WaridTR15 Dakika ve Üzeri Periyotlar İçin Önerilen Ayarlar:
EMA Uzunlukları:
Kısa EMA: 9 yerine 12 veya 14 kullanılabilir.
Uzun EMA: 21 yerine 26 veya 50 kullanılabilir.
Golden Cross için 50 EMA ve 200 EMA zaten uzun vadeli trendleri yakalar, bu nedenle değiştirmeye gerek yok.
RSI Uzunluğu:
RSI uzunluğu 14 yerine 21 veya 28 yapılabilir. Bu, daha uzun vadeli aşırı alım/aşırı satım bölgelerini daha doğru tespit eder.
Volume Filtresi:
Volume ortalaması için 20 periyot yerine 50 veya 100 periyot kullanılabilir. Bu, daha uzun vadeli hacim eğilimlerini yakalar.
Ichimoku Parametreleri:
Ichimoku, varsayılan olarak 9-26-52 periyotlarıyla çalışır. Bu, zaten uzun vadeli trendleri yakalamak için uygundur. Ancak, daha uzun periyotlar için:
Tenkan-Sen: 9 yerine 14.
Kijun-Sen: 26 yerine 52.
Senkou Span B: 52 yerine 104.
Поиск скриптов по запросу "跨境通12月4日地天板"
Volume HighlightBar colouring: this indicator is simple but effective, it repaints higher than normal candles a certain colour (by default gold/yellow) it helps to know what are valuable areas to trade around for longs and shorts.
Changing the volume multiplier manually helps you to screen volume relevant to the timeframe you are trading on.
For example, some charts 1min the best filter/setting would be 12-35 multiplier where others like btc 1-4 hourly, the filter/setting might be 8-12.
The key is having only the highest/most relevant 3-4 volume candles showing as they often represent supports and resistances.
Bollinger Bounce Reversal Strategy – Visual EditionOverview:
The Bollinger Bounce Reversal Strategy – Visual Edition is designed to capture potential reversal moves at price extremes—often termed “bounce points”—by using a combination of technical indicators. The strategy integrates Bollinger Bands, MACD, and volume analysis, and it provides rich on‑chart visual cues to help traders understand its signals and conditions. Additionally, the strategy enforces a maximum of 5 trades per day and uses fixed risk management parameters. This publication is intended for educational purposes and offers a systematic, transparent approach that you can further adjust to fit your market or risk profile.
How It Works:
Bollinger Bands:
A 20‑period simple moving average (SMA) and a user‑defined standard deviation multiplier (default 2.0) are used to calculate the Bollinger Bands.
When the price reaches or crosses these bands (i.e. falls below the lower band or rises above the upper band), it suggests that the price is in an extreme, potentially oversold or overbought, state.
MACD Filter:
The MACD (calculated with standard lengths, e.g. 12, 26, 9) provides momentum information.
For a bullish (long) signal, the MACD line should be above its signal line; for a bearish (short) signal, the MACD line should be below.
Volume Confirmation:
The strategy uses a 20‑period volume moving average to determine if current volume is strong enough to validate a signal.
A signal is confirmed only if the current volume is at or above a specified multiple (by default, 1.0×) of this moving average, ensuring that the move is supported by increased market participation.
Visual Cues:
Bollinger Bands and Fill: The basis (SMA), upper, and lower Bollinger Bands are plotted, and the area between the upper and lower bands is filled with a semi‑transparent color.
Signal Markers: When a long or short signal is generated, corresponding markers (labels) appear on the chart.
Background Coloring: The chart’s background changes color (green for long signals and red for short signals) on the bars where signals occur.
Information Table: An on‑chart table displays key indicator values (MACD, signal line, volume, average volume) and the number of trades executed that day.
Entry Conditions:
Long Entry:
A long trade is triggered when the previous bar’s close is below the lower Bollinger Band and the current bar’s close crosses above it, combined with a bullish MACD condition and strong volume.
Short Entry:
A short trade is triggered when the previous bar’s close is above the upper Bollinger Band and the current bar’s close crosses below it, with a bearish MACD condition and high volume.
Risk Management:
Daily Trade Limit: The strategy restricts trading to no more than 5 trades per day.
Stop-Loss and Take-Profit:
For each position, a stop loss is set at a fixed percentage away from the entry price (typically 2%), and a take profit is set to target a 1:2 risk-reward ratio (typically 4% from the entry price).
Backtesting Setup:
Initial Capital: $10,000
Commission: 0.1% per trade
Slippage: 1 tick per bar
These realistic parameters help ensure that backtesting results reflect the conditions of an average trader.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential to backtest extensively and paper trade before any live deployment. All risk management practices are advisory, and you should adjust parameters to suit your own trading style and risk tolerance.
Conclusion:
By combining Bollinger Bands, MACD, and volume analysis, the Bollinger Bounce Reversal Strategy – Visual Edition provides a clear, systematic method to identify potential reversal opportunities at price extremes. The added visual cues help traders quickly interpret signals and assess market conditions, while strict risk management and a daily trade cap help keep trading disciplined. Adjust and refine the settings as needed to better suit your specific market and risk profile.
Opening ScoreOverview:
The Composite Open Strategy Indicator is designed to provide traders with a unified, early-session directional bias by aggregating multiple non-correlated signals. By combining diverse analytical methods—spanning price action, volume, volatility, and time—the indicator helps you gauge whether the market is leaning bullish or bearish during the critical opening hours.
How It Works:
• Open Range Breakout (ORB) Signal:
The indicator captures the opening range (defined up to a user-specified time, e.g., 9:45 AM ET) and assigns a bullish signal when the price breaks above the high of that range, and a bearish signal when it drops below the low.
• VWAP Signal:
It compares the current price to the Volume Weighted Average Price (VWAP). A price above VWAP suggests buying pressure, while below indicates selling pressure.
• Trend Signal:
Using a simple moving average (with an adjustable period, typically around 20 bars), the indicator determines the prevailing trend. Price above the MA contributes a bullish bias, and price below contributes a bearish bias.
• Volatility Signal:
A volatility filter is applied via the Average True Range (ATR). An increasing ATR relative to the previous bar suggests rising volatility (bullish if combined with upward moves), whereas a decreasing ATR indicates the opposite.
Each of these four signals is assigned an equal weight (modifiable as needed), and their sum forms the composite score.
Display and Timing:
• Separate Panel:
The composite score is plotted as a histogram in its own indicator panel, ensuring your main price chart remains uncluttered.
• Session Filter:
The indicator is active only during the early session—from 9:30 AM to 12:30 PM Eastern Time—when the initial directional move is most relevant. Outside this time window, the indicator remains inactive.
Trading Insights:
• A positive composite score suggests a bullish bias, indicating that the aggregated signals lean toward an upward trend.
• A negative composite score points to a bearish bias, indicating a downward directional outlook.
Usage:
Ideal for traders looking to capture the market’s early trend direction, this indicator can be used as part of a broader strategy. Its design encourages consistency by combining multiple perspectives (price, volume, volatility, time) into one clear signal, allowing you to focus on setups that align with the dominant early-session move.
Before fully automating your trading approach, you can test and refine this composite method on TradingView using the built-in manual review process. Once confident in its performance, further automation can help integrate this directional bias seamlessly into your overall trading strategy.
4Hour Zone SeparatorThis custom TradingView indicator draws vertical lines on your chart to visually separate the 4-hour trading zones within a single trading day. The indicator helps traders identify key time intervals throughout the day for better market analysis and decision-making.
