookback) - lowest(SSO_low, lookback)) * 100

Finally, we will plot the indicator alongside the chart using the plot() function, which takes a source and a color property, as illustrated below.

plot(SSO, color=color.red) hline(10, color=color.gray, linestyle=hline.style_dashed) hline(90, color=color.gray, linestyle=hline.style_dashed)

Here’s the complete code:

//@version=4 study("Stochastic Smoothing Oscillator") lookback = 13 ema_lookback = 2 SSO_low = ema(low, ema_lookback) SSO_high = ema(high, ema_lookback) SSO_close = ema(close, ema_lookback) SSO = (SSO_close - lowest(SSO_low, lookback)) / (highest(SSO_high, lookback) - lowest(SSO_low, lookback)) * 100 plot(SSO, color=color.red) hline(10, color=color.gray, linestyle=hline.style_dashed) hline(90, color=color.gray, linestyle=hline.style_dashed)

The SSO operates similarly to the Stochastic Oscillator, with a bullish bias when the SSO is at lower levels and a bearish bias when it reaches higher levels.

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