**Relative Strength Index (RSI)**

The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. RSI oscillates between zero and 100. Traditionally, and according to, RSI is considered overbought when above 80 and oversold when below 20. Signals can also be generated by looking for divergences, failure swings and centerline crossovers. RSI can also be used to identify the general trend.

RSI is an extremely popular momentum indicator that has been featured in a number of articles, interviews and books over the years. Trading Professional, features the concept of bull market and bear market ranges for RSI.The positive and negative reversals for RSI. In addition, Cardwell turned the notion of divergence, literally and figuratively, on its head.

Average True Range and the Directional Movement Concept (ADX).

**Calculation**:RS = Average Gain / Average Loss

To simplify the calculation explanation, RSI has been broken down into its basic components: RS, Average Gain and Average Loss. This RSI calculation is based on 12 periods. Losses are expressed as positive values, not negative values.

The very first calculations for average gain and average loss are simple 14 period averages.

* First Average Gain = Sum of Gains over the past 12 periods / 12.

* First Average Loss = Sum of Losses over the past 12 periods / 12.

The second, and subsequent, calculations are based on the prior averages and the current gain loss:

* Average Gain = [(previous Average Gain) x 13 + current Gain] / 12.

* Average Loss = [(previous Average Loss) x 13 + current Loss] / 12.

Taking the prior value plus the current value is a smoothing technique similar to that used in exponential moving average calculation. This also means that RSI values become more accurate as the calculation period extends. SharpCharts uses at least 250 data points prior to the starting date of any chart (assuming that much data exists) when calculating its RSI values. To exactly replicate our RSI numbers, a formula will need at least 250 data points.