Features:
• Time-Based Zones: The indicator divides the day into six distinct 4-hour periods, starting from midnight (00:00) and continuing every 4 hours. Each zone is marked by a vertical line on the chart.
• User Customization: You can toggle the visibility of the lines for each 4-hour period (00:00, 04:00, 08:00, 12:00, 16:00, 20:00) based on your preference. This allows you to focus on specific zones that matter most for your analysis.
• Line Styling Options: Choose from three different line styles — Solid, Dashed, or Dotted — and adjust the thickness to your desired preference.
• Dynamic Time Adjustment: The indicator automatically adjusts for the time zone, ensuring that the 00:00 timestamp reflects the correct start of the day based on your chart’s time zone.
How It Works:
1. The indicator starts by calculating the beginning of the day at 00:00, then it sequentially places vertical lines every 4 hours.
2. Each line is color-coded for easy identification, and the lines stretch from the highest to the lowest point on the chart for that range.
3. The lines are drawn only when the chart enters a new 4-hour zone.
This tool is especially useful for day traders who want to track price action during specific times of the day and make informed decisions based on market behavior within each 4-hour period.
Arpeet MACDOverview
This strategy is based on the zero-lag version of the MACD (Moving Average Convergence Divergence) indicator, which captures short-term trends by quickly responding to price changes, enabling high-frequency trading. The strategy uses two moving averages with different periods (fast and slow lines) to construct the MACD indicator and introduces a zero-lag algorithm to eliminate the delay between the indicator and the price, improving the timeliness of signals. Additionally, the crossover of the signal line and the MACD line is used as buy and sell signals, and alerts are set up to help traders seize trading opportunities in a timely manner.
Strategy Principle
Calculate the EMA (Exponential Moving Average) or SMA (Simple Moving Average) of the fast line (default 12 periods) and slow line (default 26 periods).
Use the zero-lag algorithm to double-smooth the fast and slow lines, eliminating the delay between the indicator and the price.
The MACD line is formed by the difference between the zero-lag fast line and the zero-lag slow line.
The signal line is formed by the EMA (default 9 periods) or SMA of the MACD line.
The MACD histogram is formed by the difference between the MACD line and the signal line, with blue representing positive values and red representing negative values.
When the MACD line crosses the signal line from below and the crossover point is below the zero axis, a buy signal (blue dot) is generated.
When the MACD line crosses the signal line from above and the crossover point is above the zero axis, a sell signal (red dot) is generated.
The strategy automatically places orders based on the buy and sell signals and triggers corresponding alerts.
Advantage Analysis
The zero-lag algorithm effectively eliminates the delay between the indicator and the price, improving the timeliness and accuracy of signals.
The design of dual moving averages can better capture market trends and adapt to different market environments.
The MACD histogram intuitively reflects the comparison of bullish and bearish forces, assisting in trading decisions.
The automatic order placement and alert functions make it convenient for traders to seize trading opportunities in a timely manner, improving trading efficiency.
Risk Analysis
In volatile markets, frequent crossover signals may lead to overtrading and losses.
Improper parameter settings may cause signal distortion and affect strategy performance.
The strategy relies on historical data for calculations and has poor adaptability to sudden events and black swan events.
Optimization Direction
Introduce trend confirmation indicators, such as ADX, to filter out false signals in volatile markets.
Optimize parameters to find the best combination of fast and slow line periods and signal line periods, improving strategy stability.
Combine other technical indicators or fundamental factors to construct a multi-factor model, improving risk-adjusted returns of the strategy.
Introduce stop-loss and take-profit mechanisms to control single-trade risk.
Summary
The MACD Dual Crossover Zero Lag Trading Strategy achieves high-frequency trading by quickly responding to price changes and capturing short-term trends. The zero-lag algorithm and dual moving average design improve the timeliness and accuracy of signals. The strategy has certain advantages, such as intuitive signals and convenient operation, but also faces risks such as overtrading and parameter sensitivity. In the future, the strategy can be optimized by introducing trend confirmation indicators, parameter optimization, multi-factor models, etc., to improve the robustness and profitability of the strategy.
Classic Nacked Z-Score ArbitrageThe “Classic Naked Z-Score Arbitrage” strategy employs a statistical arbitrage model based on the Z-score of the price spread between two assets. This strategy follows the premise of pair trading, where two correlated assets, typically from the same market sector, are traded against each other to profit from relative price movements (Gatev, Goetzmann, & Rouwenhorst, 2006). The approach involves calculating the Z-score of the price spread between two assets to determine market inefficiencies and capitalize on short-term mispricing.
Methodology
Price Spread Calculation:
The strategy calculates the spread between the two selected assets (Asset A and Asset B), typically from different sectors or asset classes, on a daily timeframe.
Statistical Basis – Z-Score:
The Z-score is used as a measure of how far the current price spread deviates from its historical mean, using the standard deviation for normalization.
Trading Logic:
• Long Position:
A long position is initiated when the Z-score exceeds the predefined threshold (e.g., 2.0), indicating that Asset A is undervalued relative to Asset B. This signals an arbitrage opportunity where the trader buys Asset B and sells Asset A.
• Short Position:
A short position is entered when the Z-score falls below the negative threshold, indicating that Asset A is overvalued relative to Asset B. The strategy involves selling Asset B and buying Asset A.
Theoretical Foundation
This strategy is rooted in mean reversion theory, which posits that asset prices tend to return to their long-term average after temporary deviations. This form of arbitrage is widely used in statistical arbitrage and pair trading techniques, where investors seek to exploit short-term price inefficiencies between two assets that historically maintain a stable price relationship (Avery & Sibley, 2020).
Further, the Z-score is an effective tool for identifying significant deviations from the mean, which can be seen as a signal for the potential reversion of the price spread (Braucher, 2015). By capturing these inefficiencies, traders aim to profit from convergence or divergence between correlated assets.
Practical Application
The strategy aligns with the Financial Algorithmic Trading and Market Liquidity analysis, emphasizing the importance of statistical models and efficient execution (Harris, 2024). By utilizing a simple yet effective risk-reward mechanism based on the Z-score, the strategy contributes to the growing body of research on market liquidity, asset correlation, and algorithmic trading.
The integration of transaction costs and slippage ensures that the strategy accounts for practical trading limitations, helping to refine execution in real market conditions. These factors are vital in modern quantitative finance, where liquidity and execution risk can erode profits (Harris, 2024).
References
• Gatev, E., Goetzmann, W. N., & Rouwenhorst, K. G. (2006). Pairs Trading: Performance of a Relative-Value Arbitrage Rule. The Review of Financial Studies, 19(3), 1317-1343.
• Avery, C., & Sibley, D. (2020). Statistical Arbitrage: The Evolution and Practices of Quantitative Trading. Journal of Quantitative Finance, 18(5), 501-523.
• Braucher, J. (2015). Understanding the Z-Score in Trading. Journal of Financial Markets, 12(4), 225-239.
• Harris, L. (2024). Financial Algorithmic Trading and Market Liquidity: A Comprehensive Analysis. Journal of Financial Engineering, 7(1), 18-34.
Wagmi Lab- Bitcoin H4 Buy Sell Signals This indicator, designed primarily for Bitcoin on the H4 timeframe, is a versatile tool that can also be applied to other assets and timeframes by adjusting its parameters. It combines Exponential Moving Averages (EMAs), MACD (Moving Average Convergence Divergence), and a crossover filtering mechanism to generate reliable buy and sell signals. The indicator is ideal for traders looking to identify trend direction and potential entry/exit points with added precision.
