N-Degree Moment-Based Adaptive Detection🙏🏻 N-Degree Moment-Based Adaptive Detection (NDMBAD) method is a generalization of MBAD since the horizontal line fit passing through the data's mean can be simply treated as zero-degree polynomial regression. We can extend the MBAD logic to higher-degree polynomial regression.
I don't think I need to talk a lot about the thing there; the logic is really the same as in MBAD, just hit the link above and read if you want. The only difference is now we can gather cumulants not only from the horizontal mean fit (degree = 0) but also from higher-order polynomial regression fit, including linear regression (degree = 1).
Why?
Simply because residuals from the 0-degree model don't contain trend information, and while in some cases that's exactly what you need, in other cases, you want to model your trend explicitly. Imagine your underlying process trends in a steady manner, and you want to control the extreme deviations from the process's core. If you're going to use 0-degree, you'll be treating this beautiful steady trend as a residual itself, which "constantly deviates from the process mean." It doesn't make much sense.
How?
First, if you set the length to 0, you will end up with the function incrementally applied to all your data starting from bar_index 0. This can be called the expanding window mode. That's the functionality I include in all my scripts lately (where it makes sense). As I said in the MBAD description, choosing length is a matter of doing business & applied use of my work, but I think I'm open to talk about it.
I don't see much sense in using degree > 1 though (still in research on it). If you have dem curves, you can use Fourier transform -> spectral filtering / harmonic regression (regression with Fourier terms). The job of a degree > 0 is to model the direction in data, and degree 1 gets it done. In mean reversion strategies, it means that you don't wanna put 0-degree polynomial regression (i.e., the mean) on non-stationary trending data in moving window mode because, this way, your residuals will be contaminated with the trend component.
By the way, you can send thanks to @aaron294c , he said like mane MBAD is dope, and it's gonna really complement his work, so I decided to drop NDMBAD now, gonna be more useful since it covers more types of data.
I wanned to call it N-Order Moment Adaptive Detection because it abbreviates to NOMAD, which sounds cool and suits me well, because when I perform as a fire dancer, nomad style is one of my outfits. Burning Man stuff vibe, you know. But the problem is degree and order really mean two different things in the polynomial context, so gotta stay right & precise—that's the priority.
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Bands and Channels
Fibonacci Bands [BigBeluga]The Fibonacci Band indicator is a powerful tool for identifying potential support, resistance, and mean reversion zones based on Fibonacci ratios. It overlays three sets of Fibonacci ratio bands (38.2%, 61.8%, and 100%) around a central trend line, dynamically adapting to price movements. This structure enables traders to track trends, visualize potential liquidity sweep areas, and spot reversal points for strategic entries and exits.
🔵 KEY FEATURES & USAGE
Fibonacci Bands for Support & Resistance:
The Fibonacci Band indicator applies three key Fibonacci ratios (38.2%, 61.8%, and 100%) to construct dynamic bands around a smoothed price. These levels often act as critical support and resistance areas, marked with labels displaying the percentage and corresponding price. The 100% band level is especially crucial, signaling potential liquidity sweep zones and reversal points.
Mean Reversion Signals at 100% Bands:
When price moves above or below the 100% band, the indicator generates mean reversion signals.
Trend Detection with Midline:
The central line acts as a trend-following tool: when solid, it indicates an uptrend, while a dashed line signals a downtrend. This adaptive midline helps traders assess the prevailing market direction while keeping the chart clean and intuitive.
Extended Price Projections:
All Fibonacci bands extend to future bars (default 30) to project potential price levels, providing a forward-looking perspective on where price may encounter support or resistance. This feature helps traders anticipate market structure in advance and set targets accordingly.
Liquidity Sweep:
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-Liquidity Sweep at Previous Lows:
The price action moves below a previous low, capturing sell-side liquidity (stop-losses from long positions or entries for breakout traders).
The wick suggests that the price quickly reversed, leaving a failed breakout below support.
This is a classic liquidity grab, often indicating a bullish reversal .
-Liquidity Sweep at Previous Highs:
The price spikes above a prior high, sweeping buy-side liquidity (stop-losses from short positions or breakout entries).
The wick signifies rejection, suggesting a failed breakout above resistance.
This is a bearish liquidity sweep , often followed by a mean reversion or a downward move.
Display Customization:
To declutter the chart, traders can choose to hide Fibonacci levels and only display overbought/oversold zones along with the trend-following midline and mean reversion signals. This option enables a clearer focus on key reversal areas without additional distractions.
🔵 CUSTOMIZATION
Period Length: Adjust the length of the smoothed moving average for more reactive or smoother bands.
Channel Width: Customize the width of the Fibonacci channel.
Fibonacci Ratios: Customize the Fibonacci ratios to reflect personal preference or unique market behaviors.
Future Projection Extension: Set the number of bars to extend Fibonacci bands, allowing flexibility in projecting price levels.
Hide Fibonacci Levels: Toggle the visibility of Fibonacci levels for a cleaner chart focused on overbought/oversold regions and midline trend signals.
Liquidity Sweep: Toggle the visibility of Liquidity Sweep points
The Fibonacci Band indicator provides traders with an advanced framework for analyzing market structure, liquidity sweeps, and trend reversals. By integrating Fibonacci-based levels with trend detection and mean reversion signals, this tool offers a robust approach to navigating dynamic price action and finding high-probability trading opportunities.
RVWAP ENHANCED**Rolling VWAP with Alerts and Markers**
This Pine Script indicator enhances the traditional Rolling VWAP (Relative Volume Weighted Average Price) by adding dynamic features for improved visualization and alerting.
### Features:
1. **Dynamic VWAP Line Coloring**:
- The VWAP line changes color based on the relationship with the closing price:
- **Green** when the price is above the VWAP.
- **Red** when the price is below the VWAP.
2. **Candle and Background Coloring**:
- **Candles**: Colored green if the close is above the VWAP and red if below.
- **Background**: Subtle green or red shading indicates the price’s position relative to the VWAP.
3. **Alerts**:
- Alerts notify users when the VWAP changes direction:
- "VWAP Turned Green" for price crossing above the VWAP.
- "VWAP Turned Red" for price crossing below the VWAP.
4. **Small Dot Markers**:
- Tiny dots are plotted below the candles to mark VWAP state changes:
- **Green dot** for VWAP turning green.
- **Red dot** for VWAP turning red.
5. **Custom Time Period**:
- Users can select either a dynamic time period based on the chart's timeframe or a fixed time period (customizable in days, hours, and minutes).
6. **Standard Deviation Bands (Optional)**:
- Standard deviation bands around the VWAP can be enabled for further analysis.
This script is designed to provide clear and actionable insights into market trends using the RVWAP, making it an excellent tool for traders who rely on volume-based price action analysis.
