Machine Learning + Geometric Moving Average 250/500Indicator Description - Machine Learning + Geometric Moving Average 250/500
This indicator combines password-protected market analysis levels with two powerful Geometric Moving Averages (GMA 250 & GMA 500).
🔒 Password-Protected Custom Levels
Access pre-defined long and short price levels for select assets (crypto, stocks, and more) by entering the correct password in the indicator settings.
Once the correct password is entered, the indicator automatically displays:
Green horizontal lines for long entry zones.
Red horizontal lines for short entry zones.
If the password is incorrect, a warning label will appear on the chart.
📈 Geometric Moving Averages (GMA)
This indicator calculates GMA 250 and GMA 500, two long-term trend-following tools.
Unlike traditional moving averages, GMAs use logarithmic smoothing to better handle exponential price growth, making them especially useful for assets with strong trends (e.g., crypto and tech stocks).
GMA 250 (white line) tracks the medium-term trend.
GMA 500 (gold line) tracks the long-term trend.
⚙️ Customizable & Flexible
Works on multiple assets, including cryptocurrencies, equities, and more.
Adaptable to different timeframes and trading styles — ideal for both swing traders and long-term investors.
This indicator is ideal for traders who want to blend custom support/resistance levels with advanced geometric trend analysis to better navigate both volatile and trending markets.
Cerca negli script per "GOLD"
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
US Yield Curve (2-10yr)US Yield Curve (2-10yr) by oonoon
2-10Y US Yield Curve and Investment Strategies
The 2-10 year US Treasury yield spread measures the difference between the 10-year and 2-year Treasury yields. It is a key indicator of economic conditions.
Inversion (Spread < 0%): When the 2-year yield exceeds the 10-year yield, it signals a potential recession. Investors may shift to long-term bonds (TLT, ZROZ), gold (GLD), or defensive stocks.
Steepening (Spread widening): A rising 10-year yield relative to the 2-year suggests economic expansion. Investors can benefit by shorting bonds (TBT) or investing in financial stocks (XLF). The Amundi US Curve Steepening 2-10Y ETF can be used to profit from this trend.
Monitoring the curve: Traders can track US10Y-US02Y on TradingView for real-time insights and adjust portfolios accordingly.
Custom Buy and Sell Signal with Body Ratio and RSI
Indicator Overview:
Name: Custom Buy and Sell Signal with Body Ratio and RSI
Description: This indicator is designed to detect buy and sell opportunities by analyzing the body size and wicks of candles in combination with the RSI indicator and volume. It helps identify trend reversals under high-volume market conditions, which enhances the reliability of the signals.
Indicator Features:
RSI (Relative Strength Index): The RSI indicator is used to assess oversold (RSI < 40) or overbought (RSI > 60) conditions. These zones signal potential reversals when combined with other technical signals.
Candle Body Analysis:
The indicator compares the size of the current and previous candles to validate signals.
For a buy signal, the current candle must be bullish and have a body size proportional to that of the previous bearish candle.
Similarly, for a sell signal, the current candle must be bearish with a body size comparable to the previous bullish candle.
Wick Validation:
The indicator analyzes the wick length to reinforce or exclude signals.
For a buy signal, the lower wick of the bullish candle must be shorter than that of the previous bearish candle.
For a sell signal, the upper wick of the bearish candle must be shorter than that of the previous bullish candle and smaller than 30% of the candle's body.
High Volume:
Signals are only generated when the volume exceeds a certain threshold, ensuring that signals are issued in active market conditions.
The minimum volume should be adjusted based on the asset. For example, for gold, a minimum volume of 9000 is recommended.
Trading Strategy:
Buy Signals:
A bearish (red) candle is followed by a bullish (green) candle with a body size that is comparable to the previous candle (0.9 to 3 times the body size).
The lower wick of the bullish candle is shorter than that of the previous bearish candle, confirming the validity of the signal.
The RSI must be below 40, indicating an oversold condition.
The volume must exceed the defined threshold (e.g., > 9000 for gold) to confirm an active market.
Sell Signals:
A bullish (green) candle is followed by a bearish (red) candle with a comparable body size.
The upper wick of the bearish candle must be shorter than that of the previous bullish candle and must not exceed 30% of the body size.
The RSI must be above 60, indicating an overbought condition.
The volume must also exceed the minimum threshold for a valid signal.
Usage Guidelines:
Volume Adjustment: It is crucial to adjust the volume threshold depending on the asset you're trading. For example, for assets like gold, a minimum volume of 9000 is recommended to filter out weak signals. Each asset has a different volume dynamic, so test different thresholds on historical data to find the optimal setting.
Time Frame:
It is recommended to use this indicator on a 1-hour (1H) chart for the best signal relevance. This time frame provides a good balance between reactivity and filtering false signals.
Confluence:
Combine the signals from this indicator with other tools like support and resistance levels, moving averages, or chart patterns to increase your chances of success. Confluence of indicators improves the reliability of signals.
Risk Management:
Implement strict risk management. Use stop-losses based on volatility, such as ATR (Average True Range), or the wick size to determine exit points.
Backtesting:
Before using it live, conduct backtesting on various assets to fine-tune the parameters, especially the volume threshold, and to verify performance across different market conditions.
This indicator is an excellent tool for traders looking to identify trend reversals based on solid technical criteria such as RSI, candle structure, and volume. It is particularly effective on volatile assets with precise volume adjustment.
Shavarie's MCV IndicatorShavarie's MCV Indicator (MACD + CCI + Volume Delta) is a custom-built trend-following and volume-based indicator that helps traders confirm market direction with high accuracy. It combines the MACD (Moving Average Convergence Divergence), CCI (Commodity Channel Index), and Volume Delta, ensuring that all three indicators align before making a trading decision. The goal is to filter out false signals and provide high-probability trade setups.
History & Development
Shavarie's MCV Indicator was developed by Shavarie Gordon, an experienced swing trader, to improve trend confirmation on Gold (XAUUSD) and other markets. After testing various indicators, Shavarie discovered that MACD, CCI, and Volume Delta together provide the best combination of trend strength, momentum, and real-time volume flow. This indicator was designed to eliminate lagging signals, improve win rates, and enhance market timing for both swing and scalping strategies.
How It Works & Calculations
MACD (Moving Average Convergence Divergence)
Measures momentum and trend strength using the difference between a 12-period EMA and a 26-period EMA.
The MACD line and Signal line crossover confirms buy/sell signals.
A rising MACD histogram confirms bullish strength, while a falling histogram confirms bearish strength.
CCI (Commodity Channel Index)
Measures how far the price is from its statistical average.
Above +100 → Overbought (strong trend continuation or reversal).
Below -100 → Oversold (strong trend continuation or reversal).
When CCI aligns with MACD, it confirms momentum strength.
Volume Delta
Measures the difference between buying and selling volume in real time.
A positive delta means more aggressive buying (bullish).
A negative delta means more aggressive selling (bearish).
Helps confirm MACD and CCI trends by showing real volume strength.
Key Takeaways & Features
✅ No false signals: All three indicators must align before entering a trade.
✅ Trend confirmation: Ensures momentum and volume agree before trading.
✅ Works on multiple timeframes: Designed for swing trading on the daily and scalping on 45 min + 5 min.
✅ Great for Gold & Metals: Optimized for XAUUSD, XAUJPY, XAU/AUD, and possibly Palladium (XPDUSD).
✅ Custom-built by a professional trader: Developed by Shavarie Gordon after extensive testing.
Summary
Shavarie’s MCV Indicator is a powerful and reliable trading tool that combines momentum, trend, and volume analysis. By ensuring that MACD, CCI, and Volume Delta align, it eliminates false signals and increases trade accuracy. Whether used for swing trading or scalping, this indicator helps traders enter high-probability trades with confidence.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
---
### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
---
### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
Uptrick: Alpha TrendIntroduction
Uptrick: Alpha Trend is a comprehensive technical analysis indicator designed to provide traders with detailed insights into market trends, momentum, and risk metrics. It adapts to various trading styles—from quick scalps to longer-term positions—by dynamically adjusting its calculations and visual elements. By combining multiple smoothing techniques, advanced color schemes, and customizable data tables, the indicator offers a holistic view of market behavior.
Originality
The Alpha Trend indicator distinguishes itself by blending established technical concepts with innovative adaptations. It employs three different smoothing techniques tailored to specific trading modes (Scalp, Swing, and Position), and it dynamically adjusts its parameters to match the chosen mode. The indicator also offers a wide range of color palettes and multiple on-screen tables that display key metrics. This unique combination of features, along with its ability to adapt in real time, sets it apart as a versatile tool for both novice and experienced traders.
Features
1. Multi-Mode Trend Line
The indicator automatically selects a smoothing method based on the trading mode:
- Scalp Mode uses the Hull Moving Average (HMA) for rapid responsiveness.
- Swing Mode employs the Exponential Moving Average (EMA) for balanced reactivity.
- Position Mode applies the Weighted Moving Average (WMA) for smoother, long-term trends.
Each method is chosen to best capture the price action dynamics appropriate to the trader’s timeframe.
2. Adaptive Momentum Thresholds
It tracks bullish and bearish momentum with counters that increment as the trend confirms directional movement. When these counters exceed a user-defined threshold, the indicator generates optional buy or sell signals. This approach helps filter out minor fluctuations and highlights significant market moves.
3. Gradient Fills
Two types of fills enhance visual clarity:
- Standard Gradient Fill displays ATR-based zones above and below the trend line, indicating potential bullish and bearish areas.
- Fading Gradient Fill creates a smooth transition between the trend line and the price, visually emphasizing the distance between them.
4. Bar Coloring and Signal Markers
The indicator can color-code bars based on market conditions—bullish, bearish, or neutral—allowing for immediate visual assessment. Additionally, signal markers such as buy and sell arrows are plotted when momentum thresholds are breached.
