Lowess Channel + (RSI) [ChartPrime]The Lowess Channel + (RSI) indicator applies the LOWESS (Locally Weighted Scatterplot Smoothing) algorithm to filter price fluctuations and construct a dynamic channel. LOWESS is a non-parametric regression method that smooths noisy data by fitting weighted linear regressions at localized segments. This technique is widely used in statistical analysis to reveal trends while preserving data structure.
In this indicator, the LOWESS algorithm is used to create a central trend line and deviation-based bands. The midline changes color based on trend direction, and diamonds are plotted when a trend shift occurs. Additionally, an RSI gauge is positioned at the end of the channel to display the current RSI level in relation to the price bands.
lowess_smooth(src, length, bandwidth) =>
sum_weights = 0.0
sum_weighted_y = 0.0
sum_weighted_xy = 0.0
sum_weighted_x2 = 0.0
sum_weighted_x = 0.0
for i = 0 to length - 1
x = float(i)
weight = math.exp(-0.5 * (x / bandwidth) * (x / bandwidth))
y = nz(src , 0)
sum_weights := sum_weights + weight
sum_weighted_x := sum_weighted_x + weight * x
sum_weighted_y := sum_weighted_y + weight * y
sum_weighted_xy := sum_weighted_xy + weight * x * y
sum_weighted_x2 := sum_weighted_x2 + weight * x * x
mean_x = sum_weighted_x / sum_weights
mean_y = sum_weighted_y / sum_weights
beta = (sum_weighted_xy - mean_x * mean_y * sum_weights) / (sum_weighted_x2 - mean_x * mean_x * sum_weights)
alpha = mean_y - beta * mean_x
alpha + beta * float(length / 2) // Centered smoothing
⯁ KEY FEATURES
LOWESS Price Filtering – Smooths price fluctuations to reveal the underlying trend with minimal lag.
Dynamic Trend Coloring – The midline changes color based on trend direction (e.g., bullish or bearish).
Trend Shift Diamonds – Marks points where the midline color changes, indicating a possible trend shift.
Deviation-Based Bands – Expands above and below the midline using ATR-based multipliers for volatility tracking.
RSI Gauge Display – A vertical gauge at the right side of the chart shows the current RSI level relative to the price channel.
Fully Customizable – Users can adjust LOWESS length, band width, colors, and enable or disable the RSI gauge and adjust RSIlength.
⯁ HOW TO USE
Use the LOWESS midline as a trend filter —bullish when green, bearish when purple.
Watch for trend shift diamonds as potential entry or exit signals.
Utilize the price bands to gauge overbought and oversold zones based on volatility.
Monitor the RSI gauge to confirm trend strength—high RSI near upper bands suggests overbought conditions, while low RSI near lower bands indicates oversold conditions.
⯁ CONCLUSION
The Lowess Channel + (RSI) indicator offers a powerful way to analyze market trends by applying a statistically robust smoothing algorithm. Unlike traditional moving averages, LOWESS filtering provides a flexible, responsive trendline that adapts to price movements. The integrated RSI gauge enhances decision-making by displaying momentum conditions alongside trend dynamics. Whether used for trend-following or mean reversion strategies, this indicator provides traders with a well-rounded perspective on market behavior.
Cerca negli script per "bands"
Bitcoin Rainbow WaveBitcoin ultimate price model:
1. Power Law + 2. Rainbow Narrowing Bands + 3. Halving Cycle Harmonic Wave + 3. Wave bands
This powerful tool is designed to help traders of all levels understand and navigate the Bitcoin market. It works exclusively with BTC on any timeframe, but looks best on weekly or daily charts. The indicator provides valuable insights into historical price behavior and offers forecasts for the next decade, making it essential for both mid-term and long-term strategies.
How the Model Works
Power Law (Logarithmic Trend) : The green line represents the expected long-term price trajectory of Bitcoin based on a logarithmic regression model (power law). This suggests that Bitcoin's price generally increases as a power of 5.44 over time passed.
Rainbow Chart : Colored bands around the power law trend line illustrate a range of potential price fluctuations. The bands narrow esponentially over time, indicating increasing model accuracy as Bitcoin matures. This chart visually identifies overbought and oversold zones, as well as fair value zones.
Blue Zone : Below the power law trend, indicating an undervalued condition and a potential buying zone.
Green Zone : Around the power law trend, suggesting fair value.
Yellow Zone : Above the power law trend, but within the rainbow bands. Exercise caution, as the price may be overextended.
Red Zone : Far above the power law trend, indicating strong overbought conditions. Consider taking profits or reducing exposure.
Halving Cycle Wave : The fuchsia line represents the cyclical wave component of the model, tied to Bitcoin's halving events (approximately every four years). This wave accounts for the price fluctuations that typically occur around halvings, with price tending to increase leading up to a halving and correct afterwards. The amplitude of the wave decreases over time as the impact of halvings potentially lessens. Additional bands around the wave show the expected range of price fluctuations, aiding traders in making informed decisions.
Customizing Parameters
You can fine-tune the model's appearance by adjusting these input parameters:
show Power Law (true/false): Toggle visibility of the power law trend line.
show Wave (true/false): Toggle visibility of the halving cycle wave.
show Rainbow Chart (true/false): Toggle visibility of the rainbow bands.
show Block Marks (true/false): Toggle visibility of the 70,000 block interval markers.
Using the Model in Your Trading Strategy
Combine this indicator with technical analysis, fundamental analysis, and risk management techniques to develop a comprehensive Bitcoin trading strategy. The model can help you identify potential entry and exit points, assess market sentiment, and manage risk based on Bitcoin's position relative to the power law trend, halving cycle wave, and rainbow chart zones.
Nadaraya-Watson Probability [Yosiet]The script calculates and displays probability bands around price movements, offering insights into potential market trends.
Setting Up the Script
Window Size: Determines the length of the window for the Nadaraya-Watson estimation. A larger window smooths the data more but might lag current market conditions.
Bandwidth: Controls the bandwidth for the kernel regression, affecting the smoothness of the probability bands.
Reading the Data Table
The script dynamically updates a table positioned at the bottom right of your chart, providing real-time insights into market probabilities. Here's how to interpret the table:
Table Columns: The table is organized into three columns:
Up: Indicates the probability or relative change percentage for the upper band.
Down: Indicates the probability or relative change percentage for the lower band.
Table Rows: There are two main rows of interest:
P%: Shows the price change percentage difference between the bands and the closing price. A positive value in the "Up" column suggests the upper band is above the current close, indicating potential upward momentum. Conversely, a negative value in the "Down" column suggests downward momentum.
R%: Displays the relative inner change percentage difference between the bands, offering a measure of the market's volatility or stability within the bands.
Utilizing the Insights
Market Trends: A widening gap between the "Up" and "Down" percentages in the "P%" row might indicate increasing market volatility. Traders can use this information to adjust their risk management strategies accordingly.
Entry and Exit Points: The "R%" row provides insights into the relative position of the current price within the probability bands. Traders might consider positions closer to the lower band as potential entry points and positions near the upper band as exit points or take-profit levels.
Conclusion
The Nadaraya-Watson Probability script offers a sophisticated tool for traders looking to incorporate statistical analysis into their trading strategy. By understanding and utilizing the data presented in the script's table, traders can gain insights into market trends and volatility, aiding in decision-making processes. Remember, no indicator is foolproof; always consider multiple data sources and analyses when making trading decisions.
Deck@r True Range IndexThis Pine Script calculates the True Range Index (TRI) using ATR and Fib Levels and uses the result to generate buy and sell signals based on certain conditions.
Here's a breakdown of the code:
Inputs:
atr_period: Determines the period for calculating the Average True Range (ATR), preferred setting at 14.
atr_multiplier: Multiplier used to set the width of the ATR bands preferred setting at 1.
Calculations:
atr_value: Calculates the Average True Range (ATR) using the input period.
upper_band: Calculates the upper band of the ATR bands using a Simple Moving Average (SMA) of the close price plus the ATR multiplied by the multiplier.
lower_band: Calculates the lower band of the ATR bands using a Simple Moving Average (SMA) of the close price minus the ATR multiplied by the multiplier.
midline_75 and midline_25: Calculate midlines at Fibonacci retracement levels of 0.75 and 0.25, respectively, between the upper and lower bands.
Plotting:
Plots the upper and lower bands of the ATR bands.
Optionally plots midlines for the ATR bands (commented out in the code).
Buy and Sell Conditions:
buy_condition: Defines a condition for a buy signal, which occurs when the close price is above the midline at the Fibonacci retracement level of 0.25.
sell_condition: Defines a condition for a sell signal, which occurs when the close price is below the midline at the Fibonacci retracement level of 0.75.
Candle Color:
Sets the candle color based on the buy and sell conditions.
Buy and Sell Signals:
buy_signal: Checks for a buy signal when the close price crosses above the midline at the Fibonacci retracement level of 0.25.
sell_signal: Checks for a sell signal when the close price crosses below the midline at the Fibonacci retracement level of 0.75.
Plots buy and sell signals on the chart.
