[blackcat] L2 Six Round Positioning█ OVERVIEW
The script is an indicator designed to plot the direction (up, down, no change) of several moving averages (MA) on a separate chart, without overlaying the price data. It calculates Simple Moving Averages (SMA) for 3, 5, 8, 34, 60, 120, and 250 periods and uses conditional logic to determine the color and position of the plotted columns based on whether each MA is increasing, decreasing, or unchanged.
█ LOGICAL FRAMEWORK
The script is structured into three main sections:
1 — Input Parameters: None explicitly defined, but the script uses default settings for the indicator function.
2 — Calculations: Computes Simple Moving Averages (SMA) for seven different periods.
3 — Plotting: Uses conditional logic to plot columns representing the direction of each MA, with positions and colors indicating whether the MA is increasing, decreasing, or unchanged.
The flow of data is straightforward: the script calculates the SMAs, determines their direction, sets the appropriate color, and then plots the columns.
█ CUSTOM FUNCTIONS
• No custom functions are defined in this script. All calculations and plotting are done using built-in Pine Script functions such as ta.sma for SMA calculation and plot for plotting.
█ KEY POINTS AND TECHNIQUES
• Use of ta.sma: The script effectively uses the ta.sma function to calculate Simple Moving Averages for different periods.
• Conditional Logic: The script employs conditional logic (ternary operators) to determine the color and position of the plotted columns based on the direction of each MA.
• Plotting with plot: The plot function is used extensively to display the direction of each MA with different colors and positions.
• Color Transparency: The use of color.new with transparency (e.g., color.new(color.green, 50)) allows for visually distinct colors that are not too overpowering.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: The script could be enhanced by adding input parameters to allow users to customize the periods of the moving averages, colors, and transparency levels.
• Extensions: Similar techniques could be applied to other types of moving averages (e.g., EMA, WMA) or to other technical indicators.
• Strategy Development: This indicator could serve as a component in a larger trading strategy by providing insights into the overall trend direction across multiple timeframes.
• Related Concepts: Understanding of moving averages, conditional logic, and plotting techniques in Pine Script would be beneficial for further development and customization of this script.
Скользящие средние
VWAP Direction HistogramThe ** VWAP Direction Histogram ** indicator is a powerful tool for traders looking to gauge the directional bias of the Volume Weighted Average Price (VWAP). VWAP is a critical metric that combines price and volume to provide a weighted average price, often used to identify institutional trading activity and support/resistance levels. This indicator builds upon the traditional VWAP by calculating its directional changes over a customizable lookback period, providing clear visual cues to traders through a color-coded histogram.
By identifying whether VWAP is rising or falling over the specified lookback period, this indicator helps traders determine the prevailing trend bias in the market. A positive VWAP direction suggests upward momentum and a bullish trend bias, while a negative direction indicates downward momentum and bearish sentiment. This information is further reinforced by coloring the chart candles based on the VWAP trend, enabling quick visual analysis and enhancing decision-making for trend-following strategies. Whether you're trading intraday or longer-term, the ** VWAP Direction Histogram ** offers an intuitive and effective way to align your trades with market trends.
Duong_Sideway ZoneThis indicator is designed to identify sideway (ranging) zones on the price chart. It uses a Moving Average (MA) and criteria such as the number of price crosses over the MA, as well as breakout checks, to determine whether the market is in a sideway state. When a sideway zone is detected, it is highlighted with a yellow background on the chart.
Key Features:
MA Line: Uses a Moving Average (MA) as the basis for trend identification.
Sideway Threshold: Based on the number of price crosses over the MA within a specific period.
Breakout Check: Excludes zones from being considered sideway if a breakout occurs beyond the ATR threshold.
Visual Highlighting: Highlights sideway zones with a yellow background for easy identification.
This indicator is ideal for traders looking to identify ranging market phases to adjust their trading strategies accordingly.
For example, if within the last 20 candles, the number of times the closing price crosses the MA5 is greater than 4, it is considered a sideway zone, except in cases where the closing price of a recent candle has broken out of the highest/ lowest price of the previous 20 candles.
RSI-Adjusted 9SMAThis indicator integrates the Relative Strength Index (RSI) and a Simple Moving Average (SMA) to create a more robust trading signal by blending momentum and trend analysis. Here's how they work together:
How the RSI and SMA Work in Harmony
RSI (Momentum Indicator):
The RSI measures the speed and change of price movements, oscillating between 0 and 100.
Typically, an RSI value above 50 suggests bullish momentum, while values below 50 indicate bearish momentum.
The script further refines this by applying a 9-period EMA to the RSI. This smoothing process filters out noise, providing a clearer picture of momentum shifts.
SMA (Trend Indicator):
The SMA calculates the average price over a specific period (9 in this case), helping to smooth out price fluctuations and identify the overall trend.
By observing the SMA, traders can determine whether the market is trending upward, downward, or moving sideways.
Combining the Two for Stronger Signals:
The RSI EMA acts as a momentum filter. When it is above 50, it indicates the presence of bullish momentum. Under such conditions, the SMA turning blue provides a stronger confirmation of an uptrend.
