Z-Score Based Momentum Zones with Advanced Volatility ChannelsThe indicator "Z-Score Based Momentum Zones with Advanced Volatility Channels" combines various technical analysis components, including volatility, price changes, and volume correction, to calculate Z-Scores and determine momentum zones and provide a visual representation of price movements and volatility based on multi timeframe highest high and lowest low values.
Note: THIS IS A IMPROVEMNT OF "Multi Time Frame Composite Bands" INDICATOR OF MINE WITH MORE EMPHASIS ON MOMENTUM ZONES CALULATED BASED ON Z-SCORES
Input Options
look_back_length: This input specifies the look-back period for calculating intraday volatility. correction It is set to a default value of 5.
lookback_period: This input sets the look-back period for calculating relative price change. The default value is 5.
zscore_period: This input determines the look-back period for calculating the Z-Score. The default value is 500.
avgZscore_length: This input defines the length of the momentum block used in calculations, with a default value of 14.
include_vc: This is a boolean input that, if set to true, enables volume correction in the calculations. By default, it is set to false.
1. Volatility Bands (Composite High and Low):
Composite High and Low: These are calculated by combining different moving averages of the high prices (high) and low prices (low). Specifically:
a_high and a_low are calculated as the average of the highest (ta.highest) and lowest (ta.lowest) high and low prices over various look-back periods (5, 8, 13, 21, 34) to capture short and long-term trends.
b_high and b_low are calculated as the simple moving average (SMA) of the high and low prices over different look-back periods (5, 8, 13) to smooth out the trends.
high_c and low_c are obtained by averaging a_high with b_high and a_low with b_low respectively.
IDV Correction Calulation : In this script the Intraday Volatility (IDV) is calculated as the simple moving average (SMA) of the daily high-low price range divided by the closing price. This measures how much the price fluctuates in a given period.
Composite High and Low with Volatility: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
Composite High and Low with Volatility Correction: The final c_high and c_low values are obtained by adjusting high_c and low_c with the calculated intraday volatility (IDV). These values are used to create the "Composite High" and "Composite Low" plots.
2. Momentum Blocks Based on Z-Score:
Relative Price Change (RPC):
The Relative Price Change (rpdev) is calculated as the difference between the current high-low-close average (hlc3) and the previous simple moving average (psma_hlc3) of the same quantity. This measures the change in price over time.
Additionally, std_hlc3 is calculated as the standard deviation of the hlc3 values over a specified look-back period. The standard deviation quantifies the dispersion or volatility in the price data.
The rpdev is then divided by the std_hlc3 to normalize the price change by the volatility. This normalization ensures that the price change is expressed in terms of standard deviations, which is a common practice in quantitative analysis.
Essentially, the rpdev represents how many standard deviations the current price is away from the previous moving average.
Volume Correction (VC): If the include_vc input is set to true, volume correction is applied by dividing the trading volume by the previous simple moving average of the volume (psma_volume). This accounts for changes in trading activity.
Volume Corrected Relative Price Change (VCRPD): The vcrpd is calculated by multiplying the rpdev by the volume correction factor (vc). This incorporates both price changes and volume data.
Z-Scores: The Z-scores are calculated by taking the difference between the vcrpd and the mean (mean_vcrpd) and then dividing it by the standard deviation (stddev_vcrpd). Z-scores measure how many standard deviations a value is away from the mean. They help identify whether a value is unusually high or low compared to its historical distribution.
Momentum Blocks: The "Momentum Blocks" are essentially derived from the Z-scores (avgZScore). The script assigns different colors to the "Fill Area" based on predefined Z-score ranges. These colored areas represent different momentum zones:
Positive Z-scores indicate bullish momentum, and different shades of green are used to fill the area.
Negative Z-scores indicate bearish momentum, and different shades of red are used.
Z-scores near zero (between -0.25 and 0.25) suggest neutrality, and a yellow color is used.
밴드 및 채널
Bitcoin to GOLD [presentTrading]**Introduction and How it is Different**
Unlike traditional indicators, the BTGR offers a unique perspective on market sentiment and asset valuation by juxtaposing two seemingly disparate assets: Bitcoin, the digital gold, and Gold, the traditional store of value. This article introduces an advanced version of this ratio, complete with upper and lower bands calculated using standard deviations. These bands add an extra layer of analytical depth, allowing for more nuanced trading strategies.
BTCUSD 12h bigger picture
**Economic Principles**
The BTGR is rooted in the economic principles of asset valuation and market sentiment. Gold has long been considered a safe haven asset, a place where investors park their money during times of economic uncertainty. Bitcoin, on the other hand, is often viewed as a high-risk, high-reward investment. By comparing the two, the BTGR provides insights into the broader market sentiment.
- Risk Appetite: A high BTGR indicates a bullish sentiment towards riskier assets like Bitcoin.
- Market Uncertainty: A low BTGR suggests a bearish sentiment and a flight to the safety of Gold.
- Asset Diversification: The BTGR can be used as a tool for portfolio diversification, helping investors balance risk and reward.
**How to Use It**
Setting Up the Indicator
- Platform: The indicator is designed for use on TradingView.
- Time Frame: A 480-minute time frame is recommended for more accurate signals.
- Parameters: The moving average is set at 200 periods, and the standard deviation is calculated over the same period.
**Trading Signal**
Long Entry: Consider going long when the BTGR crosses above the upper band.
Short Entry: Consider going short when the BTGR crosses below the lower band.
Note: Due to the issue that the number of trading is less than about 100 times, the corresponding strategy is not allowed to publish.
Gaussian RibbonThe Gaussian Ribbon utilizes two "Arnaud Legoux" moving averages with the same length to identify changes in trend direction. The plotted channel consists of two lines, one based on the default offset and sigma values, and the other with slightly adjusted customizable parameters.
ALMA is a type of moving average that is related to the Gaussian function through its mathematical formula and the concept of weighted averages.
The ALMA is designed to reduce lag in moving averages and provide more timely responses to price changes. It achieves this by applying a Gaussian distribution (bell-shaped curve) as a weighting function to the price data.
The Gaussian function is used to calculate the weights in the ALMA formula. These weights give more importance to recent price data while gradually reducing the influence of older data points. This results in a smoother and more responsive moving average.