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
Quantum Uncertainty by Kingshuk GhoshLet me explain this indicator in simple, practical terms, including the fascinating physics concept that inspired me.
This indicator helps to understand when the market is predictable (safe to trade) versus unpredictable (risky to trade). It shows the probability zones where price is likely to move and warns you when conditions are too chaotic for reliable trading.
The Physics Behind It: Heisenberg's Uncertainty Principle:-
This indicator is inspired by one of the most profound discoveries in physics: Heisenberg's Uncertainty Principle.
What Is The Uncertainty Principle?
In 1927, physicist Werner Heisenberg discovered something remarkable about the universe: you cannot simultaneously know both the exact position and exact momentum of a particle with perfect precision. The more accurately you know one, the less accurately you can know the other.
Simple Analogy:
Imagine trying to photograph a speeding bullet:
Use fast shutter speed → You see exactly WHERE it is (position), but the image is frozen, so you can't tell HOW FAST it's moving (momentum)
Use slow shutter speed → You see motion blur showing HOW FAST it's moving (momentum), but you can't pinpoint exactly WHERE it is (position)
You can never have both perfect clarity simultaneously - there's always a trade-off.
How This Applies To Trading
The indicator translates this principle to financial markets:
In Physics:
Position Uncertainty × Momentum Uncertainty = Always greater than a minimum value
High uncertainty in one means high uncertainty overall
In Trading:
Price Position Uncertainty = How much the price bounces around (volatility)
Price Momentum Uncertainty = How erratic the directional strength is
Total Market Uncertainty = Price Volatility × Momentum Volatility
The Trading Insight:
Just like in physics, when BOTH price position and momentum are uncertain (highly volatile), the market becomes fundamentally unpredictable. You can't reliably know where price will go next because the system is in high uncertainty state.
Why This Matters For You
Traditional indicators often look at price OR momentum separately. This indicator recognizes that both must be considered together to truly understand market predictability, just as Heisenberg showed that position and momentum must be considered together in physics.
When both uncertainties are high simultaneously:
Price could jump anywhere
Momentum could shift instantly
Predictions become unreliable
Trading becomes gambling
When both uncertainties are low:
Price behavior is more regular
Momentum is more stable
Patterns become clearer
Trading becomes strategic
This is why the indicator's core metric multiplies price volatility by momentum volatility - it's capturing that fundamental uncertainty relationship.
Market Uncertainty
The indicator calculates how unpredictable the market currently is by examining:
How much price is bouncing around (price volatility)
How erratic the momentum is (momentum instability)
When both are high simultaneously, the market becomes highly unpredictable. When both are calm, the market is more reliable for trading.
Think of it like driving:
Low uncertainty = Clear road, good visibility, safe to drive
High uncertainty = Fog, rain, poor visibility, dangerous conditions
Probability Bands
The indicator draws colored bands around a central average price line:
White Center Line (Basis)
The average price over your lookback period
Acts as a equilibrium point where price gravitates
Blue Bands (Inner Zone)
Covers about 68% of normal price behavior
Price spends most of its time here
This is the "normal operating range"
Purple Bands (Outer Zone)
Covers about 95% of all price behavior
Price rarely ventures here
When it does, it's unusual and noteworthy
Highway Lane Analogy:
Most drivers stay in center lanes (blue zone)
Few drivers use extreme outer lanes (purple zone)
When someone drives on the shoulder, it's abnormal and signals something is happening
Wave Function Collapse
Another physics concept applied here: In quantum mechanics, particles exist in multiple states simultaneously (superposition) until they're measured - then the "wave function collapses" to a single state.
In This Indicator:
The probability bands represent all the possible states price could be in. When price moves and settles at a specific level, it's like the wave function collapsing - probability becomes reality.
The indicator helps you see:
Where price is most likely to be (high probability zones - blue bands)
Where price rarely goes (low probability zones - purple bands)
When price is in an "impossible" state (outside bands - tunneling)
Price Position
The indicator tracks where current price sits within these bands:
Upper position = Price in the top half (bullish territory)
Lower position = Price in the bottom half (bearish territory)
Extreme positions = Price in outer 30% on either side (potential reversal zones)
Quantum Tunneling Signals
This is another physics concept: In quantum mechanics, particles can sometimes "tunnel" through barriers that classical physics says they shouldn't be able to cross.
In Trading:
When price breaks through the 95% probability barrier, it's "tunneling" into statistically improbable territory - these are marked by triangles:
Green Triangle Up
Price tunneled through the upper 95% barrier
This is statistically rare (happens only 5% of the time)
Often signals price exhaustion or coming reversal downward
Like a particle that tunneled too far and will snap back
Red Triangle Down
Price tunneled through the lower 95% barrier
Also statistically unusual
Often signals panic selling may be overdone
Like a spring compressed too far, ready to bounce
These "tunneling events" are significant because they represent extreme deviations from normal probability - and markets tend to revert to normal.
Entanglement Score
In quantum physics, "entanglement" means two particles are connected such that measuring one instantly affects the other, no matter the distance.
In Trading:
This measures whether price movements are "entangled" with trading volume - do they move together in a connected way?
High Entanglement (above 0.5)
Price and volume move together
Volume confirms the price action
More reliable, trustworthy moves
Like entangled particles - they're truly connected
Low Entanglement (below 0.3)
Price moves without volume support
Suspicious, unsupported movements
Less reliable, be cautious
Like particles that aren't entangled - the connection is weak
Negative Entanglement
Price and volume move in opposite directions
Often signals divergence or potential reversal
Requires careful interpretation
Information Dashboard:
1. Uncertainty Level
Shows current market unpredictability (the core Heisenberg principle calculation):
✓ Normal (Green) = Market is behaving predictably, safe to trade
⚠ High Risk (Red) = Market is chaotic, avoid trading
This is your first checkpoint - if uncertainty is high, don't proceed further.
2. Probability Score
Shows how normal or extreme the current price is:
Percentage shown = Where price sits in the probability distribution
✓ Safe (Green) = Price in normal range (middle 70%)
⛔ Extreme (Red) = Price at statistical outliers (outer 15%)
High percentage (>85%) = Price near the average, stable situation
Low percentage (<15%) = Price at extremes, unstable situation
3. Position Indicator
Tells you which side of the market you're on:
Upper/Lower = Basic location in the bands
→ Neutral (Gray) = Price in balanced middle zone
⚠ Reversal? (Orange) = Price at extremes, watch for turnaround
This helps you anticipate potential support or resistance levels.
4. Entanglement Confirmation
Shows the correlation number and interpretation:
✓ Confirmed (Green) = Volume strongly supports price (>0.5)
⚠ Weak (Orange) = Poor volume support (<0.5)
Always prefer trading when entanglement is confirmed - it means the move is "real" with participant backing.
5. Trade Status - YOUR MAIN SIGNAL
This is the indicator's final verdict combining all factors:
✓ TRADEABLE (Green)
Uncertainty is normal
Probability is safe
Entanglement is decent
Action: Market conditions favor trading
⛔ AVOID (Red)
One or more conditions are unfavorable
Market is too unpredictable
Action: Stay out, preserve capital.
Scenario A: Perfect Buy Setup
Red triangle appears (quantum tunneling down)
Position shows "Lower" with "⚠ Reversal?" warning
Entanglement shows "✓ Confirmed"
Trade Status: "✓ TRADEABLE"
Interpretation: Price hit extreme low with volume support, likely to bounce back to probability zone
Action: Consider long entry with stop below recent low
Scenario B: Perfect Sell Setup
Green triangle appears (quantum tunneling up)
Position shows "Upper" with "⚠ Reversal?" warning
Entanglement shows "✓ Confirmed"
Trade Status: "✓ TRADEABLE"
Interpretation: Price hit extreme high, exhaustion in high uncertainty zone
Action: Consider short entry or exit longs with stop above recent high
Scenario C: High Uncertainty - Stay Out
Uncertainty shows "⚠ High Risk"
Probability shows "⛔ Extreme"
Trade Status: "⛔ AVOID"
Interpretation: Both price and momentum uncertainties are high - market is fundamentally unpredictable (Heisenberg principle in action)
Action: No trading, wait for uncertainty to decrease
Scenario D: Trending Market
Price consistently stays in upper bands
No tunneling signals
Entanglement remains high
Trade Status stays "✓ TRADEABLE"
Interpretation: Strong trend with low uncertainty
Action: Trade with the trend, don't fight it
Scenario E: Choppy, Range-Bound
Price bounces between inner blue bands
Frequent status changes between TRADEABLE and AVOID
Entanglement fluctuates
Interpretation: Market lacks direction, uncertainty fluctuating
Action: Use bands as support/resistance for scalping, or wait for breakout.
Why The Uncertainty Principle Matters In Trading
Traditional technical analysis often looks at indicators in isolation:
"RSI is oversold, so buy"
"Price is volatile, so wait"
"Volume is high, so trade"
But Heisenberg's principle teaches us that multiple uncertainties interact and compound. This indicator recognizes that truth:
When price volatility is high AND momentum is erratic:
You can't reliably predict where price will go
You can't reliably predict how strong the move will be
The combination creates fundamental unpredictability
This is when the indicator says "AVOID"
When price volatility is low AND momentum is stable:
Price behavior becomes more regular
Directional moves become more reliable
The low combined uncertainty creates tradeable conditions
This is when the indicator says "TRADEABLE"
The Probability Wave Function
In quantum mechanics, until you measure a particle, it exists in all possible states simultaneously (superposition). The probability wave describes where it's most likely to be found.