Moment-Based Adaptive DetectionMBAD (Moment-Based Adaptive Detection) : a method applicable to a wide range of purposes, like outlier or novelty detection, that requires building a sensible interval/set of thresholds. Unlike other methods that are static and rely on optimizations that inevitably lead to underfitting/overfitting, it dynamically adapts to your data distribution without any optimizations, MLE, or stuff, and provides a set of data-driven adaptive thresholds, based on closed-form solution with O(n) algo complexity.
1.5 years ago, when I was still living in Versailles at my friend's house not knowing what was gonna happen in my life tomorrow, I made a damn right decision not to give up on one idea and to actually R&D it and see what’s up. It allowed me to create this one.
The Method Explained
I’ve been wandering about z-values, why exactly 6 sigmas, why 95%? Who decided that? Why would you supersede your opinion on data? Based on what? Your ego?
Then I consciously noticed a couple of things:
1) In control theory & anomaly detection, the popular threshold is 3 sigmas (yet nobody can firmly say why xD). If your data is Laplace, 3 sigmas is not enough; you’re gonna catch too many values, so it needs a higher sigma.
2) Yet strangely, the normal distribution has kurtosis of 3, and 6 for Laplace.
3) Kurtosis is a standardized moment, a moment scaled by stdev, so it means "X amount of something measured in stdevs."
4) You generate synthetic data, you check on real data (market data in my case, I am a quant after all), and you see on both that:
lower extension = mean - standard deviation * kurtosis ≈ data minimum
upper extension = mean + standard deviation * kurtosis ≈ data maximum
Why not simply use max/min?
- Lower info gain: We're not using all info available in all data points to estimate max/min; we just pick the current higher and lower values. Lol, it’s the same as dropping exponential smoothing with alpha = 0 on stationary data & calling it a day.
You can’t update the estimates of min and max when new data arrives containing info about the matter. All you can do is just extend min and max horizontally, so you're not using new info arriving inside new data.
- Mixing order and non-order statistics is a bad idea; we're losing integrity and coherence. That's why I don't like the Hurst exponent btw (and yes, I came up with better metrics of my own).
- Max & min are not even true order statistics, unlike a percentile (finding which requires sorting, which requires multiple passes over your data). To find min or max, you just need to do one traversal over your data. Then with or without any weighting, 100th percentile will equal max. So unlike a weighted percentile, you can’t do weighted max. Then while you can always check max and min of a geometric shape, now try to calculate the 56th percentile of a pentagram hehe.
TL;DR max & min are rather topological characteristics of data, just as the difference between starting and ending points. Not much to do with statistics.
Now the second part of the ballet is to work with data asymmetry:
1) Skewness is also scaled by stdev -> so it must represent a shift from the data midrange measured in stdevs -> given asymmetric data, we can include this info in our models. Unlike kurtosis, skewness has a sign, so we add it to both thresholds:
lower extension = mean - standard deviation * kurtosis + standard deviation * skewness
upper extension = mean + standard deviation * kurtosis + standard deviation * skewness
2) Now our method will work with skewed data as well, omg, ain’t it cool?
3) Hold up, but what about 5th and 6th moments (hyperskewness & hyperkurtosis)? They should represent something meaningful as well.
4) Perhaps if extensions represent current estimated extremums, what goes beyond? Limits, beyond which we expect data not to be able to pass given the current underlying process generating the data?
When you extend this logic to higher-order moments, i.e., hyperskewness & hyperkurtosis (5th and 6th moments), they measure asymmetry and shape of distribution tails, not its core as previous moments -> makes no sense to mix 4th and 3rd moments (skewness and kurtosis) with 5th & 6th, so we get:
lower limit = mean - standard deviation * hyperkurtosis + standard deviation * hyperskewness
upper limit = mean + standard deviation * hyperkurtosis + standard deviation * hyperskewness
While extensions model your data’s natural extremums based on current info residing in the data without relying on order statistics, limits model your data's maximum possible and minimum possible values based on current info residing in your data. If a new data point trespasses limits, it means that a significant change in the data-generating process has happened, for sure, not probably—a confirmed structural break.
And finally we use time and volume weighting to include order & process intensity information in our model.
I can't stress it enough: despite the popularity of these non-weighted methods applied in mainstream open-access time series modeling, it doesn’t make ANY sense to use non-weighted calculations on time series data . Time = sequence, it matters. If you reverse your time series horizontally, your means, percentiles, whatever, will stay the same. Basically, your calculations will give the same results on different data. When you do it, you disregard the order of data that does have order naturally. Does it make any sense to you? It also concerns regressions applied on time series as well, because even despite the slope being opposite on your reversed data, the centroid (through which your regression line always comes through) will be the same. It also might concern Fourier (yes, you can do weighted Fourier) and even MA and AR models—might, because I ain’t researched it extensively yet.
I still can’t believe it’s nowhere online in open access. No chance I’m the first one who got it. It’s literally in front of everyone’s eyes for centuries—why no one tells about it?
How to use
That’s easy: can be applied to any, even non-stationary and/or heteroscedastic time series to automatically detect novelties, outliers, anomalies, structural breaks, etc. In terms of quant trading, you can try using extensions for mean reversion trades and limits for emergency exits, for example. The market-making application is kinda obvious as well.
The only parameter the model has is length, and it should NOT be optimized but picked consciously based on the process/system you’re applying it to and based on the task. However, this part is not about sharing info & an open-access instrument with the world. This is about using dem instruments to do actual business, and we can’t talk about it.
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Triple Smoothed Signals [AlgoAlpha]Introducing the Triple Smoothed Signals indicator by AlgoAlpha, a powerful tool designed to help traders identify trend direction and market momentum with greater accuracy. By applying triple smoothing techniques to your chosen data source, this indicator filters out market noise, allowing you to focus on significant price movements. Perfect for traders looking to enhance their technical analysis and gain an edge in the markets.
Key Features
🎨 Customizable Moving Averages : Choose between EMA, SMA, RMA, or WMA for both the triple smoothing and the signal line to tailor the indicator to your trading style.
🛠 Adjustable Smoothing Lengths : Configure the main smoothing length and signal length to fit different timeframes and market conditions.
🌈 Dynamic Color Fills : Visual gradients and fills highlight trend strength and direction, making chart analysis more intuitive.
🔔 Alerts : Set alerts for bullish and bearish crossover signals to stay ahead of market moves without constant chart monitoring.
📈 Clear Signal Visualization : Bullish and bearish signals are plotted directly on your chart for easy interpretation and timely decision-making.
Quick Guide to Using the Triple Smoothed Signals Indicator
🛠 Add the Indicator : Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites. Customize the settings such as the main smoothing length, signal length, data source, and moving average types to match your trading strategy.
📊 Market Analysis : Monitor the crossovers between the triple smoothed moving average and the signal line. A bullish signal is generated when the signal line crosses under the triple smoothed MA, indicating a potential upward trend. Conversely, a bearish signal occurs when the signal line crosses over the triple smoothed MA, suggesting a possible downward trend.
