Stochastic RSI

This is the Stochastic RSI, a.k.a StochRSI, introduced by Tushar S. Chande and Stanley Kroll in their book “The New Technical Trader”(1994). The indicator is calculated by applying the Stochastic oscillator formula to the relative strength index (RSI) as opposed to standard price data.

Stochastic RSI for NinjaTrader 8

Indicator Description

Applying the RSI values to the Stochastic formula enables traders to determine whether the RSI is approaching overbought or oversold. By taking advantage of both these momentum indicators, the Stochastic RSI indicator a.k.a. StochRSI, becomes a more sensitive oscillator, reflecting the historical movement of the RSI. A Stochastic RSI indicator download link is available below.

Overbought scenarios are likely when the StochRSI rise above 80 whereas values below 20 indicate oversold. A reading of zero reflects that the RSI is at its lowest level in the lookback period. A reading of 100 indicates that the RSI is at its highest level for the available data in the lookback period. Accordingly, reaching overbought/oversold levels do not necessarily mean that the current price move will pause or reverse. It simply reflects that the RSI is approaching extremes values when compared to recent readings. Finally, you may also use the Stochastic RSI indicator to identify short-term trends. When values are above 50, the market is trending higher and vice versa when below 50.

Stochastic RSI vs. the Relative Strength Index (RSI)

Although similar, the StochRSI relies on a different formula than in the standard RSI (a derivative of price). One should however note that the Stochastic RSI is a derivative of RSI itself and one step further removed from price.

In terms of usability, the StochRSI moves faster between overbought / oversold than the standard RSI. Therefore, if you apply a moving average of the Stochastic RSI indicator, it will be less erratic. For example, a 10 period Exponential Hull Moving Average of the Stochastic RSI will produce a smooth and stable output. Because many of NinjaTraders in-built indicators do not allow for applying one indicator to another (nesting), we have created a separate category for that in our library, more information available below.

Other library indicators

The indicators available from the nested indicators category can be used be used with an input series other than price. Other than the Stochastic RSI, these indicators include the ADX, ADXRCCIDirectional MovementDirectional Movement Index, DSS (Blau), DSS (Bressert)Parabolic SAR and the Fast Stochastics / Standard Stochastics. An example on how to apply the Roofing Filter to correct distortions was discussed in our post on Improving Fast Stochastic Setups (with video).

Also, because of the high number of signals generated by the Stochastic RSI, you should combine it with other tools for technical analysis.  For channel indicators, you may review the Commodity Channel IndexDonchican Channel or the Squeeze Channel. A Donchian Channel Strategy and Squeeze Setups were reviewed in our Indicator Spotlight and we’ve also looked at how the TDI indicator utilizes the RSI in three timeframes.

For support / resistance, you may consider using Fib retracement levels, using one of our Fibonacci retracement tools, such as the indicator plotting the Prior Day Fibonacci Levels. Our Indicator Spotlight newsletter previously looked at a trading strategy using Fibonacci Retracements. Additional support resistance levels can be found using the Average Range for a daily, weekly or monthly lookback period. This may for example be done using a ADR indicator, alternatively the Weekly Range Projections / Monthly Range Projections. The Indicator Spotlight furthermore reviewed the Average Daily Range Projections.

Finally, for volume analysis you may review the Relative Volume indicatorFor instruments that lack reliable volume information (FX/Crypto currencies), you may consider using the Relative Ranges indicator, which was discussed this post.

The Stochastic RSI indicator download is available for NinjaTrader 8.

Stochastic RSI