Key Features:
Customizable EMAs and MACD:
Fast EMA (default: 12): Tracks short-term price momentum.
Slow EMA (default: 26): Tracks long-term price momentum.
Signal SMA (default: 9): Smooths the MACD line to generate the signal line.
MACD Crossover Signals:
The indicator calculates the MACD line and signal line to identify potential buy and sell opportunities.
Buy signals are generated when the MACD line crosses above the signal line, indicating bullish momentum.
Sell signals are generated when the MACD line crosses below the signal line, indicating bearish momentum.
Crossover Strength Filter:
A minimum crossover distance percentage (default: 0.1%) ensures that only significant crossovers are considered, reducing false signals.
This filter helps traders avoid weak or insignificant crossovers that may not lead to strong price movements.
Trend Visualization:
The indicator highlights the trend direction by filling the area between the fast and slow EMAs with colors:
Green: Uptrend (MACD > Signal Line).
Red: Downtrend (MACD < Signal Line).
Buy/Sell Signal Markers:
Buy signals are marked with green circles below the price bars.
Sell signals are marked with red circles above the price bars.
These markers provide clear visual cues for potential entry and exit points.
Adaptable to Other Timeframes and Assets:
While optimized for the H4 timeframe, the indicator can be adjusted for other timeframes (e.g., M15, H1, D1) by modifying the EMA and SMA settings.
It can also be applied to other assets, such as stocks, forex, or commodities, by tweaking the parameters to suit the asset's volatility and characteristics.
How to Use:
Identify Trends:
Use the colored areas (green for uptrend, red for downtrend) to determine the overall market direction.
Wait for Confirmation:
Look for buy or sell signals (green or red circles) that align with the trend direction.
Ensure the crossover meets the minimum distance requirement to filter out weak signals.
Enter and Exit Trades:
Enter a long position when a buy signal appears during an uptrend.
Enter a short position or exit a long position when a sell signal appears during a downtrend.
Adjust Settings for Other Timeframes/Assets:
Experiment with the EMA and SMA periods to optimize the indicator for different timeframes or assets.
Why Use This Indicator?
Precision: The crossover strength filter reduces noise and false signals.
Versatility: Works across multiple timeframes and assets with customizable settings.
Visual Clarity: Clear trend visualization and signal markers make it easy to interpret.
This indicator is a powerful tool for traders seeking to capitalize on Bitcoin's volatility or other assets' price movements, providing a structured approach to identifying trends and potential trading opportunities.
Gold Pro StrategyHere’s the strategy description in a chat format:
---
**Gold (XAU/USD) Trend-Following Strategy**
This **trend-following strategy** is designed for trading gold (XAU/USD) by combining moving averages, MACD momentum indicators, and RSI filters to capture sustained trends while managing volatility risks. The strategy uses volatility-adjusted stops to protect gains and prevent overexposure during erratic price movements. The aim is to take advantage of trending markets by confirming momentum and ensuring entries are not made at extreme levels.
---
**Key Components**
1. **Trend Identification**
- **50 vs 200 EMA Crossover**
- **Bullish Trend:** 50 EMA crosses above 200 EMA, and the price closes above the 200 EMA
- **Bearish Trend:** 50 EMA crosses below 200 EMA, and the price closes below the 200 EMA
2. **Momentum Confirmation**
- **MACD (12,26,9)**
- **Buy Signal:** MACD line crosses above the signal line
- **Sell Signal:** MACD line crosses below the signal line
- **RSI (14 Period)**
- **Bullish Zone:** RSI between 50-70 to avoid overbought conditions
- **Bearish Zone:** RSI between 30-50 to avoid oversold conditions
3. **Entry Criteria**
- **Long Entry:** Bullish trend, MACD bullish crossover, and RSI between 50-70
- **Short Entry:** Bearish trend, MACD bearish crossover, and RSI between 30-50
4. **Exit & Risk Management**
- **ATR Trailing Stops (14 Period):**
- Initial Stop: 3x ATR from entry price
- Trailing Stop: Adjusts to lock in profits as price moves favorably
- **Position Sizing:** 100% of equity per trade (high-risk strategy)
---
**Key Logic Flow**
1. **Trend Filter:** Use the 50/200 EMA relationship to define the market's direction
2. **Momentum Confirmation:** Confirm trend momentum with MACD crossovers
3. **RSI Validation:** Ensure RSI is within non-extreme ranges before entering trades
4. **Volatility-Based Risk Management:** Use ATR stops to manage market volatility
---
**Visual Cues**
- **Blue Line:** 50 EMA
- **Red Line:** 200 EMA
- **Green Triangles:** Long entry signals
- **Red Triangles:** Short entry signals
---
**Strengths**
- **Clear Trend Focus:** Avoids counter-trend trades
- **RSI Filter:** Prevents entering overbought or oversold conditions
- **ATR Stops:** Adapts to gold’s inherent volatility
- **Simple Rules:** Easy to follow with minimal inputs
---
**Weaknesses & Risks**
- **Infrequent Signals:** 50/200 EMA crossovers are rare
- **Potential Missed Opportunities:** Strict RSI criteria may miss some valid trends
- **Aggressive Position Sizing:** 100% equity allocation can lead to large drawdowns
- **No Profit Targets:** Relies on trailing stops rather than defined exit targets
---
**Performance Profile**
| Metric | Expected Range |
|----------------------|---------------------|
| Annual Trades | 4-8 |
| Win Rate | 55-65% |
| Max Drawdown | 25-35% |
| Profit Factor | 1.8-2.5 |
---
**Optimization Recommendations**
1. **Increase Trade Frequency**
Adjust the EMAs to shorter periods:
- `emaFastLen = input.int(30, "Fast EMA")`
- `emaSlowLen = input.int(150, "Slow EMA")`
2. **Relax RSI Filters**
Adjust the RSI range to:
- `rsiBullish = rsi > 45 and rsi < 75`
- `rsiBearish = rsi < 55 and rsi > 25`
3. **Add Profit Targets**
Introduce a profit target at 1.5% above entry:
```pine
strategy.exit("Long Exit", "Long",
stop=longStopPrice,
profit=close*1.015, // 1.5% target
trail_offset=trailOffset)
```
4. **Reduce Position Sizing**
Risk a smaller percentage per trade:
- `default_qty_value=25`
---
**Best Use Case**
This strategy excels in **strong trending markets** such as gold rallies during economic or geopolitical crises. However, during sideways or choppy market conditions, the strategy might require manual intervention to avoid false signals. Additionally, integrating fundamental analysis—like monitoring USD weakness or geopolitical risks—can enhance its effectiveness.
---
This strategy offers a balanced approach for trading gold, combining trend-following principles with risk management tailored to the volatility of the market.
Enhanced Volume Profile█ OVERVIEW
The Enhanced Volume Profile (EVP) is an indicator designed to plot a volume profile on the chart based on either the visible chart range or a fixed lookback period. The script helps analyze the distribution of volume at different price levels over time, providing insights into areas of high trading activity and potential support/resistance zones.