🔔 Alerts : Enable notifications for reversal signals and trend shifts to stay informed about market movements without constantly monitoring the chart.
How It Works
The Triple Smoothed Signals indicator enhances trend detection by applying a triple smoothing process to your selected data source using the moving average type of your choice (EMA, SMA, RMA, or WMA). This triple smoothed moving average (v1) effectively reduces short-term fluctuations and noise, revealing the underlying market trend. A signal line (v2) is then calculated by smoothing the triple smoothed MA with a separate moving average, further refining the signal. The indicator calculates the normalized distance between the triple smoothed MA and the signal line over a specified period, which is used to create dynamic color gradients and fills on the chart. These visual elements provide immediate insight into trend strength and direction. Bullish and bearish signals are generated based on the crossovers between the signal line and the triple smoothed MA, and are plotted directly on the chart along with customizable alerts to assist traders in making timely decisions.
Hybrid Triple Exponential Smoothing🙏🏻 TV, I present you HTES aka Hybrid Triple Exponential Smoothing, designed by Holt & Winters in the US, assembled by me in Saint P. I apply exponential smoothing individually to the data itself, then to residuals from the fitted values, and lastly to one-point forecast (OPF) errors, hence 'hybrid'. At the same time, the method is a closed-form solution and purely online, no need to make any recalculations & optimize anything, so the method is O(1).
^^ historical OPFs and one-point forecasting interval plotted instead of fitted values and prediction interval
Before the How-to, first let me tell you some non-obvious things about Triple Exponential smoothing (and about Exponential Smoothing in general) that not many catch. Expo smoothing seems very straightforward and obvious, but if you look deeper...
1) The whole point of exponential smoothing is its incremental/online nature, and its O(1) algorithm complexity, making it dope for high-frequency streaming data that is also univariate and has no weights. Consequently:
- Any hybrid models that involve expo smoothing and any type of ML models like gradient boosting applied to residuals rarely make much sense business-wise: if you have resources to boost the residuals, you prolly have resources to use something instead of expo smoothing;
- It also concerns the fashion of using optimizers to pick smoothing parameters; honestly, if you use this approach, you have to retrain on each datapoint, which is crazy in a streaming context. If you're not in a streaming context, why expo smoothing? What makes more sense is either picking smoothing parameters once, guided by exogenous info, or using dynamic ones calculated in a minimalistic and elegant way (more on that in further drops).
2) No matter how 'right' you choose the smoothing parameters, all the resulting components (level, trend, seasonal) are not pure; each of them contains a bit of info from the other components, this is just how non-sequential expo smoothing works. You gotta know this if you wanna use expo smoothing to decompose your time series into separate components. The only pure component there, lol, is the residuals;
3) Given what I've just said, treating the level (that does contain trend and seasonal components partially) as the resulting fit is a mistake. The resulting fit is level (l) + trend (b) + seasonal (s). And from this fit, you calculate residuals;
4) The residuals component is not some kind of bad thing; it is simply the component that contains info you consciously decide not to include in your model for whatever reason;
5) Forecasting Errors and Residuals from fitted values are 2 different things. The former are deltas between the forecasts you've made and actual values you've observed, the latter are simply differences between actual datapoints and in-sample fitted values;
6) Residuals are used for in-sample prediction intervals, errors for out-of-sample forecasting intervals;
7) Choosing between single, double, or triple expo smoothing should not be based exclusively on the nature of your data, but on what you need to do as well. For example:
- If you have trending seasonal data and you wanna do forecasting exclusively within the expo smoothing framework, then yes, you need Triple Exponential Smoothing;
- If you wanna use prediction intervals for generating trend-trading signals and you disregard seasonality, then you need single (simple) expo smoothing, even on trending data. Otherwise, the trend component will be included in your model's fitted values → prediction intervals.
8) Kind of not non-obvious, but when you put one smoothing parameter to zero, you basically disregard this component. E.g., in triple expo smoothing, when you put gamma and beta to zero, you basically end up with single exponential smoothing.
^^ data smoothing, beta and gamma zeroed out, forecasting steps = 0
About the implementation
* I use a simple power transform that results in a log transform with lambda = 0 instead of the mainstream-used transformers (if you put lambda on 2 in Box-Cox, you won't get a power of 2 transform)
* Separate set of smoothing parameters for data, residuals, and errors smoothing
* Separate band multipliers for residuals and errors
* Both typical error and typical residuals get multiplied by math.sqrt(math.pi / 2) in order to approach standard deviation so you can ~use Z values and get more or less corresponding probabilities
* In script settings → style, you can switch on/off plotting of many things that get calculated internally:
- You can visualize separate components (just remember they are not pure);
- You can switch off fit and switch on OPF plotting;
- You can plot residuals and their exponentially smoothed typical value to pick the smoothing parameters for both data and residuals;
- Or you might plot errors and play with data smoothing parameters to minimize them (consult SAE aka Sum of Absolute Errors plot);
^^ nuff said
More ideas on how to use the thing
1) Use Double Exponential Smoothing (data gamma = 0) to detrend your time series for further processing (Fourier likes at least weakly stationary data);
2) Put single expo smoothing on your strategy/subaccount equity chart (data alpha = data beta = 0), set prediction interval deviation multiplier to 1, run your strat live on simulator, start executing on real market when equity on simulator hits upper deviation (prediction interval), stop trading if equity hits lower deviation on simulator. Basically, let the strat always run on simulator, but send real orders to a real market when the strat is successful on your simulator;
3) Set up the model to minimize one-point forecasting errors, put error forecasting steps to 1, now you're doing nowcasting;
4) Forecast noisy trending sine waves for fun.
^^ nuff said 2
All Good TV ∞
100s Level LinesPurpose of the Script
- Visualize Key Levels: The script highlights round-number levels (e.g., 100, 200, 300) automatically, making it easy to identify areas where price action might react.
- Improve Decision-Making: These levels can serve as benchmarks for entry, exit, stop-loss, or take-profit placement.
- Simplicity: Instead of manually drawing levels, the script dynamically updates to match the chart's price range.
Features of the Script
- Dynamic Level Calculation: The script calculates 100s levels based on the asset's current price range and plots lines above and below the visible chart area.
- Customizable Settings: Adjust line color, style (solid, dashed, or dotted), and width to suit your charting preferences.
- Auto-Scaling: Automatically adjusts to the chart's visible price range, ensuring plotted levels are always relevant.
- Labeling: Each line can optionally display its exact value (e.g., "1400," "1500") for easy reference.
- Performance Optimization: Efficient calculations ensure the script doesn’t slow down TradingView, even on volatile instruments like the US100.
How the Script Works
- The script detects the highest and lowest visible prices on the chart to define the range.
- Starting from the lowest 100-point increment within the visible range, the script calculates all 100-point levels up to the highest visible price.
- It plots horizontal lines across the chart for each calculated level.