Conversely, when the RSI EMA is below 50, it signals weakening momentum. The SMA turning white underlines the caution, suggesting potential bearish conditions or a lack of trend strength.
This combination ensures that traders are not just relying on the SMA's trend-following behavior but also factoring in the market's underlying momentum for more reliable entries and exits.
Why This Approach is Robust
Avoid False Signals:
The SMA alone can generate false signals in choppy or range-bound markets. By incorporating the RSI EMA, the script reduces the likelihood of acting on weak or non-committal trends.
Timing Entries and Exits:
When both the SMA and RSI EMA align (e.g., blue SMA and RSI EMA > 50), it provides a stronger case for entering trades. Similarly, misalignment (e.g., white SMA and RSI EMA ≤ 50) warns against entering during uncertain conditions.
Adapting to Market Conditions:
This dual approach captures both short-term momentum shifts (RSI EMA) and longer-term trend direction (SMA), making it useful across different market phases.
Practical Application
Bullish Setup:
RSI EMA > 50 + Blue SMA → Enter or stay in long positions.
Bearish Setup:
RSI EMA ≤ 50 + White SMA → Exit long positions or consider short opportunities.
This combination of indicators offers traders a balanced strategy that considers both the direction of the trend and the underlying momentum, resulting in more confident and timely decision-making.
Enhanced 20 SMA Signal BoxesEnhanced 20 SMA Signal Boxes
This indicator leverages the 20-period Simple Moving Average (SMA) to generate clear and actionable trading signals. Designed for traders looking to streamline their entry and exit decisions, the script provides a visual hierarchy with dynamic signal boxes and target levels.
Features:
Buy & Sell Signals:
Automatically detects when the price crosses above or below the 20 SMA and marks the signal candle with a yellow box for clear visualization of entry (top of the box) and risk (bottom of the box).
Dynamic Target Levels:
Three blue outlined boxes are generated for each signal to indicate profit-taking levels. The boxes dynamically adjust based on the signal candle’s range and come with customizable labels:
"Long Target" for buy signals
"Short Target" for sell signals
Alert System:
Get notified when the price enters or exits the signal candle or when target levels are reached.
Customization Options:
Adjust SMA color, thickness, and length.
Modify box opacity for better chart visibility.
Edit target labels and positionings to suit your trading style.
Risk/Reward Visualization:
The script calculates and displays the risk/reward ratio visually between the signal candle and the first target box.
Dynamic Styling:
Target boxes feature gradient shades to highlight increasing profit potential, and optional lines connect the signal candle to targets for organized visuals.
This indicator simplifies decision-making by providing clear signals and targets, making it suitable for day traders, swing traders, and scalpers alike.
Three Moving Averages Strategythis is three moving averages strategy is good for day time frame best for swing trading , probability vary for 60 to 80 to increase the probability add other indictors . you can rsi or macd.
Austin MTF EMA Entry PointsAustin MTF EMA Entry Points
Overview
The Austin MTF EMA Entry Points is a custom TradingView indicator designed to assist traders in identifying high-probability entry points by combining multiple time frame (MTF) analysis. It leverages exponential moving averages (EMAs) from the daily, 1-hour, and 15-minute charts to generate buy and sell signals that align with the overall trend.
This indicator is ideal for traders who:
Want to trade in the direction of the broader daily trend.
Seek precise entry points on lower time frames (1H and 15M).
Prefer using EMAs as their main trend-following tool.
How It Works
Daily Trend Filter:
The indicator calculates the 50 EMA on the daily chart.
The daily EMA acts as the primary trend filter:
If the current price is above the daily 50 EMA, the trend is bullish.
If the current price is below the daily 50 EMA, the trend is bearish.
Lower Time Frame Entry Points:
The indicator calculates the 20 EMA on both the 1-hour (1H) and 15-minute (15M) time frames.
Buy and sell signals are generated when the price aligns with the trend on all three time frames:
Buy Signal: Price is above the daily 50 EMA and also above the 20 EMA on both the 1H and 15M charts.
Sell Signal: Price is below the daily 50 EMA and also below the 20 EMA on both the 1H and 15M charts.
Visual and Alert Features:
Plot Lines:
The daily 50 EMA is plotted in yellow for easy identification of the main trend.
The 20 EMA from the 1H chart is plotted in blue, and the 15M chart's EMA is in purple for comparison.
Buy/Sell Markers:
Green "Up" arrows appear for buy signals.
Red "Down" arrows appear for sell signals.
Alerts:
Alerts notify users when a buy or sell signal is triggered, making it easier to act on trading opportunities in real-time.
How to Use the Indicator
Identify the Main Trend:
Check the relationship between the price and the daily 50 EMA (yellow line):
Only look for buy signals if the price is above the daily 50 EMA.
Only look for sell signals if the price is below the daily 50 EMA.
Wait for Lower Time Frame Alignment:
For a valid signal, ensure that the price is also above or below the 20 EMA (blue and purple lines) on both the 1H and 15M time frames:
This alignment confirms short-term momentum in the same direction as the daily trend.
