The Relative Strength Index (RSI) was originally developed by J. Welles Wilder. It is a momentum oscillator that measures the speed and change of price movements. The RSI fluctuates between zero and 100. Typically and according to Wilder, RSI is considered overbought at over 70 and oversold at under 30. Signals can also be generated by searching for divergences, error fluctuations and midline transitions. The RSI can also be used to identify the general trend.
RSI is a popular momentum indicator that has been presented in numerous articles, interviews and books on trading over the years. In particular, Constance Brown’s piece “Technical Analysis for the Trading Professional” describes the concept of bull market and bear market routes for RSI. Andrew Cardwell, who was Brown’s RSI mentor, introduced positive and negative reversals for RSI. In addition, Cardwell turned the concept of divergence literally and figuratively upside down.
Already in 1978, Wilder introduces RSI in his book “New Concepts in Technical Trading Systems”. This book also features the Parabolic SAR, Average True Range and Directional Movement Concept (ADX). Although Wilder’s indicators were developed before the computer age, they have proven themselves over time and are still very popular.
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To simplify the explanation of the calculation, the RSI has been broken down into its main components: RS; Average Gain and Average Loss. This RSI calculus is based on 14 periods, which is the standard proposed by Wilder in his book. Losses are expressed as positive, not negative values.
The very first calculations for average profit and average loss are simple averages for 14 periods.
First average profit = sum of the profits of the last 14 periods / 14.
First average loss = sum of the losses of the last 14 periods / 14.
The second and succeeding calculations are based on the previous averages and the current amplification loss:
Average Gain = [(previous average gain) x 13 + current gain] / 14.
Average Loss = [(previous average loss) x 13 + current loss] / 14.
Using the previous value plus the current value is a smoothing technique similar to that used in calculating an exponential moving average. This further means that the RSI values become more accurate as of the calculation period increases. SharpCharts uses a minimum of 250 data points before the start date of a graph (assuming that a lot of data is available) to calculate its RSI values. To accurately replicate our RSI numbers, a formula needs at least 250 data points.
Wilden’s formula normalizes RS and turns it into an oscillator that fluctuates between zero and 100. A plot of RS looks precisely like a plot of RSI. The normalization step facilitates the identification of extreme values because the RSI is bound to the range. The RSI is 0 if the average gain is zero. Assuming an RSI for 14 periods, a zero RSI value means that prices have decreased in all 14 periods. There were no valuation gains. The RSI is 100 if the average loss is zero. This means that prices have risen higher in all 14 periods. There were no losses to be valued.
The default review time for RSI is 14, but can be reduced to increase sensitivity or increased to decrease sensitivity. The 10-day RSI is more likely to reach overbought or oversold values than the 20-day RSI. The retrospect parameters also depend on the volatility of a security. The 14-day RSI for Internet trader Amazon (AMZN) is more likely to be overbought or oversold than the 14-day RSI for Duke Energy (DUK), a utility.
RSI is considered overbought if it is over 70 and oversold if it is under 30. These traditional values can also be adjusted to meet safety or analysis requirements better. Increasing the overbought quantity to 80 or decreasing the oversold amount to 20 reduces the number of overbought/oversold quantities. Short-term traders sometimes use 2-period RSIs to search for overbought values above 80 and oversold values below 20.
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