In summary, the Gaussian Ribbon uses the offset and power of the second ALMA to create a lag that still calculates using the same length.
Robust Bollinger Bands with Trend StrengthThe "Robust Bollinger Bands with Trend Strength" indicator is a technical analysis tool designed assess price volatility, identify potential trading opportunities, and gauge trend strength. It combines several robust statistical methods and percentile-based calculations to provide valuable information about price movements with Improved Resilience to Noise while mitigating the impact of outliers and non-normality in price data.
Here's a breakdown of how this indicator works and the information it provides:
Bollinger Bands Calculation: Similar to traditional Bollinger Bands, this indicator calculates the upper and lower bands that envelop the median (centerline) of the price data. These bands represent the potential upper and lower boundaries of price movements.
Robust Statistics: Instead of using standard deviation, this indicator employs robust statistical measures to calculate the bands (spread). Specifically, it uses the Interquartile Range (IQR), which is the range between the 25th percentile (low price) and the 75th percentile (high price). Robust statistics are less affected by extreme values (outliers) and data distributions that may not be perfectly normal. This makes the bands more resistant to unusual price spikes.
Median as Centerline: The indicator utilizes the median of the chosen price source (either HLC3 or VWMA) as the central reference point for the bands. The median is less affected by outliers than the mean (average), making it a robust choice. This can help identify the center of price action, which is useful for understanding whether prices are trending or ranging.
Trend Strength Assessment: The indicator goes beyond the standard Bollinger Bands by incorporating a measure of trend strength. It uses a robust rank-based correlation coefficient to assess the relationship between the price source and the bar index (time). This correlation coefficient, calculated over a specified length, helps determine whether a trend is strong, positive (uptrend), negative (down trend), or non-existent and weak. When the rank-based correlation coefficient shifts it indicates exhaustion of a prevailing trend. Trend Strength" indicator is designed to provide statistically valid information about trend strength while minimizing the impact of outliers and data distribution characteristics. The parameter choices, including a length of 14 and a correlation threshold of +/-0.7, considered to offer meaningful insights into market conditions and statistical validity (p-value ,0.05 statistically significant). The use of rank-based correlation is a robust alternative to traditional Pearson correlation, especially in the context of financial markets.
Trend Fill: Based on the robust rank-based correlation coefficient, the indicator fills the area between the upper and lower Bollinger Bands with different colors to visually represent the trend strength. For example, it may use green for an uptrend, red for a down trend, and a neutral color for a weak or ranging market. This visual representation can help traders quickly identify potential trend opportunities. In addition the middle line also informs about the overall trend direction of the median.
Williams %R with EMA'sThe provided Pine Script code presents a comprehensive technical trading strategy on the TradingView platform, incorporating the Williams %R indicator, exponential moving averages (EMAs), and upper bands for enhanced decision-making. This strategy aims to help traders identify potential buy and sell signals based on various technical indicators, thereby facilitating more informed trading decisions.
The key components of this strategy are as follows:
**Williams %R Indicator:** The Williams %R, also known as the "Willy," is a momentum oscillator that measures overbought and oversold conditions. In this code, the Williams %R is calculated with a user-defined period (default 21) and smoothed using an exponential moving average (EMA).
**Exponential Moving Averages (EMAs):** Two EMAs are computed on the Williams %R values. The "Fast" EMA (default 8) responds quickly to price changes, while the "Slow" EMA (default 21) provides a smoother trend-following signal. Crossovers and divergences between these EMAs can indicate potential buy or sell opportunities.
**Candle Color Detection:** The code also tracks the color of candlesticks, distinguishing between green (bullish) and red (bearish) candles. This information is used in conjunction with other indicators to identify specific trading conditions.
**Additional Upper Bands:** The script introduces upper bands at various levels (-5, -10, -20, -25) to create zones for potential buy and sell signals. These bands are visually represented on the chart and can help traders gauge the strength of a trend.
**Alert Conditions:** The code includes several alert conditions that trigger notifications when specific events occur, such as %R crossing certain levels, candle color changes within predefined upper bands, and EMA crossovers.
**Background Highlighting:** The upper bands and the zero line are visually highlighted with different colors, making it easier for traders to identify critical price levels.
This code is valuable for traders seeking a versatile technical strategy that combines multiple indicators to improve trading decisions. By incorporating the Williams %R, EMAs, candlestick analysis, and upper bands, it offers a holistic approach to technical analysis. Traders can customize the parameters to align with their trading preferences and risk tolerance. The use of alerts ensures that traders are promptly notified of potential trade setups, allowing for timely execution and risk management. Overall, this code serves as a valuable tool for traders looking to make more informed decisions in the dynamic world of financial markets.
Dynamic GANN Square Of 9 BandsDynamic GANN Square Of 9 Bands
Created on 3 Sept 2023
Adjust Increment Value:
Customize increment to match symbol and price characteristics for accuracy.
Green Line:
200 EMA. Identifies trend direction; moves with the prevailing trend.
Red Lines:
Mark prominent reversal levels closer to the red range; ideal for mean reversion strategies.
Crossing red levels may indicate trend continuation to the next red level.
Grey Lines:
Show immediate target reversal levels; watch for potential reversals.
Key Features:
Levels are different from Standard Deviation Lines.
Levels remain fixed and parallel, unaffected by volatility.
Despite its dynamism, it can serve as a leading indicator, revealing potential trend changes.
Primarily designed for trend-following strategies.
Additional Tips:
Use additional confirmations
Manage predefined risk and quantity
Additional Resources:
GANN Square Of 9 Pivots:
Apeiron Fair Value Bands ProWHAT IS IT
The Apeiron Fair Value Bands Pro is an indicator that estimates the fair value area of an asset and provides levels of interest and likely reaction. It was created to determine fair value. Knowing fair value allows traders and investors to determine when an asset is at a premium or at a discount, which allows them to make more informed decisions about when to buy or sell. Fair value is constantly changing, and sometimes waiting for it to develop each session or month can lead to missed opportunities. Therefore, it is useful to have an estimate of fair value at all times.
HOW DOES IT WORK?