- Optionally, labels can be added to display the value of each level.
How to Use the Script
- Copy the script code into the Pine Script editor in TradingView and apply it to your chart.
- Open the script settings to adjust line color, style, width, and label visibility.
- Use the plotted 100s levels as psychological support and resistance zones for trade entries, exits, and stop-loss or take-profit placement.
Example Use Cases
- Identify potential reversal points as the price approaches a 100s level in intraday trading.
- Confirm support or resistance zones on higher timeframes for swing trading setups.
- Use the levels to trail stop-losses during trending markets and lock in profits incrementally.
Customizable Options
- Line Color: Change the color of the horizontal lines.
- Line Style: Choose solid, dashed, or dotted lines.
- Line Width: Adjust the thickness of the lines for better visibility.
- Show Labels: Toggle price values on or off for each level.
Advantages
- Saves Time: Automatically plots levels, eliminating manual effort.
- Adaptable: Works on all timeframes and assets.
- Psychological Relevance: Highlights levels that align with trader psychology and market behavior.
Perfect Hammer Pattern Indicators and Alerts# Perfect Hammer Pattern Indicators and Alerts
This indicator identifies a specific and precise hammer candlestick pattern formation that can signal potential trend reversals or continuation setups. Unlike traditional hammer pattern indicators, this script focuses on exact wick measurements to identify high-probability trade setups.
## Pattern Specifications
### Bullish Setup Requirements
- Two consecutive green (bullish) candles
- Both candles must have NO lower wick (perfect bottom)
- Both candles must have an upper wick (showing buying pressure)
- Previous candle must be red (bearish) for context
- Marked with a green 'H' below the pattern
### Bearish Setup Requirements
- Two consecutive red (bearish) candles
- Both candles must have NO upper wick (perfect top)
- Both candles must have a lower wick (showing selling pressure)
- Previous candle must be green (bullish) for context
- Marked with a red 'H' above the pattern
## Trading Logic
This pattern is particularly effective because it shows clear control by either buyers (bullish pattern) or sellers (bearish pattern):
- In the bullish pattern, the absence of lower wicks indicates strong buying pressure preventing prices from falling below the open, while the upper wicks show profit-taking at highs
- In the bearish pattern, the absence of upper wicks shows strong selling pressure capping any upward movement, while the lower wicks indicate some buying support below
## Alerts
The indicator includes two alert conditions:
1. Bullish Pattern Alert: Triggers when two perfect bullish hammers appear after a bearish candle
2. Bearish Pattern Alert: Triggers when two perfect bearish hammers appear after a bullish candle
## Usage Tips
- Best used on timeframes 15 minutes and above
- Consider using in conjunction with key support/resistance levels
- Volume confirmation can increase pattern reliability
- The pattern may signal either trend continuation or reversal - always consider the larger market context
## Notes
- This indicator focuses on precise hammer formations rather than approximate patterns
- The requirement for consecutive perfect hammers makes this a relatively rare but high-probability setup
- Visual markers ('H') provide easy pattern identification on charts
Whale Supertrend (V1.0)The script "Whale Supertrend (V1.0)" is an advanced trend indicator that uses multiple Supertrends with different factors to determine entry and exit points in the market. The Supertrend is a popular indicator that combines price and volatility to help identify trend direction. The script displays buy and sell signals based on the confluence of Supertrends.
How the script works
Configuring Supertrends
The script configures six Supertrends with different factors (factor, factor1, factor2, factor3, factor4, factor5) while using the same ATR period (atrPeriod = 10).
Supertrend 1: factor = 3
Supertrend 2: factor1 = 4
Supertrend 3: factor2 = 6
Supertrend 4: factor3 = 9
Supertrend 5: factor4 = 13
Supertrend 6: factor5 = 18
For each Supertrend, the bullish (blue) and bearish (purple) trend conditions are plotted on the chart.
Signal Calculation
The script calculates the number of Supertrends in bullish and bearish trend:
bullishCount: Number of Supertrends indicating a bullish trend.
bearishCount: Number of Supertrends indicating a bearish trend.
Signal Detection
The script triggers a buy or sell signal when at least three of the six Supertrends indicate the same trend:
Buy Signal (buySignal): Triggers when bullishCount is greater than or equal to 3.
Sell Signal (sellSignal): Triggers when bearishCount is greater than or equal to 3.
To avoid repetition, signals are only displayed when the state changes:
triggerBuy: Buy signal only when buySignal becomes true for the first time.
triggerSell: Sell signal only when sellSignal becomes true for the first time.
LRSI-TTM Squeeze - AynetThis Pine Script code creates an indicator called LRSI-TTM Squeeze , which combines two key concepts to analyze momentum, squeeze conditions, and price movements in the market:
Laguerre RSI (LaRSI): A modified version of RSI used to identify trend reversals in price movements.
TTM Squeeze: Identifies market compressions (low volatility) and potential breakouts from these squeezes.
Functionality and Workflow of the Code
1. Laguerre RSI (LaRSI)
Purpose:
Provides a smoother and less noisy version of RSI to track price movements.
Calculation:
The script uses a filtering coefficient (alpha) to process price data through four levels (L0, L1, L2, L3).
Movement differences between these levels calculate buying pressure (cu) and selling pressure (cd).
The ratio of these pressures forms the Laguerre RSI:
bash
Kodu kopyala
LaRSI = cu / (cu + cd)
The LaRSI value indicates:
Below 20: Oversold condition (potential buy signal).
Above 80: Overbought condition (potential sell signal).
2. TTM Squeeze
Purpose:
Analyzes the relationship between Bollinger Bands (BB) and Keltner Channels (KC) to determine whether the market is compressed (low volatility) or expanded (high volatility).
Calculation:
Bollinger Bands:
Calculated based on the moving average (SMA) of the price, with an upper and lower band.
Keltner Channels:
Created using the Average True Range (ATR) to calculate an upper and lower band.
Squeeze States:
Squeeze On: BB is within KC.
Squeeze Off: BB is outside KC.
Other States (No Squeeze): Neither of the above applies.
3. Momentum Calculation
Momentum is computed using the linear regression of the difference between the price and its SMA. This helps anticipate the direction and strength of price movements when the squeeze ends.
Visuals on the Chart
Laguerre RSI Line:
An RSI indicator scaled to 0-100 is plotted.
The line's color changes based on its movement:
Green line: RSI is rising.
Red line: RSI is falling.
Key levels:
20 level: Oversold condition (buy signal can be triggered).
80 level: Overbought condition (sell signal can be triggered).
Momentum Histogram:
Displays momentum as histogram bars with colors based on its direction and strength:
Lime (light green): Positive momentum increasing.
Green: Positive momentum decreasing.
Red: Negative momentum decreasing.
Maroon (dark red): Negative momentum increasing.
Squeeze Status Indicator:
A marker is plotted on the zero line to indicate the squeeze state:
Yellow: Squeeze On (compression active).
