Nasan Rate of Change (ROC)**NOTE: FOR COMPARISON TRADITIONAL ROC IS PLOTTED WITH THE SAME ROC LENGTH OF 9. IT IS NOT PART OF THE INDICATOR"
The Nasan ROC indicator is smoothed version of the of the traditional ROC indicator. The Nasna ROC uses a triple pass moving average differencing strategy. A cumulative sum of the deviations obtained from the moving average differencing provides a smooth "noise free" trend and this cumulative sum of deviations is used for calculating ROC.
Let's break down the components and understand the indicator we discussed earlier:
Sequential Triple Pass Filter:
Three filters with lengths specified by length1, length2, and length3 are applied to the closing prices (close).
The filters involve calculating the cumulative sum of the differences between the closing prices and their respective moving averages.
The idea is to detrend the data and accumulate the deviations from the average over time, emphasizing longer-term trends.
Calculation of Rate of Change (ROC) of Cumulative Sum:
The Rate of Change (ROC) of the cumulative sum (rocCumulativeSum) is calculated using the ta.roc function with a specified length (rocLength).
ROC measures the percentage change in the cumulative sum over a specified period.
The ROC histogram provides insights into the momentum of the detrended series. Positive values suggest increasing momentum, while negative values suggest decreasing momentum.
Pay attention to the color of the histogram bars.
The histogram bars are colored green if the current ROC value is greater than or equal to the previous ROC value, and red otherwise.
This coloring is based on the concept that a positive ROC suggests upward momentum, while a negative ROC suggests downward momentum.
Volatility - Volume Impact:
The Average True Range (ATR) is calculated with a period of 14.
Volume strength is calculated as a factor (VCF) that considers the ratio of the simple moving average (SMA) of the current volume to the SMA of the volume over a longer period (144).
This volume factor (VCF) is then multiplied by ATR, creating a synergy with volatility and volume.
Visualization with Background Color Gradient:
A background color gradient is applied to the chart based on the calculated volume strength (f1).
The gradient color ranges from black (indicating low ATR and volume strength) to purple (indicating high ATR and volume strength). A low value indicates a ranging market with no significant price movements and it is safter to avoid signals generated from ROC histogram in these region.
Synergy of ROC and Volume Strength:
Observe how the ROC signals align with the background color gradient. For example, confirm whether positive ROC aligns with periods of high ATR and volume strength.
This synergy can provide confirmation or divergence signals, adding another layer of analysis.
Volatility
Gradient Value Overlay
This script helps with identifying certain conditions without cluttering too much of the candles.
Some use cases:
It helps identify rsi low and high values.
Directional price movement becoming difficult.
low and high volume.
it uses a percent rank to distinguish low and high values.
It then uses a gradient to match the percentile rank to heatmap type colors.
i.e. dark blue for lowest volume, white for highest volume.
Current options are:
max bars to use.
approximate color - This value will attempt to give an approximation of what the color might be for the candle close.
e.g. If you're on the 1-hour chart, and only 30 minutes have past, it will multiple the current volume by 1.5. As time passes, if no volume comes in eventually, it will multiply current volume by 1.
This approximate value is only set to work with volume-based options.
option - select the type of value you'd like to see the gradient for.
timeframe - get values from a different chart timeframe.
on/off - turns the gradient on or off.
Gradient type - color wheel or heatmap. Currently these are the only two gardient options.
color wheel's colors for low to high values:
color wheel's current colors:
dark blue
purple
pink
red
orange
yellow
green
teal
white
heatmap's current colors from low values to high values:
dark blue
purple
pink
red
orange
yellow
white
reverse gradient - will reverse the colors so dark blue will be the high value and white will be the low value. Some charts based on previous data; you might need to switch the gradient colors.
moving average length while inside timeframe - an exponential moving average is applied to the values. At 1, there is no moving average applied.
Use case for this is to smooth out the gradient.
An example use case - if your currently on the 1-hour chart, you can set the timeframe to 1 minute and then the moving average length inside timeframe to 60. You will then be seeing the color sixty 1-minute bars.
current timeframe moving average length - an exponential moving average applied to current gradient (helps with smoothing gradient).
Smooth, further smooths values.
There is no set rule for what moving average lengths to use. Adjust timeframe, and moving average lengths to get an insight.
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Moving Fib Based on Donchain/Pivot/BBThis script's purpose is to provide the user with an indicator that automatically plots Fibonacci levels. The user has three main options for determining the Fibonacci's high and low. This indicator offers an ample number of settings, making it a modular Fibonacci overlay.
The default setting is based on Donchian high and low.
Another option is to base the high and low on TradingView's Pivot indicator.
The last option is to determine Fibonacci levels based on Bollinger Bands.
Add up to 16 Fib levels with customizable settings, plot them on a log scale, and explore various other settings to personalize the Fib overlay.
This indicator can be utilized for trading momentum or mean reversion strategies
Average True Range Level█ Overview
The indicator uses color-coded columns to represent different levels of normalized ATR, helping traders identify periods of high or low volatility.
█ Calculations
The normalization process involves dividing the current True Range by the Average True Range. The formula for normalized ATR in the code is:
nAtr = nz(barRange/atr)
█ How To Use
Level < 1
During periods when the normalized ATR is less than 1, suggesting a lower level of volatility, traders may explore inside bar strategies. These strategies focus on trading within the range of the previous bar, aiming to capitalize on potential breakout opportunities.