The simplest way to have a constant estimation of fair value could probably be a Moving Average. By averaging previous prices, we get the average price which ideally reflects where most traders have been interested in participating in the market. This isn’t necessarily the most accurate fair value estimation you can get, however using different types of moving averages and combining them allows for a better estimation of the FV. It is also important to consider that price is always moving away and back into the MA, so in order to determine FV, we must allow an area for price to move within which we can consider the FVA. By taking into account volatility, previous relevant levels and the MA, the Apeiron Bands determine a FVA, where in theory price should stay most of the time.
According to the normal distribution, the price should stay within 1 standard deviation (SD) around 68% of the time and within 2 SD around 95% of the time during range periods (when data is most symmetrical). In the case of the Apeiron Bands, based on backtest data, the price tends to stay within 1 FVA around 75% of the time, within 2 FVA around 90% of the time during strong trends, around 80% and 95% correspondingly during weak trends, and >85% and >95% during ranges.
Additionally, based on backtesting data, pivots occur on average at around 1 FVA ±0.05 (This does not necessarily mean that most pivots occur at 1 FVA, however, the fact the average is 1±0.05 implies there is relevance to this level).
Finally, in order to account for volatility and the slight differences between symbols, a customizable tolerance ribbon is added to the moving average (MA) and each plotted band.
This data remains the same throughout all timeframes and types of market (tested on cryptocurrencies, forex pairs, stocks, indices and futures)
Examples of the time spent within the FVAs:
Examples of average pivot FVA :
HOW TO USE IT?
Identify potential reversal levels at premium and discount prices:
Knowing that price stays within 1 FVA the majority of time and inside 2 FVA most of the time, as well that in average pivots occur around 1 FVA, it can be inferred that both the Bands representing 1 & 2 FVA (B1 & B2) work as potential reversal levels as shown in the examples. This can be very good in confluence with other strategies to spot trade entries. If this is done taking into account if the asset is at a premium or discount allows for a higher probability of being on the right side of the market.
For example, during an uptrend price sometimes goes below it’s MA only to then continue up. In this particular case, the bands would provide an ideal entry at a discount to ride the uptrend.
During ranges, the bands can be used to identify potential pivots for each move up and down, and because of their adaptive nature they can be a great confluence to which horizontal levels are more likely to act as support and resistance.
For intraday traders, the bands can help them identify assets at one of the extremes and potentially even inside one of the bands, indicating that price is likely to reverse from there. Then they can use LTF to find ideal entries or catch the trend with the bands.
For swing traders and investors, using the bands can be a good way to scan different assets to find extended prices to either side and potential entry levels
Identify emerging trends:
Sometimes price will have a minimum reaction to the bands or no reaction at all. Knowing that price spends most of the time inside the bands, the fact that it breaks out of the FVA indicates that a new trend is likely to begin on that particular TF and price will try to establish a new FVA. Once there is a sustained PA outside the bands, a new trend can be assumed (Deviations happen as well, so it is very important to be aware of higher TF as well).
Other times, price will start sliding between B1 and B2, slowly displacing the MA. This can also be an indication for the start of a trend.
Identify exhaustions (potential tops & bottoms):
I call exhaustions to scenarios when price keeps going up/down but it fails to keep pushing the FVA with it. This indicates weakness in the trend and that a new FVA is being established. This often leads to a potential reversal or correction that marks the top or bottom of a move. Not only that, but when the new FVA is established price tends to go and test the other side of the FVA. Identifying exhaustions and being patient for them to form can potentially provide a great entry and RR ratio.
Exhaustions also happen after strong rallies or crashes, and in these cases it is advised to wait for price to re-enter its FVA, providing more clarity and often even better entries.
Exhaustions appear in all timeframes and symbols, however they can take some time to develop and it is important to be patient with them. And as always, it is highly recommended to also check for confluence on different TF.
8H Bands:
4H Bands:
Additional Features:
- Additional Bands:
The Apeiron Fair Value Bands can plot up to 4 Bands. Each fully customizable. The preset and suggested use is to have B1 & B2 and add thinner aid bands B0.5 & B1.5 which represent the middle of 1 & 2 FVA. These are not the main levels of interest but they can prove useful as support and resistance many times. Besides using mid levels, using fib values (0.618 & 1.618) can work even better on some assets and give better reactions.
NATGAS 1H Bands - Fib Mids:
The extra bands can also be used for FVA 3 and FVA 4, which can be useful during extremely volatile periods or on very LTF
- Multi Timeframe & precision:
The bands work on very low TF as well as High TF. Sometimes data can be limited on HTF and the bands will not have enough to be calculated and many LTF are very volatile and don’t work as well. In these scenarios, the bands have a setting called “Precision” under the preferences section that allows the user to decrease or increase the amount of data taken into account. This allows for optimization on any TF and even on any symbol.
GOLD 1min Bands:
EURUSD 5D Bands:
VIX 1H Bands:
- Multi Bands Confluence:
Combining 2 different length FV bands can be very useful to find confluence levels and spot trends and reversals earlier. For example, on the 15 min TF, using a 50 MA with only 1 FVA at the same time as a 200 MA with all Band can be ideal to keep track of short term moves and their micro-trends while always considering the longer trend which might be different that the short term one. As well, having MTF band confluence can indicate that a level is more likely to signal a reversal if reached.
- Multi Timeframe Confluence:
One of the best ways to use the bands is by using it in confluence with itself in other TFs, when price moves sharply into a confluent level given by multiple TFs’ Bands, it is more likely for price to find support and resistance and/or reverse there. Ex. 5 Min B2, 15 Min B1.5 & 30 Min B1, if price reaches this confluent level and shows weakness, this is likely a short term reversal level.
NATGAS MTF Bands:
How to set it up and customize it: (Explain how they are important)
- The MA Lab:
The Apeiron Bands utilizes a MA Lab to generate the most customizable MAs possible. It allows combining up to 3 different MAs, where each MA can be single, double or triple (same process as creating a DEMA or TEMA). As well each MA can be given more or less weight in the calculation of the final MA. Besides it’s features, the MA Lab allows the user to select only one MA and stick to basic settings and MA types if preferred.
When to use the MA Lab:
If you wanted a reactive MA (EMA) which was also volume weighted, you can then combine it with a VWMA and get a VW-EMA.
