This will be a short article that discusses an alternative theory on the relative strength index (RSI)which have been published in a few places. The goal of the article is to present it so that the reader becomes aware of it and if needed back-tests it.
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The Relative Strength Index
First introduced by J. Welles Wilder Jr., the RSI is one of the most popular and versatile technical indicators. Mainly used as a contrarian indicator where extreme values signal a reaction that can be exploited. Typically, we use the following steps to calculate the default RSI:
Calculate the change in the closing prices from the previous ones.
Separate the positive net changes from the negative net changes.
Calculate a smoothed moving average on the positive net changes and on the absolute values of the negative net changes.
Divide the smoothed positive changes by the smoothed negative changes. We will refer to this calculation as the Relative Strength — RS.
Apply the normalization formula shown below for every time step to get the RSI.
The above chart shows the hourly values of the GBPUSD in black with the 13-period RSI. We can generally note that the RSI tends to bounce close to 25 while it tends to pause around 75.Â
Creating the Strategy
The most common strategy used on the RSI is the oversold/overbought technique where the trader is supposed to detect extremes in momentum that signal a reversal.
An oversold level is a threshold in the RSI where the market is perceived to be oversold and ready for a bullish reaction. The idea is that too much selling has happened and the market should recover briefly.
An overbought level is a threshold in the RSI where the market is perceived to be overbought and ready for a bearish reaction. The idea is that too much buying has happened and the market should pause briefly.
Another theory exists which states that the RSI is more of a momentum confirmation strategy and therefore the overbought level is actually a buy signal while the oversold is actually a sell signal.
The signal charts show the signals generated based on a 13-period RSI and 70/30 extreme levels.
The results show that by entering trades and exiting them upon the next signal, you would get very high hit ratios but the profitability is either low or negative thus making the strategy similar to the original one.
The reason for a high hit ratio an low profitability is the small frequent gains due to successive signals and the low risk-reward ratio.
Hit Ratio = 70.24%
Hit Ratio = 69.69%
This strategy shows that the hit ratio alone is never a guarantee for a winning strategy.
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