Advanced MA Difference (and more)This Pine Script indicator calculates the difference between the price and a main moving average (SMA or EMA), allowing you to track deviations in either absolute or relative (percentage) terms. It offers several features to help visualize and smooth this difference:
- Main MA Difference: Shows the price deviation from the moving average, either as an absolute dollar amount or as a percentage.
- Fast and Slow Moving Averages: Optionally smooths the difference using fast and slow moving averages, giving insights into short-term and long-term trends in price deviations.
- Difference Between Fast and Slow MAs : Highlights the gap between these MAs, helping to identify momentum shifts.
- Customizable Visuals: Offers flexibility in displaying the difference and moving averages using lines or histograms, and includes a zero line for reference.
When to Use It:
- Use the absolute difference for tracking raw price deviations if you’re focused on concrete moves in the asset’s price.
- Use the relative difference for normalized, percentage-based deviations, especially useful when comparing different assets or time frames.
This indicator is suitable for traders looking to spot trends, price deviations, or momentum shifts relative to a moving average. Its flexibility makes it a good fit for both short-term and long-term analysis.
Moving Averages
Price vs 200 EMA IndicatorPurpose :
The Price vs. 200 MA (EMA) Indicator measures the deviation of the current price from its 200-period Exponential Moving Average (EMA). Instead of merely plotting the raw difference, the indicator calculates a standardized difference (similar to a z-score), which quantifies the deviation in terms of standard deviations over time. This helps traders understand how extreme the price is relative to its long-term average and its typical volatility.
Use Cases :
Trend Analysis:
Traders can use the standardized difference to assess how extreme the current price is relative to its long-term trend (200 EMA) while normalizing for volatility.
When the z-score approaches extreme levels (e.g., above 2 or below -2), it may indicate that the asset is overextended in either direction.
Mean Reversion Strategy:
Since the indicator identifies when the price deviates far from the 200 EMA (in terms of standard deviations), traders can use it to time mean-reversion trades, buying when the price is below -2 (oversold) and selling when it’s above +2 (overbought).
Trend Continuation or Exhaustion:
If the price continues to stay above +2 for extended periods, it could indicate a strong trend, whereas a reversion toward the EMA after reaching +2 or -2 could signal trend exhaustion or reversal.
Summary :
The Price vs. 200 MA (EMA) Indicator calculates the standardized difference (z-score) between the price and its 200-period EMA, giving traders a normalized measure of how far the price is from its long-term average, relative to typical price volatility. The color-coded plot provides a clear visual representation of potential overbought/oversold conditions and highlights when the price has deviated significantly from the 200 EMA in either direction.
RSI with Swing Trade by Kelvin_VAlgorithm Description: "RSI with Swing Trade by Kelvin_V"
1. Introduction:
This algorithm uses the RSI (Relative Strength Index) and optional Moving Averages (MA) to detect potential uptrends and downtrends in the market. The key feature of this script is that it visually changes the candle colors based on the market conditions, making it easier for users to identify potential trend swings or wave patterns.
The strategy offers flexibility by allowing users to enable or disable the MA condition. When the MA condition is enabled, the strategy will confirm trends using two moving averages. When disabled, the strategy will only use RSI to detect potential market swings.
2. Key Features of the Algorithm:
RSI (Relative Strength Index):
The RSI is used to identify potential market turning points based on overbought and oversold conditions.
When the RSI exceeds a predefined upper threshold (e.g., 60), it suggests a potential uptrend.
When the RSI drops below a lower threshold (e.g., 40), it suggests a potential downtrend.
Moving Averages (MA) - Optional:
Two Moving Averages (Short MA and Long MA) are used to confirm trends.
If the Short MA crosses above the Long MA, it indicates an uptrend.
If the Short MA crosses below the Long MA, it indicates a downtrend.
Users have the option to enable or disable this MA condition.
Visual Candle Coloring:
Green candles represent a potential uptrend, indicating a bullish move based on RSI (and MA if enabled).
Red candles represent a potential downtrend, indicating a bearish move based on RSI (and MA if enabled).
3. How the Algorithm Works:
RSI Levels:
The user can set RSI upper and lower bands to represent potential overbought and oversold levels. For example:
RSI > 60: Indicates a potential uptrend (bullish move).
RSI < 40: Indicates a potential downtrend (bearish move).
Optional MA Condition:
The algorithm also allows the user to apply the MA condition to further confirm the trend:
Short MA > Long MA: Confirms an uptrend, reinforcing a bullish signal.
Short MA < Long MA: Confirms a downtrend, reinforcing a bearish signal.
This condition can be disabled, allowing the user to focus solely on RSI signals if desired.
Swing Trade Logic:
Uptrend: If the RSI exceeds the upper threshold (e.g., 60) and (optionally) the Short MA is above the Long MA, the candles will turn green to signal a potential uptrend.
Downtrend: If the RSI falls below the lower threshold (e.g., 40) and (optionally) the Short MA is below the Long MA, the candles will turn red to signal a potential downtrend.
Visual Representation:
The candle colors change dynamically based on the RSI values and moving average conditions, making it easier for traders to visually identify potential trend swings or wave patterns without relying on complex chart analysis.
4. User Customization:
The algorithm provides multiple customization options:
RSI Length: Users can adjust the period for RSI calculation (default is 4).
RSI Upper Band (Potential Uptrend): Users can customize the upper RSI level (default is 60) to indicate a potential bullish move.
RSI Lower Band (Potential Downtrend): Users can customize the lower RSI level (default is 40) to indicate a potential bearish move.
MA Type: Users can choose between SMA (Simple Moving Average) and EMA (Exponential Moving Average) for moving average calculations.
Enable/Disable MA Condition: Users can toggle the MA condition on or off, depending on whether they want to add moving averages to the trend confirmation process.
5. Benefits of the Algorithm:
Easy Identification of Trends: By changing candle colors based on RSI and MA conditions, the algorithm makes it easy for users to visually detect potential trend reversals and trend swings.
Flexible Conditions: The user has full control over the RSI and MA settings, allowing them to adapt the strategy to different market conditions and timeframes.
Clear Visualization: With the candle color changes, users can quickly recognize when a potential uptrend or downtrend is forming, enabling faster decision-making in their trading.
6. Example Usage:
Day traders: Can apply this strategy on short timeframes such as 5 minutes or 15 minutes to detect quick trends or reversals.
Swing traders: Can use this strategy on longer timeframes like 1 hour or 4 hours to identify and follow larger market swings.
Distance From moving averageDistance From Moving Average is designed to help traders visualize the deviation of the current price from a specified moving average. Users can select from four different types of moving averages: Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), and Hull Moving Average (HMA).
Key Features:
User-Friendly Input Options:
Choose the type of moving average from a dropdown menu.
Set the length of the moving average, with a default value of 200.
Custom Moving Average Calculations:
The script computes the selected moving average using the appropriate mathematical formula, allowing for versatile analysis based on individual trading strategies.
Distance Calculation:
The indicator calculates the distance between the current price and the chosen moving average, providing insight into market momentum. A positive value indicates that the price is above the moving average, while a negative value shows it is below.
Visual Representation:
The distance is plotted on the chart, with color coding:
Lime: Indicates that the price is above the moving average (bullish sentiment).
Red: Indicates that the price is below the moving average (bearish sentiment).
Customization:
Users can further customize the appearance of the plotted line, enhancing clarity and visibility on the chart.
This indicator is particularly useful for traders looking to gauge market conditions and make informed decisions based on the relationship between current prices and key moving averages.
Multi-Setting Moving AverageThis indicator is a TradingView tool that allows you to set the calculation periods for moving averages according to different time frames.