If you want a more reactive VWMA you can double or triple it. Then in order to make it smoother you combine it with a SMMA. Finally maybe you want to use it to follow trends closely so you also combine it with a HMA to take momentum into consideration.
- Presets:
The multiplier for each band, the width of each tolerance ribbon and the individual colors of each band can all be individually selected. However, to make the user's experience as smooth as possible, FVA multipliers, Ribbon width and colors can be preset and modified all at the same time with the most basic and ideal settings. This allows for quick customization options as well as personalized detailed custom settings.
- Show only Lower or Upper bands:
This setting is meant for scouting for discounts and premiums across the board. By only showing bands on one side it cleans up the chart and makes it easier to spot important levels on only one side of the price. This can be very useful when looking for swing opportunities or when following a particular trend to only focus on potential entries for it.
MATIC 4H Bands showing only bottom bands:
AMZN 1D Bands showing only bottom bands:
Settings used in indicator preview:
- Custom MA: 200 EMA/200 WMA/200 SMMA (200 EWSMMA)
- Band 1: 0.5 - Ribbon Width: 5 - Color: Blue
- Band 2: 1 - Ribbon Width: 10 - Color: Green
- Band 3: 1.5 - Ribbon Width: 5 - Color: Blue
- Band 4: 2 - Ribbon Width: 10 - Color: Red
Disclaimer:
The bands CAN but are NOT meant to be used as a standalone indicator. Previous performance does not guarantee future performance. The bands are an analytical tool, not a signal indicator. While certain scenarios can be interpreted as a signal, never follow them blindly and always use them in confluence with other analysis, systems or indicators.
Trade Tool VDWMA + OI RSI BasedThis indicator works only for symbols where open interest data is available.
The idea was to create a combination of Volume Delta, Open Interest, RSI, Moving Average and Support / Resistance as a unified tool.
I created a Weighted Moving Average based on the Volume Delta (VDWMA). The idea behind this was to reflect the moving average on the difference between buy and sell volume.
There are two VDWMA to determine a trend. Fast and Slow. The principle is the same as with conventional moving averages. For visualization, the candles are colored based on the following logic:
up trend = Fast VDWMA is above the Slow VDWMA and the price is above the Fast VWDWMA.
down Trend = Fast VDWMA is below the Slow VDWMA and the Short is below the Fast VDWMA
Further, support and resistance zones were defined based on the close and high prices as well as close and low prices.
A simple logic looks for divergences between RSI and price to generate first signals for possible price reversals.
Another RSI was created based on the open interest.
In combination with the conventional RSI, oversold and overbought zones were defined based on the following logic, which are marked by vertical zones on the chart.
Oversold zone = RSI is below 30 and OI RSI is above 70 or below 30 and OI opening is not greater than OI closing price
Overbought zone = RSI is above 70 and OI RSI is above 70 or below 30 and OI opening is not smaller than OI closing price
Based on this, buy and sell signals were defined.
First, the support or resistance zone must remain the same for two candles, which signals that the zone has not been breached. In addition, a divergence must occur in the RSI and the price must bounce.
newsell = resistance == resistance and high >= resistance and close < resistance and bearishDiv
newbull = support == support and low <= support and close > support and bullishDiv
The OI signaling was deliberately not included as well as the trend function. The tool should be suitable for scalping as well as for swinging. Thus, depending on the tradestyle itself to decide which points you want to trade.
Have fun with it
Bitcoin Market Cap wave model weeklyThis Bitcoin Market Cap wave model indicator is rooted in the foundation of my previously developed tool, the : Bitcoin wave model
To derive the Total Market Cap from the Bitcoin wave price model, I employed a straightforward estimation for the Total Market Supply (TMS). This estimation relies on the formula:
TMS <= (1 - 2^(-h)) for any h.This equation holds true for any value of h, which will be elaborated upon shortly. It is important to note that this inequality becomes the equality at the dates of halvings, diverging only slightly during other periods.
Bitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log(BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in Total Bitcoin Market Cap ranging between 4B and 5B USD.
The projections to the future works well only for weekly timeframe.
Enjoy the mathematical insights!
Bitcoin wave modelBitcoin wave model is based on the logarithmic regression model and the sinusoidal waves, induced by the halving events.
This chart presents the outcome of an in-depth analysis of the complete set of Bitcoin price data available from October 2009 to August 2023.
The central concept is that the logarithm of the Bitcoin price closely adheres to the logarithmic regression model. If we plot the logarithm of the price against the logarithm of time, it forms a nearly straight line.
The parameters of this model are provided in the script as follows: log (BTCUSD) = 1.48 + 5.44log(h).
The secondary concept involves employing the inherent time unit of Bitcoin instead of days:
'h' denotes a slightly adjusted time measurement intrinsic to the Bitcoin blockchain. It can be approximated as (days since the genesis block) * 0.0007. Precisely, 'h' is defined as follows: h = 0 at the genesis block, h = 1 at the first halving block, and so forth. In general, h = block height / 210,000.
Adjustments are made to account for variations in block creation time.
The third concept revolves around investigating halving waves triggered by supply shock events resulting from the halvings. These halvings occur at regular intervals in Bitcoin's native time 'h'. All halvings transpire when 'h' is an integer. These events induce waves with intervals denoted as h = 1.
Consequently, we can model these waves using a sin(2pih - a) function. The parameter determining the time shift is assessed as 'a = 0.4', aligning with earlier expectations for halving events and their subsequent outcomes.
The fourth concept introduces the notion that the waves gradually diminish in amplitude over the progression of "time h," diminishing at a rate of 0.7^h.
Lastly, we can create bands around the modeled sinusoidal waves. The upper band is derived by multiplying the sine wave by a factor of 3.1*(1-0.16)^h, while the lower band is obtained by dividing the sine wave by the same factor, 3.1*(1-0.16)^h.
The current bandwidth is 2.5x. That means that the upper band is 2.5 times the lower band. These bands are forming an exceptionally narrow predictive channel for Bitcoin. Consequently, a highly accurate estimation of the peak of the next cycle can be derived.
The prediction indicates that the zenith past the fourth halving, expected around the summer of 2025, could result in prices ranging between 200,000 and 240,000 USD.