Level between 1 and 3
In instances where the normalized ATR falls between 1 and 3, indicating moderate volatility, a pullback strategy may be considered. Traders look for temporary corrections against the prevailing trend, entering positions in anticipation of the trend's resumption
Level between 2 and 3
Within the range of normalized ATR between 2 and 3, signifying a balanced level of volatility, traders might explore breakout strategies. These strategies involve identifying potential breakout levels using support and resistance or other indicators and entering trades in the direction of the breakout.
Level > 3
When the normalized ATR exceeds 3, signaling high volatility, traders should approach with caution. While not ideal for typical mean reversion strategies, this condition may indicate that the price has become overextended. Traders might wait for subsequent candles, observing a normalized ATR between 2 and 3, to consider mean reversion opportunities after potential overpricing during the high volatility period.
* Note: These strategies are suggestions and may not be suitable for all trading scenarios. Traders should exercise discretion, conduct their own analysis, and adapt strategies based on individual preferences and risk tolerance.
MADALGO's Fear and Greed OscillatorThe Fear and Greed Oscillator is a dynamic tool designed to gauge market sentiment by analyzing various components such as volatility, momentum, and volume. This indicator synthesizes multiple metrics to provide a singular view of market emotion, oscillating between fear and greed.
🔷 Calculation -
The oscillator integrates the following components, each normalized and weighted to contribute equally:
ATR (Average True Range): Represents market volatility.
MACD (Moving Average Convergence Divergence): Captures market momentum.
RSI (Relative Strength Index): Provides insights into overbought or oversold conditions.
Volume: Reflects market participation levels.
Each component is first normalized to ensure a balanced impact and then averaged to create the final oscillator value.
🔷 Color Coding -
The oscillator's plot changes color based on its value, representing market sentiment:
Green: Indicates a leaning towards greed.
Red: Suggests a leaning towards fear.
The intensity of the color represents the strength of the sentiment.
🔷 Usage -
This indicator is valuable for traders looking to understand market sentiment. It works best when combined with other forms of analysis, such as fundamental or other technical indicators, to form a comprehensive trading strategy.
🔷 Signal Lines -
Two horizontal lines represent extreme conditions:
A line for Extreme Fear.
Another for Extreme Greed.
These lines help identify when the market sentiment is at potentially unsustainable levels.
🔷 Customization -
The Fear and Greed Oscillator is designed with flexibility in mind, allowing users to adjust several parameters to match their specific analysis requirements. Understanding and utilizing these customization options can significantly enhance the indicator's relevance and effectiveness in various market conditions.
1. Length Parameters:
ATR and RSI Length: This input determines the period over which the Average True Range (ATR) and the Relative Strength Index (RSI) are calculated. Adjusting this length can affect the sensitivity of the oscillator to recent market movements. A shorter length makes the oscillator more responsive to recent changes, while a longer length smoothens it, reducing sensitivity to short-term fluctuations.
MACD Parameters: These include the Fast Length, Slow Length, and Signal Smoothing. By adjusting these, users can control how the Moving Average Convergence Divergence (MACD) component reacts to price movements. This customization is crucial for aligning the oscillator with different trading strategies, whether short-term or long-term focused.
Volume Length: This parameter sets the period for the moving average and standard deviation calculations of the volume component. Altering this length allows the oscillator to either emphasize recent volume changes or consider a broader historical context.
2. Weight Adjustments:
Component Weights: Each component (ATR, MACD, RSI, Volume) has an associated weight factor. These weights determine the relative influence of each component on the final oscillator value. Users can increase the weight of a component to give it more influence or decrease it to lessen its impact. This feature is particularly beneficial for traders who have a preference or insight into which market aspects are more indicative of fear or greed at given times.
Balancing the Components: The key to effective customization lies in balancing these weights to reflect the user's market perspective and trading style. For instance, a trader focusing on volatility might increase the weight of the ATR, while one interested in momentum might prioritize the MACD and RSI weights.
3. Color and Signal Line Customization:
Color Intensity: The intensity of the color gradient of the oscillator line can be a visual aid in quickly identifying market sentiment. Users can experiment with the colorValue calculation within the script to adjust how rapidly the color changes with the oscillator values
Extreme Levels: The extreme fear and greed levels, represented by horizontal lines, are customizable. Users can set these levels based on historical data analysis or personal risk tolerance. These lines act as alerts for potentially overextended market conditions.
🔷 Limitations -
As with any technical tool, the Fear and Greed Oscillator should not be used in isolation. It does not predict market direction but rather gauges the prevailing market emotion. Its effectiveness may vary across different markets and timeframes.
🔷 Conclusion -
The Fear and Greed Oscillator offers a unique perspective on market sentiment, encapsulating various aspects of market behavior into a single indicator. It serves as a versatile tool for traders aiming to understand the emotional undercurrents of the market.
🔷 Risk Disclaimer -
Financial trading involves significant risk. The value of investments can fluctuate, and past performance is not indicative of future results. This indicator is for informational purposes and should not be construed as financial advice. Always consider your personal circumstances and seek independent advice before making financial decisions.
Rolling Volatility Indicator
Description :
The Rolling Volatility indicator calculates the volatility of an asset's price movements over a specified period. It measures the degree of variation in the price series over time, providing insights into the market's potential for price fluctuations.
This indicator utilizes a rolling window approach, computing the volatility by analyzing the logarithmic returns of the asset's price. The user-defined length parameter determines the timeframe for the volatility calculation.
How to Use :
Adjust the "Length" parameter to set the rolling window period for volatility calculation.
Ajust "trading_days" for the sampling period, this is the total number of trading days (usually 252 days for stocks and 365 for crypto)
Higher values for the length parameter will result in a smoother, longer-term view of volatility, while lower values will provide a more reactive, shorter-term perspective.