Act on Signals:
Use the arrows as visual cues for entry points:
Enter long trades on green "Up" arrows.
Enter short trades on red "Down" arrows.
The alerts will notify you of these signals, so you don’t have to monitor the chart constantly.
Exit Strategy:
Use your preferred stop-loss, take-profit, or trailing stop strategy.
You can also exit trades if the price crosses back below/above the daily 50 EMA, signaling a potential reversal.
Use Cases
Swing Traders: Use the daily trend filter to trade in the direction of the dominant trend, while using 1H and 15M signals to fine-tune entries.
Day Traders: Leverage the 1H and 15M time frames to capitalize on short-term momentum while respecting the broader daily trend.
Position Traders: Monitor the indicator to determine potential reversals or significant alignment across time frames.
Customizable Inputs
The indicator includes the following inputs:
Daily EMA Length: Default is 50. Adjust this to change the length of the trend filter EMA.
Lower Time Frame EMA Length: Default is 20. Adjust this to change the short-term EMA for the 1H and 15M charts.
Time Frames: Hardcoded to "D", "60", and "15", but you can modify the script for different time frames if needed.
Example Scenarios
Buy Signal:
Price is above the daily 50 EMA.
Price crosses above the 20 EMA on both the 1H and 15M time frames.
A green "Up" arrow is displayed, and an alert is triggered.
Sell Signal:
Price is below the daily 50 EMA.
Price crosses below the 20 EMA on both the 1H and 15M time frames.
A red "Down" arrow is displayed, and an alert is triggered.
Strengths and Limitations
Strengths:
Aligns trades with the higher time frame trend for increased probability.
Uses multiple time frame analysis to identify precise entry points.
Visual signals and alerts make it easy to use in real-time.
Limitations:
May produce fewer signals in choppy or ranging markets.
Requires discipline to avoid overtrading when conditions are unclear.
Lag in EMAs could result in late entries in fast-moving markets.
Final Notes
The Austin MTF EMA Entry Points indicator is a powerful tool for traders who value multiple time frame alignment and trend-following strategies. While it simplifies decision-making, it is always recommended to backtest and practice proper risk management before using it in live markets.
Try it out and make smarter, trend-aligned trades today! 🚀
Bitcoin Exponential Profit Strategy### Strategy Description:
The **Bitcoin Trading Strategy** is an **Exponential Moving Average (EMA) crossover strategy** designed to identify bullish trends for Bitcoin.
1. **Indicators**:
- **Fast EMA (default 9 periods)**: Represents the short-term trend.
- **Slow EMA (default 21 periods)**: Represents the longer-term trend.
2. **Entry Condition**:
- A **bullish crossover** occurs when the Fast EMA crosses above the Slow EMA.
- The strategy enters a **long position** with a user-defined order size (default 0.01 BTC).
3. **Exit Conditions**:
- **Take Profit**: Closes the position when the profit target is reached (default $100).
- **Stop Loss**: Closes the position when the price drops below the stop loss level (default $50).
- **Bearish Crossunder**: Closes the position when the Fast EMA crosses below the Slow EMA.
4. **Visual Signals**:
- **BUY signals**: Displayed when a bullish crossover occurs.
- **SELL signals**: Displayed when a bearish crossunder occurs.
This strategy is optimized for trend-following behavior, ensuring positions are aligned with upward-moving trends while managing risk through clear stop-loss and take-profit levels.
Hourly 20 EMA on 5m ChartThis indicator shows the hourly 20ema on any current time frame that is open on your charts
Swing High/Low Pivots Strategy [LV]The Swing High/Low Pivots Strategy was developed as a counter-momentum trading tool.
The strategy is suitable for any market and the default values used in the input settings menu are set for Bitcoin (best on 15min). These values, expressed in minimum ticks (or pips if symbol is Forex) make this tool perfectly adaptable to every symbol and/or timeframe.
Check tooltips in the settings menu for more details about every user input.
STRTEGY ENTRY & EXIT MECHANISMS:
Trades Entry based on the detection of swing highs and lows for short and long entries respectively, validated by:
- Limit orders placed after each new pivot level confirmation
- Moving averages trend filter (if enabled)
- No active trade currently open
Trades Exit when the price reaches take-profit or stop-loss level as defined in the settings menu. A double entry/second take-profit level can be enabled for partial exits, with dynamic stop-loss adjustment for the remaining position.
Enhanced Trade Precision:
By limiting entries to confirmed swing high (HH, LH) or swing low (HL, LL) pivot points, the strategy ensures that trades occur at levels of significant price reversals. This precision reduces the likelihood of entering trades in the midst of a trend or during uncertain price action.
Risk Management Optimization:
The strategy incorporates clearly defined stop-loss (SL) and take-profit (TP) levels derived from the pivot points. This structured approach minimizes potential losses while locking in profits, which is critical for consistent performance in volatile markets.