Enjoy the mathematical insights!
ATR Adaptive RSI OscillatorThe " ATR Adaptive RSI Oscillator " is a versatile technical analysis tool designed to help traders make informed decisions in dynamic market conditions. It combines the Relative Strength Index (RSI) with the Average True Range (ATR) to provide adaptive and responsive insights into price trends.
Key Features :
Adaptive RSI Periods : The indicator introduces the concept of adaptive RSI periods based on the ATR (Average True Range) of the market. When enabled, it dynamically adjusts the RSI calculation period, offering longer periods during high volatility and shorter periods during low volatility. This adaptability enhances the accuracy of RSI signals across varying market conditions.
Volume-Based Smoothing : The indicator includes a smoothing feature that computes a time-decayed weighted moving average of RSI values over the last two bars, using volume-based weights. This approach offers a time-sensitive smoothing effect, reducing noise for a clearer view of trend strength compared to the standard RSI.
Divergence Detection : Traders can enable divergence detection to identify potential reversal points in the market. The indicator highlights regular bullish and bearish divergences, providing valuable insights into market sentiment shifts.
Customizable Parameters : Traders have the flexibility to customize various parameters, including RSI length, adaptive mode, ATR length, and divergence settings, to tailor the indicator to their trading strategy.
Overbought and Oversold Levels : The indicator includes overbought (OB) and oversold (OS) boundary lines that can be adjusted to suit individual preferences. These levels help traders identify potential reversal zones.
The "ATR Adaptive RSI Oscillator" is a powerful tool for traders seeking to adapt their trading strategies to changing market dynamics. Whether you're a trend follower or a contrarian trader, this indicator provides valuable insights to support your decision-making process.
[sphx] FWMAI've developed a cool indicator. The indicator calculates a Fibonacci-weighted moving average (FWMA) based on a specific length. What sets it apart is that it assists me in identifying potential trend reversals. When the indicator's color changes - from red to light red or from green to light green - it's an indication that the trend might be shifting.
What makes the indicator even more interesting: While I'm keeping an eye on these color changes, I'm also observing the price behavior. I check whether the price is in a consolidation phase during the color transition. This not only helps me detect potential trend changes but also to see whether the market is in a phase of price consolidation. The combination of this information aids me in making well-informed trading decisions.
I find the indicator so useful that I've decided to make it available to the community. You can use the code and adapt it to your own trading strategies. I hope it's as helpful to you as it has been to me. Wishing all of you successful trades and the best outcomes! Let's understand the market together and trade successfully.
Pro RSI CalculatorThe "Pro RSI Calculator" indicator is the latest addition to a series of custom trading tools that includes the "Pro Supertrend Calculator" and the "Pro Momentum Calculator."
Building upon this series, the "Pro RSI Calculator" is designed to provide traders with further insights into market trends by leveraging the Relative Strength Index (RSI) indicator.
Its primary objective remains consistent: to analyze historical price data and make informed predictions about future price movements, with a specific focus on identifying potential bullish (green) or bearish (red) candlestick patterns.
1. RSI Calculation:
The indicator begins by computing the RSI, a widely used momentum oscillator. It calculates two crucial RSI parameters:
RSI Length: This parameter determines the lookback period for RSI calculations.
RSI Upper and Lower Bands: These thresholds define overbought and oversold conditions, typically set at 70 and 30, respectively.
2. RSI Bands Visualization:
The RSI values obtained from the calculation are skillfully plotted on the price chart, appearing as two distinct lines:
Red Line: Represents the RSI when indicating a bearish trend, anticipating potential price declines.
Teal Line: Represents the RSI in bullish market conditions, signaling the possibility of price increases.
3. Consecutive Candlestick Analysis:
The indicator's core functionality revolves around tracking consecutive candlestick patterns based on their relationship with the RSI lines.
To be included in the analysis, a candlestick must consistently close either above (green candles) or below (red candles) the RSI lines for multiple consecutive periods.
4. Labeling and Enumeration:
To communicate the count of consecutive candles displaying consistent trend behavior, the indicator meticulously assigns labels to the price chart.
Label positioning varies depending on the trend's direction, appearing either below (for bullish patterns) or above (for bearish patterns) the candlesticks.
The color scheme aligns with the candle colors: green labels for bullish candles and red labels for bearish ones.
5. Tabular Data Presentation:
The indicator enhances its graphical analysis with a customizable table that prominently displays comprehensive statistical insights.
Key data points in the table include:
- Consecutive Candles: The count of consecutive candles displaying consistent trend characteristics.
- Candles Above Upper RSI: The number of candles closing above the upper RSI threshold during the consecutive period.
- Candles Below Lower RSI: The number of candles closing below the lower RSI threshold during the consecutive period.
- Upcoming Green Candle: An estimated probability of the next candlestick being bullish, derived from historical data.
- Upcoming Red Candle: An estimated probability of the next candlestick being bearish, also based on historical data.
6. Custom Configuration:
To cater to various trading strategies and preferences, the indicator offers extensive customization options.
Traders can fine-tune parameters like RSI length, upper, and lower bands, label and table placement, and table size to align with their unique trading approaches.
AI Channels (Clustering) [LuxAlgo]The AI Channels indicator is constructed based on rolling K-means clustering, a common machine learning method used for clustering analysis. These channels allow users to determine the direction of the underlying trends in the price.
We also included an option to display the indicator as a trailing stop from within the settings.
🔶 USAGE
Each channel extremity allows users to determine the current trend direction. Price breaking over the upper extremity suggesting an uptrend, and price breaking below the lower extremity suggesting a downtrend. Using a higher Window Size value will return longer-term indications.
The "Clusters" setting allows users to control how easy it is for the price to break an extremity, with higher values returning extremities further away from the price.
The "Denoise Channels" is enabled by default and allows to see less noisy extremities that are more coherent with the detected trend.
Users who wish to have more focus on a detected trend can display the indicator as a trailing stop.
🔹 Centroid Dispersion Areas
Each extremity is made of one area. The width of each area indicates how spread values within a cluster are around their centroids. A wider area would suggest that prices within a cluster are more spread out around their centroid, as such one could say that it is indicative of the volatility of a cluster.