Volatility levels can assist in identifying periods of increased market activity or potential price changes. Higher volatility may suggest increased risk and potential opportunities, while lower volatility might indicate periods of reduced market activity.
Key Features :
Customizable length parameter for adjusting the calculation period and trading days such that it can also be applied to stock market or any markets.
Visual representation of volatility with a plotted line on the chart.
The Rolling Volatility indicator can be a valuable tool for traders and analysts seeking insights into market volatility trends, aiding in decision-making processes and risk management strategies.
Logarithmic CVD [IkkeOmar]The LCVD is another Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se. However the logarithmic transformation is made to visualize the direction of the trend for the volume. This allows you to see if money is flowing in or out of an asset.
What it does is tell you if we have a flashcrash based on the difference in volume.
Think of this indicator like a form of a volatility index.
Smoothing input:
The only input is an input for the smoothing length of the logDelta.
Volume Calculation:
// @IkkeOmar
//@version=5
indicator('Logarithmic CVD', shorttitle='CVD', overlay=false)
smooth = input.int(defval = 25, title = "Smoothing Distance")
// Calculate buying and selling volume
askVolume = volume * (close > open ? 1 : 0) // Assuming higher close than open indicates buying
bidVolume = volume * (close < open ? 1 : 0) // Assuming lower close than open indicates selling
// Delta is the difference between buying and selling volume
delta = askVolume - bidVolume
// Apply logarithmic transformation to delta
// Adding a check to ensure delta is not zero as log(0) is undefined
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
// use the the ta lib for calculating the sma of the logDelta
smoothLogDelta = ta.sma(logDelta, smooth)
// Create candlestick plot
plot(logDelta, color= color.green, title='Logarithmic CVD')
plot(smoothLogDelta, color= color.rgb(145, 37, 1), title='Smooth CVD')
These lines calculate the buying and selling volumes. askVolume is calculated as the total volume when the closing price is higher than the opening price, assuming this indicates buying pressure. bidVolume is calculated as the total volume when the closing price is lower than the opening price, assuming selling pressure.
The Delta is simply the difference between buying and selling volumes.
Logarithmic Transformation:
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
Applies a logarithmic transformation to delta. The math.log function is used to calculate the natural logarithm of the absolute value of delta. The sign of delta is preserved to differentiate between positive and negative values. This transformation helps in scaling the delta values, especially useful when dealing with large numbers.
This script essentially provides a visual representation of the buying and selling pressures in a market, transformed logarithmically for better scaling and smoothed for trend analysis.
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any!
Tick Volume Direction IndicatorTick Volume Direction Indicator
This indicator captures:
• tick volume
• tick direction
The settings are as follows:
• volume or base currency value selection.
• label distance (away from the low of the candle).
• Tick volume - on/off switch for tick volume.
• label size.
• Up tick move color.
• tick move absorbed - when the tick doesn't change position.
• Down tick move.
On the first initial load, it will have the existing volume data as "?" as tradingview doesn't have a history of each tick.
Be aware, any settings change you make will refresh the tick data from start.
This indicator is one of the best real-time ways of seeing buying and selling pressure.
Logarithmic Volatility Direction Index [IkkeOmar]The LVDI is a Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se.
What it does is tell you if we have a flashcrash based on the price action and volume that is available. It is not always easy to see with the naked eye, so this indicator can help you DCA into an asset in a smarter way, if you couple it with other trend systems.
Think of this indicator like a form of a volatility index.
Inputs:
len and lenWMA are integers representing different lengths for calculations, and src is the data source
Keep in mind that "Length" is the lookback for the WMA, and the Length smooting is the lookback for the SMA of the "volume_weighted".
WMA Calculation
wma_basic = math.log10(ta.wma(src, len))
This calculates the logarithm (base 10) of the Weighted Moving Average (WMA) of the source data over len periods. WMA is a type of moving average giving more importance to recent data. The reason I use log10, is to make it transformative over a longer timeframe. This makes it easier to see the growth direction. I like to use this for crypto, since there is asymetric upside.
Volume Filter:
average_volume = ta.sma(volume, lenWMA)
volume_weighted = math.log10(wma_basic * (volume / math.log10(average_volume)))
Here, the script first calculates the Simple Moving Average (SMA) of the trading volume over lenWMA periods. Then, it computes a volume-weighted value of the WMA, adjusted by the logarithmic ratio of current volume to average volume.
Distance and Score Calculation:
distance = math.log10(src) - math.log10(volume_weighted)
score = math.sign(distance) * math.pow(math.abs(distance), 2)
The script calculates the logarithmic difference between the source data and the volume-weighted WMA. The score is determined by the sign of this distance multiplied by its square. This potentially amplifies the impact of larger distances.
Plotting:
plot(volume_weighted, title="Volume Weighted WMA", color=color.blue, linewidth = 2)
plot(ta.sma(volume_weighted, lenWMA), title="Volume Weighted WMA", color=color.rgb(189, 160, 0))
Mathematical concepts
Weighted Moving Average (WMA):
WMA is a moving average that assigns more weight to recent data points. The idea is that recent prices are more relevant to the current trend than older prices.
Logarithms:
The use of log10 (logarithm base 10) is interesting. Logarithms help in normalizing data and can make certain patterns more visible, especially when dealing with exponential growth or decay.
Volume Weighting:
Multiplying the WMA by the ratio of current volume to average volume (both logarithmic) integrates volume into the analysis. High trading volume can signify stronger market interest and can thus validate price movements.