█ KEY FEATURES
1. Visible Chart Range vs. Fixed Lookback Depth
Visible Chart Range
- Default analysis mode
- Calculates profile based on visible portion of the chart
- Dynamically updates with chart view changes
Fixed Lookback Depth
- Optional alternative to visible range
- Uses specified number of bars (10-3000)
- Provides consistent analysis depth
- Independent of chart view
2. Custom Resolution
Auto-Resolution Mode
Automatically selects timeframes based on chart's current timeframe:
≤ 1 minute: Uses 1-minute resolution
≤ 5 minutes: Uses 1-minute resolution
≤ 15 minutes: Uses 5-minute resolution
≤ 1 hour: Uses 5-minute resolution
≤ 4 hours: Uses 15-minute resolution
≤ 12 hours: Uses 15-minute resolution
≤ 1 day: Uses 1-hour resolution
≤ 3 days: Uses 2-hours resolution
≤ 1 week: Uses 4-hours resolution
Custom Resolution Override
Optional override of auto-resolution system
Provides control over data granularity
Must be lower than or equal to chart's timeframe
Falls back to auto-resolution if validation fails
3. Volume Profile Resolution
Adjustable number of points (10-400)
Controls profile granularity
Higher resolution provides more detail
Balance between precision and performance
4. Point of Control (PoC)
Identifies price level with highest traded volume
Optional display with customizable appearance
Adjustable line thickness (1-30)
Configurable color
5. Value Area (VA)
Shows price range of majority trading volume
Adjustable coverage (5-95%), default is 68%
Customizable boundary lines
Configurable lines color and thickness (1-20)
█ INPUT PARAMETERS
Lookback Settings
Use Visible Chart Range
- Default: true
- Calculates profile based on visible bars
- Ideal for focused analysis
Fixed Lookback Bars
- Range: 10-3000
- Default: 200
- Used when visible range is disabled
Resolution Settings
Enable Custom Resolution
- Default: false
- Overrides auto-resolution
Custom Resolution
- Default: 1-minute
- Changes automatically when "Enable Custom Resolution" is disabled
Volume Profile Appearance
Profile Resolution
- Range: 10-400
- Default: 200
- Controls detail level
Profile Width Scale
- Range: 1-50
- Default: 15
- Adjusts profile width
Right Offset
- Range: 0-500
- Default: 20
- Controls spacing from price bars
Profile Fill Color
- Default: #5D606B (70% transparency)
Point of Control Settings
Show Point of Control
- Default: true
- Toggles PoC visibility
PoC Line Thickness
- Range: 1-30
- Default: 1
PoC Line Color
- Default: Red
Value Area Settings
Show Value Area
- Default: true
- Toggles VA lines
Value Area Coverage
- Range: 5-95%
- Default: 68%
Value Area Line Color
- Default: Blue
Value Area Line Thickness
- Range: 1-20
- Default: 1
█ TECHNICAL IMPLEMENTATION DETAILS
Exceeding Bars Management
The script dynamically adjusts the number of bars used in the volume profile calculation based on the selected timeframe and the maximum allowed bars (max_bars_back).
If the total number of bars exceeds the predefined threshold (6000 bars), the script reduces the lookback period (lookback_bars) by trimming some of the historical data, ensuring the chart does not become overloaded with data.
The adjustment is made based on the ratio of bars per candle (bars_per_candle), ensuring that the volume profile remains computationally efficient while maintaining its relevance.
█ EXAMPLE USE CASES
1. Visible Range Mode
For analyzing a recent trend and focusing on only the visible part of the chart, enabling the "Use Visible Chart Range" option calculates the profile based on the current view, without considering historical data outside the visible area.
2. Fixed Lookback Depth
For analyzing a specific period in the past (e.g., the last 200 bars), disabling the visible range and setting a fixed lookback depth of 200 bars ensures the profile always considers the last 200 bars, regardless of the visible range.
3. Custom Resolution
If there’s a need for greater control over the timeframe used for volume profile calculations (e.g., using a 5-minute resolution on a 15-minute chart), enabling custom resolution and setting the desired timeframe provides this control.
HAPPY TRADING ✌️
Breakout Josip strategy is focused on analyzing price movements during specific time intervals (from 9:00 AM to 12:00 PM) each day. It tracks the highest and lowest prices in that period and uses them to set targets for potential trades, placing horizontal lines based on these levels. Additionally, you're interested in tracking the success and failure of trades based on whether price breaks certain levels during this time range. The strategy also calculates various metrics like the percentage of successful trades, failed trades, and total trades during a selected time range.
Multi Timeframe MAsThis Pine Script indicator, titled "Multi Timeframe MAs," allows you to plot Exponential Moving Averages (EMAs) or Simple Moving Averages (SMAs) from multiple timeframes on a single chart. This helps traders and analysts visualize and compare different moving averages across various timeframes without having to switch between charts.
Key Features:
Multiple Timeframes:
The script supports six different timeframes, ranging from minutes to weekly intervals.
Users can input their desired timeframes, including custom settings such as "60" (60 minutes), "D" (daily), and "W" (weekly).
Moving Average Types:
Users can choose between Exponential Moving Averages (EMA) and Simple Moving Averages (SMA) for each timeframe.
The script utilizes a ternary operator to determine whether to calculate an EMA or an SMA based on user input.
Customizable Periods:
Each moving average can have a different period, allowing for flexibility in analysis.
The default periods are set to commonly used values (e.g., 15, 20, 5, 12).
Visibility Controls:
Users can toggle the visibility of each moving average line, enabling or disabling them as needed.
This feature helps declutter the chart when specific moving averages are not required.
Black Stepped Lines:
All moving averages are plotted as black, stepped lines to provide a clear and consistent visual representation.
This makes it easy to distinguish these lines from other elements on the chart.
Example Use Cases:
Trend Analysis: Compare short-term and long-term trends by visualizing moving averages from different timeframes on a single chart.
Support and Resistance Levels: Identify key support and resistance levels across multiple timeframes.
Cross-Timeframe Strategy: Develop and test trading strategies that rely on the confluence of moving averages from different timeframes.
This script offers a powerful tool for traders and analysts who want to gain deeper insights into market movements by examining moving averages across multiple timeframes. With its customizable settings and user-friendly interface, it provides a versatile solution for a wide range of trading and analytical needs.
Currency ComparatorIndicator Description
This script helps you compare the price changes of various cryptocurrencies against each other.
While TradingView provides some pairs like ETH/BTC or BNB/BTC, it lacks support for comparing lower-market-cap coins against BTC or other currencies. That’s where this script comes in, allowing you to easily view ratios like DOGS/BTC, LSD/BTC, and more.
You can also analyze the relationship between two high-market-cap assets, such as ETH/SOL, which is often not available directly on TradingView.
Additionally, this indicator enables you to view the changes of two cryptocurrencies alongside a base currency. For example, you can observe how Bitcoin's rise impacts LSD and whether it strengthens or weakens relative to BTC.
Features
Maximized View: You can open the indicator in a maximized chart view and use it like any other chart for your technical analysis.
Customizable Comparisons: Compare any two assets with ease by configuring the indicator inputs.
Important Notes
1.Preserving Drawings:
Drawings and tools applied to the indicator chart are not tied to the indicator’s settings. This means changing the inputs won’t affect them. To avoid losing your work:
Open the chart of the base asset (e.g., LSD/USDT) where you want to analyze a specific pair (e.g., LSD/BTC).
Use the indicator there. This way, whenever you want to revisit your analysis, you only need to open the base chart (e.g., LSD/USDT) and update the indicator inputs to the desired pair (e.g., LSD/BTC).
2.Deleting the Indicator:
Removing the indicator from the chart will also delete all your drawings. If you need to keep them, do not delete the indicator.