Blue: Squeeze Off (compression ended, movement expected).
Gray: No Squeeze.
Information Table
A table is displayed in the top-right corner of the chart, showing closing prices for different timeframes (e.g., 1 minute, 5 minutes, 1 hour, etc.). Each timeframe is color-coded.
Alerts
LaRSI Alerts:
Crosses above 20: Exiting oversold condition (buy signal).
Crosses below 80: Exiting overbought condition (sell signal).
Squeeze Alerts:
When the squeeze ends: Indicates a potential price move.
When the squeeze starts: Indicates volatility is decreasing.
Summary
This indicator is a powerful tool for determining market trends, momentum, and squeeze conditions. It helps users identify periods when the market is likely to move or remain stagnant, providing alerts based on these analyses to support trading strategies.
BTC InsightThis script is a comprehensive tool for analyzing Bitcoin's daily price range, trend predictions, and significant volume-based order block levels. It combines multiple technical analysis concepts, including exponential moving averages (EMAs), logarithmic calculations, and custom indicators for advanced forecasting and visualization.
Key Features and Technical Details
1. Exponential Moving Averages (EMAs)
The script calculates two smoothed EMAs:
EMA1 and EMA2 are derived from the logarithmic price of Bitcoin (log(close)).
The smoothing periods and multipliers are user-configurable through inputs:
Smoothed EMA1 Period (default: 728)
Smoothed EMA2 Period (default: 728)
Initial EMA Multipliers (default: 1.0 for EMA1, 5.0 for EMA2)
A time decay factor is applied to the multipliers to adjust sensitivity over time, making the EMAs adaptive to market dynamics.
2. Logarithmic Domain Calculations
The script uses logarithmic transformations to enhance accuracy when dealing with large price changes.
Adjustments to EMAs are made in the logarithmic domain and converted back to the price domain for plotting.
3. EMA Forecasting
The script performs a linear regression analysis over a specified period (728 bars by default) to estimate future price trends for both EMAs.
Slope Adjustments:
RSI (Relative Strength Index) is incorporated to modify the forecast slope dynamically:
RSI > 70: Bearish adjustment (-0.5)
RSI < 30: Bullish adjustment (+0.5)
Forecasts are plotted as dashed lines, projecting future values of EMA1 (green) and EMA2 (red).
4. Order Block Detection
Detects order block levels based on high volume spikes relative to the average volume over a lookback period (default: 100 bars).
A volume multiplier (default: 1.5x) is applied to identify significant volume activity.
Two types of order blocks are identified:
Below EMA1: A price zone where significant buying occurred below EMA1.
Above EMA2: A price zone where significant selling occurred above EMA2.
Order blocks are visualized as shaded rectangles:
Green boxes represent order blocks below EMA1.
Red boxes represent order blocks above EMA2.
5. Customization Inputs
The script allows fine-tuning via the following parameters:
EMA Settings: Periods, multipliers, and time factors for both EMAs.
Volume Analysis Settings: Lookback period and volume multiplier for order block detection.
Order Block Box Settings: Height of the range as a percentage of the detected price.
6. Visualization
EMAs: Two smoothed exponential moving averages are plotted with configurable offsets.
Forecast Lines: Dashed lines project future EMA trends based on regression analysis.
Order Block Boxes: Highlight areas of high volume below EMA1 and above EMA2, indicating potential support or resistance zones.
How It Works in Practice
EMAs and Trend Analysis:
The EMAs represent long-term market trends, adjusted dynamically using custom multipliers and time decay.
The script forecasts the EMAs' future trajectories to anticipate potential price movements.
Order Blocks:
High-volume zones indicate areas where significant market activity occurred, providing insights into potential price reversal points or continuation zones.
RSI Integration:
RSI-based slope adjustment fine-tunes the EMA forecast, adding an extra layer of dynamic market context.
Comprehensive View:
By combining trend forecasts with volume-based zones, the script delivers a robust analysis tool for identifying potential entry/exit points, support/resistance levels, and long-term trend predictions.
Drummond Geometry - Pldot and EnvelopeThis Pine Script will:
1.Calculate and display the PL Dot (Price Level Dot), a moving average that reflects short-term market trends.
2.Plot the Envelope Top and Bottom lines based on averages of previous highs and lows, which represent key areas of resistance and support.
Drummond Geometry Overview
Drummond Geometry is a method of market analysis focused on:
PL Dot : Captures market energy and trend direction. It reacts to price deviations and serves as a magnet for price returns, often referred to as a "PL Dot Refresh."
Envelope Theory : Considers price movements as cycles oscillating between the Envelope Top and Bottom. Prices breaking these boundaries often indicate trends, retracements, or exhaustion.
The geometry helps traders visualize energy flows in the market and anticipate directional changes using established support and resistance zones.
Understanding PL Dot and Envelope Top/Bottom
PL Dot:
Formula: Average(Average(H, L, C) of last three bars)
Usage: Indicates short-term trends:
Trend: PL Dot slopes upward or downward.
Congestion: PL Dot moves horizontally.
Envelope Top and Bottom:
Formula:
Top: (11 H1 + 11 H2 + 11 H3) / 3
Bottom: (11 L1 + 11 L2 + 11 L3) / 3
Usage: Acts as dynamic resistance and support:
Price above the top: Indicates strong bullish momentum.
Price below the bottom: Indicates strong bearish momentum.
Advantages of Drummond Geometry
Clarity of Market Flow: Highlights the relationship between price and key levels (PL Dot, Envelope Top/Bottom).
Predictive Power: Suggests possible reversals or continuation based on energy distribution.
Adaptability: Works across multiple time frames and market types (trending, congestion).
Trading Strategy
PL Dot Trades:
Buy: When price returns to the PL Dot in an uptrend.
Sell: When price returns to the PL Dot in a downtrend.
Envelope Trades:
Reversal: Trade counter to price if it breaks and retreats from the Envelope Top/Bottom.
Continuation: Trade in the direction of price if it sustains movement beyond the Envelope Top/Bottom.
Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger B# Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands
## Overview
This indicator combines the Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands to create a comprehensive trading system. It provides adaptive trend following capabilities while measuring market volatility and potential reversal points.