Unlike standard moving average indicators, which require manual adjustments when changing time frames, this indicator is designed to automatically reflect the settings for each time frame, eliminating the hassle of changing settings.
このインジケーターは、異なる時間枠に応じた移動平均線の計算期間を設定できるトレーディングビューのツールです。
一般の移動平均線のインジケーターは時間枠の変更に伴って手動で設定を調整する必要がありますが、このインジケーターは時間枠ごとの設定が自動で反映されるように工夫されているため、設定変更の手間が省けます。
LiquidityFlow Dominance+Alerts (btc.d, T3, Stables)LiquidityFlow Dominance+Alerts: Overview & Usage Guide
Overview
The LiquidityFlow Dominance+Alerts indicator provides a dynamic view of liquidity flow across Bitcoin, Altcoins, and Stablecoins, helping track liquidity shifts and identify market sentiment. By integrating moving averages, custom alerts, and thresholds for extreme outliers, this indicator helps to anticipate bullish and bearish shifts in liquidity and alert market tops and bottoms.
Key features include:
1. Liquidity Flow Monitoring : Track liquidity flow across Bitcoin (BTC), Altcoins (TOTAL3), and Stablecoins (USDT, USDC, DAI).
2. Custom Alerts : Set alerts for key liquidity shifts and extreme conditions in Stablecoin dominance, both with static and moving average (MA)-based calculations.
3. Moving Averages : Use Simple, Exponential, or Weighted Moving Averages to smooth out market data for more reliable signals.
4. Outlier Detection : Identify potential tops and bottoms using thresholds for Stablecoin dominance, with alerts for extreme movements.
Functionality
Data Inputs and Key Metrics
- Symbols Monitored:
- Bitcoin Dominance (BTC.D)
- Altcoin Market Cap (TOTAL3)
- Stablecoins (USDT.D, USDC.D, DAI.D)
- Liquidity Flow Conditions:
- Track percentage changes in dominance across sectors to detect liquidity flow into Bitcoin, Altcoins, or Stablecoins.
- Custom Metrics:
- Liquidity Flow Index: BTC Dominance minus Stablecoin Dominance.
- Liquidity Flow Ratio: BTC Dominance divided by the combined dominance of Stablecoins and Altcoins.
Moving Average Integration
- Select from SMA, EMA, or WMA to apply moving averages to the dominance metrics. Moving averages help smooth out short-term volatility and provide more consistent signals.
- Moving averages are applied to each sector (BTC, Altcoins, and Stablecoins) and compared to their previous period values to determine shifts in liquidity.
Alerts and Thresholds
- % Change Lookback Period: Adjust the lookback period to align with the timeframe of your chart. Shorter timeframes may require a lower lookback period, while higher timeframes may benefit from longer periods.
- Stables Bull/Bear % for Alerts: Set a threshold for when Stablecoin dominance becomes a bullish or bearish signal relative to BTC and Altcoins. A higher threshold may be used in volatile markets to filter out noise.
- Extreme Outliers Detection: Use the **Stables Up/Down Extreme Threshold** to identify potential market tops or bottoms when Stablecoin dominance deviates significantly from historical trends. The **Extreme Lookback Period** controls the time window for detecting these anomalies.
How to Use the Indicator
Adjusting the % Change Lookback Period
- The `% Change Lookback Period` should be adjusted based on your chart’s timeframe. For example, a shorter period (e.g., 7) works well for intraday charts, while longer periods (e.g., 14) might be more suitable for daily or weekly charts.
Setting Thresholds for Alerts
- Stables Bull/Bear % for Alerts: Adjust this setting to define when Stablecoin dominance triggers bullish or bearish alerts. A value like 1% could be a good starting point for most market conditions but can be fine-tuned based on volatility.
- Extreme Lookback Period: Define the lookback period for detecting extreme moves in Stablecoin dominance. This will help identify major tops and bottoms in the market. For shorter-term trades, consider using a shorter extreme lookback (e.g., 7-10 periods).
Alerts for Liquidity Shifts
- The indicator supports alerts for key liquidity shifts, which are useful for staying ahead of market movements. Alerts can be set to notify you when liquidity moves into:
- Bitcoin: Indicating a potential bullish trend for Bitcoin.
- Altcoins: Signaling altcoins are bullish.
- Stablecoins: Suggesting a risk-off environment or market correction.
Extreme Alerts for Stables
- Extreme Up/Down Alerts: These are triggered when Stablecoin dominance crosses extreme thresholds. For example, if Stablecoin dominance rises more than 14% over a set period, it could signal a market top, while a significant drop could indicate a market bottom.
Moving Average Calculations
- In addition to static percentage changes, moving averages can be applied to smooth out dominance values. The type and length of the moving average can be customized:
- SMA (Simple Moving Average): Best for smoothing out volatility in a linear way.
- EMA (Exponential Moving Average): More responsive to recent data, making it useful in faster markets.
- WMA (Weighted Moving Average): Emphasizes more recent data, but less reactive than the EMA.
Additional Usage Tips:
- Background Colors: The indicator visually highlights the dominant liquidity flow:
- Orange: Liquidity is shifting toward Bitcoin.
- Aqua: Liquidity is flowing into Altcoins.
- Red: Liquidity is moving into Stablecoins.
Auto Anchored Swing VWAP'sThe Auto Anchored Swing VWAP's indicator automatically anchors Volume-Weighted Average Price (VWAP) lines to recent swing highs and swing lows. VWAPs often act as key support or resistance levels because they represent the average price at which the majority of trading volume has occurred over a given time.
What is VWAP? VWAP is an essential tool in trading, representing the average price of a security over a specific period, weighted by volume. It helps traders identify the average price at which most trades have been executed, providing a balanced view of price action over time.
Anchored VWAPs: Unlike traditional VWAPs, which start from the beginning of the day, anchored VWAPs allow traders to "anchor" the calculation to a specific point in time or a pivot on the chart, in this case a swing high and swing low. This version of VWAP follows the price action from a selected point forward.
When the price is above the VWAP, it indicates that the majority of traders have paid less for the asset, creating a potential support zone as buyers may step in at or near this level. On the other hand, when the price is below the VWAP, it suggests that most traders have paid a higher price, which can lead to a resistance level where sellers may appear to defend their positions.
Anchored VWAPs, in particular, provide more precise support and resistance levels by starting from a specific swing high, swing low, or other significant point on the chart. This allows traders to track how price interacts with these levels after a certain bar.
The selectable pivot lookback length in this indicator defines the number of bars to the left and right of a potential swing high or swing low that must be lower (for a swing high) or higher (for a swing low) in order to confirm the pivot. In other words, it controls how many surrounding bars need to validate a local price extreme before it is considered a true swing point.
For example, if the lookback length is set to 9, a swing high is identified when there are 9 bars to the left and 9 bars to the right that all have lower highs than the current bar. The same logic applies for swing lows, where the price must be lower than the highs of the bars to the left and right for it to be considered a swing low.
This parameter allows traders to control the sensitivity of the swing points used to anchor VWAPs. A smaller lookback value will identify more frequent and short-term swing highs and lows, making the VWAPs more responsive to recent price action. Conversely, a larger lookback value will result in fewer but more significant swing points.
Pine Script
Utilization of Pine Script’s Enum Feature: This indicator leverages Pine Script's new enum feature for the selection of the VWAP lines (solid, dashed, or dotted) style.