The bands work the same way:
Blue bands = Where price has 68% probability of being (1 standard deviation)
Purple bands = Where price has 95% probability of being (2 standard deviations)
Outside bands = Less than 5% probability (quantum tunneling territory)
When price is in the blue zone, it's in its "natural" superposition state - normal behavior.
When price tunnels outside, it's in an "improbable" state - like a quantum particle appearing where it shouldn't be. Physics tells us this can't last - the wave function will collapse back to normal probability zones. In trading, this means reversion to the mean.
Entanglement and Market Correlation
Quantum entanglement shows us that connections matter - particles don't act in isolation.
In markets:
Price shouldn't move in isolation from volume
When they're "entangled" (moving together), the move is authentic
When they're not entangled (price moves without volume), the move is suspicious
This is why the indicator checks entanglement - it's verifying that the market components are properly connected and confirming each other.
Golden Rules for the indicator:
Never trade during high uncertainty states - When the indicator shows AVOID, it's telling you that fundamental unpredictability (Heisenberg's principle) has taken over. This is non-negotiable.
Reduce position size when entanglement is weak - Even if uncertainty is low, weak volume entanglement means the move may not be authentic.
Respect the quantum tunneling signals - They mark statistical extremes where price has entered improbable territory. Reversion to normal probability zones is likely.
Don't chase price outside the bands - If you missed the tunneling entry, wait for price to return to normal probability zones.
Use the white center line as equilibrium - Like particles gravitating toward lower energy states, price tends to revert to its average.
Heisenberg's Uncertainty Principle teaches us a profound lesson: some things are fundamentally unknowable. You cannot eliminate uncertainty - you can only measure it and decide whether it's low enough to act.
This indicator embraces that wisdom:
It doesn't claim to predict the future
It doesn't promise guaranteed wins
It simply measures current uncertainty
And tells you when conditions are favorable vs. unfavorable
The market, like quantum particles, is probabilistic, not deterministic. You're trading probabilities, not certainties. The indicator helps you identify when those probabilities are in your favor (low uncertainty) and when they're not (high uncertainty).
This is a more mature, realistic approach to trading than indicators that promise to "predict" moves. Instead, this indicator honestly assesses predictability itself.
Remember: Not trading during high uncertainty is just as important as trading during low uncertainty. Preservation of capital is the foundation of long-term success. As Heisenberg taught us, some moments are simply too uncertain to act - and that's okay.
Chart attached: -NSE Persistent, EoD 05/12/25, Day Time Frame.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
AdvancedLines (FiboBands) - PaSKaL
Overview :
AdvancedLines (FiboBands) - PaSKaL is an advanced technical analysis tool designed to automate the plotting of key Fibonacci retracement levels based on the highest high and lowest low over a customizable period. This indicator helps traders identify critical price zones such as support, resistance, and potential trend reversal or continuation points.
By using AdvancedLines (FiboBands) - PaSKaL , traders can easily spot key areas where the price is likely to reverse or consolidate, or where the trend may continue. It is particularly useful for trend-following, scalping, and range-trading strategies.
Key Features:
Automatic Fibonacci Level Calculation :
- The indicator automatically calculates and plots key Fibonacci levels (0.236, 0.382, 0.5, 0.618, and 0.764), which are crucial for identifying potential support and resistance levels in the market.
Adjustable Parameters :
- Bands Length: You can adjust the bands_length setting to change the number of bars used for calculating the highest high and lowest low. This gives flexibility for using the indicator on different timeframes and trading styles.
- Visibility: The Fibonacci levels, as well as the midline (0.5 Fibonacci level), can be shown or hidden based on your preference.
- Color Customization: You can change the color of each Fibonacci level and background fills to suit your chart preferences.
Fibonacci Levels
- The main Fibonacci levels plotted are:
- 0.236 – Minor support/resistance level
- 0.382 – Moderate retracement level
- 0.5 – Midpoint retracement, often used as a key level
- 0.618 – Golden ratio, considered one of the most important Fibonacci levels
- 0.764 – Strong reversal level, often indicating a continuation or change in trend
Background Fill
- The indicator allows you to fill the background between the Fibonacci levels and the bands with customizable colors. This makes it easier to visually highlight key zones on the chart.
How the Indicator Works:
AdvancedLines (FiboBands) - PaSKaL calculates the range (difference between the highest high and the lowest low) over a user-defined number of bars (e.g., 300). Fibonacci levels are derived from this range, helping traders identify potential price reversal points.
Mathematical Basis :
Fibonacci retracement levels are based on the Fibonacci sequence, where each number is the sum of the previous two (0, 1, 1, 2, 3, 5, 8, 13, etc.). The ratios derived from this sequence (such as 0.618 and 0.382) have been widely observed in nature, market cycles, and price movements. These ratios are used to forecast potential price retracements or continuation points after a major price move.
Fibonacci Levels Calculation :
Identify the Range: The highest high and the lowest low over the defined period are calculated.
Apply Fibonacci Ratios: Fibonacci ratios (0.236, 0.382, 0.5, 0.618, and 0.764) are applied to this range to calculate the corresponding price levels.
Plot the Levels: The indicator automatically plots these levels on your chart.
Customizing Fibonacci Levels & Colors:
The "AdvancedLines (FiboBands) - PaSKaL" indicator offers various customization options for Fibonacci levels, colors, and visibility:
Fibonacci Level Ratios:
- You can customize the Fibonacci level ratios through the following inputs:
- Fibo Level 1: 0.764
- Fibo Level 2: 0.618
- Fibo Level 3: 0.5
- Fibo Level 4: 0.382
- Fibo Level 5: 0.236
- These levels determine key areas where price may reverse or pause. You can adjust these ratios based on your trading preferences.
Fibonacci Level Colors:
- Each Fibonacci level can be assigned a different color to make it more distinguishable on your chart:
- Fibo Level 1 Color (default: Yellow)
- Fibo Level 2 Color (default: Orange)
- Fibo Level 3 Color (default: Green)
- Fibo Level 4 Color (default: Red)
- Fibo Level 5 Color (default: Blue)
- You can change these colors to fit your visual preferences or to align with your existing chart themes.
Visibility of Fibonacci Levels:
- You can choose whether to display each Fibonacci level using the following visibility inputs:
- Show Fibo Level 1 (0.764): Display or hide this level.
- Show Fibo Level 2 (0.618): Display or hide this level.
- Show Fibo Level 3 (0.5): Display or hide this level.
- Show Fibo Level 4 (0.382): Display or hide this level.
- Show Fibo Level 5 (0.236): Display or hide this level.
- This allows you to customize the indicator according to the specific Fibonacci levels that are most relevant to your trading strategy.
Background Fill Color
- The background between the Fibonacci levels and price bands can be filled with customizable colors:
- Fill Color for Upper Band & Fibo Level 1: This color will fill the area between the upper band and Fibonacci Level 1.
- Fill Color for Lower Band & Fibo Level 5: This color will fill the area between the lower band and Fibonacci Level 5.
- Adjusting these colors helps highlight critical zones where price may reverse or consolidate.
How to Use AdvancedLines (FiboBands) - PaSKaL in Trading :
Range Trading :
Range traders typically buy at support and sell at resistance. Fibonacci levels provide excellent support and resistance zones in a ranging market.
Example: If price reaches the 0.618 level in an uptrend, it may reverse, providing an opportunity to sell.
Conversely, if price drops to the 0.382 level, a bounce might occur, and traders can buy, anticipating the market will stay within the range.
Trend-following Trading :
For trend-following traders, Fibonacci levels act as potential entry points during a retracement. After a strong trend, price often retraces to one of the Fibonacci levels before continuing in the direction of the trend.
Example: In a bullish trend, when price retraces to the 0.382 level, it could be a signal to buy, as the price might resume its upward movement after the correction.
In a bearish trend, retracements to levels like 0.618 or 0.764 could provide optimal opportunities for shorting as the price resumes its downward movement.
Scalping :
Scalpers focus on short-term price movements. Fibonacci levels can help identify precise entry and exit points for quick trades.
Example: If price is fluctuating in a narrow range, a scalper can enter a buy trade at 0.236 and exit at the next Fibonacci level, such as 0.382 or 0.5, capturing small but consistent profits.
Stop-Loss and Take-Profit Levels :
Fibonacci levels can also help in setting stop-loss and take-profit levels.
Example: In a bullish trend, you can set a stop-loss just below the 0.236 level and a take-profit at 0.618.
In a bearish trend, set the stop-loss just above the 0.382 level and the take-profit at 0.764.
Identifying Reversals and Continuations :
Reversals: When price reaches a Fibonacci level and reverses direction, it may indicate the end of a price move.
Trend Continuation: If price bounces off a Fibonacci level and continues in the same direction, this may signal that the trend is still intact.