5. Comprehensive Data Tables
Uptrick: Alpha Trend offers several optional tables for detailed analysis:
- Insider Info: Displays key metrics like the current trend value, bullish/bearish momentum counts, and ATR.
- Indicator Metrics: Lists input settings such as trend length, damping, signal threshold, and net momentum.
- Market Analysis: Summarizes overall trend direction, trend strength, Sortino ratio, return, and volatility.
- Price & Trend Dynamics: Details price deviation from the trend, trend slope, and ATR ratio.
- Momentum & Volatility Insights: Presents RSI, standard deviation (volatility), and net momentum.
- Performance & Acceleration Metrics: Focuses on the Sortino ratio, trend acceleration, return, and trend strength.
Each table can be positioned flexibly on the chart, allowing traders to customize the layout according to their needs.
Why It Combines Specific Smoothing Techniques
Smoothing techniques are essential for filtering out market noise and revealing underlying trends. The indicator combines three smoothing methods for the following reasons:
- The Hull Moving Average (HMA) in Scalp Mode minimizes lag and responds quickly to price changes, which is critical for short-term trading.
- The Exponential Moving Average (EMA) in Swing Mode gives more weight to recent data, striking a balance between speed and smoothness. This makes it suitable for mid-term trend analysis.
- The Weighted Moving Average (WMA) in Position Mode smooths out short-term fluctuations, offering a clear view of longer-term trends and reducing the impact of transient market volatility.
By using these specific methods in their respective trading modes, the indicator ensures that the trend line is appropriately responsive for the intended time frame, enhancing decision-making while maintaining clarity.
Inputs
1. Trend Length (Default: 30)
Defines the lookback period for the smoothing calculation. A shorter trend length results in a more responsive line, while a longer length produces a smoother, less volatile trend.
2. Trend Damping (Default: 0.75)
Controls the degree of smoothing applied to the trend line. Lower values lead to a smoother curve, whereas higher values increase sensitivity to price fluctuations.
3. Signal Strength Threshold (Default: 5)
Specifies the number of consecutive bullish or bearish bars required to trigger a signal. Higher thresholds reduce the frequency of signals, focusing on stronger moves.
4. Enable Bar Coloring (Default: True)
Toggles whether each price bar is colored to indicate bullish, bearish, or neutral conditions.
5. Enable Signals (Default: True)
When enabled, this option plots buy or sell arrows on the chart once the momentum thresholds are met.
6. Enable Standard Gradient Fill (Default: False)
Activates ATR-based gradient fills around the trend line to visualize potential support and resistance zones.
7. Enable Fading Gradient Fill (Default: True)
Draws a gradual color transition between the trend line and the current price, emphasizing their divergence.
8. Trading Mode (Options: Scalp, Swing, Position)
Determines which smoothing method and ATR period to use, adapting the indicator’s behavior to short-term, medium-term, or long-term trading.
9. Table Position Inputs
Allows users to select from nine possible chart positions (top, middle, bottom; left, center, right) for each data table.
10. Show Table Booleans
Separate toggles control the display of each table (Insider Info, Indicator Metrics, Market Analysis, and the three Deep Tables), enabling a customized view of the data.
Color Schemes
(Default) - The colors in the preview image of the indicator.
(Emerald)
(Sapphire)
(Golden Blaze)
(Mystic)
(Monochrome)
(Pastel)
(Vibrant)
(Earth)
(Neon)
Calculations
1. Trend Line Methods
- Scalp Mode: Utilizes the Hull Moving Average (HMA), which computes two weighted moving averages (one at half the length and one at full length), subtracts them, and then applies a final weighted average based on the square root of the length. This method minimizes lag and increases responsiveness.
- Swing Mode: Uses the Exponential Moving Average (EMA), which assigns greater weight to recent prices, thus balancing quick reaction with smoothness.
- Position Mode: Applies the Weighted Moving Average (WMA) to focus on longer-term trends by emphasizing the entire lookback period and reducing the impact of short-term volatility.
2. Momentum Tracking
The indicator maintains separate counters for bullish and bearish momentum. These counters increase as the trend confirms directional movement and reset when the trend reverses. When a counter exceeds the defined signal strength threshold, a corresponding signal (buy or sell) is triggered.
3. Volatility and ATR Zones
The Average True Range (ATR) is calculated using a period that adapts to the selected trading mode (shorter for Scalp, longer for Position). The ATR value is then used to define upper and lower zones around the trend line, highlighting the current level of market volatility.
4. Return and Trend Acceleration
- Return is calculated as the difference between the current and previous closing prices, providing a simple measure of price change.
- Trend Acceleration is derived from the change in the trend line’s movement (its first derivative) compared to the previous bar. This metric indicates whether the trend is gaining or losing momentum.
5. Sortino Ratio and Standard Deviation
- The Sortino Ratio measures risk-adjusted performance by comparing returns to downside volatility (only considering negative price changes).
- Standard Deviation is computed over the lookback period to assess the extent of price fluctuations, offering insights into market stability.
Usage
This indicator is suitable for various time frames and market instruments. Traders can enable or disable specific visual elements such as gradient fills, bar coloring, and signal markers based on their preference. For a minimalist approach, one might choose to display only the primary trend line. For a deeper analysis, enabling multiple tables can provide extensive data on momentum, volatility, trend dynamics, and risk metrics.
Important Note on Risk
Trading involves inherent risk, and no indicator can eliminate the uncertainty of the markets. Past performance is not indicative of future results. It is essential to use proper risk management, test any new tool thoroughly, and consult multiple sources or professional advice before making trading decisions.
Conclusion
Uptrick: Alpha Trend unifies a diverse set of calculations, adaptive smoothing techniques, and customizable visual elements into one powerful tool. By combining the Hull, Exponential, and Weighted Moving Averages, the indicator is able to provide a trend line that is both responsive and smooth, depending on the trading mode. Its advanced color schemes, gradient fills, and detailed data tables deliver a comprehensive analysis of market trends, momentum, and risk. Whether you are a short-term trader or a long-term investor, this indicator aims to clarify price action and assist you in making more informed trading decisions.
Trending Market Toolkit [LuxAlgo]The Trending Market Toolkit focuses exclusively on trending market structures and high-confluence, high-risk-to-reward entry models. It is designed to complement discretionary trading by offering different entry strategies based on market structure.
🔶 USAGE
In the chart above we can see how the tool detects several reversals, draws the broken trendlines, the reversal areas from which the tool starts looking for a trigger, and when it finally happens, a potential trade with risk and reward areas and the risk/reward ratio.
🔹 Detection Mode
Traders can choose between three different modes: trend only, reversal only, or both.
If both are active, reversals have priority over trends, so the tool will not detect a trend if a reversal is active.
In the chart above we can see all three modes.
🔹 Detection on Higher Timeframes
Traders can choose to identify structures on the chart timeframe or on a higher timeframe.
In the chart above, we have the SP500 futures on the 5m timeframe with different settings: chart timeframe, 30m, and 1H.
🔹 Risk And Targets
Depending on whether the high-risk/reward parameter is enabled, traders can choose between three different targets and two different stops.
The chart above shows how different choices affect the risk/reward ratio for the same potential trade on the Gold Futures 2m chart.
🔶 SETTINGS
Show: Traders can choose between Trends, Reversals or Both.
🔹 Structures
Swing Length: Number of candles to confirm a swing high or swing low. A higher number detects larger swings.
Custom Timeframe: Traders can make use of the current chart timeframe, or choose a custom timeframe.
Reversal Area Threshold: A higher number increases the reversal area.
🔹 Trades
Trade Trigger Length: Number of candles to confirm an internal high or internal low. A lower number detects smaller swings. It must be the same size or smaller than the swing length.
Target: Traders can choose between the default target (0) or two extended targets (0.27 or 0.618).
Risk to Reward Threshold: Set the minimum risk-to-reward ratio to detect trades. Use the 0 value to detect all trades.
High Risk to Reward: Enable/Disable the high risk to reward mode.
Ultimate Gold Correlation Matrix (Extended)This is a correlation matrix to help you visually understand the relationship between stocks. This is the correlation of the amount of change.
The color changes depending on the value of the correlation value.
By making a node diagram of this relationship, what has been difficult to understand may become clearer.
Good luck.
1. meaning of correlation coefficient
Correlation Coefficient ranges from -1 to +1.
Correlation Coefficient Value Interpretation
+1.00 Perfect positive correlation (when one goes up, the other always goes up)
+0.75 ~ +0.99 Strong positive correlation (fairly well linked)
+0.50 ~ +0.74 Moderate positive correlation
+0.30 ~ +0.49 Weak positive correlation
-0.30 ~ +0.30 No correlation (no or weak relationship)
-0.50 ~ -0.74 Moderate negative correlation
-0.75 ~ -0.99 Strong negative correlation (when one goes up, the other goes down)
-1.00 Perfect negative correlation (opposite moves)
Translated with www.DeepL.com (free version)
Ultimate Gold Correlation Matrix (Extended)This is a correlation matrix to help you visually understand the relationship between stocks. This is the correlation of the amount of change.
The color changes depending on the value of the correlation value.
By drawing a node diagram of this relationship, you may be able to clarify what has been difficult to understand so far.
Footprint IQ Pro [TradingIQ]Hello Traders!
Introducing "Footprint IQ Pro"!
Footprint IQ Pro is an all-in-one Footprint indicator with several unique features.
Features
Calculated delta at tick level
Calculated delta ratio at tick level
Calculated buy volume at tick level
Calculated sell volume at tick level
Imbalance detection
Stacked imbalance detection
Stacked imbalance alerts
Value area and POC detection
Highest +net delta levels detection
Lowest -net delta levels detection
CVD by tick levels
Customizable values area percentage
The image above thoroughly outlines what each metric in the delta boxes shows!
Metrics In Delta Boxes
"δ:", "\nδ%:", "\n⧎: ", "\n◭: ", "\n⧩: "
δ Delta (Difference between buy and sell volume)
δ% Delta Ratio (Delta as a percentage of total volume)
⧎ Total Volume At Level (Total volume at the price area)
◭ Total Buy Volume At Level (Total buy volume at the price area)
⧩ Total Sell Volume At Level (total sell volume at the price area)
Each metric comes with a corresponding symbol.