3.Precision Settings:
By default, the indicator displays up to 12 decimal places (precision). For pairs where such precision isn’t required, you can adjust it in the settings under the "Style" section to your preferred value. If you need higher precision again, simply reset it to the default value.
RSI MACD Combined Color StrategyOverview
This indicator combines RSI and MACD signals to create a powerful visual trading system, inspired by TrendSpider's AI Strategy Coder examples. It colors candles based on the alignment of three key technical conditions, providing clear visual signals for potential trend strength and direction.
Technical Components
Core Conditions
RSI (Relative Strength Index) > 50
Indicates bullish momentum when price is trading above the centerline
Traditional indicator of trend strength
MACD Line > Signal Line
Shows positive momentum
Classic signal for potential upward movement
MACD Line > 0
Confirms bullish territory
Indicates overall positive momentum
Color Coding System
🟢 Green Candles: All three conditions are met
Strongest bullish signal
Suggests high probability trading opportunities
⚪ Grey Candles: One or two conditions are met
Neutral or transitioning market
Suggests caution or waiting for stronger confirmation
🔴 Red Candles: No conditions are met
Bearish signal
Suggests potential downward pressure
How to Use This Indicator
For Entry Signals
Look for transitions from red or grey to green candles
Green candles suggest strong bullish alignment
Consider entering long positions when candles turn green
For Exit Signals
Watch for color transitions from green to grey or red
Consider taking profits when candles change from green to grey
Consider stop losses when candles turn red
Risk Management
Use color transitions as part of your broader strategy
Don't rely solely on color changes for trading decisions
Combine with other technical analysis tools and risk management practices
Customizable Parameters
RSI Length (default: 14)
MACD Fast Length (default: 12)
MACD Slow Length (default: 26)
MACD Signal Length (default: 9)
Best Practices
Use multiple timeframes for confirmation
Look for confluences with support/resistance levels
Consider volume and market context
Start with default settings and adjust based on your trading style
Backtest different parameter combinations
Notes
This indicator works best in trending markets
Grey candles can indicate transition periods
Consider market conditions and volatility when interpreting signals
Credits
Inspired by TrendSpider's AI Strategy Coder examples and adapted for TradingView using Pine Script v5.
Disclaimer
This technical indicator is for informational purposes only. Always conduct your own analysis and consider risk management principles before making trading decisions. Past performance does not guarantee future results.
IU Trailing Stop Loss MethodsThe 'IU Trailing Stop Loss Methods' it's a risk management tool which allows users to apply 12 trailing stop-loss (SL) methods for risk management of their trades and gives live alerts when the trailing Stop loss has hit. Below is a detailed explanation of each input and the working of the Script.
Main Inputs:
- bar_time: Specifies the date from which the trade begins and entry price will be the open of the first candle.
- entry_type: Choose between 'Long' or 'Short' positions.
- trailing_method: Select the trailing stop-loss method. Options include ATR, Parabolic SAR, Supertrend, Point/Pip based, Percentage, EMA, Highest/Lowest, Standard Deviation, and multiple target-based methods.
- exit_after_close: If checked, exits the trade only after the candle closes.
Optional Inputs:
ATR Settings:
- atr_Length: Length for the ATR calculation.
- atr_factor: ATR multiplier for SL calculation.
Parabolic SAR Settings:
- start, increment, maximum: Parameters for the Parabolic SAR indicator.
Supertrend Settings:
- supertrend_Length, supertrend_factor: Length and factor for the Supertrend indicator.
Point/Pip Based:
- point_base: Set trailing SL in points/pips.
Percentage Based:
- percentage_base: Set SL as a percentage of entry price.
EMA Settings:
- ema_Length: Length for EMA calculation.
Standard Deviation Settings:
- std_Length, std_factor: Length and factor for standard deviation calculation.
Highest/Lowest Settings:
- highest_lowest_Length: Length for the highest/lowest SL calculation.
Target-Based Inputs:
- ATR, Point, Percentage, and Standard Deviation based target SL settings with customizable lengths and multipliers.
Entry Logic:
- Trades initiate based on the entry_type selected and the specified bar_time.
- If Long is selected, a long trade is initiated when the conditions match, and vice versa for Short.
Trailing Stop-Loss (SL) Methods Explained:
The strategy dynamically adjusts stop-loss based on the chosen method. Each method has its calculation logic:
- ATR: Stop-loss calculated using ATR multiplied by a user-defined factor.
- Parabolic SAR: Uses the Parabolic SAR indicator for trailing stop-loss.
- Supertrend: Utilizes the Supertrend indicator as the stop-loss line.
- Point/Pip Based: Fixed point-based stop-loss.
- Percentage Based: SL set as a percentage of entry price.
- EMA: SL based on the Exponential Moving Average.
- Highest/Lowest: Uses the highest high or lowest low over a specified period.
- Standard Deviation: SL calculated using standard deviation.
Exit Conditions:
- If exit_after_close is enabled, the position will only close after the candle confirms the stop-loss hit.
- If exit_after_close is disabled, the strategy will close the trade immediately when the SL is breached.
Visualization:
The script plots the chosen trailing stop-loss method on the chart for easy visualization.
Target-Based Trailing SL Logic:
- When a position is opened, the strategy calculates the initial stop-loss and progressively adjusts it as the price moves favorably.
- Each SL adjustment is stored in an array for accurate tracking and visualization.
Alerts and Labels:
- When the Entry or trailing stop loss is hit this scripts draws a label and give alert to the user that trailing stop has been hit for the trade.
Note - on the historical data The Script will show nothing if the entry and the exit has happened on the same candle, because we don't know what was hit first SL or TP (basically how the candle was formed on the lower timeframe).
Summary:
This script offers flexible trailing stop-loss options for traders who want dynamic risk management in their strategies. By offering multiple methods like ATR, SAR, Supertrend, and EMA, it caters to various trading styles and risk preferences.
MA RSI MACD Signal SuiteThis Pine Script™ is designed for use in Trading View and generates trading signals based on moving average (MA) crossovers, RSI (Relative Strength Index) signals, and MACD (Moving Average Convergence Divergence) indicators. It provides visual markers on the chart and can be configured to suit various trading strategies.
1. Indicator Overview
The indicator includes signals for:
Moving Averages (MA): It tracks crossovers between different types of moving averages.
RSI: Signals based on RSI crossing certain levels or its signal line.
MACD: Buy and sell signals generated by MACD crossovers.
2. Inputs and Customization
Moving Averages (MAs):
You can customize up to 6 moving averages with different types, lengths, and colors.
MA Type: Choose from different types of moving averages:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
HMA (Hull Moving Average)
SMMA (RMA) (Smoothed Moving Average)
WMA (Weighted Moving Average)
VWMA (Volume Weighted Moving Average)
T3, DEMA, TEMA
Source: Select the price to base the MA on (e.g., close, open, high, low).
Length: Define the number of periods for each moving average.
Examples:
MA1: Exponential Moving Average (EMA) with a period of 9
MA2: Exponential Moving Average (EMA) with a period of 21
RSI Settings:
RSI is calculated based on a user-defined period and is used to identify potential overbought or oversold conditions.
RSI Length: Lookback period for RSI (default 14).
Overbought Level: Defines the overbought threshold for RSI (default 70).
Oversold Level: Defines the oversold threshold for RSI (default 30).
You can also adjust the smoothing for the RSI signal line and customize when to trigger buy and sell signals based on the RSI crossing these levels.