## Key Features
- Adaptive moving average that adjusts to market conditions
- Dynamic Bollinger Bands for volatility measurement
- Color-coded KAMA line indicating trend direction
- Integrated buy/sell signals based on multiple confirmations
- Customizable parameters for both KAMA and Bollinger Bands
- Optional bar confirmation wait feature
- Built-in alert conditions for trade signals
## Main Components
### 1. Kaufman Adaptive Moving Average (KAMA)
- Adapts to market volatility using an efficiency ratio
- Changes color based on trend direction (green for uptrend, red for downtrend)
- Adjustable parameters for fine-tuning:
- Base Length: Controls the main calculation period (default: 10)
- Fast EMA Length: For rapid market response (default: 2)
- Slow EMA Length: For stable market conditions (default: 30)
### 2. Bollinger Bands
- Standard deviation-based volatility bands
- Customizable length and standard deviation multiplier
- Includes expansion threshold for volatility measurement
- Components:
- Upper Band: Upper volatility threshold
- Middle Band: Simple moving average
- Lower Band: Lower volatility threshold
## Signal Generation
### Buy Signals
Generated when:
1. KAMA color changes from red to green
2. Price closes above KAMA
3. Price closes above the middle Bollinger Band
4. Signals are marked with:
- Green triangles below the candles
- "B" labels for easy identification
### Sell Signals
Generated when:
1. KAMA color changes from green to red
2. Price closes below KAMA
3. Price closes below the middle Bollinger Band
4. Signals are marked with:
- Red triangles above the candles
- "S" labels for easy identification
## Customizable Parameters
### KAMA Settings
- Base Length (1-50)
- Fast EMA Length (1-10)
- Slow EMA Length (10-50)
- Source Price Selection
- Direction Highlight Toggle
- Bar Confirmation Option
### Bollinger Bands Settings
- Length (default: 20)
- Standard Deviation Multiplier (default: 2.0)
- Expansion Threshold (0.1-3.0)
## Alert Functionality
Built-in alerts for:
- Buy signals with customizable messages
- Sell signals with customizable messages
## Best Practices
### Timeframe Selection
- Works well on multiple timeframes
- Recommended for 15m to 4h charts for optimal signal generation
- Higher timeframes provide more reliable trend signals
### Parameter Optimization
- Adjust KAMA lengths based on trading style:
- Shorter lengths for day trading
- Longer lengths for swing trading
- Fine-tune BB multiplier based on market volatility
- Consider waiting for bar confirmation in volatile markets
### Risk Management
- Use in conjunction with other indicators for confirmation
- Consider market conditions and volatility when trading signals
- Implement proper position sizing and stop-loss levels
## Technical Notes
- Written in Pine Script™ v6
- Overlay indicator (displays on price chart)
- Compatible with all TradingView-supported markets
- Resource-efficient implementation for smooth performance
## Disclaimer
This indicator is provided under the Mozilla Public License 2.0. While it can be a valuable tool for technical analysis, it should not be used as the sole basis for trading decisions. Always combine with proper risk management and additional analysis methods.
Four Supertrend By Baljit AujlaThis Pine Script is an implementation of a "Four Supertrend" indicator by Baljit Aujla. It calculates and plots four Supertrend indicators based on the Average True Range (ATR) method, allowing for different ATR periods and multipliers for each line.
Here is an explanation of the key components:
Inputs
1:- ATR Periods: Four different periods for ATR, adjustable by the user (defaults: 10, 11, 12, 13).
2:- ATR Multipliers: Four different multipliers for the ATR, adjustable by the user (defaults: 1.0, 2.0, 3.0, 4.0).
3:- Source: The data source used for calculation, default is the average of high and low prices (hl2).
4:- Change ATR Calculation Method: Option to switch between the traditional ATR and a simple moving average of true range (SMA of TR).
5:- Signal Display- Options to show buy/sell signals and highlight trends.
Logic:
The script computes four separate Supertrend lines using the ATR method for each line. For each of the four lines, it calculates an uptrend and downtrend threshold, and the trend direction changes when the close price crosses these thresholds.
For each trend line:
1. Uptrend and Downtrend Calculation: The script uses ATR-based bands above and below the price. The uptrend line is calculated by subtracting the ATR multiplied by a given multiplier from the source price, and the downtrend line is calculated by adding the ATR multiplied by a multiplier to the source price.
2. Trend Reversal Logic: The trend switches based on the price action relative to the uptrend and downtrend lines. If the price moves above the downtrend, it signals a switch to an uptrend, and vice versa for a downtrend.
3. Signal Generation: Buy signals occur when the trend changes from negative to positive (down to up), and sell signals occur when the trend changes from positive to negative (up to down).
Plots:
The script plots:
Uptrend and Downtrend Lines: These are visualized as green and red lines for each trend.
Buy/Sell Signals: Small circles are drawn on the chart when a trend change occurs (buy and sell signals).
Trend Highlighting: Background highlighting is applied to show when the market is in an uptrend (green) or downtrend (red).
Alerts:
The script has commented-out alert conditions (alertcondition), which can be enabled to send notifications when a buy or sell signal occurs, or when a trend change happens.
Enhancements:
1. Background Highlighting: This is an option to visually emphasize uptrends and downtrends by filling the background with respective colors.
2. Signal Visibility: You can toggle whether to show the buy/sell signals on the chart.
3. ATR Calculation Method: Option to change the ATR calculation method (using SMA of TR vs the default ATR).
The script is useful for identifying multi-timeframe trends with adjustable parameters and provides both signals and visual markers on the chart to aid in trading decisions.
Issues and Improvements:
The code seems to be truncated, specifically for the last Supertrend line (Line 4). To fully complete the functionality for the fourth line, the logic for up4, down4 and tread4 needs to be finished, similar to the other three lines.
Would you like help finishing the script for the fourth line or improving specific parts of it?
Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
Market Session Times and Volume [Market Spotter]Market Session Times and Volume
Market Session Times
Inputs
The inputs tab consists of timezone adjustment which would be the chosen timezone for the plotting of the market sessions based on the market timings.
Further it contains settings for each box to show/hide and change box colour and timings for Asian, London and New York Sessions.
How it works
The indicator primarily works by marking the session highs and lows for the chosen time in the inputs, each of the sessions can be input a custom time value which would plot the box. It helps to identify the important price levels and the trading range for each individual session.
The midpoint of each session is marked with a dashed line. The indicator also marks a developing session while it being formed as well to identify potential secondary levels.
Usage
It can be used to trade session breakouts, false breaks and also divide the daily movement into parts and identify possible patterns while trading.
2. Volumes
Inputs
The volume part has 2 inputs - Smoothing and Normalisation. The smoothing period can simply be used to take in charge volumes of last X bars and normalisation can be used for calculating relative volumes based on last Y bars.
How it works
The indicator takes into account the buy and sell volumes of last X bars and then displays that as a relative smoothed volume which helps to identify longer term build or distribution of volume. It plots the positive volume from 0 to 100 and negative volume from 0 to -100 which has been normalised. The colors identify gradual increase or decrease in volumes
Usage
It can also be used to trade volume spikes well and can identify potential market shifts
Candle Average PriceOverview
The Candle Average Price indicator is a custom tool designed to help traders identify key price levels by calculating and displaying the average price of recent candles on your TradingView chart. This indicator computes the average price based on a user-defined percentage of each candle's range over a specified number of candles. It then plots a horizontal line representing this average, covering only the last N candles as defined by you.
Key Features
Customizable Number of Candles: Define how many past candles to include in the average calculation.