Wider areas around a specific extremity can indicate a larger and more spread-out amount of prices within the associated cluster. In practice price entering an area has a higher chance to break an associated extremity.
🔶 DETAILS
The indicator performs K-means clustering over the most recent Window Size prices, finding a number of user-specified clusters. See here to find more information on cluster detection.
The channel extremities are returned as the centroid of the lowest, average, and highest price clusters.
K-means clustering can be computationally expensive and as such we allow users to determine the maximum number of iterations used to find the centroids as well as the number of most historical bars to perform the indicator calculation. Do note that increasing the calculation window of the indicator as well as the number of clusters will return slower results.
🔶 SETTINGS
Window Size: Amount of most recent prices to use for the calculation of the indicator.
Clusters": Amount of clusters detected for the calculation of the indicator.
Denoise Channels: When enabled, return less noisy channels extremities, disabling this setting will return the exact centroids at each time but will produce less regular extremities.
As Trailing Stop: Display the indicator as a trailing stop.
🔹 Optimization
This group of settings affects the runtime performance of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
MAX_MIN_V1
Another simple indicator, maximum, minimum and average values. The point of imbalance in the price of an asset is sought.
It is used for any temporality and in almost any asset.
You can configure the visibility of the different elements.
Bollinger Bands Heatmap (BBH)The Bollinger Bands Heatmap (BBH) Indicator provides a unique visualization of Bollinger Bands by displaying the full distribution of prices as a heatmap overlaying your price chart. Unlike traditional Bollinger Bands, which plot the mean and standard deviation as lines, BBH illustrates the entire statistical distribution of prices based on a normal distribution model.
This heatmap indicator offers traders a visually appealing way to understand the probabilities associated with different price levels. The lower the weight of a certain level, the more transparent it appears on the heatmap, making it easier to identify key areas of interest at a glance.
Key Features
Dynamic Heatmap: Changes in real-time as new price data comes in.
Fully Customizable: Adjust the scale, offset, alpha, and other parameters to suit your trading style.
Visually Engaging: Uses gradients of colors to distinguish between high and low probabilities.
Settings
Scale
Tooltip: Scale the size of the heatmap.
Purpose: The 'Scale' setting allows you to adjust the dimensions of each heatmap box. A higher value will result in larger boxes and a more generalized view, while a lower value will make the boxes smaller, offering a more detailed look at price distributions.
Values: You can set this from a minimum of 0.125, stepping up by increments of 0.125.
Scale ATR Length
Tooltip: The ATR used to scale the heatmap boxes.
Purpose: This setting is designed to adapt the heatmap to the instrument's volatility. It determines the length of the Average True Range (ATR) used to size the heatmap boxes.
Values: Minimum allowable value is 5. You can increase this to capture more bars in the ATR calculation for greater smoothing.
Offset
Tooltip: Offset mean by ATR.
Purpose: The 'Offset' setting allows you to shift the mean value by a specified ATR. This could be useful for strategies that aim to capitalize on extreme price movements.
Values: The value can be any floating-point number. Positive values shift the mean upward, while negative values shift it downward.
Multiplier
Tooltip: Bollinger Bands Multiplier.
Purpose: The 'Multiplier' setting determines how wide the Bollinger Bands are around the mean. A higher value will result in a wider heatmap, capturing more extreme price movements. A lower value will tighten the heatmap around the mean price.
Values: The minimum is 0, and you can increase this in steps of 0.2.
Length
Tooltip: Length of Simple Moving Average (SMA).
Purpose: This setting specifies the period for the Simple Moving Average that serves as the basis for the Bollinger Bands. A higher value will produce a smoother average, while a lower value will make it more responsive to price changes.
Values: Can be set to any integer value.
Heat Map Alpha
Tooltip: Opacity level of the heatmap.
Purpose: This controls the transparency of the heatmap. A lower value will make the heatmap more transparent, allowing you to see the price action more clearly. A higher value will make the heatmap more opaque, emphasizing the bands.
Values: Ranges from 0 (completely transparent) to 100 (completely opaque).
Color Settings
High Color & Low Color: These settings allow you to customize the gradient colors of the heatmap.
Purpose: Use contrasting colors for better visibility or colors that you prefer. The 'High Color' is used for areas with high density (high probability), while the 'Low Color' is for low-density areas (low probability).
Usage Scenarios for Settings
For Volatile Markets: Increase 'Scale ATR Length' for better smoothing and set a higher 'Multiplier' to capture wider price movements.
For Trend Following: You might want to set a larger 'Length' for the SMA and adjust 'Scale' and 'Offset' to focus on more probable price zones.
These are just recommendations; feel free to experiment with these settings to suit your specific trading requirements.
How To Interpret
The heatmap gives a visual representation of the range within which prices are likely to move. Areas with high density (brighter color) indicate a higher probability of the price being in that range, whereas areas with low density (more transparent) indicate a lower probability.
Bright Areas: Considered high-probability zones where the price is more likely to be.
Transparent Areas: Considered low-probability zones where the price is less likely to be.
Tips For Use
Trend Confirmation: Use the heatmap along with other trend indicators to confirm the strength and direction of a trend.
Volatility: Use the density and spread of the heatmap as an indication of market volatility.
Entry and Exit: High-density areas could be potential support and resistance levels, aiding in entry and exit decisions.
Caution
The Bollinger Bands Heatmap assumes a normal distribution of prices. While this is a standard assumption in statistics, it is crucial to understand that real-world price movements may not always adhere to a normal distribution.
Conclusion
The Bollinger Bands Heatmap Indicator offers traders a fresh perspective on Bollinger Bands by transforming them into a visual, real-time heatmap. With its customizable settings and visually engaging display, BBH can be a useful tool for traders looking to understand price probabilities in a dynamic way.
Feel free to explore its features and adjust the settings to suit your trading strategy. Happy trading!
Bollinger Bands Liquidity Cloud [ChartPrime]This indicator overlays a heatmap on the price chart, providing a detailed representation of Bollinger bands' profile. It offers insights into the price's behavior relative to these bands. There are two visualization styles to choose from: the Volume Profile and the Z-Score method.