MACD Settings:
MACD is used for identifying changes in momentum and trends.
Fast Length: The period for the fast moving average (default 12).
Slow Length: The period for the slow moving average (default 26).
Signal Length: The period for the signal line (default 9).
Smoothing Method: Choose between SMA or EMA for both the MACD and the signal line.
3. Signal Logic
Moving Average (MA) Crossover Signals:
Crossover: A bullish signal is generated when a fast MA crosses above a slow MA.
Crossunder: A bearish signal is generated when a fast MA crosses below a slow MA.
The crossovers are plotted with distinct colors, and the chart will display markers for these crossover events.
RSI Signals:
Oversold Crossover: A bullish signal when RSI crosses over its signal line below the oversold level (30).
Overbought Crossunder: A bearish signal when RSI crosses under its signal line above the overbought level (70).
RSI signals are divided into:
Aggressive (Early) Entries: Signals when RSI is crossing the oversold/overbought levels.
Conservative Entries: Signals when RSI confirms a reversal after crossing these levels.
MACD Signals:
Buy Signal: Generated when the MACD line crosses above the signal line (bullish crossover).
Sell Signal: Generated when the MACD line crosses below the signal line (bearish crossunder).
Additionally, the MACD histogram is used to identify momentum shifts:
Rising to Falling Histogram: Alerts when the MACD histogram switches from rising to falling.
Falling to Rising Histogram: Alerts when the MACD histogram switches from falling to rising.
4. Visuals and Alerts
Plotting:
The script plots the following on the price chart:
Moving Averages (MA): The selected MAs are plotted as lines.
Buy/Sell Shapes: Triangular markers are displayed for buy and sell signals generated by RSI and MACD.
Crossover and Crossunder Markers: Crosses are shown when two MAs crossover or crossunder.
Alerts:
Alerts can be configured based on the following conditions:
RSI Signals: Alerts for oversold or overbought crossover and crossunder events.
MACD Signals: Alerts for MACD line crossovers or momentum shifts in the MACD histogram.
Alerts are triggered when specific conditions are met, such as:
RSI crosses over or under the oversold/overbought levels.
MACD crosses the signal line.
Changes in the MACD histogram.
5. Example Usage
1. Trend Reversal Setup:
Buy Signal: Use the RSI oversold crossover and MACD bullish crossover to identify potential entry points in a downtrend.
Sell Signal: Use the RSI overbought crossunder and MACD bearish crossunder to identify potential exit points or short entries in an uptrend.
2. Momentum Strategy:
Combine MACD and RSI signals to identify the strength of a trend. Use MACD histogram analysis and RSI levels for confirmation.
3. Moving Average Crossover Strategy:
Focus on specific MA crossovers, such as the 9-period EMA crossing above the 21-period EMA, for buy signals. When a longer-term MA (e.g., 50-period) crosses a shorter-term MA, it may indicate a strong trend change.
6. Alerts Conditions
The script includes several alert conditions, which can be triggered and customized based on the user’s preferences:
RSI Oversold Crossover: Alerts when RSI crosses over the signal line below the oversold level (30).
RSI Overbought Crossunder: Alerts when RSI crosses under the signal line above the overbought level (70).
MACD Buy/Sell Crossover: Alerts when the MACD line crosses the signal line for a buy or sell signal.
7. Conclusion
This script is highly customizable and can be adjusted to suit different trading strategies. By combining MAs, RSI, and MACD, traders can gain multiple perspectives on the market, enhancing their ability to identify potential buy and sell opportunities.
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
VWMACD-MFI-OBV Composite# MACD-MFI-OBV Composite
A dynamic volume-based technical indicator combining Volume-Weighted MACD, Money Flow Index (MFI), and normalized On Balance Volume (OBV). This composite indicator excels at identifying breakouts and strong trend movements through multiple volume confirmations, making it particularly effective for momentum and high-volatility trading environments.
## Overview
The indicator integrates trend, momentum, and cumulative volume analysis into a unified visualization system. Each component is carefully normalized to enable direct comparison, while the background color system provides instant trend recognition. This version is specifically optimized for breakout detection and strong trend confirmation.
## Core Components
### Volume-Weighted MACD
Visualized through the background color system, this enhanced MACD implementation uses Volume-Weighted Moving Averages (VWMA) instead of traditional EMAs. This modification ensures greater sensitivity to volume-supported price movements while filtering out less significant low-volume price changes. The background alternates between green (bullish) and red (bearish) to provide immediate trend feedback.
### Money Flow Index (MFI)
Displayed as the purple line, the MFI functions as a volume-weighted momentum oscillator. Operating within a natural 0-100 range, it helps identify potential overbought and oversold conditions while confirming volume support for price movements. The MFI is particularly effective at validating breakout momentum.
### Normalized On Balance Volume (OBV)
The white line represents normalized OBV, providing insight into cumulative buying and selling pressure. The normalization process scales OBV to match other components while maintaining its ability to confirm price trends through volume analysis. This component excels at identifying strong breakout movements and volume surges.
## Signal Integration
The indicator generates its most powerful signals when all three components align, particularly during breakout conditions:
Strong Bullish Signals develop when:
- Background shifts to green (VWMACD bullish)
- MFI shows strong upward momentum
- OBV demonstrates sharp volume accumulation
Strong Bearish Signals emerge when:
- Background turns red (VWMACD bearish)
- MFI exhibits downward momentum
- OBV shows significant volume distribution
## Market Application
This indicator variant is specifically designed for:
Breakout Trading:
The OBV component provides excellent sensitivity to volume surges, making it ideal for breakout confirmation and momentum validation.
Trend Following:
Sharp OBV movements combined with MFI momentum help identify and confirm strong trending conditions.
High Volatility Markets:
The indicator's design excels in active, volatile markets where clear signal generation is crucial for decision-making.
## Technical Implementation
Default Parameters:
Volume-Weighted MACD maintains traditional periods (12/26/9) while leveraging volume weighting. MFI uses standard 14-period calculation with 80/20 overbought/oversold thresholds. All components undergo normalization over a 100-period lookback for stable comparison.
Visual Elements:
- Background: VWMACD trend indication (green/red)
- Purple Line: Money Flow Index
- White Line: Normalized OBV
- Yellow Line: Combined signal (arithmetic mean of normalized components)
- Reference Lines: Key levels at 20, 50, and 80
## Trading Methodology
The indicator supports a systematic approach to breakout and momentum trading:
1. Breakout Identification
Monitor for background color changes accompanied by significant OBV movement, indicating potential breakout conditions.
2. Volume Surge Confirmation
Examine OBV slope and magnitude to confirm genuine breakout scenarios versus false moves.
3. Momentum Validation
Use MFI to confirm breakout strength and identify potential exhaustion points.
4. Combined Signal Analysis
The yellow line provides a unified view of all components, helping identify high-probability breakout opportunities.
## Interpretation Guidelines
Breakout Confirmation:
Strong breakouts typically show alignment of all three components with notable OBV surge. This configuration often precedes significant price movements.
Trend Strength:
Continuous OBV expansion during trends, supported by steady MFI readings, suggests sustained momentum.
## Market Selection
Optimal Markets Include:
- High-beta growth stocks
- Momentum-driven securities
- Stocks with significant volatility
- Active trading instruments
- Examples: TSLA, NVDA, growth stocks
## Version Information
Current Version: 2.0.0
This indicator represents a specialized adaptation of volume-based analysis, optimized for breakout trading and momentum strategies in high-volatility environments.