Trend Filtering for Better Entry:
The use of a configurable moving average filter adds a layer of trend validation. This prevents entering trades against the dominant market trend, increasing the probability of success for each trade.
Avoidance of Noise:
The lookback period (length parameter) confirms pivots only after a set number of bars, effectively filtering out market noise and ensuring that entries are based on reliable, well-defined price movements.
Adaptability Across Markets:
The strategy is versatile and can be applied across different markets (Forex, stocks, crypto) due to its dynamic use of ticks and pips converters. It adapts seamlessly to varying price scales and asset types.
Dual Quantity Entries:
The original and optionnal double-entry mechanism allows traders to capture both short-term and extended profits by scaling out of positions. This adaptive approach caters to varying risk appetites and market conditions.
Clear Visualization:
The plotted pivot points, entry limits, SL, and TP levels provide visual clarity, making it easy for traders to track the strategy's behavior and make informed decisions.
Automated Execution with Alerts:
Integrated alerts for both entries and exits ensure timely actions without the need for constant market monitoring, enhancing efficiency. Configurable alert messages are suitable for API use.
Any feedback, comments, or suggestions for improvement are always welcome.
Hope you enjoy!
Spread Analysis (COIN/BTC)The Spread Analysis (COIN/BTC) indicator calculates the Z-score of the price ratio between Coinbase stock ( NASDAQ:COIN ) and Bitcoin ( CRYPTOCAP:BTC ). It helps identify overbought or oversold conditions based on deviations from the historical mean of their price relationship.
Key Features:
Z-Score Calculation:
• Tracks the relative price ratio of NASDAQ:COIN to $BTC.
• Compares the current ratio to its historical average, highlighting extreme overvaluation or undervaluation.
• Buy and Sell Signals:
• Buy Signal: Triggered when the Z-score is less than -2, indicating NASDAQ:COIN may be undervalued relative to $BTC.
• Sell Signal: Triggered when the Z-score exceeds 2, suggesting NASDAQ:COIN may be overvalued relative to $BTC.
• Dynamic Z-Score Visualization:
• Blue line plots the Z-score over time.
• Dashed lines at +2 and -2 mark overbought and oversold thresholds.
• Green and red triangles highlight actionable buy and sell signals.
Use Case:
This indicator is ideal for identifying relative valuation opportunities between NASDAQ:COIN and $BTC. Use it to exploit divergences in their historical relationship and anticipate potential reversions to the mean.
Limitations:
• Best suited for range-bound markets; may produce false signals in strongly trending conditions.
• Assumes a consistent correlation between NASDAQ:COIN and CRYPTOCAP:BTC , which may break during independent price drivers like news or earnings.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
DAILY Supertrend + EMA Crossover with RSI FilterThis strategy is a technical trading approach that combines multiple indicators—Supertrend, Exponential Moving Averages (EMAs), and the Relative Strength Index (RSI)—to identify and manage trades.
Core Components:
1. Exponential Moving Averages (EMAs):
Two EMAs, one with a shorter period (fast) and one with a longer period (slow), are calculated. The idea is to spot when the faster EMA crosses above or below the slower EMA. A fast EMA crossing above the slow EMA often suggests upward momentum, while crossing below suggests downward momentum.
2. Supertrend Indicator:
The Supertrend uses Average True Range (ATR) to establish dynamic support and resistance lines. These lines shift above or below price depending on the prevailing trend. When price is above the Supertrend line, the trend is considered bullish; when below, it’s considered bearish. This helps ensure that the strategy trades only in the direction of the overall trend rather than against it.
3. RSI Filter:
The RSI measures momentum. It helps avoid buying into markets that are already overbought or selling into markets that are oversold. For example, when going long (buying), the strategy only proceeds if the RSI is not too high, and when going short (selling), it only proceeds if the RSI is not too low. This filter is meant to improve the quality of the trades by reducing the chance of entering right before a reversal.
4. Time Filters:
The strategy only triggers entries during user-specified date and time ranges. This is useful if one wants to limit trading activity to certain trading sessions or periods with higher market liquidity.
5. Risk Management via ATR-based Stops and Targets:
Both stop loss and take profit levels are set as multiples of the ATR. ATR measures volatility, so when volatility is higher, both stops and profit targets adjust to give the trade more breathing room. Conversely, when volatility is low, stops and targets tighten. This dynamic approach helps maintain consistent risk management regardless of market conditions.
Overall Logic Flow:
- First, the market conditions are analyzed through EMAs, Supertrend, and RSI.
- When a buy (long) condition is met—meaning the fast EMA crosses above the slow EMA, the trend is bullish according to Supertrend, and RSI is below the specified “overbought” threshold—the strategy initiates or adds to a long position.
- Similarly, when a sell (short) condition is met—meaning the fast EMA crosses below the slow EMA, the trend is bearish, and RSI is above the specified “oversold” threshold—it initiates or adds to a short position.
- Each position is protected by an automatically calculated stop loss and a take profit level based on ATR multiples.