Day & Swing Trading EMA Clouds with Adaptive LevelsDay & Swing Trading EMA Clouds with Adaptive Levels is a tool designed for traders who need a flexible indicator that adapts to both short-term (day trading) and long-term (swing trading) strategies. The indicator blends EMA clouds and adaptive support/resistance levels, making it suitable for analyzing trend strength and key price zones.
How It Works:
EMA Clouds for Trend Detection:
This indicator uses three EMAs (Fast, Intermediate, Slow) to create two clouds:
Fast Cloud: The area between the fast and Intermediate EMAs.
Slow Cloud: The area between the Intermediate and slow EMAs.
The cloud colors change based on trend direction:
Positive (uptrend): When the fast EMA is above the Intermediate EMA (turquoise) or the Intermediate EMA is above the slow EMA (teal).
Negative (downtrend): When the fast EMA is below the Intermediate EMA (pink) or the Intermediate EMA is below the slow EMA (magenta).
Traders can use these clouds to visually gauge market momentum and trend reversals.
Adaptive EMA Settings Based on Trading Mode:
The EMA lengths adjust automatically depending on whether you're in Day Trading or Swing Trading mode:
Day Trading Mode uses shorter periods to capture quick price movements:
Fast EMA: 5-period
Mid EMA: 13-period
Slow EMA: 21-period
Swing Trading Mode uses longer periods to capture broader trends:
Fast EMA: 12-period
Mid EMA: 26-period
Slow EMA: 50-period
This dynamic adjustment allows you to switch between trading styles seamlessly, with the EMAs reflecting the most relevant timeframes for each strategy.
Adaptive Support and Resistance Levels:
Depending on the selected trading mode, the indicator dynamically plots key levels:
Day Trading Mode: Previous day’s high, low, and midpoint, as well as 2-day levels.
Swing Trading Mode: Previous month’s high, low, and midpoint, as well as 2-month levels.
These levels act as dynamic support and resistance zones, giving traders critical areas to monitor for potential reversals or breakouts.
Buy & Sell Signals:
Visual buy/sell signals are generated when the fast EMA crosses above or below the slow EMA. These signals can help traders identify potential trend reversals.
Customization:
You can fully adjust the transparency and colors of the clouds to fit your personal preferences and trading style.
Why This Combination?
Combining EMA clouds with adaptive levels provides traders with a complete picture. The clouds highlight the underlying market momentum and trend strength, while the adaptive levels offer potential entry/exit points based on historical price action. This unique mashup allows traders to follow trends and plan trades around key support and resistance zones.
EMA GridThe EMA Grid indicator is a powerful tool that calculates the overall market sentiment by comparing the order of 20 different Exponential Moving Averages (EMAs) over various lengths. The indicator assigns a rating based on how well-ordered the EMAs are relative to each other, representing the strength and direction of the market trend. It also smooths out the macro movements using cumulative calculations and visually represents the market sentiment through color-coded bands.
EMA Calculation:
The indicator uses a series of EMAs with different lengths, starting from 5 and going up to 100. Each EMA is calculated either using the exponential moving averages.
The EMAs form the grid that the indicator uses to measure the order and distance between them.
Rating Calculation:
The indicator computes the relative distance between consecutive EMAs and sums these differences.
The cumulative sum is further smoothed using multiple EMAs with different lengths (from 3 to 21). This smooths out short-term fluctuations and helps identify broader trends.
Market Sentiment Rating:
The overall sentiment is calculated by comparing the values of these smoothing EMAs. If the shorter-term EMA is above the longer-term EMA, it contributes positively to the sentiment; otherwise, it contributes negatively.
The final rating is a normalized value based on the relationship between these EMAs, producing a sentiment score between 1 (bullish) and -1 (bearish).
Color Coding and Bands:
The indicator uses the sentiment rating to color the space between the 100 EMA and 200 EMA, representing the strength of the trend.
If the sentiment is bullish (rating > 0), the band is shaded green. If the sentiment is bearish (rating < 0), the band is shaded red.
The intensity of the color is based on the strength of the sentiment, with stronger trends resulting in more saturated colors.
Utility for Traders:
The EMA Grid is ideal for traders looking to gauge the broader market trend by analyzing the structure and alignment of multiple EMAs. The color-coded band between the 100 and 200 EMAs provides an at-a-glance view of market momentum, helping traders make informed decisions based on the trend's strength and direction.
This indicator can be used to identify bullish or bearish conditions and offers a smoothed perspective on market trends, reducing noise and highlighting significant trend shifts.
Quantoshi Global Liquidity StrategyThis strategy leverages global liquidity data alongside technical indicators like the Rate of Change (ROC) and Double Exponential Moving Average (DEMA) to identify optimal long-entry points during major market trends. The script is designed to capture long-term, sustained momentum and includes built-in risk management by filtering out rapid price spikes. It is best suited for swing trading or long-term trend trading.
Key Features:
Global Liquidity Data:
The strategy incorporates data from major global central banks and M2 money supply to calculate a comprehensive liquidity index, which is a critical component for long-term trend detection.
ROC-DEMA Crossover:
It combines the Rate of Change (ROC) and a 100-period Double Exponential Moving Average (DEMA) to identify momentum shifts. Long entries are triggered when these indicators confirm an upward trend.
Price Thresholds:
The strategy compares the current price to the price from several candles ago to ensure positions are not entered during unsustainable price surges.
Custom Alerts:
Automated alerts for long entries and exits allow users to automate their trades or receive timely notifications when market conditions are met.
How It Works:
The strategy enters long positions when ROC and DEMA signals confirm a positive trend, and the price conditions suggest a sustainable upward momentum. Long exits occur when the momentum reverses, with a clear crossover signal of ROC below DEMA. Custom alert messages make it ideal for automated trading setups.
Why It's Unique:
This strategy combines liquidity data with technical indicators to filter noise and focus on significant market shifts. It allows traders to capture major trend reversals without needing to actively monitor the charts, making it useful for those focused on swing or long-term trading.
Backtesting & Risk Management:
Given its long-term focus, this strategy generates only a few signals per decade when used on a weekly timescale. As a result, traditional backtesting show few trades, but historical analysis reveals its effectiveness in capturing major market movements.
Account Size:
The backtest is based on a $1,000 account size to represent a realistic trading scenario.
Commissions & Tick size: Commission fees of 0.1% and a tick size of 100 are applied to reflect real-world trading conditions.
Trade Size:
Risk per trade is limited to 5% of the account balance to align with sound risk management practices.
Daksh RSI POINT to ShootHere are the key points and features of the Pine Script provided:
### 1. **Indicator Settings**:
- The indicator is named **"POINT and Shoot"** and is set for non-overlay (`overlay=false`) on the chart.
- `max_bars_back=4000` is defined, indicating the maximum number of bars that the script can reference.
### 2. **Input Parameters**:
- `Src` (Source): The price source, default is `close`.
- `rsilen` (RSI Length): The length for calculating RSI, default is 20.
- `linestylei`: Style for the trend lines (`Solid` or `Dashed`).
- `linewidth`: Width of the plotted lines, between 1 and 4.
- `showbroken`: Option to show broken trend lines.
- `extendlines`: Option to extend trend lines.
- `showpivot`: Show pivot points (highs and lows).
- `showema`: Show a weighted moving average (WMA) line.
- `len`: Length for calculating WMA, default is 9.
### 3. **RSI Calculation**:
- Calculates a custom RSI value using relative moving averages (`ta.rma`), and optionally uses On-Balance Volume (`ta.obv`) if `indi` is set differently.
- Plots RSI values as a green or red line depending on its position relative to the WMA.
### 4. **Pivot Points**:
- Utilizes the `ta.pivothigh` and `ta.pivotlow` functions to detect pivot highs and lows over the defined period.