That said, until you become comfortable with the symbol, you can also turn on the descriptive labels setting!
The image above exemplifies the feature.
The image above shows Footprint IQ's full power!
Additionally, traders with an upgraded TradingView plan can make use of the "1-Second" feature Footprint IQ offers!
The image above shows each footprint generated using 1-second volume data. 1-second data is highly granular compared to 1-minute data and, consequently, each footprint is exceptionally more accurate!
Imbalance Detection
Footprint IQ pro is capable of detecting user-defined delta imbalances.
The image above further explains how Footprint IQ detects imbalances!
The imbalance percentage is customizable in the settings, and is set to 70% by default.
Therefore,
When net delta is positive, and the positive net delta constitutes >=70% of the total volume, a buying imbalance will be detected (upwards triangle).
When net delta is negative, and the negative net delta constitutes >=70% of the total volume, a buying imbalance will be detected (downwards triangle).
Stacked Imbalance Detection
In addition to imbalance detection, Footprint IQ Pro can also detect stacked imbalances!
The image above shows Footprint IQ Pro detecting stacked imbalances!
Stacked imbalances occur when consecutive imbalances at sequential price areas occur. Stacked imbalances are generally interpreted as significant price moves that are supported by volume, rather than a significant result with disproportionate effort.
The criteria for stacked imbalance detection (how many imbalances must occur at sequential price areas) is customizable in the settings.
The default value is three. Therefore, when three imbalances occur at sequential price areas, golden triangles will begin to print to show a stacked imbalance.
Additionally, traders can set alerts for when stacked imbalances occur!
Highest +Delta and Highest -Delta Levels
In addition to being a fully-fledged Footprint indicator, Footprint IQ Pro goes one step further by detecting price areas where the greater +Delta and -Delta are!
The image above shows price behavior near highest +Delta price areas detected by Footprint IQ!
These +Delta levels are considered important as there has been strong interest from buyers at these price areas when they are traded at.
It's expected that these levels can function as support points that are supported by volume.
The image above shows a similar function for resistance points!
Blue lines = High +Delta Detected Price Areas
Red lines = High -Delta Detected Price Areas
Value Area Detection
Similar to traditional volume profile, Footprint IQ Pro displays the value area per bar.
Green lines next to each footprint show the value area for the bar. The value area % is customizable in the settings.
CVD Levels
Footprint IQ Pro is capable of storing historical volume delta information to provide CVD measurements at each price area!
The image above exemplifies this feature!
When this feature is enabled, you will see the CVD of each price area, rather than the net delta!
And that's it!
Thank you so much to TradingView for offering the greatest charting platform for everyone to create on!
If you have any feature requests you'd like to see for Footprint IQ, please feel free to share them with us!
Thank you!
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.
C&P MA/KT Compare & Predict Moving average / Current market price.
This is simple table indicator. Located at right-top of chart. Shows which way will MA's head go.
I made this indicator for automate candle countings & compare price. With this friend, you will be know trend more faster then waiting traditional MA golden / dead crossing.
In factory settings, current market price will be compared with closing price of the candle, corresponding to previous number 7, 25, 60, 99, 130, 240. If Current market price is lower then past, the box for the corresponding MA is highlighted in red and appears as Down. In opposite case, it will be highlighted in green and indicates Up.
MA와 시장가 차이로 MA의 머리 방향을 예측해주는 간단한 지표입니다.
수동으로 캔들 되돌려서 종가와 시장가 비교하는게 너무 번거로워서 자동화를 위해 제작되었습니다. 해당 지표를 이용하시면 MA의 골든/데드 크로스를 기다리는 것보다 더 빠른 예측이 가능합니다.
차트 우측 상단에 예측 값이 표시되며, 기본 설정에선 7, 25, 60, 99, 130, 240개 전 캔들의 종가와 시장가가 비교됩니다. 시장가가 비교 값보다 높을 때는 초록 배경에 Up 텍스트가 출력됩니다. 반대의 경우엔 빨간색 배경에 Down 표기가 나타납니다.
Standardized Leveraged ETF Fund of FlowsThis indicator tracks and standardizes the 3-month fund flows of major leveraged ETFs across different asset classes, including equities, gold, and bonds.
The fund flows are summed over a 3-month period (63 trading days) and then standardized using a 500-day rolling mean and standard deviation.
The resulting normalized fund flow values are plotted in three distinct colors:
Blue for Equities Fund Flows
Yellow for Gold Fund Flows
Green for Bond Fund Flows
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.
MA Smoothed RSI For Loop | QuantPabloMA Smoothed Source For RSI Loop | Crypto_Mercenary_
Conceptual Foundation and Innovation
The "MA Smoothed Source For RSI Loop" indicator developed by Crypto_Mercenary_ innovates by smoothing the source data used for RSI calculation with various moving averages before feeding it into a for-loop scoring system. Rather than smoothing the RSI itself, this approach focuses on pre-processing the price data to reduce noise, thereby providing a cleaner input for RSI computation. The for-loop then evaluates this smoothed RSI to generate momentum signals, offering traders a refined method for detecting market trends and potential reversals.
Technical Composition and Calculation
The indicator's functionality is divided into two main parts:
Source Smoothing: Before calculating RSI, the source data (typically close price) is smoothed using one of several moving averages (EMA, SMA, WMA, VWMA, HMA, RMA, DEMA, or none) as selected by the user. This smoothing aims to filter out short-term volatility, providing a more consistent base for RSI calculation.
RSI Calculation and For-Loop Scoring:
RSI: Calculated using the smoothed source data over a user-defined length.
For-Loop Mechanism: A loop runs from a to b, comparing the current RSI value with past values of this smoothed RSI. A score (counter) is generated, which increases or decreases based on whether the current RSI exceeds or falls below past values. If the weighted option is activated, this comparison gives more weight to recent data points, adjusting the score accordingly.
The final score is then potentially normalized for better interpretation, compared against thresholds to determine market momentum signals.
Features and User Inputs
This indicator is highly customizable, allowing traders to tailor its behavior:
Weighted Calculation: Option to adjust scoring to favor recent price action.
RSI Length: Sets the period for RSI calculation.
Source: The price data to be smoothed before RSI calculation, default is close.
MA Type: Choice from various moving averages to smooth the source data.
Smooth Length: Length of the moving average used for smoothing.
For Loop Range: Defines the historical range (a to b) for the scoring loop.
Thresholds: Custom thresholds to define when signals for uptrends or downtrends are generated.
Practical Applications
This indicator is particularly beneficial for:
Identifying Momentum Shifts: The scoring system helps in detecting potential changes in market momentum.
Noise Reduction: By smoothing the source data, it aims to provide more reliable RSI signals in volatile markets.
Trend Analysis: Assists in confirming or challenging the current market trend based on the smoothed RSI's performance.
Advantages and Strategic Value
The "MA Smoothed Source For RSI Loop" offers an advantage by focusing on cleaning the input data for RSI, which can lead to more accurate momentum readings. Its flexibility in configuration allows traders to adapt the indicator to different market conditions or asset volatilities, enhancing its strategic value in trading decisions.
Alerts and Visual Cues
Visual Signals: The indicator plots the loop score, with colors indicating uptrends (gold) or downtrends (blue). Horizontal lines at thresholds and shaded areas between them provide visual aids for trend analysis.
**No explicit alerts in the script, but users can set up custom alerts based on the signals.
Summary and Usage Tips
The "MA Smoothed Source For RSI Loop | Crypto_Mercenary_" provides a nuanced approach to RSI by smoothing the price data before its calculation, resulting in potentially more reliable signals. Traders can use this indicator to gain a clearer picture of market momentum, adjusting parameters to fit different market behaviors or trading strategies. Remember, the effectiveness of this tool largely depends on its customization to the specific market context.
Note: Backtests are based on past results and do not guarantee future performance.
AdvancedLines (FiboBands) - PaSKaL
Overview :
AdvancedLines (FiboBands) - PaSKaL is an advanced technical analysis tool designed to automate the plotting of key Fibonacci retracement levels based on the highest high and lowest low over a customizable period. This indicator helps traders identify critical price zones such as support, resistance, and potential trend reversal or continuation points.
By using AdvancedLines (FiboBands) - PaSKaL , traders can easily spot key areas where the price is likely to reverse or consolidate, or where the trend may continue. It is particularly useful for trend-following, scalping, and range-trading strategies.
Key Features:
Automatic Fibonacci Level Calculation :
- The indicator automatically calculates and plots key Fibonacci levels (0.236, 0.382, 0.5, 0.618, and 0.764), which are crucial for identifying potential support and resistance levels in the market.
Adjustable Parameters :
- Bands Length: You can adjust the bands_length setting to change the number of bars used for calculating the highest high and lowest low. This gives flexibility for using the indicator on different timeframes and trading styles.
- Visibility: The Fibonacci levels, as well as the midline (0.5 Fibonacci level), can be shown or hidden based on your preference.
- Color Customization: You can change the color of each Fibonacci level and background fills to suit your chart preferences.
Fibonacci Levels
- The main Fibonacci levels plotted are:
- 0.236 – Minor support/resistance level
- 0.382 – Moderate retracement level
- 0.5 – Midpoint retracement, often used as a key level
- 0.618 – Golden ratio, considered one of the most important Fibonacci levels
- 0.764 – Strong reversal level, often indicating a continuation or change in trend
Background Fill
- The indicator allows you to fill the background between the Fibonacci levels and the bands with customizable colors. This makes it easier to visually highlight key zones on the chart.
How the Indicator Works:
AdvancedLines (FiboBands) - PaSKaL calculates the range (difference between the highest high and the lowest low) over a user-defined number of bars (e.g., 300). Fibonacci levels are derived from this range, helping traders identify potential price reversal points.