Conclusion :
AdvancedLines (FiboBands) - PaSKaL is an essential tool for any trader who uses Fibonacci retracements in their trading strategy. By automatically plotting key Fibonacci levels, this indicator helps traders quickly identify support and resistance zones, forecast potential reversals, and make more informed trading decisions.
For Trend-following Traders: Use Fibonacci levels to find optimal entry points after a price retracement.
For Range Traders: Identify key levels where price is likely to reverse or bounce within a range.
For Scalpers: Pinpoint small price movements and take advantage of quick profits by entering and exiting trades at precise Fibonacci levels.
By incorporating AdvancedLines (FiboBands) - PaSKaL into your trading setup, you will gain a deeper understanding of price action, improve your decision-making process, and enhance your overall trading performance.
Zero Lag Trend Signals (MTF) [AlgoAlpha]Zero Lag Trend Signals 🚀📈
Ready to take your trend-following strategy to the next level? Say hello to Zero Lag Trend Signals , a precision-engineered Pine Script™ indicator designed to eliminate lag and provide rapid trend insights across multiple timeframes. 💡 This tool blends zero-lag EMA (ZLEMA) logic with volatility bands, trend-shift markers, and dynamic alerts. The result? Timely signals with minimal noise for clearer decision-making, whether you're trading intraday or on longer horizons. 🔄
🟢 Zero-Lag Trend Detection : Uses a zero-lag EMA (ZLEMA) to smooth price data while minimizing delay.
⚡ Multi-Timeframe Signals : Displays trends across up to 5 timeframes (from 5 minutes to daily) on a sleek table.
📊 Volatility-Based Bands : Adaptive upper and lower bands, helping you identify trend reversals with reduced false signals.
🔔 Custom Alerts : Get notified of key trend changes instantly with built-in alert conditions.
🎨 Color-Coded Visualization : Bullish and bearish signals pop with clear color coding, ensuring easy chart reading.
⚙️ Fully Configurable : Modify EMA length, band multiplier, colors, and timeframe settings to suit your strategy.
How to Use 📚
⭐ Add the Indicator : Add the indicator to favorites by pressing the star icon. Set your preferred EMA length and band multiplier. Choose your desired timeframes for multi-frame trend monitoring.
💻 Watch the Table & Chart : The top-right table dynamically updates with bullish or bearish signals across multiple timeframes. Colored arrows on the chart indicate potential entry points when the price crosses the ZLEMA with confirmation from volatility bands.
🔔 Enable Alerts : Configure alerts for real-time notifications when trends shift—no need to monitor charts constantly.
How It Works 🧠
The script calculates the zero-lag EMA (ZLEMA) by compensating for data lag, giving traders more responsive moving averages. It checks for volatility shifts using the Average True Range (ATR), multiplied to create upper and lower deviation bands. If the price crosses above or below these bands, it marks the start of new trends. Additionally, the indicator aggregates trend data from up to five configurable timeframes and displays them in a neat summary table. This helps you confirm trends across different intervals—ideal for multi-timeframe analysis. The visual signals include upward and downward arrows on the chart, denoting potential entries or exits when trends align across timeframes. Traders can use these cues to make well-timed trades and avoid lag-related pitfalls.
E9 Bollinger RangeThe E9 Bollinger Range is a technical trading tool that leverages Bollinger Bands to track volatility and price deviations, along with additional trend filtering via EMAs.
The script visually enhances price action with a combination of trend-filtering EMAs, bar colouring for trend direction, signals to indicate potential buy and sell points based on price extension and engulfing patterns.
Here’s a breakdown of its key components:
Bollinger Bands: The strategy plots multiple Bollinger Band deviations to create different price levels. The furthest deviation bands act as warning signs for traders when price extends significantly, signaling potential overbought or oversold conditions.
Bar Colouring: Visual bar colouring is applied to clearly indicate trend direction: green bars for an uptrend and red bars for a downtrend.
EMA Filtering: Two EMAs (50 and 200) are used to help filter out false signals, giving traders a better sense of the underlying trend.
This combination of signals, visual elements, and trend filtering provides traders with a systematic approach to identifying price deviations and taking advantage of market corrections.
Brief History of Bollinger Bands
Bollinger Bands were developed by John Bollinger in the early 1980s as a tool to measure price volatility in financial markets. The bands consist of a moving average (typically 20 periods) with upper and lower bands placed two standard deviations away. These bands expand and contract based on market volatility, offering traders a visual representation of price extremes and potential reversal zones.
John Bollinger’s work revolutionized technical analysis by incorporating volatility into trend detection. His bands remain widely used across markets, including stocks, commodities, and cryptocurrencies. With the ability to highlight overbought and oversold conditions, Bollinger Bands have become a staple in many trading strategies.
Adjustable Percentage Range Moving AverageAdjustable Percentage Range Moving Average (APRMA)
The Adjustable Percentage Range Moving Average (APRMA) is a technical analysis tool designed for traders and market analysts who seek a dynamic approach to understanding market volatility and trend identification. Unlike traditional moving averages, the APRMA incorporates user-adjustable percentage bands around a central moving average line, offering a customizable view of price action relative to its recent history.
Key Features:
Central Moving Average: At its core, APRMA calculates a moving average (type of your choice) of the price over a specified number of periods, serving as the baseline for the indicator.
Percentage Bands: Surrounding the moving average are four bands, two above and two below, set at user-defined percentages away from the central line. These bands expand and contract based on the percentage input, not on standard deviation like Bollinger Bands, which allows for a consistent visual interpretation of how far the price has moved from its average.
Customizability: Users can adjust:
The length of the moving average period to suit short-term, medium-term, or long-term analysis.
The percentage offset for the bands, enabling traders to set the sensitivity of the indicator according to the asset's volatility or their trading strategy.
Visual Interpretation:
When the price moves towards or beyond the upper band, it might indicate that the asset is potentially overbought or that a strong upward trend is in place.
Conversely, price action near or below the lower band could suggest an oversold condition or a strong downward trend.
The space between the bands can be used to gauge volatility; narrower bands suggest lower current volatility relative to the average, while wider bands indicate higher volatility.
Usage in Trading:
Trend Confirmation: A price staying above the moving average and pushing the upper band might confirm an uptrend, while staying below and testing the lower band could confirm a downtrend.
Reversion Strategies: Traders might look for price to revert to the mean (moving average) when it touches or crosses the bands, setting up potential entry or exit points.
Breakout Signals: A price moving decisively through a band after a period of consolidation within the bands might signal a breakout.
The APRMA provides a clear, adaptable framework for traders to visualize where the price stands in relation to its recent average, offering insights into potential overbought/oversold conditions, trend strength, and volatility, all tailored by the trader's strategic preferences.
Volume Channel - [With Volume Filter]The indicator calculates two volume-weighted moving averages (VWMA) using different lengths, and filters them based on a moving average of volume. The filtered VWMA values are then plotted on the chart as lines, representing the fast and slow moving averages. In addition, upper and lower bands are calculated based on the slow VWMA and plotted as lines on the chart.
The fast and slow VWMA lines can be used to identify trends in the market. When the fast VWMA is above the slow VWMA, it is an indication of an uptrend, and when the fast VWMA is below the slow VWMA, it is an indication of a downtrend. The position of the VWMA lines relative to the upper and lower bands can also be used to identify potential trade signals.
When the price is near the upper band, it indicates that the market is overbought, and when the price is near the lower band, it indicates that the market is oversold. Traders can use these signals to enter or exit trades.
The indicator also includes a volume filter, which means that the VWMA values are only calculated when the volume is above a certain moving average of volume. This helps to filter out noise in the market and provide more accurate signals.
Explanation for each parameter
vwmaLength1: This is the length of the fast volume-weighted moving average (VWMA) used in the calculation. The default value is 10, and it can be adjusted by the user.
vwmaLength2: This is the length of the slow volume-weighted moving average (VWMA) used in the calculation. The default value is 25, and it can be adjusted by the user.
bandLength: This is the length of the moving average used to calculate the upper and lower bands. The default value is 34, and it is not adjustable by the user.
volumeFilterLength: This is the length of the moving average of volume used as a filter for the VWMA calculation. The default value is 5, and it can be adjusted by the user.
src: This is the input source for the VWMA calculation. The default value is close, which means the indicator is using the closing price of each bar. However, the user can select a different input source by changing this parameter.
filteredVwma1: This is the filtered VWMA calculated based on the volume filter and the fast VWMA length. It is plotted as a line on the chart and can be used to identify short-term trends.
filteredVwma2: This is the filtered VWMA calculated based on the volume filter and the slow VWMA length. It is plotted as a line on the chart and can be used to identify long-term trends.
ma: This is the moving average of the filtered slow VWMA values, which is used to calculate the upper and lower bands. It is plotted as a line on the chart.
offs: This is the offset used to calculate the upper and lower bands. It is based on the standard deviation of the filtered slow VWMA values and is multiplied by 1.6185 * 3. It is plotted as a line on the chart.
up: This is the upper band calculated as the moving average plus the offset. It is plotted as a line on the chart and can be used to identify overbought conditions.
dn: This is the lower band calculated as the moving average minus the offset. It is plotted as a line on the chart and can be used to identify oversold conditions.