- Stores up to 10 recent pivot points for highs and lows.
### 5. **Trend Line Drawing**:
- Lines are drawn based on pivot highs and lows.
- Calculates potential trend lines using linear interpolation and validates them by checking if subsequent bars break or respect the trend.
- If the trend is broken, and `showbroken` is enabled, it draws dotted lines to represent these broken trends.
### 6. **Line Management**:
- Initializes multiple lines (`l1` to `l20` and `t1` to `t20`) and uses these lines for drawing uptrend and downtrend lines.
- The maximum number of lines is set to 20 for uptrends and 20 for downtrends, due to a limit on the total number of lines that can be displayed on the chart.
### 7. **Line Style and Color**:
- Defines different colors for uptrend lines (`ulcolor = color.red`) and downtrend lines (`dlcolor = color.blue`).
- Line styles are determined by user input (`linestyle`) and use either solid or dashed patterns.
- Broken lines use a dotted style to indicate invalidated trends.
### 8. **Pivot Point Plotting**:
- Plots labels "H" and "L" for pivot highs and lows, respectively, to visually indicate turning points on the chart.
### 9. **Utility Functions**:
- Uses helper functions to get the values and positions of the last 10 pivot points, such as `getloval`, `getlopos`, `gethival`, and `gethipos`.
- The script uses custom logic for line placement based on whether the pivots are lower lows or higher highs, with lines adjusted dynamically based on price movement.
### 10. **Plotting and Visuals**:
- The main RSI line is plotted using a color gradient based on its position relative to the WMA.
- Horizontal lines (`hline1` and `hline2`) are used for visual reference at RSI levels of 60 and 40.
- Filled regions between these horizontal lines provide visual cues for potential overbought or oversold zones.
These are the main highlights of the script, which focuses on trend detection, visualization of pivot points, and dynamic line plotting based on price action.
Pi Cycle Top & Bottom Indicator [InvestorUnknown]The Pi Cycle Top & Bottom Indicator is designed for long-term cycle analysis, particularly useful for detecting significant market tops and bottoms in assets like Bitcoin. By comparing the behavior of two moving averages, one with a shorter period (default 111) and the other with a longer period (default 350), the indicator helps investors identify potential turning points in the market.
Key Features:
Dual Moving Average System:
The indicator uses two moving averages (MA) to create a cyclic oscillator. The shorter moving average (Short Length MA) is more reactive to recent price changes, while the longer moving average (Long Length MA) smooths out long-term trends. Users can select between:
Simple Moving Average (SMA): A straightforward average of closing prices.
Exponential Moving Average (EMA): Places more weight on recent prices, making it more responsive to market changes.
Oscillator Mode Options:
The Pi Cycle Indicator offers two modes of oscillation to better suit different analysis styles:
RAW Mode: This mode calculates the raw ratio of the Short MA to the Long MA, offering a simple comparison of the two averages.
LOG(X) Mode: In this mode, the oscillator takes the natural logarithm of the Short MA to Long MA ratio. This transformation compresses extreme values and highlights relative changes more effectively, making it particularly useful for spotting shifts in long-term trends.
Cyclical Analysis:
The core of the Pi Cycle Indicator is its ability to visualize the relationship between the two moving averages. The ratio of the Short MA to the Long MA is plotted as an oscillator. When the oscillator crosses above or below a baseline (which is 1 for RAW mode and 0 for LOG(X) mode), it signals potential market turning points.
Visual Representation:
The indicator provides a clear visual display of market conditions:
Orange Line: Represents the Pi Cycle Oscillator, which shows the relationship between the short and long moving averages.
Gray Baseline: A reference line that dynamically adjusts based on the oscillator mode. Crosses above or below this line help indicate possible trend reversals.
Shaded Areas: Color-filled areas between the oscillator and the baseline, which are shaded green when the market is bullish (oscillator above baseline) and red when bearish (oscillator below baseline). This provides a visual cue to assist in identifying potential market tops and bottoms.
Use Cases:
The Pi Cycle Top & Bottom Indicator is primarily used in long-term market analysis, such as Bitcoin cycles, to identify significant tops and bottoms. These moments often coincide with large cyclical shifts, making it valuable for those aiming to enter or exit positions at key moments in the market cycle.
By analyzing the interaction between short-term and long-term trends, investors can gain insight into broader market dynamics and make more informed decisions regarding entry and exit points. The ability to switch between moving average types (SMA/EMA) and oscillator modes (RAW/LOG) adds flexibility for adapting to different market environments.
Arjunology for Stocks IndicatorArjunology for Stocks Indicator is a unique trend-following and exit management system that combines the power of Exponential Moving Averages (EMA) and Average True Range (ATR) to capture market trends and manage trade exits dynamically. It is designed to help traders identify potential buy and sell points based on market trends while incorporating volatility adjustments to avoid false signals and provide more reliable trade entries and exits.
Key Features:
1. Exponential Moving Averages (EMAs):
• Two EMAs (Short EMA and Long EMA) are used to determine trend direction and potential crossover signals.
• Short EMA reacts quickly to price changes, giving an indication of shorter-term trends.
• Long EMA provides a more stable measure of the overall trend direction, helping filter out market noise.
• Bullish Crossovers: When the short EMA crosses above the long EMA, it signals a potential uptrend (buy condition).
• Bearish Crossovers: When the short EMA crosses below the long EMA, it signals a potential downtrend (sell condition).
2. Average True Range (ATR):
• ATR is used to assess market volatility and avoid false signals during low volatility periods.
• A trailing stop loss mechanism based on ATR ensures that the indicator adapts to the current market environment, with higher volatility allowing for wider stops and lower volatility leading to tighter stops.
• A flat ATR threshold is used to avoid signals during quiet periods, where price movement may be too insignificant to trade effectively.
3. Buy and Sell Visual Cues:
• Green Triangle at the bottom of the candle when a bullish crossover (buy) condition is met.
• Red Triangle at the top of the candle when a bearish crossover (sell) condition is met.
• These visual cues help traders quickly identify trade entry points based on the trend signals.
4. Dynamic Exit Management:
• The indicator provides an Blue candle background to highlight exit points, with an “EXIT” label at the bottom of the candle in blue. This visual exit signal ensures clarity when a trade should be exited based on the trend reversal.
Justification for Combining EMAs and ATR in This Script:
The Exponential Moving Averages (EMAs) and Average True Range (ATR) serve complementary purposes in this script, enhancing each other’s functionality to provide a more complete trading system:
1. Trend Identification with EMAs:
• The combination of short and long EMAs is a widely trusted method for determining the trend direction. The crossovers between these EMAs provide clear entry signals for buy or sell trades. However, relying solely on EMAs can lead to false signals during periods of low volatility or market consolidation.
2. ATR for Volatility and Stop Loss:
• To prevent false signals during low-volatility conditions, the script uses ATR as a filter. This ensures that trades are only taken when the market has enough momentum, reducing the risk of being caught in “choppy” conditions where price action may be flat and untradeable.
• Additionally, the ATR-based trailing stop provides dynamic trade management, adjusting stop-loss levels according to the current volatility. This makes the system adaptive and prevents tight stops in volatile conditions or unnecessarily wide stops in calm markets.
3. Why They Work Together:
• The EMAs handle the trend direction, which is the foundation of the trading system, while the ATR adjusts the trade management to account for changing volatility. This means that the trader is always entering trades that are likely to follow a strong trend, while avoiding stagnant markets and using volatility-adaptive exit points.
• Without ATR, EMAs might generate signals during low-volatility periods that are unreliable. On the other hand, ATR alone wouldn’t provide a clear direction for trend-following. Together, these indicators create a balanced approach where trades are not only timely but also carefully managed.