Mathematical Basis :
Fibonacci retracement levels are based on the Fibonacci sequence, where each number is the sum of the previous two (0, 1, 1, 2, 3, 5, 8, 13, etc.). The ratios derived from this sequence (such as 0.618 and 0.382) have been widely observed in nature, market cycles, and price movements. These ratios are used to forecast potential price retracements or continuation points after a major price move.
Fibonacci Levels Calculation :
Identify the Range: The highest high and the lowest low over the defined period are calculated.
Apply Fibonacci Ratios: Fibonacci ratios (0.236, 0.382, 0.5, 0.618, and 0.764) are applied to this range to calculate the corresponding price levels.
Plot the Levels: The indicator automatically plots these levels on your chart.
Customizing Fibonacci Levels & Colors:
The "AdvancedLines (FiboBands) - PaSKaL" indicator offers various customization options for Fibonacci levels, colors, and visibility:
Fibonacci Level Ratios:
- You can customize the Fibonacci level ratios through the following inputs:
- Fibo Level 1: 0.764
- Fibo Level 2: 0.618
- Fibo Level 3: 0.5
- Fibo Level 4: 0.382
- Fibo Level 5: 0.236
- These levels determine key areas where price may reverse or pause. You can adjust these ratios based on your trading preferences.
Fibonacci Level Colors:
- Each Fibonacci level can be assigned a different color to make it more distinguishable on your chart:
- Fibo Level 1 Color (default: Yellow)
- Fibo Level 2 Color (default: Orange)
- Fibo Level 3 Color (default: Green)
- Fibo Level 4 Color (default: Red)
- Fibo Level 5 Color (default: Blue)
- You can change these colors to fit your visual preferences or to align with your existing chart themes.
Visibility of Fibonacci Levels:
- You can choose whether to display each Fibonacci level using the following visibility inputs:
- Show Fibo Level 1 (0.764): Display or hide this level.
- Show Fibo Level 2 (0.618): Display or hide this level.
- Show Fibo Level 3 (0.5): Display or hide this level.
- Show Fibo Level 4 (0.382): Display or hide this level.
- Show Fibo Level 5 (0.236): Display or hide this level.
- This allows you to customize the indicator according to the specific Fibonacci levels that are most relevant to your trading strategy.
Background Fill Color
- The background between the Fibonacci levels and price bands can be filled with customizable colors:
- Fill Color for Upper Band & Fibo Level 1: This color will fill the area between the upper band and Fibonacci Level 1.
- Fill Color for Lower Band & Fibo Level 5: This color will fill the area between the lower band and Fibonacci Level 5.
- Adjusting these colors helps highlight critical zones where price may reverse or consolidate.
How to Use AdvancedLines (FiboBands) - PaSKaL in Trading :
Range Trading :
Range traders typically buy at support and sell at resistance. Fibonacci levels provide excellent support and resistance zones in a ranging market.
Example: If price reaches the 0.618 level in an uptrend, it may reverse, providing an opportunity to sell.
Conversely, if price drops to the 0.382 level, a bounce might occur, and traders can buy, anticipating the market will stay within the range.
Trend-following Trading :
For trend-following traders, Fibonacci levels act as potential entry points during a retracement. After a strong trend, price often retraces to one of the Fibonacci levels before continuing in the direction of the trend.
Example: In a bullish trend, when price retraces to the 0.382 level, it could be a signal to buy, as the price might resume its upward movement after the correction.
In a bearish trend, retracements to levels like 0.618 or 0.764 could provide optimal opportunities for shorting as the price resumes its downward movement.
Scalping :
Scalpers focus on short-term price movements. Fibonacci levels can help identify precise entry and exit points for quick trades.
Example: If price is fluctuating in a narrow range, a scalper can enter a buy trade at 0.236 and exit at the next Fibonacci level, such as 0.382 or 0.5, capturing small but consistent profits.
Stop-Loss and Take-Profit Levels :
Fibonacci levels can also help in setting stop-loss and take-profit levels.
Example: In a bullish trend, you can set a stop-loss just below the 0.236 level and a take-profit at 0.618.
In a bearish trend, set the stop-loss just above the 0.382 level and the take-profit at 0.764.
Identifying Reversals and Continuations :
Reversals: When price reaches a Fibonacci level and reverses direction, it may indicate the end of a price move.
Trend Continuation: If price bounces off a Fibonacci level and continues in the same direction, this may signal that the trend is still intact.
Conclusion :
AdvancedLines (FiboBands) - PaSKaL is an essential tool for any trader who uses Fibonacci retracements in their trading strategy. By automatically plotting key Fibonacci levels, this indicator helps traders quickly identify support and resistance zones, forecast potential reversals, and make more informed trading decisions.
For Trend-following Traders: Use Fibonacci levels to find optimal entry points after a price retracement.
For Range Traders: Identify key levels where price is likely to reverse or bounce within a range.
For Scalpers: Pinpoint small price movements and take advantage of quick profits by entering and exiting trades at precise Fibonacci levels.
By incorporating AdvancedLines (FiboBands) - PaSKaL into your trading setup, you will gain a deeper understanding of price action, improve your decision-making process, and enhance your overall trading performance.
Advanced Multi-Timeframe Trading System (Risk Managed)Description:
This strategy is an original approach that combines two main analytical components to identify potential trade opportunities while simulating realistic trading conditions:
1. Market Trend Analysis via an Approximate Hurst Exponent
• What It Does:
The strategy computes a rough measure of market trending using an approximate Hurst exponent. A value above 0.5 suggests persistent, trending behavior, while a value below 0.5 indicates a tendency toward mean-reversion.
• How It’s Used:
The Hurst exponent is calculated on both the chart’s current timeframe and a higher timeframe (default: Daily) to capture both local and broader market dynamics.
2. Fibonacci Retracement Levels
• What It Does:
Using daily high and low data from a selected timeframe (default: Daily), the script computes key Fibonacci retracement levels.
• How It’s Used:
• The 61.8% level (Golden Ratio) serves as a key threshold:
• A long entry is signaled when the price crosses above this level if the daily Hurst exponent confirms a trending market.
• The 38.2% level is used to identify short-entry opportunities when the price crosses below it and the daily Hurst indicates non-trending conditions.
Signal Logic:
• Long Entry:
When the price crosses above the 61.8% Fibonacci level (Golden Ratio) and the daily Hurst exponent is greater than 0.5, suggesting a trending market.
• Short Entry:
When the price crosses below the 38.2% Fibonacci level and the daily Hurst exponent is less than 0.5, indicating a less trending or potentially reversing market.
Risk Management & Trade Execution:
• Stop-Loss:
Each trade is risk-managed with a stop-loss set at 2% below (for longs) or above (for shorts) the entry price. This ensures that no single trade risks more than a small, sustainable portion of the account.
• Take Profit:
A take profit order targets a risk-reward ratio of 1:2 (i.e., the target profit is twice the amount risked).
• Position Sizing:
Trades are executed with a fixed position size equal to 10% of account equity.
• Trade Frequency Limits:
• Daily Limit: A maximum of 5 trades per day
• Overall Limit: No more than 510 trades during the backtesting period (e.g., since 2019)
These limits are imposed to simulate realistic trading frequency and to avoid overtrading in backtest results.
Backtesting Parameters:
• Initial Capital: $10,000
• Commission: 0.1% per trade
• Slippage: 1 tick per bar
These settings aim to reflect the conditions faced by the average trader and help ensure that the backtesting results are realistic and not misleading.
Chart Overlays & Visual Aids:
• Fibonacci Levels:
The key Fibonacci retracement levels are plotted on the chart, and the zone between the 61.8% and 38.2% levels is highlighted to show a key retracement area.
• Market Trend Background:
The chart background is tinted green when the daily Hurst exponent indicates a trending market (value > 0.5) and red otherwise.
• Information Table:
An on-chart table displays key parameters such as the current Hurst exponent, daily Hurst value, the number of trades executed today, and the global trade count.
Disclaimer:
Past performance is not indicative of future results. This strategy is experimental and provided solely for educational purposes. It is essential that you backtest and paper trade using your own settings before considering any live deployment. The Hurst exponent calculation is an approximation and should be interpreted as a rough gauge of market behavior. Adjust the parameters and risk management settings according to your personal risk tolerance and market conditions.
Additional Notes:
• Originality & Usefulness:
This script is an original mashup that combines trend analysis with Fibonacci retracement methods. The description above explains how these components work together to provide trading signals.
• Realistic Results:
The strategy uses realistic account sizes, commission rates, slippage, and risk management rules to generate backtesting results that are representative of real-world trading.
• Educational Purpose:
This script is intended to support the TradingView community by offering insights into combining multiple analysis techniques in one strategy. It is not a “get-rich-quick” system but rather an educational tool to help traders understand risk management and trade signal logic.
By using this script, you acknowledge that trading involves risk and that you are responsible for testing and adjusting the strategy to fit your own trading environment. This publication is fully open source, and any modifications should include proper attribution if significant portions of the code are reused.
Twitter Model ICT [TradingFinder] MMXM ERL D + FVG + M15 MSS/SMT🔵 Introduction
The Twitter Model ICT is a trading approach based on ICT (Inner Circle Trader) models, focusing on price movement between external and internal liquidity in lower timeframes. This model integrates key concepts such as Market Structure Shift (MSS), Smart Money Technique (SMT) divergence, and CISD level break to identify precise entry points in the market.
The primary goal of this model is to determine key liquidity levels, such as the previous day’s high and low (PDH/PDL) and align them with the Fair Value Gap (FVG) in the 1-hour timeframe. The overall strategy involves framing trades around the 1H FVG and using the M15 Market Structure Shift (MSS) for entry confirmation.
The Twitter Model ICT is designed to utilize external liquidity levels, such as PDH/PDL, as key entry zones. The model identifies FVG in the 1-hour timeframe, which acts as a magnet for price movement. Additionally, traders confirm entries using M15 Market Structure Shift (MSS) and SMT divergence.