CCI ±100 Price Deviation with SMA & VWAP Trend ColorIndicator Synopsis: CCI ±100 Price Deviation with SMA & VWAP
Purpose:
This indicator combines trend filtering, momentum smoothing, and dynamic price bands to help identify intraday trading opportunities. It’s designed for:
15-minute chart → trend identification
1–2 minute chart → precise entries based on dynamic bands
Components:
SMA of Typical Price (smaTP)
Smooth average of the current bar’s typical price (hlc3).
Acts as a dynamic midpoint for the ±100 deviation bands.
±100 Deviation Bands
Calculated using a modified CCI formula:
Upper = SMA TP + 0.015 × MAD × 100
Lower = SMA TP - 0.015 × MAD × 100
Works as dynamic support/resistance and potential reversal zones.
SMA of CCI length (scaled to price)
Smooths the CCI momentum signal to the price scale.
Acts as a confirmation filter for trade direction near bands.
Optional toggle and customizable color/line width.
VWAP (Volume Weighted Average Price)
Optional overlay with trend-based coloring:
Price above VWAP → bullish → green
Price below VWAP → bearish → red
Acts as primary trend filter.
How to Use the Indicator
Step 1: Determine Trend (15-minute chart)
Check VWAP trend:
Price > VWAP → bullish trend → only consider long trades
Price < VWAP → bearish trend → only consider short trades
Confirm with SMA TP slope:
Rising SMA → bullish bias
Falling SMA → bearish bias
This ensures you only trade in the direction of the intraday trend.
JOPA Channel (Dual-Volumed) v1 [JopAlgo]JOPA Channel (Dual-Volumed) v1
Short title: JOPAV1 • License: MPL-2.0 • Provider: JopAlgo
We have developed our own, first channel-based trading indicator and we’re making it available to all traders. The goal was a channel that breathes with the tape—built on a volume-weighted backbone—so the outcome stays lively instead of static. That led to the JOPA Channel.
All important features (at a glance)
In one line: A Rolling-VWAP channel whose width adapts with two volumes (RVOL + dollar-flow), adds order-flow asymmetry (OBV tilt) and regime awareness (Efficiency Ratio), and frames risk with outer containment bands from residual extremes—so you see fair value, momentum, and exhaustion in one view.
Feature list
Rolling VWAP centerline: Tracks where volume traded (fair value).
Dual-volume width: Bands expand/contract with relative volume and value traded (price×volume).
OBV tilt: Upper/lower widths skew toward the side actually pushing.
Regime adapter (ER): Tighter in trend, wider in chop—automatically.
Outer containment rails: Residual-extreme ceilings/floors, smoothed + margin.
20% / 80% guides: 20% light blue (discount), 80% light red (premium).
Squeeze dots (optional): Orange circles below candles during compression.
Non-repainting: Uses rolling sums and past-only math; no lookahead.
Default visual in this release
Containment rails + fill: ON (stepline, medium).
Inner Value rails + fill: Rails OFF (stepline, thin), fill ON (drawn only if rails are shown).
20% & 80% guides: ON (dashed, thin; 20% light blue, 80% light red).
Squeeze dots: OFF by default (orange circles when enabled).
What you see on the chart
RVWAP (centerline): Your compass for fair value.
Inner Value Bands (optional): Tight rails for breakouts and pullback timing.
Outer Containment Bands (default ON): High-confidence ceilings/floors for targets and fades.
20% / 80% guides: Quick read of “where in the channel” price is sitting.
Squeeze dots (optional): Volatility compression heads-up (no text labels).
Non-repainting note: The indicator does not revise closed bars. Forecast-Lock uses linear regression to extrapolate 1–3 bars ahead without using future data.
How to use it
Core reads (works on any timeframe)
Bias: Above a rising RVWAP → long bias; below a falling RVWAP → short bias.
Breakouts (momentum): Close beyond an Inner Value rail with RVOL ≥ threshold (alert provided).
Reversions (fades): Tag Outer Containment, stall, then close back inside → expect mean reversion toward RVWAP.
20/80 timing:
At/above 80% (light red) → premium/exhaustion risk; trim longs or consider fades if RVOL cools.
At/below 20% (light blue) → discount/exhaustion risk; trim shorts or consider longs if RVOL cools.
Squeeze clusters: When dots bunch up, expect a range break; use the Breakout alert as confirmation.
Playbooks by trading style
Day Trading (1–5m)
Setup: Keep the chart clean (Containment ON, Value rails OFF). Toggle Inner Value ON when hunting a breakout or timing a pullback.
Pullback Long: Dip to RVWAP / Lower Value with sub-threshold RVOL, then a close back above RVWAP → long.
Stop: Just beyond Lower Containment or the pullback swing.
Targets (1:1:1): ⅓ at RVWAP, ⅓ at Upper Value, ⅓ trail toward Upper Containment.
Breakout Long: After a squeeze cluster, take the Breakout Long alert (close > Upper Value, RVOL ≥ min). If no retest, demand the next bar holds outside.
Range Fade: Only when RVWAP is flat and dots cluster; short Upper Containment → RVWAP (mirror for longs at the lower rail).
Intraday (15m–1H)
HTF compass: Take bias from 4H.
Pullback Long: “Touch & reclaim” of RVWAP while RVOL cools; enter on the reclaim close or break of that candle’s high.
Breakout: Run Inner Value ON; act on Breakout alerts (RVOL gate ≈ 1.10–1.15 typical).
Avoid low-probability fades against the 4H slope unless RVWAP is flat.
Swing (4H–1D)
Continuation: In uptrends, buy pullbacks to RVWAP / Lower Value with sub-threshold RVOL; scale at Upper Containment.
Adds: Post-squeeze Breakout Long adds; trail on RVWAP or Lower Value.
Fades: Prefer when RVWAP flattens and price oscillates between containments.
Position (1D+)
Framework: Daily RVWAP slope + position within containment.
Add rule: Each reclaim of RVWAP after a dip is an add; trim into Upper Containment or near 80% light red.
Sizing: Containment distance is larger—size down and trail on RVWAP.
Inputs & Settings (complete)
Core
Source: Price input for RVWAP.
Rolling VWAP Length: Window of the centerline (higher = smoother).
Volume Baseline (RVOL): SMA window for relative volume.
Inner Value Bands (volatility-based width)
k·StdDev(residuals), k·ATR, k·MAD(residuals): Blend three measures into base width.
StdDev / ATR / MAD Lengths: Lookbacks for each.
Two-Volume Fusion
RVOL Exponent: How aggressively width responds to relative volume.
Dollar-Flow Gain: Adds push from price×volume (value traded).
Dollar-Flow Z-Window: Standardization window for dollar-flow.
Asymmetry (Order-Flow Tilt)
Enable Tilt (OBV): Lets flow skew upper/lower widths.
Tilt Strength (0..1): Gain applied to OBV slope z-score.
OBV Slope Z-Window: Window to standardize OBV slope.
Regime Adapter
Efficiency Ratio Lookback: Measures trend vs chop.
ER Width Min/Max: Maps ER into a width factor (tighter in trend, wider in chop).
Band Tracking (inner value rails)
Tracking Mode:
Base: Pure base rails.
Parallel-Lock: Smooth RVWAP & width; track in parallel.
Slope-Lock: Adds a fraction of recent slope (momentum-friendly).
Forecast-Lock: 1–3 bar extrapolation via linreg (non-repainting on closed bars).
Attach Strength (0..1): Blend tracked rails vs base rails.
Tracking Smooth Length: EMA smoothing of RVWAP and width.
Slope Influence / Forecast Lead Bars: Gains for the chosen mode.
Outer Containment Bands
Show Containment Bands: Master toggle (default ON).
Residual Extremes Lookback: Highest/lowest residual window.
Extreme Smoothing (EMA): Stability on extreme lines.
Margin vs inner width: Extra padding relative to smoothed inner width.
Squeeze & Alerts
Squeeze Window / Threshold: Width vs average; at/under threshold = dot (when enabled).
Min RVOL for Breakout: Required RVOL for breakout alerts.
Style (defaults in this release)
Inner Value rails: OFF (stepline, thin).
Inner & Containment fills: ON.
Containment rails: ON (stepline, medium).
20% / 80% guides: ON — 20% light blue, 80% light red, dashed, thin.
Squeeze dots: OFF by default (orange circles below candles when enabled).
Practical templates (copy/paste into a plan)
Momentum Breakout
Context: Squeeze cluster near RVWAP; Inner Value ON.
Trigger: Breakout Long (close > Upper Value & RVOL ≥ min).
Stop: Below Lower Value (tight) or below RVWAP (safer).
Targets (1:1:1): ⅓ Value → ⅓ Containment → ⅓ trail on RVWAP.
Pullback Continuation
Context: Uptrend; dip to RVWAP / Lower Value with cooling RVOL.
Trigger: Close back above RVWAP or break of reclaim candle’s high.
Stop: Just outside Lower Containment or pullback swing.