How to Use:
• Buy Entry: Enter when the green triangle appears, indicating a bullish EMA crossover.
• Sell Entry: Enter short when the red triangle appears, indicating a bearish EMA crossover.
• Exit: Follow the orange background and blue “EXIT” label as a visual cue to exit the trade.
The combination of these tools allows traders to identify meaningful trend reversals while also managing risk dynamically, making the Arjunology for Stocks Indicator both versatile and effective for various market conditions.
Flexible Moving Average StrategyThis strategy offers flexibility to choose between SMA and EMA, and allows users to set the review frequency to Daily, Weekly, or Monthly. It adapts to different market conditions by providing full control over the length and timeframe of the Moving Average.
### Key Features:
- **Moving Average Method**: Select between SMA and EMA.
- **Review Frequency**: Choose Daily, Weekly, or Monthly review periods.
- **Customizable**: Set the Moving Average length and timeframe.
- **Entry/Exit Rules**:
- **Enter Long**: When the close price is above the Moving Average at the end of the period.
- **Exit**: When the close price falls below the Moving Average.
### Parameters:
- **Review Frequency**: Daily, Weekly, Monthly
- **Moving Average Method**: SMA or EMA
- **Length & Timeframe**: Fully adjustable
This strategy suits traders who prefer a flexible, trend-following approach based on long-term price movements.
EMA CheatsheetEMA Clouds Indicator: A Comprehensive Guide for Traders
The Exponential Moving Average (EMA) Clouds indicator is a dynamic tool designed to provide traders with visual cues about the current trend and potential shifts in market momentum. The EMA is a type of moving average that gives more weight to recent price data, making it highly responsive to price changes compared to a Simple Moving Average (SMA). When used in the form of clouds, EMAs are layered on top of each other to form a visual representation of bullish and bearish trends.
Understanding EMA Clouds
EMA Clouds consist of two or more EMAs, typically a short-term EMA (e.g., 9-period) and a longer-term EMA (e.g., 21-period). When these two EMAs are plotted together, they create a "cloud" between them. The interaction between these EMAs gives traders critical insights into the market's trend:
Bullish Clouds: When the shorter-term EMA crosses above the longer-term EMA, the market is considered to be in a bullish trend. This creates a green (or lighter colored) cloud between the EMAs, signaling upward momentum. Bullish clouds suggest that buyers are in control, and the price is likely to continue higher.
Bearish Clouds: Conversely, when the shorter-term EMA crosses below the longer-term EMA, the market is considered to be in a bearish trend. This forms a red (or darker colored) cloud between the EMAs, indicating downward momentum. Bearish clouds imply that sellers are dominating the market, and the price is likely to decline.
Key Components of the EMA Clouds Indicator:
Short-Term EMA: This is the fast-moving average (e.g., 9-period EMA) and reacts quickly to recent price changes. It’s used to detect short-term shifts in momentum.
Long-Term EMA: This is the slower-moving average (e.g., 21-period EMA), which smooths out price data over a longer period and identifies the general trend direction.
Cloud: The area between the short-term and long-term EMAs. When this cloud is green (bullish), it indicates that the short-term trend is stronger than the long-term trend. When the cloud turns red (bearish), it suggests that the short-term trend is weaker than the long-term trend.
Cloud Thickness: The thickness of the cloud provides additional information about the strength of the trend. A thicker cloud suggests strong price divergence between short and long-term trends, which could indicate a robust trend. A thinner cloud, on the other hand, may signal trend weakness or consolidation.
Precision Cloud by Dr ABIRAM SIVPRASAD
Precision Cloud by Dr. Abhiram Sivprasad"
The " Precision Cloud" script, created by Dr. Abhiram Sivprasad, is a multi-purpose technical analysis tool designed for Forex, Bitcoin, Commodities, Stocks, and Options trading. It focuses on identifying key levels of support and resistance, combined with moving averages (EMAs) and central pivot ranges (CPR), to help traders make informed trading decisions. The script also provides a visual "light system" to highlight potential long or short positions, aiding traders in entering trades with a clear strategy.
Key Features of the Script:
Central Pivot Range (CPR):
The CPR is calculated as the average of the high, low, and close of the price, while the top and bottom pivots are derived from it. These act as dynamic support and resistance zones.
The script can plot daily CPR, support, and resistance levels (S1/R1, S2/R2, S3/R3) as well as optional weekly and monthly pivot points.
The CPR helps identify whether the price is in a bullish, bearish, or neutral zone.
Support and Resistance Levels:
Three daily support (S1, S2, S3) and resistance (R1, R2, R3) levels are plotted based on the CPR.
These levels act as potential reversal or breakout points, allowing traders to make decisions around key price points.
EMA (Exponential Moving Averages):
The script includes two customizable EMAs (default periods of 9 and 21). You can choose the source for these EMAs (open, high, low, or close).
The crossovers between EMA1 and EMA2 help identify potential trend reversals or momentum shifts.
Lagging Span:
The Lagging Span is plotted with a customizable displacement (default 26), which helps identify overall trend direction by comparing past price with the current price.
Light System:
A color-coded table provides a visual representation of market conditions:
Green indicates bullish signals (e.g., price above CPR, EMAs aligning positively).
Red indicates bearish signals (e.g., price below CPR, EMAs aligning negatively).
Yellow indicates neutral conditions, where there is no clear trend direction.
The system includes lights for CPR, EMA, Long Position, and Short Position, helping traders quickly assess whether the market is in a buying or selling opportunity.
Trading Strategies Using the Script
1. Forex Trading:
Trend-Following with EMAs: Use the EMA crossovers to capture trending markets in Forex. A green light for the EMA combined with a price above the daily or weekly pivot levels suggests a buying opportunity. Conversely, if the EMA light turns red and price falls below the CPR levels, look for shorting opportunities.
Reversal Strategy: Watch for price action near the daily S1/R1 levels. If price holds above S1 and the EMA is green, this could signal a reversal from support. The same applies to resistance levels.
2. Bitcoin Trading:
Momentum Breakouts: Bitcoin is known for its sharp moves. The script helps to identify breakouts from the CPR range. If the price breaks above the TC (Top Central Pivot) with bullish EMA alignment (green light), it could signal a strong uptrend.
Lagging Span Confirmation: Use the Lagging Span to confirm the trend direction. For Bitcoin's volatility, when the lagging span shows consistent alignment with the price and CPR, it often indicates continuation of the trend.
3. Commodities Trading:
Support/Resistance Bounce: Commodities such as gold and oil often react well to pivot levels. Look for price bouncing off S1 or R1 for potential entry points. A green CPR light along with price above the pivot range supports a bullish bias.
EMA Pullback Strategy: If price moves in a strong trend and pulls back to one of the EMAs, a green EMA light suggests re-entry on a pullback. If the EMA light is red and price breaks below the BC (Bottom Central Pivot), short positions could be considered.
4. Stocks Trading:
Long Position Strategy: For stocks, use the combination of the long position light turning green (price above TC and EMA alignment) as a signal to buy. This could be especially useful for riding bullish trends in growth stocks or during earnings seasons when volatility is high.
Short Position Strategy: If the short position light turns green, indicating price below BC and EMAs turning bearish, this could be an ideal setup for shorting overvalued stocks or during market corrections.
5. Options Trading:
Directional Bias for Options: The light system is particularly helpful for options traders. A green long position light provides a clear signal to buy call options, while a green short position light supports buying puts.