Adaptive Fourier Transform Supertrend [QuantAlgo]Discover a brand new way to analyze trend with Adaptive Fourier Transform Supertrend by QuantAlgo , an innovative technical indicator that combines the power of Fourier analysis with dynamic Supertrend methodology. In essence, it utilizes the frequency domain mathematics and the adaptive volatility control technique to transform complex wave patterns into clear and high probability signals—ideal for both sophisticated traders seeking mathematical precision and investors who appreciate robust trend confirmation!
🟢 Core Architecture
At its core, this indicator employs an adaptive Fourier Transform framework with dynamic volatility-controlled Supertrend bands. It utilizes multiple harmonic components that let you fine-tune how market frequencies influence trend detection. By combining wave analysis with adaptive volatility bands, the indicator creates a sophisticated yet clear framework for trend identification that dynamically adjusts to changing market conditions.
🟢 Technical Foundation
The indicator builds on three innovative components:
Fourier Wave Analysis: Decomposes price action into primary and harmonic components for precise trend detection
Adaptive Volatility Control: Dynamically adjusts Supertrend bands using combined ATR and standard deviation
Harmonic Integration: Merges multiple frequency components with decreasing weights for comprehensive trend analysis
🟢 Key Features & Signals
The Adaptive Fourier Transform Supertrend transforms complex wave calculations into clear visual signals with:
Dynamic trend bands that adapt to market volatility
Sophisticated cloud-fill visualization system
Strategic L/S markers at key trend reversals
Customizable bar coloring based on trend direction
Comprehensive alert system for trend shifts
🟢 Practical Usage Tips
Here's how you can get the most out of the Adaptive Fourier Transform Supertrend :
1/ Setup:
Add the indicator to your favorites, then apply it to your chart ⭐️
Start with close price as your base source
Use standard Fourier period (14) for balanced wave detection
Begin with default harmonic weight (0.5) for balanced sensitivity
Start with standard Supertrend multiplier (2.0) for reliable band width
2/ Signal Interpretation:
Monitor trend band crossovers for potential signals
Watch for convergence of price with Fourier trend
Use L/S markers for trade entry points
Monitor bar colors for trend confirmation
Configure alerts for significant trend reversals
🟢 Pro Tips
Fine-tune Fourier parameters for optimal sensitivity:
→ Lower Base Period (8-12) for more reactive analysis
→ Higher Base Period (15-30) to filter out noise
→ Adjust Harmonic Weight (0.3-0.7) to control shorter trend influence
Customize Supertrend settings:
→ Lower multiplier (1.5-2.0) for tighter bands
→ Higher multiplier (2.0-3.0) for wider bands
→ Adjust ATR length based on market volatility
Strategy Enhancement:
→ Compare signals across multiple timeframes
→ Combine with volume analysis
→ Use with support/resistance levels
→ Integrate with other momentum indicators
Xmaster Formula Indicator [TradingFinder] No Repaint Strategies🔵 Introduction
The Xmaster Formula Indicator is a powerful tool for forex trading, combining multiple technical indicators to provide insights into market trends, support and resistance levels, and price reversals. Developed in the early 2010s, it is widely valued for generating reliable buy and sell signals.
Key components include Exponential Moving Averages (EMA) for identifying trends and price momentum, and MACD (Moving Average Convergence Divergence) for analyzing trend strength and direction.
The Stochastic Oscillator and RSI (Relative Strength Index) enhance accuracy by signaling potential price reversals. Additionally, the Parabolic SAR assists in identifying trend reversals and managing risk.
By integrating these tools, the Xmaster Formula Indicator provides a comprehensive view of market conditions, empowering traders to make informed decisions.
🔵 How to Use
The Xmaster Formula Indicator offers two distinct methods for generating signals: Standard Mode and Advance Mode. Each method caters to different trading styles and strategies.
Standard Mode :
In Standard Mode, the indicator uses normalized moving average data to generate buy and sell signals. The difference between the short-term (10-period) and long-term (38-period) EMAs is calculated and normalized to a 0-100 scale.
Buy Signal : When the normalized value crosses above 55, accompanied by the trend line turning green, a buy signal is generated.
Sell Signal : When the normalized value crosses below 45, and the trend line turns red, a sell signal is issued.
This mode is simple, making it ideal for traders looking for straightforward signals without the need for additional confirmations.
Advance Mode :
Advance Mode combines multiple technical indicators to provide more detailed and robust signals.
This method analyzes trends by incorporating :
🟣 MACD
Buy Signal : When the MACD histogram bars are positive.
Sell Signal : When the MACD histogram bars are negative.
🟣 RSI
Buy Signal : When RSI is below 30, indicating oversold conditions.
Sell Signal : When RSI is above 70, suggesting overbought conditions.
🟣 Stochastic Oscillator
Buy Signal : When Stochastic is below 20.
Sell Signal : When Stochastic is above 80.
🟣 Parabolic SAR
Buy Signal : When SAR is below the price.
Sell Signal : When SAR is above the price.
A signal is generated in Advance Mode only when all these indicators align :
Buy Signal : All conditions point to a bullish trend.
Sell Signal : All conditions indicate a bearish trend.
This mode is more comprehensive and suitable for traders who prefer deeper analysis and stronger confirmations before executing trades.
🔵 Settings
Method :
Choose between "Standard" and "Advance" modes to determine how signals are generated. In Standard Mode, signals are based on normalized moving average data, while in Advance Mode, signals rely on the combination of MACD, RSI, Stochastic Oscillator, and Parabolic SAR.
Moving Average Settings :
Short Length : The period for the short-term EMA (default is 10).
Mid Length : The period for the medium-term EMA (default is 20).
Long Length : The period for the long-term EMA (default is 38).
MACD Settings :
Fast Length : The period for the fast EMA in the MACD calculation (default is 12).
Slow Length : The period for the slow EMA in the MACD calculation (default is 26).
Signal Line : The signal line period for MACD (default is 9).
Stochastic Settings :
Length : The period for the Stochastic Oscillator (default is 14).
RSI Settings :
Length : The period for the Relative Strength Index (default is 14).
🔵 Conclusion
The Xmaster Formula Indicator is a versatile and reliable tool for forex traders, offering both simplicity and advanced analysis through its Standard and Advance modes. In Standard Mode, traders benefit from straightforward signals based on normalized moving average data, making it ideal for quick decision-making.
Advance Mode, on the other hand, provides a more detailed analysis by combining multiple indicators like MACD, RSI, Stochastic Oscillator, and Parabolic SAR, delivering stronger confirmations for critical market decisions.
While the Xmaster Formula Indicator offers valuable insights and reliable signals, it is important to use it alongside proper risk management and other analytical methods. By leveraging its capabilities effectively, traders can enhance their trading strategies and achieve better outcomes in the dynamic forex market.
Enhanced VIP-like IndicatorSettings Breakdown Tutorial: Optimizing a Trading Strategy
This guide explains the key trading strategy settings and how to customize them based on your trading style and goals. Each parameter is essential for tailoring the strategy to market conditions and your risk appetite.
1. Short Moving Average Length (Default: 9)
• Purpose: Tracks short-term trends using a small number of candles.
• Settings Tips:
• Smaller Values (e.g., 9): Quickly react to price changes, useful for fast-moving markets.
• Larger Values (e.g., 12-15): Generate smoother signals for less volatile trades.