Distance and Score:
The distance measures how far the current price is from the volume-weighted WMA on a logarithmic scale. The score squares this distance, potentially highlighting large divergences.
Case example
In the case above (which is a low timeframe that shouldn't be your main system) we see the blue line going up before going below the moving average line (orange). This indicates a local bottom zone. Does that mean that we wont go lower? No! What you can do is calculate a zone range.
We have an average line, you can get that from the POC with the VRVP.
Then you take the low and high of that zone and take the average:
(3.17% + 2.33%) / 2 = 2.75%
This means that we expect that the price can fall an additional 2.75%! Low and behold. When you check the same chart as above:
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any!
Channel CorridorOVERVIEW
The Channel Corridor indicator is designed to operate on a log chart of asset prices (e.g., BTCUSD), specifically on a weekly timeframe.
The intent of the indicator is to provide a visual representation of market dynamics, focusing on a dynamically adjusted corridor around a Simple Moving Average (SMA) of an asset's price. The corridor adapts to changing market conditions. The indicator includes channels within the corridor for additional reference points.
PURPOSE
Trend Identification: The channel corridor can aid in visualising the overall trend, as it dynamically adjusts the corridor based on an SMA and user-defined parameters.
Volatility Assessment: The width of the channel corridor can may act as a gauge of market volatility.
Reversal Points: The channel corridor may signal potential trend reversals or corrections when an asset price approaches the upper or lower bounds of the corridor.
Long-Term Trend Analysis: The channel corridor may aid in longer-term trend analysis.
CONSIDERATIONS
Validation: It's recommended that careful back-testing over historical data be done before acting on any identified opportunities.
User Discretion: Trading decisions should not rely solely on this script. Users should exercise judgment and consider market conditions.
CREDIT
Ideation: Thanks @Sw1ngTr4der for the idea and corridor seed code
Historical Volatility StudyThe goal of this script it to provide you an idea to forecast the future momentum by looking at historical volatility.
This chart has basically three parts.
1. Three lines are there. The multi color line represents the historical annualized volatility in terms of minimum look back period . The white line represents the historical annualized volatility in terms of medium term look back period . The green line represents the historical annualized volatility in terms of longer term look back period .
2. The back ground color has three components. Green zone is the zone where overall volatility is on the lower side. Red zone is the zone where overall volatility is on the higher side. Purple zone means fluctuating volatility.
3. The multi color line has three colors. Red color means volatility moving towards extreme low. Yellow means it is moving towards extreme high. Purple means it is in normal course of action.
This tool can be used as a confirmation tool with other studies to aid you to make better decisions. For example- look at the diagram below.
Make your thorough study before making any trading decision. Thanks.
Fibonacci Bollinger Volume Weighted DeviationDiscover market dynamics with the 'Fibonacci Bollinger Volume Weighted Deviation' indicator – a unique tool blending Fibonacci ratios, Bollinger Bands, and volume-weighted analysis. Ideal for spotting overbought/oversold conditions and potential market turnarounds, this indicator is a must-have for traders seeking nuanced insights into price behavior and volatility.
Description:
"The 'Fibonacci Bollinger Volume Weighted Deviation' indicator presents a novel approach to market trend analysis by integrating Fibonacci ratios with the classic concept of Bollinger Bands. Designed for traders who incorporate Fibonacci levels in their market analysis, this indicator adapts Bollinger Bands to a user-defined Fibonacci ratio. It creates dynamic upper and lower bands around a Simple Moving Average (SMA), offering insights into price deviations and potential overbought or oversold market states.
Incorporating volume data, this indicator provides a volume-weighted perspective of price deviations. This feature is crucial in gauging the market sentiment, as significant volumes linked with price deviations can signal strong market moves. By plotting these deviations and emphasizing those that significantly diverge from the volume-weighted average, it aids in pinpointing potential turning points or key support and resistance zones.
Versatile in nature, the 'Fibonacci Bollinger Volume Weighted Deviation' indicator is adaptable to various trading styles and market conditions. It proves especially valuable in markets where Fibonacci levels are a key factor. Traders can explore long positions when prices fall below the lower band and consider short positions when prices breach the upper band. The addition of volume-weighted deviation analysis refines these trading signals, offering a more sophisticated and nuanced decision-making process for entries and exits.
As a standalone tool or in conjunction with other technical instruments, this indicator is an invaluable addition to any technical analyst's toolkit. It not only enhances traditional Fibonacci and Bollinger Band methodologies but also integrates volume analysis to provide a comprehensive view of market trends and movements."
DNA GRAVITY PRICE V1 PINESCRIPTLABSWe can observe that this indicator displays the range within which the asset fluctuates around the average price, and its behavior depends on the parameters of amplitude and angular frequency. "price_mas" is a measure calculated as part of the indicator. It is derived by adding an adjusted amplitude (A_mas) multiplied by the cosine of the combination of angular frequency (w), time, and a phase shift (phi) to the average price (P0). This calculated value oscillates around the actual asset price and is used to identify potential turning points and the range where the price has established itself within the specified lookback period.
2.- At its core, the indicator utilizes the innovative concept of 'price_mas,' a calculated metric visualized in three essential colors: green to indicate low levels, blue for medium levels, and red for high levels. These colors reflect the position of the price in relation to a range determined by historical highs and lows.
In the context of the "DNA GRAVITY PRICE V1 " indicator, low, medium, and high levels specifically refer to the calculated value of 'price_mas,' which is a derived measure within the indicator. They do not directly refer to the actual asset price but rather to a calculated value that the indicator uses to analyze and predict the behavior of the asset's price.