Pivot Breakout Strategy: Buy options (calls or puts) when the price breaks above resistance or below support, with confirmation from the CPR and EMA lights. This helps capture the sharp moves required for profitable options trades.
Conclusion
The S&R Precision Cloud script is a versatile tool for traders across markets, including Forex, Bitcoin, Commodities, Stocks, and Options. It combines critical technical elements like pivot ranges, support and resistance levels, EMAs, and the Lagging Span to provide a clear picture of market conditions. The intuitive light system helps traders quickly assess whether to take a long or short position, making it an excellent tool for both new and experienced traders.
The S&R Precision Cloud by Dr. Abhiram Sivprasad script is a technical analysis tool designed to assist traders in making informed decisions. However, it should not be interpreted as financial or investment advice. The signals generated by the script are based on historical price data and technical indicators, which are inherently subject to market fluctuations and do not guarantee future performance.
Trading in Forex, Bitcoin, Commodities, Stocks, and Options carries a high level of risk and may not be suitable for all investors. You should be aware of the risks involved and be willing to accept them before engaging in such activities. Always conduct your own research and consult with a licensed financial advisor or professional before making any trading decisions.
The creators of this script are not responsible for any financial losses that may occur from its use. Past performance is not indicative of future results, and the use of this script is at your own risk.
AHR999 Bitcoin Buy/Sell Signals Indicator - Accurate Trading OppThis Pine Script indicator combines the AHR999 metric with Bitcoin's historical price trends to provide clear buy and sell signals, assisting you in making informed trading decisions at crucial moments. It calculates the AHR999 index based on Bitcoin's 200-day Geometric Moving Average (GMA) and the estimated price, offering customizable buy and sell thresholds for precise entry and exit points. Ideal for traders looking to capture long-term investment trends, this indicator helps you effectively identify Bitcoin market opportunities.
Sigma 2.0 - Advanced Buy and Sell Signal IndicatorOverview:
Sigma 2.0 is a sophisticated trading indicator designed to help traders identify potential buy and sell opportunities across various financial markets. By leveraging advanced mathematical calculations and incorporating multiple analytical tools, Sigma 2.0 aims to enhance trading strategies by providing precise entry and exit signals.
Key Features:
Advanced Sigma Calculations:
Utilizes a combination of Exponential Moving Averages (EMAs) and price deviations to calculate the Sigma lines (sigma1 and sigma2).
Detects potential trend reversals through the crossover of these Sigma lines.
Customizable Signal Filtering:
Offers the ability to filter buy and sell signals based on user-defined thresholds.
Helps reduce false signals in volatile markets by setting overbought and oversold levels.
Overbought and Oversold Detection:
Identifies extreme market conditions where price reversals are more likely.
Changes the background color of the chart to visually indicate overbought or oversold states.
Integration of Exponential Moving Averages (EMAs):
Includes EMAs of different lengths (10, 21, 55, 200) to assist in identifying market trends.
EMAs act as dynamic support and resistance levels.
Higher Timeframe Signal Incorporation:
Allows users to include signals from a higher timeframe to align trades with the broader market trend.
Enhances the reliability of signals by considering multiple timeframes.
Custom Alerts:
Provides alert conditions for both buy and sell signals.
Enables traders to receive notifications, ensuring timely decision-making.
How It Works:
Sigma Calculation Methodology:
The indicator calculates an average price (ap) and applies EMAs to derive the Sigma lines.
sigma1 represents the smoothed price deviation, while sigma2 is a moving average of sigma1.
A crossover of sigma1 above sigma2 generates a buy signal, indicating potential upward momentum.
Conversely, a crossover of sigma1 below sigma2 generates a sell signal.
Signal Filtering and Thresholds:
Users can enable filtering to only consider signals when sigma1 is below or above certain thresholds.
This helps in focusing on more significant market movements and reducing noise.
Overbought/Oversold Levels:
The indicator monitors sigma1 to detect when the market is in extreme conditions.
Background color changes provide a quick visual cue for these conditions.
EMA Analysis:
The plotted EMAs help in confirming the trend direction.
They can be used alongside Sigma signals to validate trade entries and exits.
Higher Timeframe Signals:
Incorporates signals from a user-selected higher timeframe.
Helps in aligning trades with the overall market trend, increasing the potential success rate.
How to Use:
Adding the Indicator to Your Chart:
Search for "Sigma 2.0" in the TradingView Indicators menu and add it to your chart.
Configuring the Settings:
Adjust the Sigma configurations (Channel Length, Average Length, Signal Line Length) to suit your trading style.
Set the overbought and oversold levels according to your risk tolerance.
Choose whether to filter signals by thresholds.
Select the higher timeframe for additional signal confirmation.
Interpreting the Signals:
Buy Signals:
Indicated by a green triangle below the price bar.
Occur when sigma1 crosses above sigma2 and other conditions are met.
Sell Signals:
Indicated by a red triangle above the price bar.
Occur when sigma1 crosses below sigma2 and other conditions are met.
Higher Timeframe Signals:
Plotted with lime (buy) and maroon (sell) triangles.
Help confirm signals in the current timeframe.
Utilizing EMAs:
Observe the EMAs to gauge the overall trend.
Consider aligning buy signals when the price is above key EMAs and sell signals when below.
Setting Up Alerts:
Use the built-in alert conditions to receive notifications for buy and sell signals.
Customize alert messages as needed.
Credits:
Original Concept Inspiration:
This indicator is inspired by the WaveTrend oscillator and other momentum-based indicators.
Special thanks to the original authors whose work laid the foundation for this enhanced version.
Disclaimer:
Trading involves significant risk, and past performance is not indicative of future results.
This indicator is a tool to assist in analysis and should not be the sole basis for any trading decision.
Always perform thorough analysis and consider multiple factors before entering a trade.
Note:
Ensure your chart is clean and only includes this indicator when publishing.
The script is open-source and can be modified to fit individual trading strategies.
For any questions or support, feel free to reach out or comment.
Hyperbolic Tangent Volatility Stop [InvestorUnknown]The Hyperbolic Tangent Volatility Stop (HTVS) is an advanced technical analysis tool that combines the smoothing capabilities of the Hyperbolic Tangent Moving Average (HTMA) with a volatility-based stop mechanism. This indicator is designed to identify trends and reversals while accounting for market volatility.
Hyperbolic Tangent Moving Average (HTMA):
The HTMA is at the heart of the HTVS. This custom moving average uses a hyperbolic tangent transformation to smooth out price fluctuations, focusing on significant trends while ignoring minor noise. The transformation reduces the sensitivity to sharp price movements, providing a clearer view of the underlying market direction.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by applying a non-linear transformation to the difference between the source price and its simple moving average, then adjusting it using the standard deviation of the price data. The result is a moving average that better tracks the real market direction.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
Volatility Stop (VolStop):
HTVS employs a Volatility Stop mechanism based on the Average True Range (ATR). This stop dynamically adjusts based on market volatility, ensuring that the indicator adapts to changing conditions and avoids false signals in choppy markets.
The VolStop follows the price, with a higher ATR pushing the stop farther away to avoid premature exits during volatile periods. Conversely, when volatility is low, the stop tightens to lock in profits as the trend progresses.
The ATR Length and ATR Multiplier are customizable, allowing traders to control how tightly or loosely the stop follows the price.
pine_volStop(src, atrlen, atrfactor) =>
if not na(src)
var max = src
var min = src
var uptrend = true
var float stop = na
atrM = nz(ta.atr(atrlen) * atrfactor, ta.tr)
max := math.max(max, src)
min := math.min(min, src)
stop := nz(uptrend ? math.max(stop, max - atrM) : math.min(stop, min + atrM), src)
uptrend := src - stop >= 0.0
if uptrend != nz(uptrend , true)
max := src
min := src
stop := uptrend ? max - atrM : min + atrM
Backtest Mode:
HTVS includes a built-in backtest mode, allowing traders to evaluate the indicator's performance on historical data. In backtest mode, it calculates the cumulative equity curve and compares it to a simple buy and hold strategy.