Targets: RVWAP → Upper Value → Upper Containment.
Containment Reversion (range)
Context: RVWAP flat; repeated containment tags.
Trigger: Stall at containment, then close back inside.
Stop: A step beyond that containment.
Target: RVWAP; runner only if RVOL stays muted.
Alerts included
DVWAP Breakout Long / Short (Value Bands)
Top Zone / Bottom Zone (20% / 80% guides)
Tip: On lower TFs, act on Breakout alerts with higher-TF bias (e.g., trade 5–15m in the direction of 1H/4H RVWAP slope/position).
Best practices
Let RVWAP be the compass; if unsure, wait until price picks a side.
Respect RVOL; low-RVOL breaks are prone to fail.
Use guides for timing, not certainty. Pair 20/80 zones with flow context.
Start with defaults; change one knob at a time.
Common pitfalls
Fading every containment touch → only fade when RVWAP is flat or RVOL cools.
Over-tuning inputs → the defaults are robust; small tweaks go a long way.
Fighting the higher timeframe on low TFs → expensive habit.
Footer — License & Publishing
License: Mozilla Public License 2.0 (MPL-2.0). You may modify and redistribute; keep this file under MPL and provide source for this file.
Originality: © 2025 JopAlgo. No third-party code reused; Pine built-ins and common formulas only.
Publishing: Keep this header/description intact when releasing on TradingView. Avoid promotional links in the public script text.
My S.T.A.C.K.📊 My S.T.A.C.K. (Simplified TA Combined Kit)
All your favorite technical tools in one clean, customizable overlay.
My S.T.A.C.K. is a power-packed indicator designed to streamline your chart by combining the most commonly used technical analysis tools into a single, space-saving script. Whether you're a trend trader, swing trader, or just looking to declutter your view — this kit gives you everything you need, nothing you don’t.
🔧 Features:
5 Customizable Moving Averages: Choose your type (SMA, EMA, WMA, etc.) and periods to match your strategy.
Bollinger Bands: Visualize volatility and overbought/oversold zones with precision.
Donchian Channels: Spot breakouts and trend reversals based on high/low ranges.
ATR Bands: Adaptive support/resistance zones based on Average True Range.
Clean Visualization: Toggle each element on or off, adjust colors, and focus only on what matters.
✅ Ideal For:
- Traders who want multiple indicators in one place
- Reducing indicator clutter on TradingView
- Quick visual analysis without switching scripts
BB ATR Fractal MMThe Bollinger Bands + ATR with Fractal indicator is a powerful combination of Bollinger Bands, ATR (Average True Range), and Fractal to help identify market volatility and potential entry/exit points on the chart.
Bollinger Bands help to assess the market’s volatility by calculating upper and lower bands based on the simple moving average (SMA) and standard deviation. It’s an excellent tool for identifying overbought and oversold conditions.
ATR (Average True Range) is used to measure market volatility. It helps determine how much the price is moving, and it can be used to adjust the Bollinger Bands, creating bands that reflect the current volatility more accurately.
Fractal helps to identify peaks and troughs in the market, supporting decision-making by highlighting potential reversal points. Fractals mark regions where price may reverse direction, making it easier to spot possible trade opportunities.
How to Use:
Bollinger Bands Upper and Lower Bands: These bands help to identify overbought or oversold conditions. If the price breaks above the upper band, the market may be overbought. If the price breaks below the lower band, the market may be oversold.
ATR: It indicates the volatility level of the market. When the market shows large volatility (ATR increases), the Bollinger Bands expand to reflect higher price swings.
Fractal: Arrows appear at the market’s peaks and troughs, helping identify entry points for buying (at fractal lows) or selling (at fractal highs). These signals can help you make trading decisions based on potential price reversals.
Wick Trend Analysis with Supertrend and RSI -AYNETScientific Explanation
1. Wick Trend Analysis
Upper and Lower Wicks:
Calculated based on the difference between the high or low price and the candlestick body (open and close).
The trend of these wick lengths is derived using the Simple Moving Average (SMA) over the defined trend_length period.
Trend Direction:
Positive change (ta.change > 0) indicates an increasing trend.
Negative change (ta.change < 0) indicates a decreasing trend.
2. Supertrend Indicator
ATR Bands:
The Supertrend uses the Average True Range (ATR) to calculate dynamic upper and lower bands:
upper_band
=
hl2
+
(
supertrend_atr_multiplier
×
ATR
)
upper_band=hl2+(supertrend_atr_multiplier×ATR)
lower_band
=
hl2
−
(
supertrend_atr_multiplier
×
ATR
)
lower_band=hl2−(supertrend_atr_multiplier×ATR)
Trend Detection:
If the price is above the upper band, the Supertrend moves to the lower band.
If the price is below the lower band, the Supertrend moves to the upper band.
The Supertrend helps identify the prevailing market trend.
3. RSI (Relative Strength Index)
The RSI measures the momentum of price changes and ranges between 0 and 100:
Overbought Zone (Above 70): Indicates that the price may be overextended and due for a pullback.
Oversold Zone (Below 30): Indicates that the price may be undervalued and due for a reversal.
Visualization Features
Wick Trend Lines:
Upper wick trend (green) and lower wick trend (red) show the relative strength of price rejection on both sides.
Wick Trend Area:
The area between the upper and lower wick trends is filled dynamically:
Green: Upper wick trend is stronger.
Red: Lower wick trend is stronger.
Supertrend Line:
Displays the Supertrend as a blue line to highlight the market's directional bias.
RSI:
Plots the RSI line, with horizontal dotted lines marking the overbought (70) and oversold (30) levels.
Applications
Trend Confirmation:
Use the Supertrend and wick trends together to confirm the market's directional bias.
For example, a rising lower wick trend with a bullish Supertrend suggests strong bullish sentiment.
Momentum Analysis:
Combine the RSI with wick trends to assess the strength of price movements.
For example, if the RSI is oversold and the lower wick trend is increasing, it may signal a potential reversal.
Signal Generation:
Generate entry signals when all three indicators align:
Bullish Signal:
Lower wick trend increasing.
Supertrend bullish.
RSI rising from oversold.
Bearish Signal:
Upper wick trend increasing.
Supertrend bearish.
RSI falling from overbought.
Future Improvements
Alert System:
Add alerts for alignment of Supertrend, RSI, and wick trends:
pinescript
Kodu kopyala
alertcondition(upper_trend_direction == 1 and supertrend < close and rsi > 50, title="Bullish Signal", message="Bullish alignment detected.")
alertcondition(lower_trend_direction == 1 and supertrend > close and rsi < 50, title="Bearish Signal", message="Bearish alignment detected.")
Custom Thresholds:
Add thresholds for wick lengths and RSI levels to filter weak signals.
Multiple Timeframes:
Incorporate multi-timeframe analysis for more robust signal generation.
Conclusion
This script combines wick trends, Supertrend, and RSI to create a comprehensive framework for analyzing market sentiment and detecting potential trading opportunities. By visualizing trends, market bias, and momentum, traders can make more informed decisions and reduce reliance on single-indicator strategies.
Heikin-Ashi Band Proximity IndicatorHeikin-Ashi Band Proximity Indicator
Overview:
The Heikin-Ashi Band Proximity Indicator is a an analytical tool engineered to pinpoint critical price junctures where the Heikin-Ashi closing values align with the upper and lower thresholds of the Dynamic Adaptive Regression Bands . This indicator delineates these intersections through distinct green and red lines plotted over the last 100 candles, demarcating prospective support and resistance zones.
Purpose:
This indicator helps traders identify potential buy and sell zones based on proximity to dynamically calculated bands using Heikin-Ashi smoothed prices combined with linear regression and standard deviation calculations.
How It Works:
- Heikin-Ashi Transformation: Smooths price data to help isolate trends and reversals, reducing market noise and highlighting clearer trends.
- Regression Bands: Calculates the central regression line and deviations to form adaptive bands that act as dynamic levels of support and resistance.
- Color-Coded Indications: Green lines typically denote zones where prices may receive upward support, enhancing the likelihood of a price increase, while red lines suggest probable resistance zones where price pullbacks or stagnation are anticipated.
Trading Potential Application:
- Buy Signal: When the Heikin-Ashi close approaches the lower green band, it might indicate a potential upward reversal.
- Sell Signal: Conversely, proximity to the upper red band may suggest a downward reversal.
- Market Behavior: When prices diverge from these bands without surpassing them, they frequently revert to these levels, indicating that the bands serve as persistent attractors of price, exerting a gravitational pull over extended periods. This behavior underscores the bands' role in stabilizing price movements by establishing persistent points of reversion within the market's volatility landscape.
Calculation Details:
- ha_close is computed as the average of the open, high, low, and close, which smoothens the price series.
- Regression lines and deviations are calculated to create bands that adapt to recent price actions, providing dynamic support and resistance levels.
Usage:
Useful for traders looking for an indicator to enhance their decision-making by identifying potential entry and exit points based on price stability and volatility. The clear, color-coded system aids in quick decision-making under various market conditions.