Intended Result:
By blending trend detection, momentum filtering, and volatility-adjusted risk management, the strategy aims to capture moves in the primary trend direction while avoiding entries at excessively stretched prices. Allowing multiple entries can potentially amplify gains in strong trends but also increases exposure, which traders should consider in their risk management approach.
In essence, this strategy tries to ride established trends as indicated by the Supertrend and EMAs, filter out poor-quality entries using RSI, and dynamically manage trade risk through ATR-based stops and targets.
EMA with VWAPThis indicator combines two popular technical analysis tools: the Exponential Moving Average (EMA) and the Volume Weighted Average Price (VWAP), into a single, powerful overlay on your chart. It allows you to analyze both trend direction using the EMA and institutional interest and fair value using the VWAP, all while saving valuable indicator slots on your TradingView layout.
Key Features:
- Exponential Moving Average (EMA):
- Calculates the EMA based on a user-defined Length and Source (e.g., close, open, hl2).
- Includes an optional Offset to shift the EMA line forward or backward on the chart.
- Offers a Smoothing Line feature, allowing you to further smooth the EMA using various moving average types (SMA, EMA, SMMA (RMA), WMA, VWMA) with a customizable Smoothing Length.
- EMA and Smoothing Line can be toggled on or off.
- EMA and Smoothing Line have independent offset capabilities.
Volume Weighted Average Price (VWAP):
-Calculates the VWAP, a crucial indicator that reflects the average price weighted by volume.
- Offers a wide range of Anchor Periods for resetting the VWAP calculation, including: Session, Week, Month, Quarter, Year, Decade, Century, Earnings, Dividends, and Splits.
- Includes an optional Offset to shift the VWAP line.
- Option to Hide VWAP on 1D or Above timeframes to focus on intraday analysis.
- Provides up to three customizable Standard Deviation Bands above and below the VWAP, visually representing volatility and potential support/resistance levels.
- Bands can be calculated using either "Standard Deviation" or "Percentage" methods.
- Bands can be turned on or off independently.
How to Use:
- EMA: Use the EMA to identify the overall trend direction. An upward-sloping EMA suggests an uptrend, while a downward-sloping EMA suggests a downtrend. The Smoothing Line can help confirm the EMA's trend.
- VWAP: The VWAP acts as a benchmark for the "fair" price of an asset during the selected anchor period. Prices above the VWAP may indicate bullish sentiment, while prices below may indicate bearish sentiment.
- Bands: The Standard Deviation Bands can help identify potential overbought and oversold conditions. Price reaching the upper bands might suggest overbought levels, while price reaching the lower bands might suggest oversold levels.
Customization:
- The indicator offers extensive customization through its settings:
- EMA Settings: Adjust the EMA length, source, offset, smoothing method, and smoothing length.
- VWAP Settings: Choose the VWAP anchor period, source, offset, and whether to hide it on daily or higher timeframes.
- VWAP Bands Settings: Control the visibility, multiplier, and calculation method for each of the three standard deviation bands.
Benefits:
- Consolidated Analysis: Combines two essential indicators into one, providing a comprehensive view of price action and volume.
- Saves Indicator Slots: Frees up valuable indicator slots on your TradingView chart.
- Highly Customizable: Offers a wide range of settings to tailor the indicator to your specific trading style and preferences.
- Visual Clarity: Clearly displays the EMA, VWAP, and optional bands on the chart, facilitating quick and easy analysis.
This combined EMA and VWAP indicator is a valuable tool for traders of all levels, offering a powerful and flexible way to analyze market trends and identify potential trading opportunities.
20/50 SMA Cross 200 SMAThis Pine Script code is designed to identify and visualize crossovers of two shorter-term Simple Moving Averages (SMAs), a 20-period SMA and a 50-period SMA, with a longer-term 200-period SMA on a price chart. It also includes alerts for these crossover events. Here's a breakdown:
**Purpose:**
The core idea behind this script is to detect potential trend changes. Crossovers of shorter-term moving averages over a longer-term moving average are often interpreted as bullish signals, while crossovers below are considered bearish.
**Key Components:**
1. **Moving Average Calculation:**
* `sma20 = ta.sma(close, 20)`: Calculates the 20-period SMA of the closing price.
* `sma50 = ta.sma(close, 50)`: Calculates the 50-period SMA of the closing price.
* `sma200 = ta.sma(close, 200)`: Calculates the 200-period SMA of the closing price.
2. **Crossover Detection:**
* `crossUp20 = ta.crossover(sma20, sma200)`: Returns `true` when the 20-period SMA crosses above the 200-period SMA.
* `crossDown20 = ta.crossunder(sma20, sma200)`: Returns `true` when the 20-period SMA crosses below the 200-period SMA.
* Similar logic applies for `crossUp50` and `crossDown50` with the 50-period SMA.
3. **Recent Crossover Tracking (Crucial Improvement):**
* `lookback = 7`: Defines a lookback period of 7 bars.
* `var bool hasCrossedUp20 = false`, etc.: Declares `var` (persistent) boolean variables to track if a crossover has occurred *within* the last 7 bars. This is the most important correction from previous versions.