This algorithm stands out for its ability to capture the 'strength' of the price through the 'price_mas' zones. Once the price exits the zones marked by the 'price_mas' (red, blue, and green plots), it tends to return with significant force.
Buy & Sell Signals:
Buy Signal: If the price and the Donchian lines cross above the high threshold, visually represented by red diamonds, it indicates a strong bullish momentum. This not only shows that the price is rising but also that the trend is strong enough to push the Donchian lines, which represent price extremes over a certain period, above the threshold. This convergence of movements, marked by the crossing over the red diamonds, suggests a higher probability of the bullish trend continuing.
Sell Signal: Similarly, if the price and the Donchian lines fall below the low threshold, visualized as green diamonds, this signals a significant bearish momentum. The simultaneous decline of the price and the Donchian lines below this threshold, marked by the green diamonds, indicates that not only is the price decreasing, but the bearish trend is strong enough to influence the price extremes calculated by the Donchian lines.
Configuration:
-The "Initial Dynamic Length of MAS Price" parameter controls the smoothness and sensitivity of the indicator. A high value smooths the Simple Moving Average (SMA), making the indicator less responsive to short-term price fluctuations. On the other hand, a low value makes the indicator more sensitive to short-term price fluctuations, generating faster and more volatile signals
-This parameter, "MAS Amplitude Percentage," determines the amplitude as a percentage. Increasing the Initial Dynamic Price will result in a larger amplitude relative to the price, leading to wider ranges for the indicator. Decreasing this value will have the opposite effect, reducing the amplitude relative to the price. Increasing "A_mas_pct" can make signals more extreme and less frequent, while decreasing it will make signals smoother and more frequent.
-This parameter, "Angular Frequency of MAS," affects the frequency of oscillations in the calculation of the "Initial Dynamic Price." A higher value of "w" will make the oscillations faster and more frequent, which means that the indicator will be more responsive to abrupt price changes. Conversely, a lower value will make the oscillations slower and smoother, making the indicator less sensitive to rapid price changes. Modifying ""Angular Frequency of MAS,"" directly impacts the frequency of oscillations in the indicator.
Español:
Podemos observar que este indicador muestra el rango en el cual el activo fluctúa alrededor del precio promedio y su comportamiento depende de los parámetros de amplitud y frecuencia angular. "price_mas" es una medida calculada como parte del indicador. Se deriva al sumar una amplitud ajustada (A_mas) multiplicada por el coseno de la combinación de frecuencia angular (w), tiempo y un desplazamiento de fase (phi) al precio promedio (P0). Este valor calculado oscila alrededor del precio real del activo y se utiliza para identificar posibles puntos de giro y el rango donde el precio se ha establecido dentro del período de búsqueda especificado.
En su núcleo, el indicador utiliza el innovador concepto de 'price_mas', una métrica calculada visualizada en tres colores esenciales: verde para indicar niveles bajos, azul para niveles medios y rojo para niveles altos. Estos colores reflejan la posición del precio en relación con un rango determinado por los máximos y mínimos históricos.
En el contexto del indicador "DNA GRAVITY PRICE V1", los niveles bajos, medios y altos se refieren específicamente al valor calculado de 'price_mas', que es una medida derivada dentro del indicador. No se refieren directamente al precio real del activo, sino a un valor calculado que el indicador utiliza para analizar y predecir el comportamiento del precio del activo.
Este algoritmo se destaca por su capacidad para capturar la 'fortaleza' del precio a través de las zonas de 'price_mas'. Una vez que el precio sale de las zonas marcadas por 'price_mas' (trazas rojas, azules y verdes), tiende a regresar con una fuerza significativa. Este comportamiento es crucial para los operadores, ya que proporciona oportunidades tanto para capitalizar las retracciones de precios como para anticipar posibles cambios de tendencia.
Señales de Compra y Venta:
Señal de Compra: Si el precio y las líneas Donchian cruzan por encima del umbral alto, visualmente representado por diamantes rojos, indica un fuerte impulso alcista. Esto no solo muestra que el precio está aumentando, sino que la tendencia es lo suficientemente fuerte como para empujar las líneas Donchian, que representan los extremos de precio durante un período determinado, por encima del umbral. Esta convergencia de movimientos, marcada por el cruce sobre los diamantes rojos, sugiere una mayor probabilidad de que la tendencia alcista continúe.
Señal de Venta: De manera similar, si el precio y las líneas Donchian caen por debajo del umbral bajo, visualizado como diamantes verdes, esto señala un fuerte impulso bajista. La caída simultánea del precio y las líneas Donchian por debajo de este umbral, marcada por los diamantes verdes, indica que no solo el precio está disminuyendo, sino que la tendencia bajista es lo suficientemente fuerte como para influir en los extremos de precio calculados por las líneas Donchian.
Configuración:
El parámetro "Longitud Dinámica Inicial de MAS Price" controla la suavidad y la sensibilidad del indicador. Un valor alto suaviza el Promedio Móvil Simple (SMA), lo que hace que el indicador sea menos sensible a las fluctuaciones de precio a corto plazo. Por otro lado, un valor bajo hace que el indicador sea más sensible a las fluctuaciones de precio a corto plazo, generando señales más rápidas y volátiles.
Este parámetro, "Porcentaje de Amplitud de MAS," determina la amplitud como un porcentaje. Aumentar el valor de "Longitud Dinámica Inicial de MAS Price" dará como resultado una amplitud más grande en relación con el precio, lo que conducirá a rangos más amplios para el indicador. Disminuir este valor tendrá el efecto contrario, reduciendo la amplitud en relación con el precio. Aumentar "Porcentaje de A_mas" puede hacer que las señales sean más extremas y menos frecuentes, mientras que disminuirlo hará que las señales sean más suaves y más frecuentes.
