 # Relative Strength Index (RSI) and Trading Strategies

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.

## Calculation

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.