2. Long Moving Average Length (Default: 21)
• Purpose: Identifies long-term trends.
• Settings Tips:
• Higher Values (e.g., 50): Spot broader trends at the expense of slower signals.
• Trend Analysis: The interaction of short and long MAs helps determine bullish or bearish trends (e.g., bullish when short MA crosses above long MA).
3. Higher Timeframe MA Length (Default: 200)
• Purpose: Filters long-term trends on a higher timeframe (e.g., daily).
• Settings Tips:
• 200 Periods: Standard for defining bullish (price above) or bearish (price below) markets.
• Adjustable: Use 100 for faster responses or stick with 200 for reliability.
4. Higher Timeframe (Default: 1 Day)
• Purpose: Defines the timeframe for the higher moving average.
• Settings Tips:
• Shorter Timeframes (e.g., 4 Hours): More frequent trading signals.
• Daily Timeframe: Best for swing trading and identifying macro trends.
5. RSI Length (Default: 14)
• Purpose: Measures momentum over a specific number of candles.
• Settings Tips:
• Lower Values (e.g., 7): More sensitive to price changes, ideal for quick trades.
• Higher Values (e.g., 20): Smooth signals for more stable markets.
6. RSI Overbought (70) and Oversold (30) Levels
• Purpose: Marks thresholds for overbought and oversold conditions.
• Settings Tips:
• Stricter Levels (e.g., 80/20): Fewer, higher-quality signals.
• Looser Levels (e.g., 65/35): More frequent signals, suitable for active trading.
7. Pivot Left Bars (5) and Pivot Right Bars (5)
• Purpose: Confirms pivot points (support/resistance) based on surrounding candles.
• Settings Tips:
• Higher Values (e.g., 10): Stronger but less frequent pivot points.
• Lower Values: More responsive, for traders seeking quick pivots.
8. Take Profit Percentage (Default: 2%)
• Purpose: Defines the profit level to exit trades.
• Settings Tips:
• Higher Values (e.g., 5%): For swing traders holding positions longer.
• Lower Values (e.g., 1%): For scalpers focusing on quick trades.
9. Minimum Volume (Default: 1,000,000)
• Purpose: Ensures sufficient liquidity for trading.
• Settings Tips:
• Lower Values: For lower-volume markets.
• Higher Values: Reduces risk in high-liquidity assets.
10. Stop Loss Percentage (Default: 1%)
• Purpose: Sets the maximum acceptable loss per trade.
• Settings Tips:
• Lower Values (e.g., 0.5%): Reduces risk, suited for conservative trading.
• Higher Values (e.g., 2%): Allows more price fluctuation, ideal for volatile markets.
11. Entry Conditions
• Options:
• MA Crossover & RSI: Combines trend-following and momentum for well-rounded signals.
• Pivot Breakout: Focuses on support/resistance breakouts for high-impact trades.
• Settings Tips:
• Trend-Following Traders: Use MA Crossover & RSI.
12. Exit Conditions
• Options:
• Opposite Signal: Exits when the trade’s opposite condition occurs (e.g., bullish to bearish).
• Fixed Take Profit/Stop Loss: Exits based on predefined profit/loss thresholds.
• Settings Tips:
• Opposite Signal: Ideal for trend-following strategies.
Summary
Customizing these settings aligns the strategy with your trading goals. Test configurations in a demo environment before live trading to refine the approach and optimize results. Always balance profit potential with risk management.
• Fixed Levels: Better for strict risk management.
• Breakout Traders: Opt for Pivot Breakout.
Implied and Historical VolatilityAbstract
This TradingView indicator visualizes implied volatility (IV) derived from the VIX index and historical volatility (HV) computed from past price data of the S&P 500 (or any selected asset). It enables users to compare market participants' forward-looking volatility expectations (via VIX) with realized past volatility (via historical returns). Such comparisons are pivotal in identifying risk sentiment, volatility regimes, and potential mispricing in derivatives.
Functionality
Implied Volatility (IV):
The implied volatility is extracted from the VIX index, often referred to as the "fear gauge." The VIX represents the market's expectation of 30-day forward volatility, derived from options pricing on the S&P 500. Higher values of VIX indicate increased uncertainty and risk aversion (Whaley, 2000).
Historical Volatility (HV):
The historical volatility is calculated using the standard deviation of logarithmic returns over a user-defined period (default: 20 trading days). The result is annualized using a scaling factor (default: 252 trading days). Historical volatility represents the asset's past price fluctuation intensity, often used as a benchmark for realized risk (Hull, 2018).
Dynamic Background Visualization:
A dynamic background is used to highlight the relationship between IV and HV:
Yellow background: Implied volatility exceeds historical volatility, signaling elevated market expectations relative to past realized risk.
Blue background: Historical volatility exceeds implied volatility, suggesting the market might be underestimating future uncertainty.
Use Cases
Options Pricing and Trading:
The disparity between IV and HV provides insights into whether options are over- or underpriced. For example, when IV is significantly higher than HV, options traders might consider selling volatility-based derivatives to capitalize on elevated premiums (Natenberg, 1994).
Market Sentiment Analysis:
Implied volatility is often used as a proxy for market sentiment. Comparing IV to HV can help identify whether the market is overly optimistic or pessimistic about future risks.
Risk Management:
Institutional and retail investors alike use volatility measures to adjust portfolio risk exposure. Periods of high implied or historical volatility might necessitate rebalancing strategies to mitigate potential drawdowns (Campbell et al., 2001).
Volatility Trading Strategies:
Traders employing volatility arbitrage can benefit from understanding the IV/HV relationship. Strategies such as "long gamma" positions (buying options when IV < HV) or "short gamma" (selling options when IV > HV) are directly informed by these metrics.
Scientific Basis
The indicator leverages established financial principles:
Implied Volatility: Derived from the Black-Scholes-Merton model, implied volatility reflects the market's aggregate expectation of future price fluctuations (Black & Scholes, 1973).
Historical Volatility: Computed as the realized standard deviation of asset returns, historical volatility measures the intensity of past price movements, forming the basis for risk quantification (Jorion, 2007).
Behavioral Implications: IV often deviates from HV due to behavioral biases such as risk aversion and herding, creating opportunities for arbitrage (Baker & Wurgler, 2007).
Practical Considerations
Input Flexibility: Users can modify the length of the HV calculation and the annualization factor to suit specific markets or instruments.
Market Selection: The default ticker for implied volatility is the VIX (CBOE:VIX), but other volatility indices can be substituted for assets outside the S&P 500.
Data Frequency: This indicator is most effective on daily charts, as VIX data typically updates at a daily frequency.
Limitations
Implied volatility reflects the market's consensus but does not guarantee future accuracy, as it is subject to rapid adjustments based on news or events.
Historical volatility assumes a stationary distribution of returns, which might not hold during structural breaks or crises (Engle, 1982).
References
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy, 81(3), 637-654.
Whaley, R. E. (2000). "The Investor Fear Gauge." The Journal of Portfolio Management, 26(3), 12-17.
Hull, J. C. (2018). Options, Futures, and Other Derivatives. Pearson Education.
Natenberg, S. (1994). Option Volatility and Pricing: Advanced Trading Strategies and Techniques. McGraw-Hill.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2001). The Econometrics of Financial Markets. Princeton University Press.
Jorion, P. (2007). Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill.
Baker, M., & Wurgler, J. (2007). "Investor Sentiment in the Stock Market." Journal of Economic Perspectives, 21(2), 129-151.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