Bullish Twitter Model :
In a bullish setup, the price sweeps the previous day’s low (PDL), and after confirming reversal signals, buys are executed in internal liquidity zones. Conversely, in a bearish setup, the price sweeps the previous day’s high (PDH), and after confirming weakness signals, sells are executed.
Bearish Twitter Model :
In short setups, entries are only executed above the Midnight Open, while in long setups, entries are taken below the Midnight Open. Adhering to these principles allows traders to define precise entry and exit points and analyze price movement with greater accuracy based on liquidity and market structure.
🔵 How to Use
The Twitter Model ICT is a liquidity-based trading strategy that analyzes price movements relative to the previous day’s high and low (PDH/PDL) and Fair Value Gap (FVG). This model is applicable in both bullish and bearish directions and utilizes the 1-hour (1H) and 15-minute (M15) timeframes for entry confirmation.
The price first sweeps an external liquidity level (PDH or PDL) and then provides an entry opportunity based on Market Structure Shift (MSS) and SMT divergence. Additionally, the entry should be positioned relative to the Midnight Open, meaning long entries should occur below the Midnight Open and short entries above it.
🟣 Bullish Twitter Model
In a bullish setup, the price first sweeps the previous day’s low (PDL) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bullish Fair Value Gap (FVG) forms, which serves as the price target.
To confirm the entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should be observed, signaling a trend reversal to the upside. Additionally, SMT divergence with correlated assets can indicate weakness in selling pressure.
Under these conditions, a long position is taken below the Midnight Open, with a stop-loss placed at the lowest point of the recent bearish move. The price target for this trade is the FVG in the 1-hour timeframe.
🟣 Bearish Twitter Model
In a bearish setup, the price first sweeps the previous day’s high (PDH) and reaches an external liquidity level. Then, in the 1-hour timeframe (1H), a bearish Fair Value Gap (FVG) is identified, serving as the trade target.
To confirm entry, a Market Structure Shift (MSS) in the 15-minute timeframe (M15) should form, signaling a trend shift to the downside. If an SMT divergence is present, it can provide additional confirmation for the trade.
Once these conditions are met, a short position is taken above the Midnight Open, with a stop-loss placed at the highest level of the recent bullish move. The trade's price target is the FVG in the 1-hour timeframe.
🔵 Settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
Daily Position : Determines whether only the first signal of the day is considered or if signals are evaluated throughout the entire day.
Session : Specifies in which trading sessions the indicator will be active.
Second Symbol : This setting allows you to select another asset for comparison with the primary asset. By default, "XAUUSD" (Gold) is set as the second symbol, but you can change it to any currency pair, stock, or cryptocurrency. For example, you can choose currency pairs like EUR/USD or GBP/USD to identify divergences between these two assets.
Divergence Fractal Periods : This parameter defines the number of past candles to consider when identifying divergences. The default value is 2, but you can change it to suit your preferences. This setting allows you to detect divergences more accurately by selecting a greater number of candles.
The indicator allows displaying sessions based on various time zones. The user can select one of the following options :
UTC (Coordinated Universal Time)
Local Time of the Session
User’s Local Time
Show Open Price : Displays the New York market opening price.
Show PDH / PDL : Displays the previous day’s high and low to identify potential entry points.
Show SMT Divergence : Displays lines and labels for bullish ("+SMT") and bearish ("-SMT") divergences.
🔵 Conclusion
The Twitter Model ICT is an effective approach for analyzing and executing trades in financial markets, utilizing a combination of liquidity principles, market structure, and SMT confirmations to identify optimal entry and exit points.
By analyzing the previous day’s high and low (PDH/PDL), Fair Value Gaps (FVG), and Market Structure Shift (MSS) in the 1H and M15 timeframes, traders can pinpoint liquidity-driven trade opportunities. Additionally, considering the Midnight Open level helps traders avoid random entries and ensures better trade placement.
By applying this model, traders can interpret market movements based on liquidity flow and structural changes, allowing them to fine-tune their trading decisions with higher precision. Ultimately, the Twitter Model ICT provides a structured and logical approach for traders who seek to trade based on liquidity behavior and trend shifts in the market.
Advanced Trend and Volatility Indicator with Alerts by ZaimonThis script presents a comprehensive analytical tool that integrates multiple technical indicators to provide a holistic view of market trends and volatility. By uniquely combining Moving Averages (MA), Relative Strength Index (RSI), Stochastic Oscillator, Bollinger Bands, and Average True Range (ATR), it offers nuanced insights into price movements and helps identify potential trading opportunities.
---
### **Key Features and Integration:**
1. **Moving Averages (MA20 & MA50):**
- **Trend Identification:**
- **Methodology:** Calculates two Simple Moving Averages—MA20 (short-term) and MA50 (long-term).
- **Bullish Trend:** When MA20 crosses above MA50, indicating upward momentum.
- **Bearish Trend:** When MA20 crosses below MA50, signaling downward momentum.
- **Golden Cross & Death Cross Alerts:**
- **Golden Cross:** MA20 crossing above MA50 generates a bullish alert and visual symbol.
- **Death Cross:** MA20 crossing below MA50 triggers a bearish alert and visual symbol.
- **Integration:**
- Serves as the foundational trend indicator, influencing interpretations of other indicators within the script.
2. **Relative Strength Index (RSI):**
- **Momentum Measurement:**
- **Methodology:** Calculates RSI to assess the speed and change of price movements over a 14-period length.
- **Overbought/Oversold Conditions:** Customizable thresholds set at 70 (overbought) and 30 (oversold).
- **Alerts:**
- Generates alerts when RSI crosses above or below the specified thresholds.
- **Integration:**
- Confirms trend strength identified by MAs.
- Overbought/Oversold signals can precede potential trend reversals, especially when aligned with MA crossovers.
3. **Stochastic Oscillator:**
- **Momentum and Reversal Signals:**
- **Methodology:** Uses %K and %D lines to evaluate price momentum relative to high-low range over recent periods.
- **Bullish Signal:** %K crossing above %D in oversold territory (below 20).
- **Bearish Signal:** %K crossing below %D in overbought territory (above 80).
- **Alerts:**
- Provides alerts on bullish and bearish crossovers in extreme regions.
- **Integration:**
- Enhances RSI signals by providing additional momentum confirmation.
- When both RSI and Stochastic indicate overbought/oversold conditions, it strengthens the likelihood of a reversal.
4. **Bollinger Bands:**
- **Volatility Visualization:**
- **Methodology:** Plots upper and lower bands based on standard deviations from a moving average (BB Basis).
- **Dynamic Support/Resistance:** Prices touching or exceeding the bands may indicate potential reversals.
- **Integration:**
- Works with RSI and Stochastic to identify overextended price movements.
- Helps in assessing volatility alongside trend and momentum indicators.
5. **Average True Range (ATR):**
- **Volatility Assessment:**
- **Methodology:** Calculates ATR over a 14-period length to measure market volatility.
- **ATR Bands:** Plots upper and lower bands relative to the current price using an ATR multiplier.
- **Integration:**
- Assists in setting stop-loss and take-profit levels based on current volatility.
- Complements Bollinger Bands for a comprehensive volatility analysis.
6. **Information Table:**
- **Real-Time Data Display:**
- Shows current values of MA20, MA50, RSI, Stochastic %K and %D, BB Basis, ATR, and Trend Status.
- **Trend Status Indicator:**
- Displays "Bullish," "Bearish," or "Sideways" based on MA conditions.
- **Integration:**
- Provides a consolidated view for quick decision-making without analyzing individual indicators separately.
7. **Periodic Labels:**
- **Enhanced Visibility:**
- Adds labels every 50 bars showing RSI and Stochastic values.
- **Integration:**
- Helps track momentum changes over time and spot longer-term patterns.
---
### **How the Components Work Together:**
- **Synergistic Analysis:**
- **Trend Confirmation:** MA crossovers establish the primary trend, while RSI and Stochastic confirm momentum within that trend.
- **Volatility Context:** Bollinger Bands and ATR provide context on market volatility, refining entry and exit points suggested by trend and momentum indicators.
- **Signal Strength:** Concurrent signals from multiple indicators increase confidence in trading decisions.
---
### **Usage Guidelines:**
1. **Trend Analysis:**
- **Identify Trend Direction:**
- Observe MA20 and MA50 crossovers.
- Refer to the Trend Status in the information table.
- **Confirm with Momentum Indicators:**
- Ensure RSI and Stochastic support the identified trend.
2. **Entry and Exit Points:**
- **Overbought/Oversold Conditions:**
- Look for RSI and Stochastic reaching extreme levels.
- Consider entering positions when oversold in a bullish trend or overbought in a bearish trend.
- **Bollinger Band Interactions:**
- Use price interactions with Bollinger Bands to identify potential reversal zones.
3. **Risk Management:**
- **ATR-Based Levels:**
- Set stop-loss and take-profit levels using ATR bands to account for current volatility.
- **Adjusting to Volatility:**
- Modify position sizes and targets based on Bollinger Band width and ATR values.
4. **Alerts Setup:**
- **Customize Alert Thresholds:**
- Configure alerts for MA crossovers, RSI levels, and Stochastic crossovers according to your trading strategy.
- **Stay Informed:**
- Use alerts to monitor key events without constant chart observation.
---
### **Customization:**
- **Flexible Parameters:**
- All indicator lengths, thresholds, and settings are adjustable to suit different trading styles and timeframes.
- **Adjustable Visuals:**
- Modify plot colors, line styles, and label positions to enhance chart readability.
---
### **Originality and Value Addition:**
This script differentiates itself by:
- **Integrated Approach:**
- Seamlessly combining multiple indicators to provide a more comprehensive analysis than using each indicator separately.
- **Enhanced Visualization:**
- Utilizing plots, fills, labels, and an information table to present data intuitively.
- **User-Friendly Features:**
- Pre-configured alerts and real-time data displays reduce the need for manual monitoring.