Este parámetro, "Frecuencia Angular de MAS," afecta la frecuencia de las oscilaciones en el cálculo del "Precio Móvil Simple Inicial." Un valor más alto de "w" hará que las oscilaciones sean más rápidas y frecuentes, lo que significa que el indicador será más receptivo a cambios abruptos en el precio. Por otro lado, un valor más bajo hará que las oscilaciones sean más lentas y suaves, haciendo que el indicador sea menos sensible a cambios rápidos en el precio. Modificar "Frecuencia Angular de MAS" afecta directamente la frecuencia de las oscilaciones en el indicador.
Anchored Chandelier ExitThe Chandelier Exit is a popular tool among traders used to help determine appropriate stop loss levels. Originally developed by Chuck LeBeau, the Chandelier Exit takes into account market volatility and adjusts the stop loss level dynamically. This indicator builds upon the original Chandelier Exit by allowing the trader to select an anchor date or starting point for the indicator to begin calculating from.
The Original Chandelier Exit
Before we get into the details of the Anchored Chandelier Exit, let's review the original. Essentially a dynamic ATR stop loss, the Chandelier Exit provides a trailing stop that moves higher or lower based on volatility.
The Chandelier Exit is calculated based on the following criteria:
🔶ATR - The ATR is used to measure the volatility of a security over a lookback period. The ATR length determines the number of bars to consider when calculating the average true range. The shorter the length, the more responsive the level will be.
🔶ATR Multiplier - The default multiplier is set to 3. This is used to determine the sensitivity of the Chandelier Exit. The higher the ATR multiplier the wider the stop levels will be. A lower multiplier will tighten stop levels.
🔶Highest / Lowest Points - Determine the highest high (bullish trade) or lowest low (bearish trade) during the lookback period. The default length is 22 bars.
Calculating the Chandelier Exit
Bullish trades - Highest High - ATR * Multiplier
Bearish trades - Lowest Low + ATR * Multiplier
The Anchored Chandelier Exit
The Anchored Chandelier Exit is a new twist on the original, allowing traders to adapt their stop loss levels based on specific market events, levels or bars.
Similar to the original, traders can select the ATR length and multiplier, however, the high or low from which the ATR is subtracted or added is first determined at the anchor bar.
As new bars form, the indicator checks for the previous high/low to be breached. If the high or low is exceeded, the highest/lowest point is updated and the Chandelier Exit is recalculated.
When the indicator is first loaded to your chart, it will ask you to select an anchor bar and choose the bias for the trade.
A bullish (long) bias trade will plot the Chandelier Exit below price action, while a bearish (short) bias trade will plot the Chandelier Exit above price action.
Indicator Features
🔶Custom Start Date
🔶Bullish or Bearish Bias
🔶Selectable ATR Length & Multiplier
🔶Custom Colors
🔶Exit With Close or Wicks
🔶Exit Alerts
With careful parameter optimization, the Anchored Chandelier Exit can be a useful tool for helping traders manage risk based on market volatility.
Fibonacci Enhanced Bollinger BandsDiscover the synergistic power of Fibonacci ratios with traditional Bollinger Bands in the 'Fibonacci Enhanced Bollinger Bands' indicator. Ideal for traders seeking dynamic price levels for strategic entries and exits, this tool adds a unique Fibonacci twist to your technical analysis toolkit.
Introduction to Fibonacci Enhanced Bollinger Bands
'Fibonacci Enhanced Bollinger Bands' is a trading indicator that combines the classic Bollinger Bands approach with the powerful insights of Fibonacci ratios. By integrating these two concepts, this indicator offers traders a unique perspective on market volatility and potential support/resistance levels.
How It Works
Core Concept : The indicator calculates Bollinger Bands using a selected Fibonacci ratio. This ratio is applied to the standard deviation of the price series, providing a dynamic range around a Simple Moving Average (SMA).
Trading Strategies
Long Opportunities : The area below the lower band can be considered a potential zone for long positions. Prices in this zone may indicate an oversold market condition, suggesting a possible reversal or pullback.
Short Opportunities : Conversely, the area above the upper band might signal short-selling opportunities. Prices in this region could imply an overbought scenario, potentially leading to a price decline.
Versatility : Whether you're a day trader, swing trader, or long-term investor, this indicator adapts to various timeframes and assets, making it a versatile tool in your trading arsenal.
Conclusion
The 'Fibonacci Enhanced Bollinger Bands' indicator is designed for traders who wish to leverage the power of Fibonacci ratios in conjunction with the volatility insights provided by Bollinger Bands. It's an excellent tool for identifying potential reversal zones and refining entry and exit points. Try it out to enhance your market analysis and support your trading decisions with the combined wisdom of Fibonacci and Bollinger Bands.
Dynamic Volume-Volatility Adjusted MomentumThis Indicator in a refinement of my earlier script PC*VC Moving average Old with easier to follow color codes, overbought and oversold zones. This script has converted the previous script into a standardized measure by converting it into Z-scores and also incorporated a volatility based dynamic length option. Below is a detailed Explanation.