* The logic using `ta.barssince()` is the key:
* If a crossover happens (`crossUp20` is true), the corresponding `hasCrossedUp20` is set to `true`.
* If no crossover happens on the current bar, it checks if a crossover happened within the last 7 bars using `ta.barssince(crossUp20) <= lookback`. If so, it keeps `hasCrossedUp20` as `true`. After 7 bars, it becomes `false`.
4. **Plotting Crossovers:**
* `plotshape(...)`: Plots circles on the chart to visually mark the crossovers.
* Green circles below the bars for bullish crossovers (20 and 50).
* Red circles above the bars for bearish crossovers (20 and 50).
* Different shades of green/red (green/lime, red/maroon) distinguish between 20 and 50 SMA crossovers.
5. **Plotting Moving Averages (Optional but Helpful):**
* `plot(sma20, color=color.blue, linewidth=1)`: Plots the 20-period SMA in blue.
* Similar logic for the 50-period SMA (orange) and 200-period SMA (gray).
6. **Alerts:**
* `alertcondition(...)`: Triggers alerts when crossovers occur. This is essential for real-time trading signals.
**How it Works (in Simple Terms):**
The script continuously calculates the 20, 50, and 200 SMAs. It then monitors for instances where the 20 or 50 SMA crosses the 200 SMA. When such a crossover happens, a colored circle is plotted on the chart, and an alert is triggered. The key improvement is that it remembers if a crossover occurred in the last 7 bars and continues to display the circle during that period.
**Use Case:**
Traders use this type of indicator to identify potential entry and exit points in the market. A bullish crossover (shorter SMA crossing above the longer SMA) might be a signal to buy, while a bearish crossover might be a signal to sell.
**Key Improvements over Previous Versions:**
* **Correct Lookback Implementation:** The use of `ta.barssince()` and `var` variables is the correct and efficient way to check for crossovers within a lookback period. This fixes the major flaw in earlier versions.
* **Clear Visualizations:** The use of `plotshape` with distinct colors makes it easy to distinguish between 20 and 50 SMA crossovers.
* **Alerts:** The inclusion of alerts makes the script much more practical for real-time trading.
This improved version provides a robust and useful tool for identifying and tracking SMA crossovers.
FIR Low Pass Filter Suite (FIR)The FIR Low Pass Filter Suite is an advanced signal processing indicator that applies finite impulse response (FIR) filtering techniques to price data. At its core, the indicator uses windowed-sinc filtering, which provides optimal frequency response characteristics for separating trend from noise in financial data.
The indicator offers multiple window functions including Kaiser, Kaiser-Bessel Derived (KBD), Hann, Hamming, Blackman, Triangular, and Lanczos. Each window type provides different trade-offs between main-lobe width and side-lobe attenuation, allowing users to fine-tune the frequency response characteristics of the filter. The Kaiser and KBD windows provide additional control through an alpha parameter that adjusts the shape of the window function.
A key feature is the ability to operate in either linear or logarithmic space. Logarithmic filtering can be particularly appropriate for financial data due to the multiplicative nature of price movements. The indicator includes an envelope system that can adaptively calculate bands around the filtered price using either arithmetic or geometric deviation, with separate controls for upper and lower bands to account for the asymmetric nature of market movements.
The implementation handles edge effects through proper initialization and offers both centered and forward-only filtering modes. Centered mode provides zero phase distortion but introduces lag, while forward-only mode operates causally with no lag but introduces some phase distortion. All calculations are performed using vectorized operations for efficiency, with carefully designed state management to handle the filter's warm-up period.
Visual feedback is provided through customizable color gradients that can reflect the current trend direction, with optional glow effects and background fills to enhance visibility. The indicator maintains high numerical precision throughout its calculations while providing smooth, artifact-free output suitable for both analysis and visualization.
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
Market StructureThis is an advanced, non-repainting Market Structure indicator that provides a robust framework for understanding market dynamics across any timeframe and instrument.
Key Features:
- Non-repainting market structure detection using swing highs/lows
- Clear identification of internal and general market structure levels
- Breakout threshold system for structure adjustments
- Integrated multi-timeframe compatibility
- Rich selection of 30+ moving average types, from basic to advanced adaptive variants
What Makes It Different:
Unlike most market structure indicators that repaint or modify past signals, this implementation uses a fixed-length lookback period to identify genuine swing points.
This means once a structure level or pivot is identified, it stays permanent - providing reliable signals for analysis and trading decisions.
The indicator combines two layers of market structure:
1. Internal Structure (lighter lines) - More sensitive to local price action
2. General Structure (darker lines) - Shows broader market context
Technical Details:
- Uses advanced pivot detection algorithm with customizable swing size
- Implements consecutive break counting for structure adjustments
- Supports both close and high/low price levels for breakout detection
- Includes offset option for better visual alignment
- Each structure break is validated against multiple conditions to prevent false signals
Offset on:
Offset off:
Moving Averages Library:
Includes comprehensive selection of moving averages, from traditional to advanced adaptive types:
- Basic: SMA, EMA, WMA, VWMA
- Advanced: KAMA, ALMA, VIDYA, FRAMA
- Specialized: Hull MA, Ehlers Filter Series
- Adaptive: JMA, RPMA, and many more
Perfect for:
- Price action analysis
- Trend direction confirmation
- Support/resistance identification
- Market structure trading strategies
- Multiple timeframe analysis
This open-source tool is designed to help traders better understand market dynamics and make more informed trading decisions. Feel free to use, modify, and enhance it for your trading needs.