By explaining how each component interacts and contributes to the overall analysis, the script adds substantial value to traders seeking a multi-faceted tool for market analysis.
---
### **Additional Notes:**
- **Learning Resource:**
- The script is well-commented, serving as an educational tool for those learning Pine Script and technical analysis integration.
- **Further Enhancements:**
- Opportunities exist to incorporate additional indicators like MACD or ADX, and to develop advanced alert logic, such as RSI or Stochastic divergences.
---
### **Disclaimer:**
- **Educational Purpose Only:**
- This script is provided for informational purposes and should not be construed as financial advice.
- **Risk Acknowledgment:**
- Trading involves significant risk; past performance is not indicative of future results.
- **Due Diligence:**
- Users should conduct their own analysis and consider consulting a financial professional before making trading decisions.
---
By providing detailed explanations of the methodologies and the synergistic use of multiple indicators, this script aligns with TradingView's guidelines for originality and usefulness. It offers traders a unique tool that enhances market analysis through the thoughtful integration of technical indicators.
Global M2 Index Percentage### **Global M2 Index Percentage**
**Description:**
The **Global M2 Index Percentage** is a custom indicator designed to track and visualize the global money supply (M2) in a normalized percentage format. It aggregates M2 data from major economies (e.g., the US, EU, China, Japan, and the UK) and adjusts for exchange rates to provide a comprehensive view of global liquidity. This indicator helps traders and investors understand the broader macroeconomic environment, identify trends in money supply, and make informed decisions based on global liquidity conditions.
---
### **How It Works:**
1. **Data Aggregation**:
- The indicator collects M2 data from key economies and adjusts it using exchange rates to calculate a global M2 value.
- The formula for global M2 is:
\
2. **Normalization**:
- The global M2 value is normalized into a percentage (0% to 100%) based on its range over a user-defined period (default: 13 weeks).
- The formula for normalization is:
\
3. **Visualization**:
- The indicator plots the M2 Index as a line chart.
- Key reference levels are highlighted:
- **10% (Red Line)**: Oversold level (low liquidity).
- **50% (Black Line)**: Neutral level.
- **80% (Green Line)**: Overbought level (high liquidity).
---
### **How to Use the Indicator:**
#### **1. Understanding the M2 Index:**
- **Below 10%**: Indicates extremely low liquidity, which may signal economic contraction or tight monetary policy.
- **Above 80%**: Indicates high liquidity, which may signal loose monetary policy or potential inflationary pressures.
- **Between 10% and 80%**: Represents a neutral to moderate liquidity environment.
#### **2. Trading Strategies:**
- **Long-Term Investing**:
- Use the M2 Index to assess global liquidity trends.
- **High M2 Index (e.g., >80%)**: Consider investing in risk assets (stocks, commodities) as liquidity supports growth.
- **Low M2 Index (e.g., <10%)**: Shift to defensive assets (bonds, gold) as liquidity tightens.
- **Short-Term Trading**:
- Combine the M2 Index with technical indicators (e.g., RSI, MACD) for timing entries and exits.
- **M2 Index Rising + RSI Oversold**: Potential buying opportunity.
- **M2 Index Falling + RSI Overbought**: Potential selling opportunity.
#### **3. Macroeconomic Analysis**:
- Use the M2 Index to monitor the impact of central bank policies (e.g., quantitative easing, rate hikes).
- Correlate the M2 Index with inflation data (CPI, PPI) to anticipate inflationary or deflationary trends.
---
### **Key Features:**
- **Customizable Timeframe**: Adjust the lookback period (e.g., 13 weeks, 26 weeks) to suit your trading style.
- **Multi-Economy Data**: Aggregates M2 data from the US, EU, China, Japan, and the UK for a global perspective.
- **Normalized Output**: Converts raw M2 data into an easy-to-interpret percentage format.
- **Reference Levels**: Includes key levels (10%, 50%, 80%) for quick analysis.
---
### **Example Use Case:**
- **Scenario**: The M2 Index rises from 49% to 62% over two weeks.
- **Interpretation**: Global liquidity is increasing, potentially due to central bank stimulus.
- **Action**:
- **Long-Term**: Increase exposure to equities and commodities.
- **Short-Term**: Look for buying opportunities in oversold assets (e.g., RSI < 30).
---
### **Why Use the Global M2 Index Percentage?**
- **Macro Insights**: Understand the broader economic environment and its impact on financial markets.
- **Risk Management**: Identify periods of high or low liquidity to adjust your portfolio accordingly.
- **Enhanced Timing**: Combine with technical analysis for better entry and exit points.
---
### **Conclusion:**
The **Global M2 Index Percentage** is a powerful tool for traders and investors seeking to incorporate macroeconomic data into their strategies. By tracking global liquidity trends, this indicator helps you make informed decisions, whether you're trading short-term or planning long-term investments. Add it to your TradingView charts today and gain a deeper understanding of the global money supply!
---
**Disclaimer**: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consult with a professional before making investment decisions.
Price Imbalance as Consecutive Levels of AveragesOverview
The Price Imbalance as Consecutive Levels of Averages indicator is an advanced technical analysis tool designed to identify and visualize price imbalances in financial markets. Unlike traditional moving average (MA) indicators that update continuously with each new price bar, this indicator employs moving averages calculated over consecutive, non-overlapping historical windows. This unique approach leverages comparative historical data to provide deeper insights into trend strength and potential reversals, offering traders a more nuanced understanding of market dynamics and reducing the likelihood of false signals or fakeouts.
Key Features
Consecutive Rolling Moving Averages: Utilizes three distinct simple moving averages (SMAs) calculated over consecutive, non-overlapping windows to capture different historical segments of price data.
Dynamic Color-Coded Visualization: SMA lines change color and style based on the relationship between the averages, highlighting both extreme and normal market conditions.
Median and Secondary Median Lines: Provides additional layers of price distribution insight during normal trend conditions through the plotting of primary and secondary median lines.
Fakeout Prevention: Filters out short-term volatility and sharp price movements by requiring consistent historical alignment of multiple moving averages.
Customizable Parameters: Offers flexibility to adjust SMA window lengths and line extensions to align with various trading strategies and timeframes.
Real-Time Updates with Historical Context: Continuously recalculates and updates SMA lines based on comparative historical windows, ensuring that the indicator reflects both current and past market conditions.
Inputs & Settings
Rolling Window Lengths:
Window 1 Length (Most Recent) Bars: Number of bars used to calculate the most recent SMA. (Default: 5, Range: 2–300)
Window 2 Length (Preceding) Bars: Number of bars for the second SMA, shifted by Window 1. (Default: 8, Range: 2–300)
Window 3 Length (Third Rolling) Bars: Number of bars for the third SMA, shifted by the combined lengths of Window 1 and Window 2. (Default: 13, Range: 2–300)
Horizontal Line Extension:
Horizontal Line Extension (Bars): Determines how far each SMA line extends horizontally on the chart. (Default: 10 bars, Range: 1–100)
Functionality and Theory
1. Calculating Consecutive Simple Moving Averages (SMAs):
The indicator calculates three SMAs, each based on distinct and consecutive historical windows of price data. This approach contrasts with traditional MAs that continuously update with each new price bar, offering a static view of past trends rather than an ongoing one.
Mean1 (SMA1): Calculated over the most recent Window 1 Length bars. Represents the short-term trend.
Mean1=∑i=1N1CloseiN1
Mean1=N1∑i=1N1Closei
Where N1N1 is the length of Window 1.
Mean2 (SMA2): Calculated over the preceding Window 2 Length bars, shifted back by Window 1 Length bars. Represents the medium-term trend.
\text{Mean2} = \frac{\sum_{i=1}^{N_2} \text{Close}_{i + N_1}}}{N_2}
Where N2N2 is the length of Window 2.
Mean3 (SMA3): Calculated over the third rolling Window 3 Length bars, shifted back by the combined lengths of Window 1 and Window 2 bars. Represents the long-term trend.
\text{Mean3} = \frac{\sum_{i=1}^{N_3} \text{Close}_{i + N_1 + N_2}}}{N_3}
Where N3N3 is the length of Window 3.
2. Determining Market Conditions:
The relationship between the three SMAs categorizes the market condition into either extreme or normal states, enabling traders to quickly assess trend strength and potential reversals.
Extreme Bullish:
Mean3Mean2>Mean1
Mean3>Mean2>Mean1
Indicates a strong and sustained downward trend. SMA lines are colored purple and styled as dashed lines.
Normal Bullish:
Mean1>Mean2andnot in extreme bullish condition
Mean1>Mean2andnot in extreme bullish condition
Indicates a standard upward trend. SMA lines are colored green and styled as solid lines.
Normal Bearish:
Mean1Mean2>Mean1
Mean3>Mean2>Mean1
Normal Bullish:
Mean1>Mean2andnot in Extreme Bullish
Mean1>Mean2andnot in Extreme Bullish
Normal Bearish:
Mean1 Mean2 > Mean3
Visualization: All three SMAs are displayed as gold dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained upward trend. Traders may consider entering long positions, confident in the trend's strength without the distraction of additional lines.
2. Normal Bullish Condition:
SMAs Alignment: Mean1 > Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are green solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms an upward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
3. Extreme Bearish Condition:
SMAs Alignment: Mean3 > Mean2 > Mean1
Visualization: All three SMAs are displayed as purple dashed lines.
Median Lines: Not displayed to maintain chart clarity.
Interpretation: Indicates a strong and sustained downward trend. Traders may consider entering short positions, confident in the trend's strength without the distraction of additional lines.
4. Normal Bearish Condition:
SMAs Alignment: Mean1 < Mean2 (not in extreme condition)
Visualization: Mean1 and Mean2 are red solid lines; Mean3 is gray.
Median Lines: A thin blue dotted median line is plotted between Mean1 and Mean2, with two additional thin blue dashed lines as secondary medians.
Interpretation: Confirms a downward trend while providing deeper insights into price distribution. Traders can use the median and secondary median lines to identify optimal entry points and manage risk more effectively.