Adjustable Percentage Level: Choose any percentage of each candle's range (from low to high) to calculate the price level.
Dynamic Horizontal Line: The indicator plots a horizontal line representing the calculated average, updating with each new bar and covering only the specified number of candles.
How It Works
Price at Specified Percentage:
For each candle, the indicator calculates a price level at your chosen percentage within the candle's range.
Formula: Price = Low + (Percentage Level / 100) * (High - Low)
Average Price Calculation:
It computes the average of these price levels over the last N candles.
Formula: Average Price = Sum of Price Levels over N Candles / N
Horizontal Line Plotting:
A horizontal line is drawn at the calculated average price level.
The line spans from N candles ago to the current candle, covering exactly the number of candles specified.
Input Parameters
Number of Candles (length):
Description: The number of recent candles over which the average is calculated.
Default Value: 4
Range: 1 to any positive integer.
Usage: Adjust this to include more or fewer candles in the calculation. A higher number smooths the average, while a lower number makes it more responsive to recent price changes.
Percentage Level (%):
Description: The percentage within each candle's range to calculate the price level.
Default Value: 50%
Range: 0% (candle low) to 100% (candle high).
Usage: Modify this to focus on different parts of each candle:
0%: Uses the low of each candle.
50%: Uses the midpoint of each candle.
100%: Uses the high of each candle.
Custom Percentage: Any value between 0% and 100% to target specific levels.
How to Use the Indicator
Adding the Indicator to Your Chart:
Open the TradingView chart of your preferred financial instrument.
Click on Indicators at the top of the chart.
Select Invite-Only Scripts if you've saved the script there, or use the Pine Editor to paste and apply the script.
Configuring the Settings:
After adding the indicator, click on the gear icon ⚙️ next to its name to open settings.
Adjust the Number of Candles (length) to your desired period.
Set the Percentage Level (%) (percentage) to the specific level within each candle's range you want to analyze.
Interpreting the Horizontal Line:
The horizontal line represents the average price calculated based on your inputs.
It updates with each new bar, always reflecting the most recent data over the specified number of candles.
The line only spans the last N candles, providing a focused view of recent price action.
Practical Applications
Identifying Support and Resistance Levels:
The average price line can act as a dynamic support or resistance level.
Traders can watch for price reactions around this line to make trading decisions.
Trend Analysis:
Observing how the price interacts with the average line can provide insights into the current trend's strength and potential reversals.
Entry and Exit Signals:
Use the line as a reference point for setting stop-loss orders or taking profits.
Combine it with other indicators for more robust trading signals.
In highly volatile markets, consider increasing the number of candles to avoid false signals.
Limitations and Considerations
Not a Standalone Tool:
This indicator should not be used in isolation for making trading decisions. Always consider additional analysis.
Market Conditions Matter:
The indicator may perform differently in trending markets versus ranging markets.
Data Refresh:
Ensure you have a stable internet connection and that your TradingView chart is set to the correct time frame.
Conclusion
The Candle Average Price indicator is a flexible and user-friendly tool that provides valuable insights into recent price action by calculating the average price based on your specific criteria. By adjusting the parameters to suit your trading style, you can incorporate this indicator into your technical analysis to help identify potential trading opportunities.
Disclaimer: Trading financial instruments involves risk, and past performance is not indicative of future results. This indicator is a tool to assist in analysis and should not be considered financial advice.
Happy Trading!
TMA Bands TMA (Triangular Moving Average):
Üçgen hareketli ortalamalar, fiyat verilerini yumuşatarak trendi daha net göstermek için kullanılır.
"Centered Asymmetric Bands" terimi, bu indikatörün merkezlenmiş bir yapıda çalıştığını ve farklı genişliklerde bantlar içerdiğini gösteriyor.
Diamonds Infiniti - Aynet FiboThe "Diamonds Infiniti - Aynet Fibo" Pine Script combines the geometric visualization of diamond patterns with Fibonacci retracement levels to create an innovative technical indicator for analyzing market trends and potential reversal points. Below is a detailed explanation of the code and its functionality:
Key Features
Dynamic Fibonacci Levels
High and Low Points: The script calculates the highest high and lowest low over a user-defined lookback period (lookback) to establish a price range.
Fibonacci Price Levels: Using the defined price range, the script calculates the Fibonacci retracement levels (0%, 23.6%, 38.2%, 50%, 61.8%, 100%) relative to the low point.
Trend Change Detection
Crossovers and Crossunders: The script monitors whether the closing price crosses over or under the calculated Fibonacci levels. This detection is encapsulated in the isTrendChange function.
Trend Signal: If a trend change occurs at any of the Fibonacci levels (23.6%, 38.2%, 50%, 61.8%), the script flags it as a trend change and stores the bar index of the last signal.
Diamond Pattern Visualization
Diamond Construction: The drawDiamond function draws a diamond shape at a given bar index using a central price, a top price, and a bottom price.
Trigger for Drawing Diamonds: When a trend change is detected, the script draws two diamonds—one on the left and one on the right—connected by a central line. The diamonds are based on the calculated price range (price_range) and a user-defined pattern height (patternHeight).
Fibonacci Level Visualization
Overlay of Fibonacci Levels: The script plots the calculated Fibonacci levels (23.6%, 38.2%, 50%, 61.8%) on the chart as dotted lines for easier visualization.
Scientific and Trading Use Cases
Trend Visualization:
The diamond pattern visually highlights trend changes around key Fibonacci retracement levels, providing traders with clear indicators of potential reversal zones.
Support and Resistance Zones:
Fibonacci retracement levels are widely recognized as key support and resistance zones. Overlaying these levels helps traders anticipate price behavior in these areas.
Adaptive Trading:
By dynamically recalculating Fibonacci levels and diamond patterns based on the most recent price range, the script adapts to changing market conditions.
Possible Enhancements
Multi-Timeframe Support:
Extend the script to calculate Fibonacci levels and diamond patterns across multiple timeframes for broader market analysis.
Alerts:
Add alerts for when the price crosses specific Fibonacci levels or when a new diamond pattern is drawn.
Additional Patterns:
Include other geometric patterns like triangles or rectangles for further trend analysis.
This script is a powerful visualization tool that combines Fibonacci retracement with unique diamond patterns. It simplifies complex price movements into easily interpretable signals, making it highly effective for both novice and experienced traders.
Fibonacci Renko Trend - AynetThe "Fibonacci Renko Trend - Aynet" Pine Script combines the Renko charting technique with Fibonacci retracement levels to create a highly customizable and adaptive trend-following tool. Below is a detailed explanation of the script and its components:
Scientific and Trading Applications
Noise Reduction:
By using Renko charts, the script filters out time-based noise and focuses solely on price movement, making it ideal for trend-following strategies.
Adaptability:
The ATR-based box size ensures that the Renko blocks automatically adjust to market volatility, making the tool versatile for different market conditions and asset classes.
