Triple CCI Strategy MFI Confirmed [Skyrexio]Overview
Triple CCI Strategy MFI Confirmed leverages 3 different periods Commodity Channel Index (CCI) indicator in conjunction Money Flow Index (MFI) and Exponential Moving Average (EMA) to obtain the high probability setups. Fast period CCI is used for having the high probability to enter in the direction of short term trend, middle and slow period CCI are used for confirmation, if market now likely in the mid and long-term uptrend. MFI is used to confirm trade with the money inflow/outflow with the high probability. EMA is used as an additional trend filter. Moreover, strategy uses exponential moving average (EMA) to trail the price when it reaches the specific level. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Four layers trade filtering system: Strategy utilizes two different period CCI indicators, MFI and EMA indicators to confirm the signals produced by fast period CCI.
Trailing take profit level: After reaching the trailing profit activation level scrip activate the trailing of long trade using EMA. More information in methodology.
Methodology
The strategy opens long trade when the following price met the conditions:
Fast period CCI shall crossover the zero-line.
Slow and Middle period CCI shall be above zero-lines.
Price shall close above the EMA. Crossover is not obligatory
MFI shall be above 50
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with EMA. If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
CCI Fast Length (by default = 14, used for calculation short term period CCI)
CCI Middle Length (by default = 25, used for calculation short term period CCI)
CCI Slow Length (by default = 50, used for calculation long term period CCI)
MFI Length (by default = 14, used for calculation MFI
EMA Length (by default = 50, period of EMA, used for trend filtering EMA calculation)
Trailing EMA Length (by default = 20)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is CCI, MFI and EMA.
The Commodity Channel Index (CCI) is a momentum-based technical indicator that measures the deviation of a security's price from its average price over a specific period. It helps traders identify overbought or oversold conditions and potential trend reversals.
The CCI formula is:
CCI = (Typical Price − SMA) / (0.015 × Mean Deviation)
Typical Price (TP): This is calculated as the average of the high, low, and closing prices for the period.
Simple Moving Average (SMA): This is the average of the Typical Prices over a specific number of periods.
Mean Deviation: This is the average of the absolute differences between the Typical Price and the SMA.
The result is a value that typically fluctuates between +100 and -100, though it is not bounded and can go higher or lower depending on the price movement.
The Money Flow Index (MFI) is a technical indicator that measures the strength of money flowing into and out of a security. It combines price and volume data to assess buying and selling pressure and is often used to identify overbought or oversold conditions. The formula for MFI involves several steps:
1. Calculate the Typical Price (TP):
TP = (high + low + close) / 3
2. Calculate the Raw Money Flow (RMF):
Raw Money Flow = TP × Volume
3. Determine Positive and Negative Money Flow:
If the current TP is greater than the previous TP, it's Positive Money Flow.
If the current TP is less than the previous TP, it's Negative Money Flow.
4. Calculate the Money Flow Ratio (MFR):
Money Flow Ratio = Sum of Positive Money Flow (over n periods) / Sum of Negative Money Flow (over n periods)
5. Calculate the Money Flow Index (MFI):
MFI = 100 − (100 / (1 + Money Flow Ratio))
MFI above 80 can be considered as overbought, below 20 - oversold.
The Exponential Moving Average (EMA) is a type of moving average that places greater weight and significance on the most recent data points. It is widely used in technical analysis to smooth price data and identify trends more quickly than the Simple Moving Average (SMA).
Formula:
1. Calculate the multiplier
Multiplier = 2 / (n + 1) , Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
This strategy leverages Fast period CCI, which shall break the zero line to the upside to say that probability of short term trend change to the upside increased. This zero line crossover shall be confirmed by the Middle and Slow periods CCI Indicators. At the moment of breakout these two CCIs shall be above 0, indicating that there is a high probability that price is in middle and long term uptrend. This approach increases chances to have a long trade setup in the direction of mid-term and long-term trends when the short-term trend starts to reverse to the upside.
Additionally strategy uses MFI to have a greater probability that fast CCI breakout is confirmed by this indicator. We consider the values of MFI above 50 as a higher probability that trend change from downtrend to the uptrend is real. Script opens long trades only if MFI is above 50. As you already know from the MFI description, it incorporates volume in its calculation, therefore we have another one confirmation factor.
Finally, strategy uses EMA an additional trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements. It’s also important to make a note, that script uses another one EMA (by default = 20 period) as a trailing profit level.