Customization and Flexibility
The Price Imbalance as Consecutive Levels of Averages indicator is highly adaptable, allowing traders to tailor it to their specific trading styles and market conditions through adjustable parameters:
SMA Window Lengths: Modify the lengths of Window 1, Window 2, and Window 3 to capture different historical trend segments, whether focusing on short-term fluctuations or long-term movements.
Line Extension: Adjust the horizontal extension of SMA and median lines to align with different trading horizons and chart preferences.
Color and Style Preferences: While default colors and styles are optimized for clarity, traders can customize these elements to match their personal chart aesthetics and enhance visual differentiation.
This flexibility ensures that the indicator remains versatile and applicable across various markets, asset classes, and trading strategies, providing valuable insights tailored to individual trading needs.
Conclusion
The Price Imbalance as Consecutive Levels of Averages indicator offers a comprehensive and innovative approach to analyzing price trends and imbalances within financial markets. By utilizing three consecutive, non-overlapping SMAs and incorporating median lines during normal trend conditions, the indicator provides clear and actionable insights into trend strength and price distribution. Its unique design leverages comparative historical data, distinguishing it from traditional moving averages and enhancing its utility in identifying genuine market movements while minimizing false signals. This dynamic and customizable tool empowers traders to refine their technical analysis, optimize their trading strategies, and navigate the markets with greater confidence and precision.
Geo. Geo.
This library provides a comprehensive set of geometric functions based on 2 simple types for point and line manipulation, point array calculations, some vector operations (Borrowed from @ricardosantos ), angle calculations, and basic polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
View the source code for detailed documentation on each function and type.
═════════════════════════════════════════════════════════════════════════
█ OVERVIEW
This library enhances TradingView's Pine Script with robust geometric capabilities. It introduces the Point and Line types, along with a suite of functions for various geometric operations. These functionalities empower you to perform advanced calculations, manipulations, and analyses involving points, lines, vectors, angles, and polygons directly within your Pine scripts. The example is at the bottom of the script. ( Commented out )
█ CONCEPTS
This library revolves around two fundamental types:
• Point: Represents a point in 2D space with x and y coordinates, along with optional 'a' (angle) and 'v' (value) fields for versatile use. Crucially, for plotting, utilize the `.to_chart_point()` method to convert Points into plottable chart.point objects.
• Line: Defined by a starting Point and a slope , enabling calculations like getting y for a given x, or finding intersection points.
█ FEATURES
• Point Manipulation: Perform operations like addition, subtraction, scaling, rotation, normalization, calculating distances, dot products, cross products, midpoints, and more with Point objects.
• Line Operations: Create lines, determine their slope, calculate y from x (and vice versa), and find the intersection points of two lines.
• Vector Operations: Perform vector addition, subtraction, multiplication, division, negation, perpendicular vector calculation, floor, fractional part, sine, absolute value, modulus, sign, round, scaling, rescaling, rotation, and ceiling operations.
• Angle Calculations: Compute angles between points in degrees or radians, including signed, unsigned, and 360-degree angles.
• Polygon Analysis: Calculate the area, perimeter, and centroid of polygons. Check if a point is inside a given polygon and determine the convex hull perimeter.
• Chart Plotting: Conveniently convert Point objects to chart.point objects for plotting lines and points on the chart. The library also includes functions for plotting lines between individual and series of points.
• Utility Functions: Includes helper functions such as square root, square, cosine, sine, tangent, arc cosine, arc sine, arc tangent, atan2, absolute distance, golden ratio tolerance check, fractional part, and safe index/check for chart plotting boundaries.
█ HOW TO USE
1 — Include the library in your script using:
import kaigouthro/geo/1
2 — Create Point and Line objects:
p1 = geo.Point(bar_index, close)
p2 = geo.Point(bar_index , open)
myLine = geo.Line(p1, geo.slope(p1, p2))
// maybe use that line to detect a crossing for an alert ... hmmm
3 — Utilize the provided functions:
distance = geo.distance(p1, p2)
intersection = geo.intersection(line1, line2)
4 — For plotting labels, lines, convert Point to chart.point :
label.new(p1.to_chart_point(), " Hi ")
line.new(p1.to_chart_point(),p2.to_chart_point())
█ NOTES
This description provides a concise overview. Consult the library's source code for in-depth documentation, including detailed descriptions, parameter types, and return values for each function and method. The source code is structured with comprehensive comments using the `//@` format for seamless integration with TradingView's auto-documentation features.
█ Possibilities..
Library "geo"
This library provides a comprehensive set of geometric functions and types, including point and line manipulation, vector operations, angle calculations, and polygon analysis. It offers tools for creating, transforming, and analyzing geometric shapes and their relationships.
sqrt(value)
Square root function
Parameters:
value (float) : (float) - The number to take the square root of
Returns: (float) - The square root of the input value
sqr(x)
Square function
Parameters:
x (float) : (float) - The number to square
Returns: (float) - The square of the input value
cos(v)
Cosine function
Parameters:
v (float) : (series float) - The value to find the cosine of
Returns: (series float) - The cosine of the input value
sin(v)
Sine function
Parameters:
v (float) : (series float) - The value to find the sine of
Returns: (series float) - The sine of the input value
tan(v)
Tangent function
Parameters:
v (float) : (series float) - The value to find the tangent of
Returns: (series float) - The tangent of the input value
acos(v)
Arc cosine function
Parameters:
v (float) : (series float) - The value to find the arc cosine of
Returns: (series float) - The arc cosine of the input value
asin(v)
Arc sine function
Parameters:
v (float) : (series float) - The value to find the arc sine of
Returns: (series float) - The arc sine of the input value
atan(v)
Arc tangent function
Parameters:
v (float) : (series float) - The value to find the arc tangent of
Returns: (series float) - The arc tangent of the input value
atan2(dy, dx)
atan2 function
Parameters:
dy (float) : (float) - The y-coordinate
dx (float) : (float) - The x-coordinate
Returns: (float) - The angle in radians
gap(_value1, __value2)
Absolute distance between any two float values
Parameters:
_value1 (float) : First value
__value2 (float)
Returns: Absolute Positive Distance
phi_tol(a, b, tolerance)
Check if the ratio is within the tolerance of the golden ratio
Parameters:
a (float) : (float) The first number
b (float) : (float) The second number
tolerance (float) : (float) The tolerance percennt as 1 = 1 percent
Returns: (bool) True if the ratio is within the tolerance, false otherwise
frac(x)
frad Fractional
Parameters:
x (float) : (float) - The number to convert to fractional
Returns: (float) - The number converted to fractional
safeindex(x, limit)
limiting int to hold the value within the chart range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
safecheck(x, limit)
limiting int check if within the chartplottable range
Parameters:
x (float) : (float) - The number to limit
limit (int)
Returns: (int) - The number limited to the chart range
interpolate(a, b, t)
interpolate between two values
Parameters:
a (float) : (float) - The first value
b (float) : (float) - The second value
t (float) : (float) - The interpolation factor (0 to 1)
Returns: (float) - The interpolated value
gcd(_numerator, _denominator)
Greatest common divisor of two integers
Parameters:
_numerator (int)
_denominator (int)
Returns: (int) The greatest common divisor
method set_x(self, value)
Set the x value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new x-coordinate
method set_y(self, value)
Set the y value of the point, and pass point for chaining
Namespace types: Point
Parameters:
self (Point) : (Point) The point to modify
value (float) : (float) The new y-coordinate
method get_x(self)
Get the x value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the x-coordinate from
Returns: (float) The x-coordinate
method get_y(self)
Get the y value of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point to get the y-coordinate from
Returns: (float) The y-coordinate
method vmin(self)
Lowest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The lowest value between x and y
method vmax(self)
Highest element of the point
Namespace types: Point
Parameters:
self (Point) : (Point) The point
Returns: (float) The highest value between x and y
method add(p1, p2)
Addition
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the add of the two points
method sub(p1, p2)
Subtraction
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - the sub of the two points
method mul(p, scalar)
Multiplication by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to multiply by
Returns: (Point) - the multiplied point of the point and the scalar
method div(p, scalar)
Division by scalar
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
scalar (float) : (float) - The scalar to divide by
Returns: (Point) - the divided point of the point and the scalar
method rotate(p, angle)
Rotate a point around the origin by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
Returns: (Point) - the rotated point
method length(p)
Length of the vector from origin to the point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point
Returns: (float) - the length of the point
method length_squared(p)
Length squared of the vector
Namespace types: Point
Parameters:
p (Point) : (Point) The point
Returns: (float) The squared length of the point
method normalize(p)
Normalize the point to a unit vector
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
Returns: (Point) - the normalized point
method dot(p1, p2)
Dot product
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the dot of the two points
method cross(p1, p2)
Cross product result (in 2D, this is a scalar)
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the cross of the two points
method distance(p1, p2)
Distance between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the distance of the two points
method Point(x, y, a, v)
Point Create Convenience
Namespace types: series float, simple float, input float, const float
Parameters:
x (float)
y (float)
a (float)
v (float)
Returns: (Point) new point
method angle(p1, p2)
Angle between two points in degrees
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - the angle of the first point and the second point
method angle_between(p, pivot, other)
Angle between two points in degrees from a pivot point
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to calculate the angle from
pivot (Point) : (Point) - The pivot point
other (Point) : (Point) - The other point
Returns: (float) - the angle between the two points
method translate(p, from_origin, to_origin)
Translate a point from one origin to another
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to translate
from_origin (Point) : (Point) - The origin to translate from
to_origin (Point) : (Point) - The origin to translate to
Returns: (Point) - the translated point
method midpoint(p1, p2)
Midpoint of two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (Point) - The midpoint of the two points
method rotate_around(p, angle, pivot)
Rotate a point around a pivot point by an angle (in degrees)
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to rotate
angle (float) : (float) - The angle to rotate by in degrees
pivot (Point) : (Point) - The pivot point to rotate around