Fibonacci-Based Decision Making:
The integration of Fibonacci retracement levels provides a structured framework for identifying key support and resistance levels. Traders can use these levels to anticipate price reversals or continuations.
Visualization:
The color-coded Renko blocks allow traders to quickly identify trends and potential reversals without additional indicators, improving decision-making efficiency.
Possible Improvements
Signal Generation:
Add entry and exit signals when price crosses significant Fibonacci levels or when a trend reversal is detected.
Multi-Timeframe Support:
Extend the script to compute Renko levels and Fibonacci ratios for multiple timeframes simultaneously.
Alerts:
Implement alert notifications for key events, such as trend changes or Fibonacci level breaches.
This script is a robust tool for traders looking to combine the simplicity of Renko charts with the analytical power of Fibonacci retracement levels. It offers a clear visualization of price trends and potential reversal points, making it suitable for both novice and experienced traders.
Average High-Low Multi Time Frame Lines SunilTitle: Multi-Timeframe Average High-Low Levels with Custom Timeframes
Description:
This indicator calculates the average of high and low prices across up to four customizable timeframes. By default, it includes 30 minutes, 1 hour, 3 hours, and 1 day, but you can modify these directly in the input settings to suit your trading strategy.
Features:
Plots average high-low levels for selected timeframes with distinct colors.
Highlights buy zones (green) when the price is above all levels and sell zones (red) when the price is below all levels.
Marks areas where all levels align with a subtle blue background.
Use this tool to identify key levels and potential trading opportunities across multiple timeframes at a glance!
First 15-Min Candle Detector [With Breakout Alerts]Indicator: First 15-Minute Candle Detector
Purpose
This indicator helps traders by identifying and marking the high, low, and mid-point of the first 15-minute candle of the market session. It also provides visual aids and alerts for price breakouts above or below these levels, making it ideal for intraday trading strategies.
This script is suitable for traders focusing on early session momentum or reversal strategies.
Key Features
Market Start Customization: Configure the market start time (hour and minute) to align with your trading session or exchange timezone.
Visual Aids:
Horizontal lines to mark the High , Low , and Mid-point of the first 15-minute candle.
Background highlighting to identify the first 15-minute candle.
Configurable colors and line widths for clear visuals.
Breakout Alerts:
Real-time alerts for breakouts above the high or below the low of the first 15-minute candle.
Customizable alert messages.
Alerts configured using alertcondition .
Dynamic Adjustments:
Adapts dynamically to timeframes of 15 minutes or lower.
Resets and recalculates at the start of each new session.
Inputs and Configurations
Market Settings:
Market Start Hour: Default is 9.
Market Start Minute: Default is 30.
Visual Settings:
Enable/disable background highlighting.
Set colors for the background, high line, low line, and mid-line.
Adjust line width (1 to 5).
Toggle the visibility of the mid-line.
Alert Settings:
Enable breakout alerts.
Set custom alert messages for high and low breakouts.
How It Works
// First 15-Minute Candle Detection
The indicator monitors the first 15-minute candle after the market opens based on the configured start time. It records the high , low , and calculates the mid-point of this candle.
// Visual Markings
Horizontal lines are drawn at the high, low, and mid-point of the first 15-minute candle, extending to the right for the rest of the session.
// Breakout Detection
The indicator checks for price breakouts above the high or below the low of the first 15-minute candle and triggers alerts if enabled.
// Dynamic Reset
The indicator resets values and deletes previous session lines at the start of each new session.
Conditions and Alerts
Breakout Conditions:
High Breakout: The closing price exceeds the high of the first 15-minute candle.
Low Breakout: The closing price falls below the low of the first 15-minute candle.
Alert Triggers: Configurable alerts notify you of breakouts in real-time.
Use Cases
Intraday Traders: Ideal for early-session momentum or reversal strategies.
Breakout Traders: Helps identify entry points when price breaks key levels.
Visual Clarity: Simplifies tracking important session levels.
Limitations
Works only on 15-minute or lower timeframes.
Requires accurate market start time configuration.
EMA with Supply and Demand Zones
The EMA with Supply and Demand Strategy is a trend-following trading approach that integrates Exponential Moving Averages (EMA) with supply and demand zones to identify potential entry and exit points. Below is a detailed description of its components and logic:
Key Components of the Strategy
1. EMA (Exponential Moving Average)
The EMA is used as a trend filter:
Bullish Trend: Price is above the EMA.
Bearish Trend: Price is below the EMA.
The EMA ensures that trades align with the overall market trend, reducing counter-trend risks.
2. Supply and Demand Zones
Demand Zone:
Represents areas where the price historically found support (buyers dominated).
Calculated using the lowest low over a specified lookback period.
Used for identifying potential long entry points.
Supply Zone:
Represents areas where the price historically faced resistance (sellers dominated).
Calculated using the highest high over a specified lookback period.
Used for identifying potential short entry points.
3. Trade Conditions
Long Trade:
Triggered when:
The price is above the EMA (bullish trend).
The low of the current candle touches or penetrates the most recent demand zone.
Short Trade:
Triggered when:
The price is below the EMA (bearish trend).
The high of the current candle touches or penetrates the most recent supply zone.
4. Exit Conditions
Long Exit:
Exit the trade when the price closes below the EMA, indicating a potential trend reversal.
Short Exit:
Exit the trade when the price closes above the EMA, signaling a potential upward reversal.
Visual Representation
EMA: A blue line plotted on the chart to show the trend.
Supply Zones: Red horizontal lines representing potential resistance levels.
Demand Zones: Green horizontal lines representing potential support levels.
These zones dynamically adjust to reflect the most recent 3 levels.
How the Strategy Works
Trend Identification:
The EMA determines the direction of the trade:
Look for long trades only in a bullish trend (price above EMA).
Look for short trades only in a bearish trend (price below EMA).
Entry Points:
Wait for price interaction with a supply or demand zone:
If the price touches a demand zone during a bullish trend, initiate a long trade.
If the price touches a supply zone during a bearish trend, initiate a short trade.
Risk Management:
The strategy exits trades if the price moves against the trend (crosses the EMA).
This ensures minimal exposure during adverse market movements.
Benefits of the Strategy
Trend Alignment:
Reduces counter-trend trades, improving the win rate.
Clear Entry and Exit Rules:
Combines price action (zones) with a reliable trend filter (EMA).
Dynamic Levels:
The supply and demand zones adapt to changing market conditions.
Customization Options
EMA Length:
Adjust to suit different timeframes or market conditions (e.g., 20 for faster trends, 50 for slower trends).
Lookback Period:
Fine-tune to capture broader or narrower supply and demand zones.
Risk/Reward Preferences:
Pair the strategy with stop-loss and take-profit levels for enhanced control.
This strategy is ideal for traders looking for a structured approach to identify high-probability trades while aligning with the prevailing trend. Backtest and optimize parameters based on your trading style and the specific asset you're tradin