Conclusion:
The Heikin-Ashi Band Proximity Indicator is invaluable for traders aiming to capitalize on price movements near critical levels. Its methodology provides a unique approach to understanding market dynamics and enhancing trading strategies.
Normal Weighted Average PriceIntroducing the "Normal Weighted Average Price" (NWAP) by OmegaTools. This innovative script refines the traditional concept of VWAP by eliminating volume from the equation, offering a unique perspective on price movements and market trends.
The NWAP script is meticulously crafted to provide traders with a straightforward yet powerful tool for analyzing price action. By focusing solely on price data, the NWAP offers a clear, volume-independent view of the market's average price, augmented with bands that denote varying levels of price deviation.
Key Features:
NWAP Core: At the heart of this script is the Normal Weighted Average Price line, offering a pure, volume-excluded average price over your chosen timeframe.
Dynamic Bands: Includes upper and lower bands, plus extreme levels, calculated using the standard deviation from the NWAP. These bands help identify potential overbought and oversold conditions.
Customizable Timeframe: Whether you're a day trader or a long-term investor, the NWAP script allows you to set your preferred analysis period, ensuring relevance to your trading strategy.
Bands Width Adjustment: Tailor the width of the deviation bands with a simple multiplier to fit your risk tolerance and trading style.
Visual Zones: The script visually demarcates premium and discount zones between the bands, aiding in quick assessment of market conditions.
Usage Tips:
Ideal for traders seeking a volume-neutral method to gauge market sentiment and potential reversal points.
Use the NWAP and its bands to refine entry and exit points, especially in markets where volume data may be less reliable or skewed.
Combine with other technical indicators for a comprehensive trading strategy.
Stochastic Momentum Channel with Volume Filter [IkkeOmar]A stochastic version of my momentum channel volume filter
The "Stochastic Momentum" indicator combines the concepts of Stochastic and Bollinger Bands to provide insights into price momentum and potential trend reversals. It can be used to identify overbought and oversold conditions, as well as potential bullish and bearish signals.
The indicator calculates a Stochastic RSI using the RSI (Relative Strength Index) of a given price source. It applies smoothing to the Stochastic RSI values using moving averages to generate two lines: the %K line and the %D line. The %K line represents the current momentum, while the %D line represents a filtered version of the momentum.
Additionally, the indicator plots Bollinger Bands around the moving average of the Stochastic RSI. The upper and lower bands represent levels where the price is considered relatively high or low compared to its recent volatility. The distance between the bands reflects the current market volatility.
Here's how the indicator can be interpreted:
Stochastic Momentum (%K and %D lines):
When the %K line crosses above the %D line, it suggests a potential upward move or bullish momentum.
When the %K line crosses below the %D line, it indicates a potential downward move or bearish momentum.
The color of the plot changes based on the relationship between the %K and %D lines. Green indicates %K > %D, while red indicates %K < %D.
Bollinger Bands (Upper and Lower Bands):
When the price crosses above the upper band, it suggests an overbought condition, indicating a potential reversal or pullback.
When the price crosses below the lower band, it suggests an oversold condition, indicating a potential reversal or bounce.
To identify potential upward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses above the lower band, it may signal a potential upward move or bounce.
If the %K line crosses above the %D line while the %K line is below the upper band, it may indicate a potential upward move.
To identify potential downward moves, consider the following conditions:
If the price is not in a contraction phase (the bands are not narrowing), and the price crosses below the upper band, it may signal a potential downward move or pullback.
If the %K line crosses below the %D line while the %K line is above the lower band, it may indicate a potential downward move.
Code explanation
Input Variables:
The input function is used to create customizable input variables that can be adjusted by the user.
smoothK and smoothD are inputs for the smoothing periods of the %K and %D lines, respectively.
lengthRSI represents the length of the RSI calculation.
lengthStoch is the length parameter for the stochastic calculation.
volumeFilterLength determines the length of the volume filter used to filter the RSI.
Source Definition:
The src variable is an input that defines the price source used for the calculations.
By default, the close price is used, but the user can choose a different price source.
RSI Calculation:
The rsi1 variable calculates the RSI using the ta.rsi function.
The RSI is a popular oscillator that measures the strength and speed of price movements.
It is calculated based on the average gain and average loss over a specified period.
In this case, the RSI is calculated using the src price source and the lengthRSI parameter.
Volume Filter:
The code calculates a volume filter to filter the RSI values based on the average volume.
The volumeAvg variable calculates the simple moving average of the volume over a specified period (volumeFilterLength).
The filteredRsi variable stores the RSI values that meet the condition of having a volume greater than or equal to the average volume (volume >= volumeAvg).
Stochastic Calculation:
The k variable calculates the %K line of the Stochastic RSI using the ta.stoch function.
The ta.stoch function takes the filtered RSI values (filteredRsi) as inputs and calculates the %K line based on the length parameter (lengthStoch).
The smoothK parameter is used to smooth the %K line by applying a moving average.
The d variable represents the %D line, which is a smoothed version of the %K line obtained by applying another moving average with a period defined by smoothD.
Momentum Calculation:
The kd variable calculates the average of the %K and %D lines, representing the momentum of the Stochastic RSI.
Bollinger Bands Calculation:
The ma variable calculates the moving average of the momentum values (kd) using the ta.sma function with a period defined by bandLength.
The offs variable calculates the offset by multiplying the standard deviation of the momentum values with a factor of 1.6185.
The up and dn variables represent the upper and lower bands, respectively, by adding and subtracting the offset from the moving average.
The Bollinger Bands provide a measure of volatility and can indicate potential overbought and oversold conditions.
Color Assignments:
The colors for the plot and Bollinger Bands are assigned based on certain conditions.
If the %K line is greater than the %D line, the plotCol variable is set to green. Otherwise, it is set to red.
The upCol and dnCol variables are set to different colors based on whether the fast moving average (fastMA) is above or below the upper and lower bands, respectively.
Plotting:
The Stochastic Momentum (%K) is plotted using the plot function with the assigned color (plotCol).
The upper and lower Bollinger Bands are plotted using the plot function with the respective colors (upCol and dnCol).
The fast moving average (fastMA) is plotted in black color to distinguish it from the bands.
The hline function is used to plot horizontal lines representing the upper and lower bands of the Stochastic Momentum.
The code combines the Stochastic RSI, Bollinger Bands, and color logic to provide visual representations of momentum and potential trend reversals. It allows traders to observe the interaction between the Stochastic Momentum lines, the Bollinger Bands, and price movements, enabling them to make informed trading decisions.
02 SMC + BB Breakout (Improved)This strategy combines Smart Money Concepts (SMC) with Bollinger Band breakouts to identify potential trading opportunities. SMC focuses on identifying key price levels and market structure shifts, while Bollinger Bands help pinpoint overbought/oversold conditions and potential breakout points. The strategy also incorporates higher timeframe trend confirmation to filter out trades that go against the prevailing trend.
Key Components:
Bollinger Bands:
Calculated using a Simple Moving Average (SMA) of the closing price and a standard deviation multiplier.
The strategy uses the upper and lower bands to identify potential breakout points.
The SMA (basis) acts as a centerline and potential support/resistance level.
The fill between the upper and lower bands can be toggled by the user.
Higher Timeframe Trend Confirmation:
The strategy allows for optional confirmation of the current trend using a higher timeframe (e.g., daily).
It calculates the SMA of the higher timeframe's closing prices.
A bullish trend is confirmed if the higher timeframe's closing price is above its SMA.
This helps filter out trades that go against the prevailing long-term trend.
Smart Money Concepts (SMC):
Order Blocks:
Simplified as recent price clusters, identified by the highest high and lowest low over a specified lookback period.
These levels are considered potential areas of support or resistance.
Liquidity Zones (Swing Highs/Lows):
Identified by recent swing highs and lows, indicating areas where liquidity may be present.
The Swing highs and lows are calculated based on user defined lookback periods.
Market Structure Shift (MSS):
Identifies potential changes in market structure.
A bullish MSS occurs when the closing price breaks above a previous swing high.
A bearish MSS occurs when the closing price breaks below a previous swing low.
The swing high and low values used for the MSS are calculated based on the user defined swing length.
Entry Conditions:
Long Entry:
The closing price crosses above the upper Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bullish.
A bullish MSS must have occurred.
Short Entry:
The closing price crosses below the lower Bollinger Band.
If higher timeframe confirmation is enabled, the higher timeframe trend must be bearish.
A bearish MSS must have occurred.
Exit Conditions:
Long Exit:
The closing price crosses below the Bollinger Band basis.
Or the Closing price falls below 99% of the order block low.
Short Exit:
The closing price crosses above the Bollinger Band basis.
Or the closing price rises above 101% of the order block high.
Position Sizing:
The strategy calculates the position size based on a fixed percentage (5%) of the strategy's equity.
This helps manage risk by limiting the potential loss per trade.
Visualizations:
Bollinger Bands (upper, lower, and basis) are plotted on the chart.
SMC elements (order blocks, swing highs/lows) are plotted as lines, with user-adjustable visibility.
Entry and exit signals are plotted as shapes on the chart.
The Bollinger band fill opacity is adjustable by the user.