Backtest Results
Operating window: Date range of backtests is 2022.04.01 - 2024.11.25. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -4.13%
Maximum Single Profit: +19.66%
Net Profit: +5421.21 USDT (+54.21%)
Total Trades: 108 (44.44% win rate)
Profit Factor: 2.006
Maximum Accumulated Loss: 777.40 USDT (-7.77%)
Average Profit per Trade: 50.20 USDT (+0.85%)
Average Trade Duration: 44 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Cari dalam skrip untuk "20蒙古币兑换人民币"
Z The Good Stuff +I created this script to have a couple datapoints that I want to look at when going through charts to find trade ideas. Qullamaggie is one of my biggest inspirations and I built in a couple of his concepts with a touch to help me with sizing properly, all explained below:
Box 1: ADR %, Average Daily Range, gives and indication of how volatile the stock is. It uses the 20 day average % move of the current stock on the chart.
Box 2: LOD Distance, low of day distance is a quality of life element I created. It calculates the low for the current candle and color codes it red or green depending on if it's higher or lower than the daily ADR. The logic is that if a stock has an average speed, buying on a setup it is preferred if the stop distance (assuming a low of day stop) should be less than the ADR to improve the odds of more upside.
Box 3: Todays DV, this shows a rough estimate of how much money was traded on the particular day.
Box 4: ADV 20 days, similar to above this shows the 20 day $ traded average. The point to look at it is to have a better idea what position size is possible to not get stuck in something too illiquid.
Box 5: Market cap, just shows the market cap of the stock to know what size the company is.
Box 6: Number of shares, this is an additional quality of life aspect. If using low of day stops, this part calculates based on the users' inputted portfolio size and portfolio risk preference and then calculates how many stocks to buy to stay within the risk parameters. It is obviously not a sole decision making parameter nor does it guarantee any execution, but if a stock is showing an entry you want to take you can use the number of shares to help you know how many to buy. The preset is a portfolio of 10000 and a risk of 0.25%. This means that the number of shares to buy will be at the current price with lod stop that would result in a 0.25% portfolio loss. OF COURSE the actual loss depends on the execution and if the user places a stop loss order.
Hope you find it useful and feel free to give feedback! Cheers!
LRSI-TTM Squeeze - AynetThis Pine Script code creates an indicator called LRSI-TTM Squeeze , which combines two key concepts to analyze momentum, squeeze conditions, and price movements in the market:
Laguerre RSI (LaRSI): A modified version of RSI used to identify trend reversals in price movements.
TTM Squeeze: Identifies market compressions (low volatility) and potential breakouts from these squeezes.
Functionality and Workflow of the Code
1. Laguerre RSI (LaRSI)
Purpose:
Provides a smoother and less noisy version of RSI to track price movements.
Calculation:
The script uses a filtering coefficient (alpha) to process price data through four levels (L0, L1, L2, L3).
Movement differences between these levels calculate buying pressure (cu) and selling pressure (cd).
The ratio of these pressures forms the Laguerre RSI:
bash
Kodu kopyala
LaRSI = cu / (cu + cd)
The LaRSI value indicates:
Below 20: Oversold condition (potential buy signal).
Above 80: Overbought condition (potential sell signal).
2. TTM Squeeze
Purpose:
Analyzes the relationship between Bollinger Bands (BB) and Keltner Channels (KC) to determine whether the market is compressed (low volatility) or expanded (high volatility).
Calculation:
Bollinger Bands:
Calculated based on the moving average (SMA) of the price, with an upper and lower band.
Keltner Channels:
Created using the Average True Range (ATR) to calculate an upper and lower band.
Squeeze States:
Squeeze On: BB is within KC.
Squeeze Off: BB is outside KC.
Other States (No Squeeze): Neither of the above applies.
3. Momentum Calculation
Momentum is computed using the linear regression of the difference between the price and its SMA. This helps anticipate the direction and strength of price movements when the squeeze ends.
Visuals on the Chart
Laguerre RSI Line:
An RSI indicator scaled to 0-100 is plotted.
The line's color changes based on its movement:
Green line: RSI is rising.
Red line: RSI is falling.
Key levels:
20 level: Oversold condition (buy signal can be triggered).
80 level: Overbought condition (sell signal can be triggered).
Momentum Histogram:
Displays momentum as histogram bars with colors based on its direction and strength:
Lime (light green): Positive momentum increasing.
Green: Positive momentum decreasing.
Red: Negative momentum decreasing.
Maroon (dark red): Negative momentum increasing.
Squeeze Status Indicator:
A marker is plotted on the zero line to indicate the squeeze state:
Yellow: Squeeze On (compression active).
Blue: Squeeze Off (compression ended, movement expected).
Gray: No Squeeze.
Information Table
A table is displayed in the top-right corner of the chart, showing closing prices for different timeframes (e.g., 1 minute, 5 minutes, 1 hour, etc.). Each timeframe is color-coded.
Alerts
LaRSI Alerts:
Crosses above 20: Exiting oversold condition (buy signal).
Crosses below 80: Exiting overbought condition (sell signal).