Backtesting features can be adjusted to focus on specific signal types, such as Long Only, Short Only, or Long & Short.
An optional Buy and Hold Equity plot provides insight into how the indicator performs relative to simply holding the asset over time.
The indicator includes a Hints Table, which provides useful recommendations on how to best display the indicator for different use cases. For example, when using the overlay mode, it suggests displaying the indicator in the same pane as price action, while backtest mode is recommended to be used in a separate pane for better clarity.
The Hyperbolic Tangent Volatility Stop offers traders a balanced approach to trend-following, using the robustness of the HTMA for smoothing and the adaptability of the Volatility Stop to avoid whipsaw trades during volatile periods. With its backtesting features and alert system, this indicator provides a comprehensive toolkit for active traders.
Hyperbolic Tangent SuperTrend [InvestorUnknown]The Hyperbolic Tangent SuperTrend (HTST) is designed for technical analysis, particularly in markets with assets that have lower prices or price ratios. This indicator leverages the Hyperbolic Tangent Moving Average (HTMA), a custom moving average calculated using the hyperbolic tangent function, to smooth price data and reduce the impact of short-term volatility.
Hyperbolic Tangent Moving Average (HTMA):
The indicator's core uses a hyperbolic tangent function to calculate a smoothed average of the price. The HTMA provides enhanced trend-following capabilities by dampening the impact of sharp price swings and maintaining a focus on long-term market movements.
The hyperbolic tangent function (tanh) is commonly used in mathematical fields like calculus, machine learning and signal processing due to its properties of “squashing” inputs into a range between -1 and 1. The function provides a non-linear transformation that can reduce the impact of extreme values while retaining a certain level of smoothness.
tanh(x) =>
e_x = math.exp(x)
e_neg_x = math.exp(-x)
(e_x - e_neg_x) / (e_x + e_neg_x)
The HTMA is calculated by taking the difference between the price and its simple moving average (SMA), applying a multiplier to control sensitivity, and then transforming it using the hyperbolic tangent function.
htma(src, len, mul) =>
tanh_src = tanh((src - ta.sma(src, len)) * mul) * ta.stdev(src, len) + ta.sma(src, len)
htma = ta.sma(tanh_src, len)
Important Note: The Hyperbolic Tangent function becomes less accurate with very high prices. For assets priced above 100,000, the results may deteriorate, and for prices exceeding 1 million, the function may stop functioning properly. Therefore, this indicator is better suited for assets with lower prices or lower price ratios.
SuperTrend Calculation:
In addition to the HTMA, the indicator includes an Average True Range (ATR)-based SuperTrend calculation, which helps identify uptrends and downtrends in the market. The SuperTrend is adjusted dynamically using the HTMA to avoid false signals in fast-moving markets.
The ATR period and multiplier are customizable, allowing users to fine-tune the sensitivity of the trend signals.
pine_supertrend(src, calc_price, atrPeriod, factor) =>
atr = ta.atr(atrPeriod)
upperBand = src + factor * atr
lowerBand = src - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or calc_price < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or calc_price > prevUpperBand ? upperBand : prevUpperBand
int _direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
_direction := 1
else if prevSuperTrend == prevUpperBand
_direction := calc_price > upperBand ? -1 : 1
else
_direction := calc_price < lowerBand ? 1 : -1
superTrend := _direction == -1 ? lowerBand : upperBand
Inbuilt Backtest Mode:
The HTST includes an inbuilt backtest mode that enables users to test the indicator's performance against historical data, similar to TradingView strategies.
The backtest mode allows you to compare the performance of different indicator settings with a simple buy and hold strategy to assess its effectiveness in different market conditions.
Hint Table for Display Modes:
The indicator includes a Hint Table that recommends the best pane to use for different display modes. For example, it suggests using the "Overlay" mode in the same pane as the price action, while the "Backtest Mode" is better suited for a separate pane. This ensures a more organized and clear visual experience.
The Hint Table appears as a small table at the bottom of the chart with easy-to-follow recommendations, ensuring the best setup for both visual clarity and indicator functionality.
With these features, the Hyperbolic Tangent SuperTrend Indicator offers traders a versatile and customizable tool for analyzing price trends while providing additional functionalities like backtesting and display mode hints for optimal usability.
Momentum Cloud.V33🌟 Introducing MomentumCloud.V33 🌟
MomentumCloud.V33 is a cutting-edge indicator designed to help traders capture market momentum with clarity and precision. This versatile tool combines moving averages, directional movement indexes (DMI), and volume analysis to provide real-time insights into trend direction and strength. Whether you’re a scalper, day trader, or swing trader, MomentumCloud.V33 adapts to your trading style and timeframe, making it an essential addition to your trading toolkit. 📈💡
🔧 Customizable Parameters:
• Moving Averages: Adjust the periods of the fast (MA1) and slow (MA2) moving averages to fine-tune your trend analysis.
• DMI & ADX: Customize the DMI length and ADX smoothing to focus on strong, actionable trends.
• Volume Multiplier: Modify the cloud thickness based on trading volume, emphasizing trends with significant market participation.
📊 Trend Detection:
• Color-Coded Clouds:
• Green Cloud: Indicates a strong uptrend, suggesting buying opportunities.
• Red Cloud: Indicates a strong downtrend, signaling potential short trades.
• Gray Cloud: Reflects a range-bound market, helping you avoid low-momentum periods.
• Dynamic Volume Integration: The cloud thickness adjusts dynamically with trading volume, highlighting strong trends supported by high market activity.
📈 Strength & Momentum Analysis:
• Strength Filtering: The ADX component ensures that only strong trends are highlighted, filtering out market noise and reducing false signals.
• Visual Momentum Gauge: The cloud color and thickness provide a quick visual representation of market momentum, enabling faster decision-making.
🔔 Alerts:
• Custom Alerts: Set up alerts for when the trend shifts or reaches critical levels, keeping you informed without needing to constantly monitor the chart.
🎨 Visual Enhancements:
• Gradient Cloud & Shadows: The indicator features a gradient-filled cloud with shadowed moving averages, enhancing both aesthetics and clarity on your charts.
• Adaptive Visual Cues: MomentumCloud.V33’s color transitions and dynamic thickness provide an intuitive feel for the market’s rhythm.
🚀 Quick Guide to Using MomentumCloud.V33
1. Add the Indicator: Start by adding MomentumCloud.V33 to your chart. Customize the settings such as MA periods, DMI length, and volume multiplier to match your trading style.
2. Analyze the Market: Observe the color-coded cloud and its thickness to gauge market momentum and trend direction. The thicker the cloud, the stronger the trend.
3. Set Alerts: Activate alerts for trend changes or key levels to capture trading opportunities without needing to watch the screen continuously.
⚙️ How It Works:
MomentumCloud.V33 calculates market momentum by combining moving averages, DMI, and volume. The cloud color changes based on the trend direction, while its thickness reflects the strength of the trend as influenced by trading volume. This integrated approach ensures you can quickly identify robust market movements, making it easier to enter and exit trades at optimal points.
Settings Overview:
• Moving Averages: Define the lengths for the fast and slow moving averages.
• DMI & ADX: Adjust the DMI length and ADX smoothing to focus on significant trends.
