Profitable RSI (Relative Strength Index)

Introduction
As you know the Relative Strength Index (RSI) was originally developed by J. Welles Wilder and was described in his book "New Concepts in Technical Trading Systems" (1978). It is intended to measure the strength or weakness of an instrument for the specified period.

The most basic strategy is to use the crossovers as trade signals:

• when RSI crosses above 30, go Long
  
• when RSI crosses below 70, go Short
  
• Exit when a crossover occurs in the opposite direction
  

What is this tool?
This tool is a performance scanner that uses a decision tree-based algorithm under the hood to find the most profitable settings for RSI. It analyzes the range of periods between 2 to 100 and backtests the RSI for each period using the strategy mentioned above across the entire history of an instrument. If the more profitable parameter was found, the indicator will switch its value to the found one immediately.

So, instead of manually selecting parameters just apply it to your chart and relax - the algorithm will do it for you.

The algorithm can work in two modes: Basic and Advanced "Early Switch". The Early Switch algorithm makes some assumptions and activates a set of optimizations to find the better setting DURING the trades, not after they were closed.

The difference is illustrated on the screenshot below:

Additionally you can set up a backtest window through indicator's settings (the optimizers which were published before will get this feature soon).

Alerts
It has a special alert that notifies when a more profitable period was detected.

NOTE: It does not change what has already been plotted.
NOTE 2: This is not a strategy, but an algorithmic optimizer.

Day after day. Night after night.
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Day after day. Night by to night.
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Notas de prensa:

• Optimization update
  

Notas de prensa:

• Optimization update №2
  

Notas de prensa:

• Removed the end date for analysis
  

Notas de prensa:

• Added OB/OS levels optimization (3 parameters optimization)
  
• From now it analyzes Overbought levels starting from 60 to 70 and Oversold levels from 30 to 40
  

Notas de prensa:

• Optimization update
  

Notas de prensa:

• Security update
  

Notas de prensa:

• Update
  

Notas de prensa:

• Update
  

Notas de prensa:

• Update
  

Notas de prensa:

• Update
  

Notas de prensa:

• Update