3 EMA + RSI with Trail Stop [Free990] (LOW TF)This trading strategy combines three Exponential Moving Averages (EMAs) to identify trend direction, uses RSI to signal exit conditions, and applies both a fixed percentage stop-loss and a trailing stop for risk management. It aims to capture momentum when the faster EMAs cross the slower EMA, then uses RSI thresholds, time-based exits, and stops to close trades.
Short Explanation of the Logic
Trend Detection: When the 10 EMA crosses above the 20 EMA and both are above the 100 EMA (and the current price bar closes higher), it triggers a long entry signal. The reverse happens for a short (the 10 EMA crosses below the 20 EMA and both are below the 100 EMA).
RSI Exit: RSI crossing above a set threshold closes long trades; crossing below another threshold closes short trades.
Time-Based Exit: If a trade is in profit after a set number of bars, the strategy closes it.
Stop-Loss & Trailing Stop: A fixed stop-loss based on a percentage from the entry price guards against large drawdowns. A trailing stop dynamically tightens as the trade moves in favor, locking in potential gains.
Detailed Explanation of the Strategy Logic
Exponential Moving Average (EMA) Setup
Short EMA (out_a, length=10)
Medium EMA (out_b, length=20)
Long EMA (out_c, length=100)
The code calculates three separate EMAs to gauge short-term, medium-term, and longer-term trend behavior. By comparing their relative positions, the strategy infers whether the market is bullish (EMAs stacked positively) or bearish (EMAs stacked negatively).
Entry Conditions
Long Entry (entryLong): Occurs when:
The short EMA (10) crosses above the medium EMA (20).
Both EMAs (short and medium) are above the long EMA (100).
The current bar closes higher than it opened (close > open).
This suggests that momentum is shifting to the upside (short-term EMAs crossing up and price action turning bullish). If there’s an existing short position, it’s closed first before opening a new long.
Short Entry (entryShort): Occurs when:
The short EMA (10) crosses below the medium EMA (20).
Both EMAs (short and medium) are below the long EMA (100).
The current bar closes lower than it opened (close < open).
This indicates a potential shift to the downside. If there’s an existing long position, that gets closed first before opening a new short.
Exit Signals
RSI-Based Exits:
For long trades: When RSI exceeds a specified threshold (e.g., 70 by default), it triggers a long exit. RSI > short_rsi generally means overbought conditions, so the strategy exits to lock in profits or avoid a pullback.
For short trades: When RSI dips below a specified threshold (e.g., 30 by default), it triggers a short exit. RSI < long_rsi indicates oversold conditions, so the strategy closes the short to avoid a bounce.
Time-Based Exit:
If the trade has been open for xBars bars (configurable, e.g., 24 bars) and the trade is in profit (current price above entry for a long, or current price below entry for a short), the strategy closes the position. This helps lock in gains if the move takes too long or momentum stalls.
Stop-Loss Management
Fixed Stop-Loss (% Based): Each trade has a fixed stop-loss calculated as a percentage from the average entry price.
For long positions, the stop-loss is set below the entry price by a user-defined percentage (fixStopLossPerc).
For short positions, the stop-loss is set above the entry price by the same percentage.
This mechanism prevents catastrophic losses if the market moves strongly against the position.
Trailing Stop:
The strategy also sets a trail stop using trail_points (the distance in price points) and trail_offset (how quickly the stop “catches up” to price).
As the market moves in favor of the trade, the trailing stop gradually tightens, allowing profits to run while still capping potential drawdowns if the price reverses.
Order Execution Flow
When the conditions for a new position (long or short) are triggered, the strategy first checks if there’s an opposite position open. If there is, it closes that position before opening the new one (prevents going “both long and short” simultaneously).
RSI-based and time-based exits are checked on each bar. If triggered, the position is closed.
If the position remains open, the fixed stop-loss and trailing stop remain in effect until the position is exited.
Why This Combination Works
Multiple EMA Cross: Combining 10, 20, and 100 EMAs balances short-term momentum detection with a longer-term trend filter. This reduces false signals that can occur if you only look at a single crossover without considering the broader trend.
RSI Exits: RSI provides a momentum oscillator view—helpful for detecting overbought/oversold conditions, acting as an extra confirmation to exit.
Time-Based Exit: Prevents “lingering trades.” If the position is in profit but failing to advance further, it takes profit rather than risking a trend reversal.
Fixed & Trailing Stop-Loss: The fixed stop-loss is your safety net to cap worst-case losses. The trailing stop allows the strategy to lock in gains by following the trade as it moves favorably, thus maximizing profit potential while keeping risk in check.