Returns: (Point) - the rotated point
method multiply(_a, _b)
Multiply vector _a with _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the multiplication
method divide(_a, _b)
Divide vector _a by _b
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The result of the division
method negate(_a)
Negative of vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to negate
Returns: (Point) The negated point
method perp(_a)
Perpendicular Vector of _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The perpendicular point
method vfloor(_a)
Compute the floor of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The floor of the point
method fractional(_a)
Compute the fractional part of the elements from vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The fractional part of the point
method vsin(_a)
Compute the sine of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sine of the point
lcm(a, b)
Least common multiple of two integers
Parameters:
a (int) : (int) The first integer
b (int) : (int) The second integer
Returns: (int) The least common multiple
method vabs(_a)
Compute the absolute of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The absolute of the point
method vmod(_a, _b)
Compute the mod of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (float) : (float) The mod
Returns: (Point) The mod of the point
method vsign(_a)
Compute the sign of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The sign of the point
method vround(_a)
Compute the round of argument vector _a
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (Point) The round of the point
method normalize_y(p, height)
normalizes the y value of a point to an input height
Namespace types: Point
Parameters:
p (Point) : (Point) - The point to normalize
height (float) : (float) - The height to normalize to
Returns: (Point) - the normalized point
centroid(points)
Calculate the centroid of multiple points
Parameters:
points (array) : (array) The array of points
Returns: (Point) The centroid point
random_point(_height, _width, _origin, _centered)
Random Point in a given height and width
Parameters:
_height (float) : (float) The height of the area to generate the point in
_width (float) : (float) The width of the area to generate the point in
_origin (Point) : (Point) The origin of the area to generate the point in (default: na, will create a Point(0, 0))
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
Returns: (Point) The random point in the given area
random_point_array(_origin, _height, _width, _centered, _count)
Random Point Array in a given height and width
Parameters:
_origin (Point) : (Point) The origin of the area to generate the array (default: na, will create a Point(0, 0))
_height (float) : (float) The height of the area to generate the array
_width (float) : (float) The width of the area to generate the array
_centered (bool) : (bool) Center the origin point in the area, otherwise, positive h/w (default: false)
_count (int) : (int) The number of points to generate (default: 50)
Returns: (array) The random point array in the given area
method sort_points(points, by_x)
Sorts an array of points by x or y coordinate
Namespace types: array
Parameters:
points (array) : (array) The array of points to sort
by_x (bool) : (bool) Whether to sort by x-coordinate (true) or y-coordinate (false)
Returns: (array) The sorted array of points
method equals(_a, _b)
Compares two points for equality
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (bool) True if the points are equal, false otherwise
method max(origin, _a, _b)
Maximum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The maximum point
method min(origin, _a, _b)
Minimum of two points from origin, using dot product
Namespace types: Point
Parameters:
origin (Point)
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (Point) The minimum point
method avg_x(points)
Average x of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average x-coordinate
method avg_y(points)
Average y of point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The average y-coordinate
method range_x(points)
Range of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of x-coordinates
method range_y(points)
Range of y values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The range of y-coordinates
method max_x(points)
max of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The max of x-coordinates
method min_y(points)
min of x values in point array
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (float) The min of x-coordinates
method scale(_a, _scalar)
Scale a point by a scalar
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to scale
_scalar (float) : (float) The scalar value
Returns: (Point) The scaled point
method rescale(_a, _length)
Rescale a point to a new magnitude
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rescale
_length (float) : (float) The new magnitude
Returns: (Point) The rescaled point
method rotate_rad(_a, _radians)
Rotate a point by an angle in radians
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_radians (float) : (float) The angle in radians
Returns: (Point) The rotated point
method rotate_degree(_a, _degree)
Rotate a point by an angle in degrees
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to rotate
_degree (float) : (float) The angle in degrees
Returns: (Point) The rotated point
method vceil(_a, _digits)
Ceil a point to a certain number of digits
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to ceil
_digits (int) : (int) The number of digits to ceil to
Returns: (Point) The ceiled point
method vpow(_a, _exponent)
Raise both point elements to a power
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_exponent (float) : (float) The exponent
Returns: (Point) The point with elements raised to the power
method perpendicular_distance(_a, _b, _c)
Distance from point _a to line between _b and _c
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
_b (Point) : (Point) The start point of the line
_c (Point) : (Point) The end point of the line
Returns: (float) The perpendicular distance
method project(_a, _axis)
Project a point onto another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The point to project onto
Returns: (Point) The projected point
method projectN(_a, _axis)
Project a point onto a point of unit length
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to project
_axis (Point) : (Point) The unit length point to project onto
Returns: (Point) The projected point
method reflect(_a, _axis)
Reflect a point on another
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The point to reflect on
Returns: (Point) The reflected point
method reflectN(_a, _axis)
Reflect a point to an arbitrary axis
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to reflect
_axis (Point) : (Point) The axis to reflect to
Returns: (Point) The reflected point
method angle_rad(_a)
Angle in radians of a point
Namespace types: Point
Parameters:
_a (Point) : (Point) The point
Returns: (float) The angle in radians
method angle_unsigned(_a, _b)
Unsigned degree angle between 0 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The unsigned angle in degrees
method angle_signed(_a, _b)
Signed degree angle between -180 and +180 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The signed angle in degrees
method angle_360(_a, _b)
Degree angle between 0 and 360 by given two points
Namespace types: Point
Parameters:
_a (Point) : (Point) The first point
_b (Point) : (Point) The second point
Returns: (float) The angle in degrees (0-360)
method clamp(_a, _vmin, _vmax)
Restricts a point between a min and max value
Namespace types: Point
Parameters:
_a (Point) : (Point) The point to restrict
_vmin (Point) : (Point) The minimum point
_vmax (Point) : (Point) The maximum point
Returns: (Point) The restricted point
method lerp(_a, _b, _rate_of_move)
Linearly interpolates between points a and b by _rate_of_move
Namespace types: Point
Parameters:
_a (Point) : (Point) The starting point
_b (Point) : (Point) The ending point
_rate_of_move (float) : (float) The rate of movement (0-1)
Returns: (Point) The interpolated point
method slope(p1, p2)
Slope of a line between two points
Namespace types: Point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
Returns: (float) - The slope of the line
method gety(self, x)
Get y-coordinate of a point on the line given its x-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
x (float) : (float) - The x-coordinate
Returns: (float) - The y-coordinate
method getx(self, y)
Get x-coordinate of a point on the line given its y-coordinate
Namespace types: Line
Parameters:
self (Line) : (Line) - The line
y (float) : (float) - The y-coordinate
Returns: (float) - The x-coordinate
method intersection(self, other)
Intersection point of two lines
Namespace types: Line
Parameters:
self (Line) : (Line) - The first line
other (Line) : (Line) - The second line
Returns: (Point) - The intersection point
method calculate_arc_point(self, b, p3)
Calculate a point on the arc defined by three points
Namespace types: Point
Parameters:
self (Point) : (Point) The starting point of the arc
b (Point) : (Point) The middle point of the arc
p3 (Point) : (Point) The end point of the arc
Returns: (Point) A point on the arc
approximate_center(point1, point2, point3)
Approximate the center of a spiral using three points
Parameters:
point1 (Point) : (Point) The first point
point2 (Point) : (Point) The second point
point3 (Point) : (Point) The third point
Returns: (Point) The approximate center point
createEdge(center, radius, angle)
Get coordinate from center by radius and angle
Parameters:
center (Point) : (Point) - The center point
radius (float) : (float) - The radius of the circle
angle (float) : (float) - The angle in degrees
Returns: (Point) - The coordinate on the circle
getGrowthFactor(p1, p2, p3)
Get growth factor of spiral point
Parameters:
p1 (Point) : (Point) - The first point
p2 (Point) : (Point) - The second point
p3 (Point) : (Point) - The third point
Returns: (float) - The growth factor
method to_chart_point(point)
Convert Point to chart.point using chart.point.from_index(safeindex(point.x), point.y)
Namespace types: Point
Parameters:
point (Point) : (Point) - The point to convert
Returns: (chart.point) - The chart.point representation of the input point
method plotline(p1, p2, col, width)
Draw a line from p1 to p2
Namespace types: Point
Parameters:
p1 (Point) : (Point) First point
p2 (Point) : (Point) Second point
col (color)
width (int)
Returns: (line) Line object
method drawlines(points, col, ignore_boundary)
Draw lines between points in an array
Namespace types: array
Parameters:
points (array) : (array) The array of points
col (color) : (color) The color of the lines
ignore_boundary (bool) : (bool) The color of the lines
method to_chart_points(points)
Draw an array of points as chart points on the chart with line.new(chartpoint1, chartpoint2, color=linecolor)
Namespace types: array
Parameters:
points (array) : (array) - The points to draw
Returns: (array) The array of chart points
polygon_area(points)
Calculate the area of a polygon defined by an array of points
Parameters:
points (array) : (array) The array of points representing the polygon vertices
Returns: (float) The area of the polygon
polygon_perimeter(points)
Calculate the perimeter of a polygon
Parameters:
points (array) : (array) Array of points defining the polygon
Returns: (float) Perimeter of the polygon
is_point_in_polygon(point, _polygon)
Check if a point is inside a polygon
Parameters:
point (Point) : (Point) The point to check
_polygon (array)
Returns: (bool) True if the point is inside the polygon, false otherwise
method perimeter(points)
Calculates the convex hull perimeter of a set of points
Namespace types: array
Parameters:
points (array) : (array) The array of points
Returns: (array) The array of points forming the convex hull perimeter
Point
A Point, can be used for vector, floating calcs, etc. Use the cp method for plots
Fields:
x (series float) : (float) The x-coordinate
y (series float) : (float) The y-coordinate
a (series float) : (float) An Angle storage spot
v (series float) : (float) A Value
Line
Line
Fields:
point (Point) : (Point) The starting point of the line
slope (series float) : (float) The slope of the line
GOMTRY.