The "Dynamic Volume-Volatility Adjusted Momentum" or "Nasan Momentum Oscillator" is designed to capture market momentum while accounting for volume and volatility fluctuations. It leverages the Typical Price (TP), calculated as the average of high, low, and close prices, and introduces the Price Coefficient (PC) based on deviations from the simple moving average (SMA) across various time frames. Additionally, the Volume Coefficient (VC) compares current volume to SMA, and calculates Intraday Volatility (IDV) which gauges the daily price range relative to the close. Then intraday volatility ratio is calculated ( IDV Ratio) as the ratio of current Intraday Volatility (IDV) to the average of IDV for three different length periods, which provides a relative measure of current intraday volatility compared to its recent historical average. An inter-day ATR based Relative Volatility (RV) is calculated to adjusts for changing market volatility based on which the dynamic length adjustment adapts the moving average (standard length is 14). The PC *VC/IDV Ratio integrates price, volume, and volatility information which provides a volume and volatility adjusted momentum. This volume and volatility adjusted momentum is converted into a standardized Z-Score. The Z-Score measures deviations from the mean. Color-coded plots visually represent momentum, and thresholds aid in identifying overbought or oversold conditions.
The indicator incorporates a nuanced approach to emphasize the joint impact of price and volume while considering the stabilizing effect of lower intraday volatility. Placing the volume ratio (VC) in the numerator means that higher volume positively contributes to the overall ratio, aligning with the observation that increased volumes often accompany robust price movements. Simultaneously, the decision to include the inverse of intraday volatility (1/IDV) in the denominator acts as a dampener, reducing the impact of extreme intraday volatility on the momentum indicator. This design choice aims to filter out noise, giving more weight to significant price changes supported by substantial trading activity. In essence, the indicator's design seeks to provide a more robust momentum measure that balances the influence of price, volume, and volatility in the analysis of market dynamics.
Unbound RSIUnbound RSI
Description
The Unbound RSI or de-oscillated RSI indicator is a novel technical analysis indicator that combines the concepts of the Relative Strength Index (RSI) and moving averages, applied directly over the price chart. This indicator is unique in its approach by transforming the oscillatory nature of the RSI into a format that aligns with the price action, thereby offering a distinctive view of market momentum and trends.
Key Features
Multi-Length RSI Analysis: Incorporates three different lengths of RSI (short, medium, and long), providing insights into the momentum and trend strength at various timeframes.
Deoscillation of RSI: The RSI for each length is 'deoscillated' by adjusting its scale to align with the actual price movements. This is achieved by shifting and scaling the RSI values, effectively merging them with the price line.
Average True Range (ATR) Scaling: The deoscillation process includes scaling by the Average True Range (ATR), making the indicator responsive to the asset’s volatility.
Optional Smoothing: Provides an option to apply a simple moving average (SMA) smoothing to each deoscillated RSI line, reducing noise and highlighting more significant trends.
Dynamic Moving Average (MA) Baseline: Features a moving average calculated from the medium length (default value) de-oscillated RSI, serving as a dynamic baseline to identify overarching trends.
How It’s Different
Unlike standard RSI indicators that oscillate in a fixed range, this indicator transforms the RSI to move in tandem with the price, offering a unique perspective on momentum and trend changes. The use of multiple timeframes for RSI and the inclusion of a dynamic MA baseline provide a multifaceted view of market conditions.
Potential Usage
Trend Identification: The position of the price in relation to the different deoscillated RSI lines and the MA baseline can indicate the prevailing market trend.
Momentum Shifts: Crossovers of the price with the deoscillated RSI lines or the MA baseline can signal potential shifts in momentum, offering entry or exit points.
Volatility Awareness: The ATR-based scaling of the deoscillated RSI lines means the indicator adjusts to changes in volatility, potentially offering more reliable signals in different market conditions.
Comparative Analysis: By comparing the short, medium, and long deoscillated RSI lines, traders can gauge the strength of trends and the convergence or divergence of momentum across timeframes.
Best Practices
Backtesting: Given its novel nature, it’s crucial to backtest the indicator across different assets and market conditions.
Complementary Tools: Combine with other technical analysis tools (like support/resistance levels, other oscillators, volume analysis) for more robust trading signals.
Risk Management: Always use sound risk management strategies, as no single indicator provides foolproof signals.
Gap SMAGap SMA Indicator - Analyzing Price Gaps with Moving Averages
Description:
The Gap SMA (Simple Moving Average) indicator is a powerful tool designed to analyze price gaps, a phenomenon occurring when the market opens significantly higher or lower than the previous session's close. These gaps often signify abrupt shifts in market sentiment, driven by fundamental news, earnings reports, or overnight geopolitical events.
This indicator calculates and visualizes the average gap-up and gap-down based on historical data, aiding traders in identifying potential support or resistance levels driven by gap behavior.
What is a Gap?
In financial markets, a gap occurs when there is a notable difference (upward or downward) between the previous session's close and the current session's open. Gaps can be categorized as gap-ups (when the current open is higher than the previous close) or gap-downs (when the current open is lower than the previous close).
Key Features:
User-Defined Parameters: Adjust the number of gaps considered and a multiplier factor for precise customization.
Average Gap Visualization: Plotting lines representing the moving average of gap-ups and gap-downs.
Alert System: Alerts notify traders when the close price crosses above/below the average gap lines, offering potential entry or exit signals.
This tool is particularly useful for swing traders and investors interested in understanding historical gap patterns and integrating this information into their decision-making process. It can assist in determining potential stop-loss levels, defining entry or exit points, and gauging market sentiment based on gap behavior.
Feel free to experiment with various settings and timeframes to suit your trading strategy and risk tolerance. Your feedback and suggestions for further enhancements are highly appreciated!