Features
Volume Profile: This method illustrates how the price interacts with the Bollinger bands based on the traded volume.
Z-Score: In this mode, the indicator samples the real distribution of Z-Scores within a specified window and rescales this distribution to the desired sample size. It then maps the distribution as a heatmap by calculating the corresponding price for each Z-Score sample and representing its weight via color and transparency.
Parameters
Length: The period for the simple moving average that forms the base for the Bollinger bands.
Multiplier: The number of standard deviations from the moving average to plot the upper and lower Bollinger bands.
Main:
Style: Choose between "Volume" and "Z-Score" visual styles.
Sample Size: The size of the bin. Affects the granularity of the heatmap.
Window Size: The lookback window for calculating the heatmap. When set to Z-Score, a value of `0` implies using all available data. It's advisable to either use `0` or the highest practical value when using the Z-Score method.
Lookback: The amount of historical data you want the heatmap to represent on the chart.
Smoothing: Implements sinc smoothing to the distribution. It smoothens out the heatmap to provide a clearer visual representation.
Heat Map Alpha: Controls the transparency of the heatmap. A higher value makes it more opaque, while a lower value makes it more transparent.
Weight Score Overlay: A toggle that, when enabled, displays a letter score (`S`, `A`, `B`, `C`, `D`) inside the heatmap boxes, based on the weight of each data point. The scoring system categorizes each weight into one of these letters using the provided percentile ranks and the median.
Color
Color: Color for high values.
Standard Deviation Color: Color to represent the standard deviation on the Bollinger bands.
Text Color: Determines the color of the letter score inside the heatmap boxes. Adjusting this parameter ensures that the score is visible against the heatmap color.
Usage
Once this indicator is applied to your chart, the heatmap will be overlaid on the price chart, providing a visual representation of the price's behavior in relation to the Bollinger bands. The intensity of the heatmap is directly tied to the price action's intensity, defined by your chosen parameters.
When employing the Volume Profile style, a brighter and more intense area on the heatmap indicates a higher trading volume within that specific price range. On the other hand, if you opt for the Z-Score method, the intensity of the heatmap reflects the Z-Score distribution. Here, a stronger intensity is synonymous with a more frequent occurrence of a specific Z-Score.
For those seeking an added layer of granularity, there's the "Weight Score Overlay" feature. When activated, each box in your heatmap will sport a letter score, ranging from `S` to `D`. This score categorizes the weight of each data point, offering a concise breakdown:
- `S`: Data points with a weight of 1.
- `A`: Weights below 1 but greater than or equal to the 75th percentile rank.
- `B`: Weights under the 75th percentile but at or above the median.
- `C`: Weights beneath the median but surpassing the 25th percentile rank.
- `D`: All that fall below the 25th percentile rank.
This scoring feature augments the heatmap's visual data, facilitating a quicker interpretation of the weight distribution across the dataset.
Further Explanations
Volume Profile
A volume profile is a tool used by traders to visualize the amount of trading volume occurring at specific price levels. This kind of profile provides a deep insight into the market's structure and helps traders identify key areas of support and resistance, based on where the most trading activity took place. The concept behind the volume profile is that the amount of volume at each price level can indicate the potential importance of that price.
In this indicator:
- The volume profile mode creates a visual representation by sampling trading volumes across price levels.
- The representation displays the balance between bullish and bearish volumes at each level, which is further differentiated using a color gradient from `low_color` to `high_color`.
- The volume profile becomes more refined with sinc smoothing, helping to produce a smoother distribution of volumes.
Z-Score and Distribution Resampling
Z-Score, in the context of trading, represents the number of standard deviations a data point (e.g., closing price) is from the mean (average). It’s a measure of how unusual or typical a particular data point is in relation to all the data. In simpler terms, a high Z-Score indicates that the data point is far away from the mean, while a low Z-Score suggests it's close to the mean.
The unique feature of this indicator is that it samples the real distribution of z-scores within a window and then resamples this distribution to fit the desired sample size. This process is termed as "resampling in the context of distribution sampling" . Resampling provides a way to reconstruct and potentially simplify the original distribution of z-scores, making it easier for traders to interpret.
In this indicator:
- Each Z-Score corresponds to a price value on the chart.
- The resampled distribution is then used to display the heatmap, with each Z-Score related price level getting a heatmap box. The weight (or importance) of each box is represented as a combination of color and transparency.
How to Interpret the Z-Score Distribution Visualization:
When interpreting the Z-Score distribution through color and alpha in the visualization, it's vital to understand that you're seeing a representation of how unusual or typical certain data points are without directly viewing the numerical Z-Score values. Here's how you can interpret it:
Intensity of Color: This often corresponds to the distance a particular data point is from the mean.
Lighter shades (closer to `low_color`) typically indicate data points that are more extreme, suggesting overbought or oversold conditions. These could signify potential reversals or significant deviations from the norm.
Darker shades (closer to `high_color`) represent data points closer to the mean, suggesting that the price is relatively typical compared to the historical data within the given window.
Alpha (Transparency): The degree of transparency can indicate the significance or confidence of the observed deviation. More opaque boxes might suggest a stronger or more reliable deviation from the mean, implying that the observed behavior is less likely to be a random occurrence.
More transparent boxes could denote less certainty or a weaker deviation, meaning that the observed price behavior might not be as noteworthy.
- Combining Color and Alpha: By observing both the intensity of color and the level of transparency, you get a richer understanding. For example:
- A light, opaque box could suggest a strong, significant deviation from the mean, potentially signaling an overbought or oversold scenario.
- A dark, transparent box might indicate a weak, insignificant deviation, suggesting the price is behaving typically and is close to its average.
3M_RANGE/ErkOzi/Hello Dear Investors,
Today, I'd like to introduce you to an indicator called "3M Range" and explain how this indicator is calculated, as well as the kind of strategy it can offer.
What is the 3M Range Indicator?
"3M Range" is an analytical tool designed to identify and visualize market movements within three-month periods. This indicator employs specific levels and Fibonacci levels to assist investors in understanding market trends.
How is it Calculated?
The indicator utilizes the opening, highest, and lowest prices of three-month periods starting on Mondays. By using these prices, the indicator tracks weekly opening prices and marks the opening prices every Monday.