Trading Logic:
The strategy aims to capitalize on Bollinger Band breakouts that are confirmed by SMC signals and higher timeframe trend. It looks for breakouts that align with potential market structure shifts and key price levels (order blocks, swing highs/lows). The higher timeframe filter helps avoid trades that go against the overall trend.
In essence, the strategy attempts to identify high-probability breakout trades by combining momentum (Bollinger Bands) with structural analysis (SMC) and trend confirmation.
Key User-Adjustable Parameters:
Bollinger Bands Length
Standard Deviation Multiplier
Higher Timeframe
Higher Timeframe Confirmation (on/off)
SMC Elements Visibility (on/off)
Order block lookback length.
Swing lookback length.
Bollinger band fill opacity.
This detailed description should provide a comprehensive understanding of the strategy's logic and components.
***DISCLAIMER: This strategy is for educational purposes only. It is not financial advice. Past performance is not indicative of future results. Use at your own risk. Always perform thorough backtesting and forward testing before using any strategy in live trading.***
Elastic Volume-Weighted Student-T TensionOverview
The Elastic Volume-Weighted Student-T Tension Bands indicator dynamically adapts to market conditions using an advanced statistical model based on the Student-T distribution. Unlike traditional Bollinger Bands or Keltner Channels, this indicator leverages elastic volume-weighted averaging to compute real-time dispersion and location parameters, making it highly responsive to volatility changes while maintaining robustness against price fluctuations.
This methodology is inspired by incremental calculation techniques for weighted mean and variance, as outlined in the paper by Tony Finch:
📄 "Incremental Calculation of Weighted Mean and Variance" .
Key Features
✅ Adaptive Volatility Estimation – Uses an exponentially weighted Student-T model to dynamically adjust band width.
✅ Volume-Weighted Mean & Dispersion – Incorporates real-time volume weighting, ensuring a more accurate representation of market sentiment.
✅ High-Timeframe Volume Normalization – Provides an option to smooth volume impact by referencing a higher timeframe’s cumulative volume, reducing noise from high-variability bars.
✅ Customizable Tension Parameters – Configurable standard deviation multipliers (σ) allow for fine-tuned volatility sensitivity.
✅ %B-Like Oscillator for Relative Price Positioning – The main indicator is in form of a dedicated oscillator pane that normalizes price position within the sigma ranges, helping identify overbought/oversold conditions and potential momentum shifts.
✅ Robust Statistical Foundation – Utilizes kurtosis-based degree-of-freedom estimation, enhancing responsiveness across different market conditions.
How It Works
Volume-Weighted Elastic Mean (eμ) – Computes a dynamic mean price using an elastic weighted moving average approach, influenced by trade volume, if not volume detected in series, study takes true range as replacement.
Dispersion (eσ) via Student-T Distribution – Instead of assuming a fixed normal distribution, the bands adapt to heavy-tailed distributions using kurtosis-driven degrees of freedom.
Incremental Calculation of Variance – The indicator applies Tony Finch’s incremental method for computing weighted variance instead of arithmetic sum's of fixed bar window or arrays, improving efficiency and numerical stability.
Tension Calculation – There are 2 dispersion custom "zones" that are computed based on the weighted mean and dynamically adjusted standard student-t deviation.
%B-Like Oscillator Calculation – The oscillator normalizes the price within the band structure, with values between 0 and 1:
* 0.00 → Price is at the lower band (-2σ).
* 0.50 → Price is at the volume-weighted mean (eμ).
* 1.00 → Price is at the upper band (+2σ).
* Readings above 1.00 or below 0.00 suggest extreme movements or possible breakouts.
Recommended Usage
For scalping in lower timeframes, it is recommended to use the fixed α Decay Factor, it is in raw format for better control, but you can easily make a like of transformation to N-bar size window like in EMA-1 bar dividing 2 / decayFactor or like an RMA dividing 1 / decayFactor.
The HTF selector catch quite well Higher Time Frame analysis, for example using a Daily chart and using as HTF the 200-day timeframe, weekly or monthly.
Suitable for trend confirmation, breakout detection, and mean reversion plays.
The %B-like oscillator helps gauge momentum strength and detect divergences in price action if user prefer a clean chart without bands, this thanks to pineScript v6 force overlay feature.
Ideal for markets with volume-driven momentum shifts (e.g., futures, forex, crypto).
Customization Parameters
Fixed α Decay Factor – Controls the rate of volume weighting influence for an approximation EWMA approach instead of using sum of series or arrays, making the code lightweight & computing fast O(1).
HTF Volume Smoothing – Instead of a fixed denominator for computing α , a volume sum of the last 2 higher timeframe closed candles are used as denominator for our α weight factor. This is useful to review mayor trends like in daily, weekly, monthly.
Tension Multipliers (±σ) – Adjusts sensitivity to dispersion sigma parameter (volatility).
Oscillator Zone Fills – Visual cues for price positioning within the cloud range.
Posible Interpretations
As market within indicators relay on each individual edge, this are just some key ideas to glimpse how the indicator could be interpreted by the user:
📌 Price inside bands – Market is considered somehow "stable"; price is like resting from tension or "charging batteries" for volume spike moves.
📌 Price breaking outer bands – Potential breakout or extreme movement; watch for reversals or continuation from strong moves. Market is already in tension or generating it.
📌 Narrowing Bands – Decreasing volatility; expect contraction before expansion.
📌 Widening Bands – Increased volatility; prepare for high probability pull-back moves, specially to the center location of the bands (the mean) or the other side of them.
📌 Oscillator is just the interpretation of the price normalized across the Student-T distribution fitting "curve" using the location parameter, our Elastic Volume weighted mean (eμ) fixed at 0.5 value.
Final Thoughts
The Elastic Volume-Weighted Student-T Tension indicator provides a powerful, volume-sensitive alternative to traditional volatility bands. By integrating real-time volume analysis with an adaptive statistical model, incremental variance computation, in a relative price oscillator that can be overlayed in the chart as bands, it offers traders an edge in identifying momentum shifts, trend strength, and breakout potential. Think of the distribution as a relative "tension" rubber band in which price never leave so far alone.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality.
FRAMA Channel [BigBeluga]This is a trend-following indicator that utilizes the Fractal Adaptive Moving Average (FRAMA) to create a dynamic channel around the price. The FRAMA Channel helps identify uptrends, downtrends, and ranging markets by examining the relationship between the price and the channel's boundaries. It also marks trend changes with arrows, optionally displaying either price values or average volume at these key points.
🔵 IDEA
The core idea behind the FRAMA Channel indicator is to use the fractal nature of markets to adapt to different market conditions. By creating a channel around the FRAMA line, it not only tracks price trends but also adapts its sensitivity based on market volatility. When the price crosses the upper or lower bands of the channel, it signals a potential shift in trend direction. If the price remains within the channel and crosses over the upper or lower bands without a breakout, the market is likely in a ranging phase with low momentum. This adaptive approach makes the FRAMA Channel effective in both trending and ranging market environments.
🔵 KEY FEATURES & USAGE
◉ Dynamic FRAMA Channel with Trend Signals:
The FRAMA Channel uses a fractal-based moving average to create an adaptive channel around the price. When the price crosses above the upper band, it signals an uptrend and plots an upward arrow with the price (or average volume) value. Conversely, when the price crosses below the lower band, it signals a downtrend and marks the point with a downward arrow. This dynamic adaptation to market conditions helps traders identify key trend shifts effectively.
◉ Ranging Market Detection:
If the price remains within the channel, and only the high crosses the upper band or the low crosses the lower band, the indicator identifies a ranging market with low momentum. In this case, the channel turns gray, signaling a neutral trend. This is particularly useful for avoiding false signals during periods of market consolidation.
◉ Color-Coded Candles and Channel Bands:
Candles and channel bands are color-coded to reflect the current trend direction. Green indicates an upward trend, blue shows a downward trend, and gray signals a neutral or ranging market. This visual representation makes it easy to identify the market condition at a glance, helping traders make informed decisions quickly.
◉ Customizable Display of Price or Average Volume:
On trend change signals, the indicator allows users to choose whether to display the price at the point of trend change or the average volume of 10 bars. This flexibility enables traders to focus on the information that is most relevant to their strategy, whether it's the exact price entery or the volume context of the market shift. Displaying the average volume allows to see the strength of the trend change.
Price Data:
Average Volume of points:
🔵 CUSTOMIZATION
Length & Bands Distance: Adjust the length for the FRAMA calculation to control the sensitivity of the channel. A shorter length makes the channel more reactive to price changes, while a longer length smooths it out. The Bands Distance setting determines how far the bands are from the FRAMA line, helping to define the breakout and ranging conditions.
Signals Data: Choose between displaying the price or the average volume on trend change arrows. This allows traders to focus on either the exact price level of trend change or the market volume context.
Color Settings: Customize the colors for upward momentum, downward momentum, and neutral states to suit your charting preferences. You can also toggle whether to color the candles based on the momentum for a clearer visual of the trend direction.
The FRAMA Channel indicator adapts to market conditions, providing a versatile tool for identifying trends and ranging markets with clear visual cues.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
