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Percentile of Historical Volatility Correlation

Percentile of Historical Volatility and Correlation Coefficient shows if the asset is cheap or expensive based on the volatility. It is used to determine a good entry point. It has two indicators built in: Historical Volatility is ranked percentile wise and its correlation to price action which gives an indication of the direction of a possible future move. Together the both indicators can give good entries and direction.

 

Historical Volatility is a statistical measure of the dispersion of returns for an asset over a given period (Sample Size Historical Volatility). In this indicator the volatility model is calculated as the standard deviation of returns. Weighted with percentile with the given period (Sample Size Percentile). It shows the percentage of candles over the last selected period (Sample Size Percentile) where Historic Volatility was traded below the current level.

That means if PHV (Percentile of Historical Volatility) is at 5%, it was traded only 5% of the time (within percentile period) below that level. If PHV is above 80% it indicates, that historical volatility is higher than usual. So, a strategy could be, enter at a very low PHV, as it will likely expand and a bigger move will happen.

The indicator values are displayed as Columns and range from 0 to 100 [%]. It is NOT a directional indicator, only together with Correlation it is possible to determine direction.

 

Correlation Coefficient is shown in the panel below the PHV to correlate the non-directional indicator to price, to make it directional. Traditional Pearson Correlation is used. It is shown as line and scaled. Usually, it goes from -1 to 1, for representation it is scaled to -100 to 0 (so -50 is zero line). The correlation line is coloured from the calculated p-value, based on significance confidence level of 0.05 (5%). If the correlation line turns “green” is shows significant positive correlation of PHV to price. If it turns “red” significant negative correlation is determined.

 

Example Strategies:

• PHV rising (percentile of historical volatility increasing) AND significant positive correlation = possible larger movement in price action to the upside expected (LONG)

• PHV rising (percentile of historical volatility increasing) AND significant negative correlation = possible larger movement in price action to the downside expected (SHORT)

• PHV falling (percentile of historical volatility decreasing) AND negative correlation = price will likely move slowly up (LONG)

• PHV falling (percentile of historical volatility decreasing) AND positive correlation = price will likely move slowly down (SHORT)

 

The Input Settings:

Sample Size Historical Volatility: Default 10, length of periods back to calculated historical volatility.

Sample Size Percentile: Default 100 (Recommendation use power of Sample Size Historical Volatility), length of periods back to calculated percentile of historical volatility.

Sample Size Correlation: Default 10, length of periods back to calculated correlation of PHV and Price

 

 

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


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Introduction to Sideways Market Analyzer Notable period of Low volatility and non-trending movements in the financial market is considered as Sideways Market. Sooner or later, the low volatility will increase and the price will pick up a trend after Sideways Market. In terms of trading point of view, Sideways Market can serve as the very good entry timing for traders. Sideways Market is also quite often the representation of accumulation of large orders from big investors. Therefore, knowing the
Ace Supply Demand Zone Indicator The concept of supply demand relies on the quantity mismatching between buying and selling volumes in the financial market. Supply and demand zone can provide the good entry and exit. A zone is easier to trade than a line. The supply demand zone can provide the detailed trading plan and the risk management. Its ability to predict market direction is high. There are two distinctive points about Ace Supply Demand Zone Indicator. Ace Supply Demand Zone indicator was
Golden Spikes Detector
Batsirayi L Marango
5 (1)
Golden Spikes Detector Cet indicateur est basé sur une stratégie avancée principalement pour les pics de trading sur les indices Boom et Crash. Des algorithmes complexes ont été mis en œuvre pour détecter uniquement les entrées à forte probabilité. Il alerte sur les entrées potentielles d’achat et de vente. Pour échanger des pics sur le courtier Deriv ou Binary, prenez uniquement les alertes Buy Boom et Sell Cash. Il a été optimisé pour être chargé sur une période de 5 minutes, bien qu'une analy
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Drift
Florian Nuebling
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. L
FREE
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
This z-score indicator shows the correct z-score of an asset, as it uses the normalized price data for calculation, which is the only correct way. Z-score is only applicable for normal distributed data, therefore not the actual price is considered, but the normalised returns, which were assumed to follow a normal distribution. Returns are mean reverting and assumed to follow a normal distribution, therefore z-score calculation of returns is more reliable than z-score on price, as price is NOT m
The RSI2.0 indicator uses normalized price data and signal processing steps to get a normal distributed oscillator with no skew (mean is zero). Therefore, it can give much better reads than the traditional RSI.   Areas/Levels of reversal: Overbought or oversold levels from traditional RSI have no statistical significance, therefore the standard deviation bands are implemented here, which can be used in similar way as possible reversal points.   Divergence: As the indicator is nearly normal dist
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
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 u
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