How Does the Indicator's Strategy Work?
Using this indicator, you can refine your long-term investment strategies:
Identify Three-Month Periods: The indicator follows the opening, highest, and lowest prices in three-month periods. This allows for a clearer understanding of long-term trends.
Utilize Fibonacci Levels: The indicator calculates Fibonacci levels to show support and resistance levels. These levels can help predict potential reversals or ongoing movements.
Observe Monday Opening Prices: The indicator distinctly marks Monday opening prices. This helps you capture potential movements at the beginning of the week.
Evaluate Trends and Opportunities: By using the indicator, you can observe long-term trends and potential market opportunities more clearly.
In Conclusion,
The "3M Range" indicator provides long-term investors with a better analytical tool by showcasing market movements within three-month periods. The indicator marks Monday opening prices and allows for analysis supported by Fibonacci levels. By using this indicator, you can shape your long-term investment strategies more consciously.
Always remember that, as with anything, making careful and informed decisions is crucial when investing. I hope this indicator helps you better navigate your long-term investments.
Note: Understanding market risks and utilizing analytical tools carefully is always important. Best of luck!
Smoothing ATR bandThere are two bands calculated with the ATR and I added "Smoothing" into the script.
Smoothing ATR with multiplier can display two bands above and below the price.
We can ONLY find some ATR bands in Community Scripts with "Basic" setting which is used to set Stop Loss.
And yet , Smoothing ATR with multiplier is capable of making traders manifestly recognize OverBought & OverSold.
FurtherMore, I added a condition with "plotshape", which is "Stop Hunt"
Stop Hunt is an absolutely usual strategy to clean the leverage and it always makes high volatility moves.
When high> above band and close< above band , long signal, it means it had been abundantly bought but the larger traders weren't satisfied; therefore, they quickly sold out to lower the price. The sell condition is on the contrary.
The signals mainly make traders manifestly recognize OverBought & OverSold.
MTF Fair Value Gap [BigBeluga]The MTF Fair Value Gap (FVG) indicator provides multi-timeframe options to observe lower or higher gaps in different timeframes within your current one. This can enhance the confluence in your trading decisions.
🔶 USAGE
An FVG is formed when a candle has an 'empty' body, leaving a gap. These areas are often filled before the market continues to trend in its original direction.
In practical terms, FVGs serve to highlight support areas (bullish FVGs) and resistance zones (bearish FVGs). As a gap is filled, signaling the end of the existing imbalance, it tends to foreshadow an impending price reversal.
While this approach is inherently contrarian, individuals seeking a more trend-following strategy can opt to use FVG identification as straightforward signals. This entails taking a long position upon detecting a bullish FVG and adopting a short position in the presence of a bearish FVG.
🔹 Mitigation
The mitigation point is where the user selects when the FVG is considered filled or no longer usable.
Source => Choose the candle's low/high or close as the mitigation point.
Point => Choose the FVG's mitigation point to trigger after the candle's Source has filled it. Users can choose between the middle point or the top/bottom of the FVG.
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🔹 MTF
This script can display MTF FVGs from different timeframes while showing the current one. This is extremely useful as it avoids the need to switch timeframes frequently and can add significant confluence with the current FVG.
🔹 Threshold
The Threshold is an input to remove insignificant FVGs that are too small to be truly useful. Users can choose between:
Auto => Automatically remove unusable FVGs.
Manual => Set an automatic Threshold.
🔶 TIPS
Users can choose how many FVGs to display on the current chart for better visualization.
Users can choose which FVGs to display: only the current one, only MTF ones, or both.
Volatility Price RangeThe Volatility Price Range is an overlay which estimates a price range for the next seven days and next day, based on historical volatility (already available in TradingView). The upper and lower bands are calculated as follows:
The Volatility for one week is calculated using the formula: WV = HV * √t where:
WV: one-week volatility
HV: annual volatility
√: square root
t: the time factor expressed in years
From this formula we can deduce the weekly volatility WV = HV * √(1 / 52) = HV / 7.2 where 52: weeks in a year.
The daily volatility DV = HV * √(1 / 365) = HV / 19.1 where 365: days in a year.
To calculate the lower and upper value of the bands, the weekly/daily volatility value obtained will be subtracted/added from/to the current price.
dharmatech : Standard Deviation ChannelDESCRIPTION
Based on version by leojez.
Adds a 3rd standard deviation level.
Twice as fast as original version.
Refactored and simplified source code.
HOW TO USE
Load your chart
Adjust the timeframe and zoom of the chart so that the trend you're interested in is in view.
Add the indicator
Use the measuring tool to measure the number of bars from the start of the trend to the latest candle.
Open settings for the indicator.
Set the length value to the number of bars that you noted.
Foxy's Acceleration BandsFoxy's Acceleration Bands is a dynamic technical indicator designed to help traders identify potential support and resistance levels using logarithmic regression and adaptable moving averages. By plotting bands around price movements, this indicator offers insights into potential zones where price acceleration, resistance, and support might occur.
How to Use:
Apply the "Foxy's Acceleration Bands" indicator to your TradingView chart.
Customize the indicator parameters as per your requirements:
factor: Adjust the sensitivity of the bands.
length: Set the length for moving averages and regression calculations.
mult: Modify the multiplier for upper bands.
Show Middle Bands: Toggle the display of middle bands.
Show Upper Bands: Toggle the display of upper bands.
Band MA Type: Choose the moving average type for the bands.
Middle MA Type: Select the moving average type for the central band.
Draw Prediction: Enable prediction lines for potential future price trends.
Prediction Slope Type: Choose between a fixed or dynamic slope length for prediction lines.
Fixed Slope Length: Set the slope length for prediction lines (if enabled).
Interpretation:
Upper Bands: The red upper bands indicate potential resistance zones where price acceleration might occur.
Middle Bands: The orange central band provides insights into the prevailing price trend.
Lower Bands: The green lower bands suggest potential support zones where price deceleration might happen.
Prediction Lines: If enabled, dotted lines visualize potential future price trends based on historical data.
Important Note: Foxy's Acceleration Bands is designed to assist traders in identifying potential support and resistance zones. Always complement its insights with other analysis techniques and prudent risk management strategies.
