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Returns based Bollinger Bands

Bollinger Bands based on Returns

 

This indicator characterizes the price and volatility by providing a channel/band of standard deviations like the Bollinger Bands. In contrary to standard Bollinger Bands which uses price directly, this indicator uses returns due to normalization.

 

The standard Bollinger Bands based on price directly, were one of the first quant or statistical methods for retail traders available. The issue with these bands, standard deviations can only be calculated, if the underlying data is normal distributed. But price (data basis for Bollinger Bands) is log-normal distributed.

This indicator normalizes the underlaying price data to a normal distributed data, calculates the (standard) deviation and transfers the values back to its price domain. With this approach it is from statistical point of view, much more accurate and reflects the actual probabilities much better.

 

Similar as the standard Bollinger Bands, the upper and lower band for this indicator also reflects the limit, where it is unlike for the candle to close outside of this channel/band. If selected multiplier is 1.96 (1.96 Standard deviations), the probability is 95% that it will not close outside. If you choose multiplier 1.0 (1 SD), chances are 68.5% that it will not close outside.

 

Input:

Sample Size: 21 (periods back to calculate returns-based Bollinger Bands)

Multiplier: 1.96 (1.96 standard deviations)



Remark: Indicator is provided for statistical analysis and showing probabilities only and should not be construed as financial advice.


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This Oscillator describes the drift of an asset, as part of the geometric Brownian Motion (GBM). As a data basis the mean reverting log returns of the asset price is considered. It gives the percentile of drift directional. For instance, a value of 0.05 means a drift of 5%, based on the selected sample size. If the value is positive, drift to higher asset values is determined.  This indicator should be used in confluence with other indicators based on volatility, probability and statistics. Li
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The indicator ‘Probability Range Bands’ gives a prediction of the amount, how much the asset is moving from its current price. The range bands give probabilities, that the candle close will not exceed this certain price level. It is also called the expected move for the current candle close.   This Indicator is based on statistical methods, probabilities and volatility. Asset price is assumed to follow a log-normal distribution. Therefore, log returns are used in this indicator to determine the
The Returns Momentum Oscillator (RMO) shows the difference of exponentially weighted volatility. It is used to find market tops and bottoms. Volatility comes in waves, and as the Returns often front run price action it gives directional prediction of market movement.   The Oscillator signal is RMSed (root mean squared) to make the distribution closer to Gaussian distribution. While the traditional RSI indicators are often stuck in overbought or oversold areas for a long time, RMSing of the sign
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