Variable Keltner Channel For DCAHello Everyone,
Sharing the indicator that I'm using for Dollar Cost Averaging into the stocks & ETFs in my portfolio.
Instead of entering regularly each month, entry only happens when the share price is below the indicator.
This indicator is based on Exponential Moving Average & Keltner Channel.
When 21 EMA is above 34 EMA, the line is 1 ATR below the 21 EMA. (green color)
When 21 EMA is below 34 EMA, the line is 2 ATR below the 21 EMA. (red color)
Exploring ways to refine this further, especially during sideways or transition to downtrend, do comment if you have any idea.
This strategy itself was based on SMA 50 strategy for DCA.
Red Candle ATRThis ATR - Average True Range - Measures only red candles, giving the average true range of market declines.
SuperTrend ToolkitThe SuperTrend Toolkit (Super Kit) introduces a versatile approach to trend analysis by extending the application of the SuperTrend indicator to a wide array of @TradingView's built-in or Community Scripts . This tool facilitates the integration of the SuperTrend algorithm with various indicators, including oscillators, moving averages, overlays, and channels.
Methodology:
The SuperTrend, at its core, calculates a trend-following indicator based on the Average-True-Range (ATR) and price action. It creates dynamic support and resistance levels, adjusting to changing market conditions, and aiding in trend identification.
pine_st(simple float factor = 3., simple int length = 10) =>
float atr = ta.atr(length)
float up = hl2 + factor * atr
up := up < nz(up ) or close > nz(up ) ? up : nz(up )
float lo = hl2 - factor * atr
lo := lo > nz(lo ) or close < nz(lo ) ? lo : nz(lo )
int dir = na
float st = na
if na(atr )
dir := 1
else if st == nz(up )
dir := close > up ? -1 : 1
else
dir := close < lo ? 1 : -1
st := dir == -1 ? lo : up
@TradingView's native SuperTrend lacks the flexibility to incorporate different price sources into its calculation.
Community scripts, addressed the limitation by implementing the option to input different price sources, for example, one of the most popular publications, @KivancOzbilgic's SuperTrend script.
In May 2023, @TradingView introduced an update allowing the passing of another indicator's plot as a source value via the input.source() function. However, the built-in ta.atr function still relied on the chart's price data, limiting the formerly mentioned scripts to the chart's price data alone.
Unique Approach -
This script addresses the aforementioned limitations by processing the data differently.
Firstly we create a User-Defined-Type (UDT) replicating a bar's open, high, low, close (OHLC) values.
type bar
float o = open
float h = high
float l = low
float c = close
We then use this type to store the external input data.
src = input.source(close, "External Source")
bar b = bar.new(
nz(src ) , open 𝘷𝘢𝘭𝘶𝘦
math.max(nz(src ), src), high 𝘷𝘢𝘭𝘶𝘦
math.min(nz(src ), src), low 𝘷𝘢𝘭𝘶𝘦
src ) close 𝘷𝘢𝘭𝘶𝘦
Finally, we pass the data into our custom built SuperTrend with ATR functions to derive the external source's version of the SuperTrend indicator.
supertrend st = b.st(mlt, len)
- Setup Guide -
Utility and Use Cases:
Universal Compatibility - Apply SuperTrend to any built-in indicator or script, expanding its use beyond traditional price data.
- A simple example on one of my own public scripts -
Trend Analysis - Gain additional trend insights into otherwise mainly mean reverting or volume indicators.
- Alerts Setup Guide -
The Super Kit empowers traders and analysts with a tool that adapts the robust SuperTrend algorithm to a myriad of indicators, allowing comprehensive trend analysis and strategy development.
Market SessionsMarket Sessions Indicator Overview:
The "Market Sessions" indicator is a powerful tool designed to enhance traders' insights by providing comprehensive information about key market sessions, daily high/low values, and important exponential moving averages (EMAs) directly on the trading chart.
Key Features:
Market Sessions Display:
Visually represents Sydney/Tokyo, London, and New York sessions using distinct color-coded shapes.
Enhances visibility by dynamically changing the background color during specific trading sessions.
Daily High/Low:
Plots and labels the high and low values of the previous trading day on the chart.
Customizable colors for daily high and low markers.
Exponential Moving Averages (EMAs):
Includes 20, 50, and 200-period EMAs for comprehensive trend analysis.
Users have the flexibility to customize the visibility and color of each EMA.
Dashboard Information:
Real-time information about the current and upcoming market sessions.
Displays the time remaining for the upcoming session, aiding in timely decision-making.
Stock Session Information:
Clearly marks open and close times for Asia, Euro, and USA stock sessions.
Customizable visibility options for stock open/close lines, allowing for a tailored chart display.
Usage Guidelines:
Market Session Identification: Easily identify distinct market sessions using color-coded shapes and background color changes.
Daily Analysis: Quickly reference labeled lines for the high and low values of the previous trading day.
Trend Analysis: Observe the plotted EMAs on the chart for insights into the prevailing trends.
Real-time Monitoring: Utilize the dashboard for real-time information on current and upcoming sessions.
Stock Session Details: Identify specific open and close times for stock sessions, aiding in strategic planning.
Customization Options:
User-Friendly Parameters: Customize visibility, color, and positioning based on individual preferences.
Dashboard Configuration: Adjust dashboard position, text placement, and EMA parameters to tailor the indicator to specific needs.
Backtesting Feature:
The indicator includes a backtest feature, allowing users to visualize past sessions for testing and refining trading strategies.
This Market Sessions Indicator provides traders with a holistic view of market dynamics, facilitating informed decision-making and enhancing overall trading experiences.