• Volume Multiplier: Customize the multiplier to control cloud thickness, highlighting volume-driven trends.
📚 How to Use MomentumCloud.V33:
• Trend Identification: The direction and color of the cloud indicate the prevailing trend, while the cloud’s thickness suggests the trend’s strength.
• Trade Execution: Use the green cloud to look for long entries and the red cloud for short positions. The gray cloud advises caution, as it represents a range-bound market.
• Alerts: Leverage the custom alerts to stay on top of market movements and avoid missing critical trading opportunities.
Unleash the power of trend and momentum analysis with MomentumCloud.V33! Happy trading! 📈🚀✨
Enhanced MACD and RSI Buy/Sell Signals - Created by Marco NucupKey Features:
EMA Filter: Adds an Exponential Moving Average (EMA) to filter signals based on the trend. Buys are only considered when the price is above the EMA, and sells when below it.
Customizable Inputs: Users can adjust parameters for EMA, MACD, and RSI directly from the TradingView interface, allowing for more personalized strategies.
Alerts: The script includes alert conditions for both buy and sell signals, enabling users to receive notifications.
Signal Plotting: Visual indicators for buy and sell signals on the chart, along with the EMA line for trend reference.
Multi-Step FlexiMA - Strategy [presentTrading]It's time to come back! hope I can not to be busy for a while.
█ Introduction and How It Is Different
The FlexiMA Variance Tracker is a unique trading strategy that calculates a series of deviations between the price (or another indicator source) and a variable-length moving average (MA). Unlike traditional strategies that use fixed-length moving averages, the length of the MA in this system varies within a defined range. The length changes dynamically based on a starting factor and an increment factor, creating a more adaptive approach to market conditions.
This strategy integrates Multi-Step Take Profit (TP) levels, allowing for partial exits at predefined price increments. It enables traders to secure profits at different stages of a trend, making it ideal for volatile markets where taking full profits at once might lead to missed opportunities if the trend continues.
BTCUSD 6hr Performance
█ Strategy, How It Works: Detailed Explanation
🔶 FlexiMA Concept
The FlexiMA (Flexible Moving Average) is at the heart of this strategy. Unlike traditional MA-based strategies where the MA length is fixed (e.g., a 50-period SMA), the FlexiMA varies its length with each iteration. This is done using a **starting factor** and an **increment factor**.
The formula for the moving average length at each iteration \(i\) is:
`MA_length_i = indicator_length * (starting_factor + i * increment_factor)`
Where:
- `indicator_length` is the user-defined base length.
- `starting_factor` is the initial multiplier of the base length.
- `increment_factor` increases the multiplier in each iteration.
Each iteration applies a **simple moving average** (SMA) to the chosen **indicator source** (e.g., HLC3) with a different length based on the above formula. The deviation between the current price and the moving average is then calculated as follows:
`deviation_i = price_current - MA_i`
These deviations are normalized using one of the following methods:
- **Max-Min normalization**:
`normalized_i = (deviation_i - min(deviations)) / range(deviations)`
- **Absolute Sum normalization**:
`normalized_i = deviation_i / sum(|deviation_i|)`
The **median** and **standard deviation (stdev)** of the normalized deviations are then calculated as follows:
`median = median(normalized deviations)`
For the standard deviation:
`stdev = sqrt((1/(N-1)) * sum((normalized_i - mean)^2))`
These values are plotted to provide a clear indication of how the price is deviating from its variable-length moving averages.
For more detail:
🔶 Multi-Step Take Profit
This strategy uses a multi-step take profit system, allowing for exits at different stages of a trade based on the percentage of price movement. Three take-profit levels are defined:
- Take Profit Level 1 (TP1): A small, quick profit level (e.g., 2%).
- Take Profit Level 2 (TP2): A medium-level profit target (e.g., 8%).
- Take Profit Level 3 (TP3): A larger, more ambitious target (e.g., 18%).
At each level, a corresponding percentage of the trade is exited:
- TP Percent 1: E.g., 30% of the position.
- TP Percent 2: E.g., 20% of the position.
- TP Percent 3: E.g., 15% of the position.
This approach ensures that profits are locked in progressively, reducing the risk of market reversals wiping out potential gains.
Local
🔶 Trade Entry and Exit Conditions
The entry and exit signals are determined by the interaction between the **SuperTrend Polyfactor Oscillator** and the **median** value of the normalized deviations:
- Long entry: The SuperTrend turns bearish, and the median value of the deviations is positive.
- Short entry: The SuperTrend turns bullish, and the median value is negative.
Similarly, trades are exited when the SuperTrend flips direction.
* The SuperTrend Toolkit is made by @EliCobra
█ Trade Direction
The strategy allows users to specify the desired trade direction:
- Long: Only long positions will be taken.
- Short: Only short positions will be taken.
- Both: Both long and short positions are allowed based on the conditions.
This flexibility allows the strategy to adapt to different market conditions and trading styles, whether you're looking to buy low and sell high, or sell high and buy low.
█ Usage
This strategy can be applied across various asset classes, including stocks, cryptocurrencies, and forex. The primary use case is to take advantage of market volatility by using a flexible moving average and multiple take-profit levels to capture profits incrementally as the market moves in your favor.
How to Use:
1. Configure the Inputs: Start by adjusting the **Indicator Length**, **Starting Factor**, and **Increment Factor** to suit your chosen asset. The defaults work well for most markets, but fine-tuning them can improve performance.
2. Set the Take Profit Levels: Adjust the three **TP levels** and their corresponding **percentages** based on your risk tolerance and the expected volatility of the market.
3. Monitor the Strategy: The SuperTrend and the FlexiMA variance tracker will provide entry and exit signals, automatically managing the positions and taking profits at the pre-set levels.
█ Default Settings
The default settings for the strategy are configured to provide a balanced approach that works across different market conditions:
Indicator Length (10):
This controls the base length for the moving average. A lower length makes the moving average more responsive to price changes, while a higher length smooths out fluctuations, making the strategy less sensitive to short-term price movements.
Starting Factor (1.0):
This determines the initial multiplier applied to the moving average length. A higher starting factor will increase the average length, making it slower to react to price changes.
Increment Factor (1.0):
This increases the moving average length in each iteration. A larger increment factor creates a wider range of moving average lengths, allowing the strategy to track both short-term and long-term trends simultaneously.
Normalization Method ('None'):
Three methods of normalization can be applied to the deviations:
- None: No normalization applied, using raw deviations.
- Max-Min: Normalizes based on the range between the maximum and minimum deviations.
- Absolute Sum: Normalizes based on the total sum of absolute deviations.
Take Profit Levels:
- TP1 (2%): A quick exit to capture small price movements.
- TP2 (8%): A medium-term profit target for stronger trends.
- TP3 (18%): A long-term target for strong price moves.
Take Profit Percentages:
- TP Percent 1 (30%): Exits 30% of the position at TP1.
- TP Percent 2 (20%): Exits 20% of the position at TP2.
- TP Percent 3 (15%): Exits 15% of the position at TP3.
Effect of Variables on Performance:
- Short Indicator Lengths: More responsive to price changes but prone to false signals.
- Higher Starting Factor: Slows down the response, useful for longer-term trend following.
- Higher Increment Factor: Widens the variability in moving average lengths, making the strategy adapt to both short-term and long-term price trends.
- Aggressive Take Profit Levels: Allows for quick profit-taking in volatile markets but may exit positions prematurely in strong trends.
The default configuration offers a moderate balance between short-term responsiveness and long-term trend capturing, suitable for most traders. However, users can adjust these variables to optimize performance based on market conditions and personal preferences.