Overall, this approach tries to capture momentum from EMA crossovers, protect profits with trailing stops, and limit risk through both a fixed percentage stop-loss and exit signals from RSI/time-based logic.
[blackcat] L1 Simple Dual Channel Breakout█ OVERVIEW
The script " L1 Simple Dual Channel Breakout" is an indicator designed to plot dual channel breakout bands and their long-term EMAs on a chart. It calculates short-term and long-term moving averages and deviations to establish upper, lower, and middle bands, which traders can use to identify potential breakout opportunities.
█ LOGICAL FRAMEWORK
Structure:
The script is structured into several main sections:
• Input Parameters: The script does not explicitly define input parameters for the user to adjust, but it uses default values for short_term_length (5) and long_term_length (181).
• Calculations: The calculate_dual_channel_breakout function performs the core calculations, including the blast condition, typical price, short-term and long-term moving averages, and dynamic moving averages.
• Plotting: The script plots the short-term bands (upper, lower, and middle) and their long-term EMAs. It also plots conditional line breaks when the short-term bands cross the long-term EMAs.
Flow of Data and Logic:
1 — The script starts by defining the calculate_dual_channel_breakout function.
2 — Inside the function, it calculates various moving averages and deviations based on the input prices and lengths.
3 — The function returns the calculated bands and EMAs.
4 — The script then calls this function with predefined lengths and plots the resulting bands and EMAs on the chart.
5 — Conditional plots are added to highlight breakouts when the short-term bands cross the long-term EMAs.
█ CUSTOM FUNCTIONS
The script defines one custom function:
• calculate_dual_channel_breakout(close_price, high_price, low_price, short_term_length, long_term_length): This function calculates the short-term and long-term bands and EMAs. It takes five parameters: close_price, high_price, low_price, short_term_length, and long_term_length. It returns an array containing the upper band, lower band, middle band, long-term upper EMA, long-term lower EMA, and long-term middle EMA.
█ KEY POINTS AND TECHNIQUES
• Typical Price Calculation: The script uses a modified typical price calculation (2 * close_price + high_price + low_price) / 4 instead of the standard (high_price + low_price + close_price) / 3.
• Short-term and Long-term Bands: The script calculates short-term bands using a simple moving average (SMA) of the typical price and long-term bands using a relative moving average (RMA) of the close price.
• Conditional Plotting: The script uses conditional plotting to highlight breakouts when the short-term bands cross the long-term EMAs, enhancing visual identification of trading signals.
• EMA for Long-term Trends: The use of Exponential Moving Averages (EMAs) for long-term bands helps in smoothing out short-term fluctuations and focusing on long-term trends.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
• Modifications: Users can add input parameters to allow customization of short_term_length and long_term_length, making the indicator more flexible.
• Enhancements: The script could be extended to include alerts for breakout conditions, providing traders with real-time notifications.
• Alternative Bands: Users might experiment with different types of moving averages (e.g., WMA, HMA) for the short-term and long-term bands to see if they yield better results.
• Additional Indicators: Combining this indicator with other technical indicators (e.g., RSI, MACD) could provide a more comprehensive trading strategy.
• Backtesting: Users can backtest the strategy using Pine Script's strategy functions to evaluate its performance over historical data.
VWAP SlopeThis script calculates and displays the slope of the Volume Weighted Average Price (VWAP) . It compares the current VWAP with its value from a user-defined lookback period to determine the slope. The slope is color-coded: green for an upward trend (positive slope) and red for a downward trend (negative slope) .
Key Points:
VWAP Calculation: The script calculates the VWAP based on a user-defined timeframe (default: daily), which represents the average price weighted by volume.
Slope Determination: The slope is calculated by comparing the current VWAP to its value from a previous period, providing insight into market trends.
Color-Coding: The slope line is color-coded to visually indicate the market direction: green for uptrend and red for downtrend.
This script helps traders identify the direction of the market based on VWAP , offering a clear view of trends and potential turning points.
VWAP - TrendThis Pine Script calculates the Volume Weighted Average Price (VWAP) for a specified timeframe and plots its Linear Regression over a user-defined lookback period . The regression line is color-coded: green indicates an uptrend and red indicates a downtrend. The line is broken at the end of each day to prevent it from extending into the next day, ensuring clarity on a daily basis.
Key Features:
VWAP Calculation: The VWAP is calculated based on a selected timeframe, providing a smoothed average price considering volume.
Linear Regression: The script calculates a linear regression of the VWAP over a custom lookback period to capture the underlying trend.
Color-Coding: The regression line is color-coded to easily identify trends—green for an uptrend and red for a downtrend.
Day-End Break: The regression line breaks at the end of each day to prevent continuous plotting across days, which helps keep the analysis focused within daily intervals.
User Inputs: The user can adjust the VWAP timeframe and the linear regression lookback period to tailor the indicator to their preferences.
This script provides a visual representation of the VWAP trend, helping traders identify potential market directions and turning points based on the linear regression of the VWAP.