Squeeze Alerts:
When the squeeze ends: Indicates a potential price move.
When the squeeze starts: Indicates volatility is decreasing.
Summary
This indicator is a powerful tool for determining market trends, momentum, and squeeze conditions. It helps users identify periods when the market is likely to move or remain stagnant, providing alerts based on these analyses to support trading strategies.
MACD, ADX & RSI -> for altcoins# MACD + ADX + RSI Combined Indicator
## Overview
This advanced technical analysis tool combines three powerful indicators (MACD, ADX, and RSI) into a single view, providing a comprehensive analysis of trend, momentum, and divergence signals. The indicator is designed to help traders identify potential trading opportunities by analyzing multiple aspects of price action simultaneously.
## Components
### 1. MACD (Moving Average Convergence Divergence)
- **Purpose**: Identifies trend direction and momentum
- **Components**:
- Fast EMA (default: 12 periods)
- Slow EMA (default: 26 periods)
- Signal Line (default: 9 periods)
- Histogram showing the difference between MACD and Signal line
- **Visual**:
- Blue line: MACD line
- Orange line: Signal line
- Green/Red histogram: MACD histogram
- **Interpretation**:
- Histogram color changes indicate potential trend shifts
- Crossovers between MACD and Signal lines suggest entry/exit points
### 2. ADX (Average Directional Index)
- **Purpose**: Measures trend strength and direction
- **Components**:
- ADX line (default threshold: 20)
- DI+ (Positive Directional Indicator)
- DI- (Negative Directional Indicator)
- **Visual**:
- Navy blue line: ADX
- Green line: DI+
- Red line: DI-
- **Interpretation**:
- ADX > 20 indicates a strong trend
- DI+ crossing above DI- suggests bullish momentum
- DI- crossing above DI+ suggests bearish momentum
### 3. RSI (Relative Strength Index)
- **Purpose**: Identifies overbought/oversold conditions and divergences
- **Components**:
- RSI line (default: 14 periods)
- Divergence detection
- **Visual**:
- Purple line: RSI
- Horizontal lines at 70 (overbought) and 30 (oversold)
- Divergence labels ("Bull" and "Bear")
- **Interpretation**:
- RSI > 70: Potentially overbought
- RSI < 30: Potentially oversold
- Bullish/Bearish divergences indicate potential trend reversals
## Alert System
The indicator includes several automated alerts:
1. **MACD Alerts**:
- Rising to falling histogram transitions
- Falling to rising histogram transitions
2. **RSI Divergence Alerts**:
- Bullish divergence formations
- Bearish divergence formations
3. **ADX Trend Alerts**:
- Strong trend development (ADX crossing threshold)
- DI+ crossing above DI- (bullish)
- DI- crossing above DI+ (bearish)
## Settings Customization
All components can be fine-tuned through the settings panel:
### MACD Settings
- Fast Length
- Slow Length
- Signal Smoothing
- Source
- MA Type options (SMA/EMA)
### ADX Settings
- Length
- Threshold level
### RSI Settings
- RSI Length
- Source
- Divergence calculation toggle
## Usage Guidelines
### Entry Signals
Strong entry signals typically occur when multiple components align:
1. MACD histogram color change
2. ADX showing strong trend (>20)
3. RSI showing divergence or leaving oversold/overbought zones
### Exit Signals
Consider exits when:
1. MACD crosses signal line in opposite direction
2. ADX shows weakening trend
3. RSI reaches extreme levels with divergence
### Risk Management
- Use the indicator as part of a complete trading strategy
- Combine with price action and support/resistance levels
- Consider multiple timeframe analysis for confirmation
- Don't rely solely on any single component
## Technical Notes
- Built for TradingView using Pine Script v5
- Compatible with all timeframes
- Optimized for real-time calculation
- Includes proper error handling and NA value management
- Memory-efficient calculations for smooth performance
## Installation
1. Copy the provided Pine Script code
2. Open TradingView Chart
3. Create New Indicator -> Pine Editor
4. Paste the code and click "Add to Chart"
5. Adjust settings as needed through the indicator settings panel
## Version Information
- Version: 2.0
- Last Updated: November 2024
- Platform: TradingView
- Language: Pine Script v5
Multi-Symbol Scanner: Advanced EMA-RSI-Volume Strategy# Multi-Symbol Tech Stock Scanner: Advanced EMA-RSI-Volume Strategy
## Technical Analysis Methodology
This scanner implements a sophisticated multi-timeframe analysis approach combining three key technical elements:
### 1. Dual EMA System (Primary Trend Detection)
- **Long-term EMA (820 periods)**: Acts as the primary trend identifier
- Chosen specifically for tech stocks' longer-term price waves
- Helps filter out minor market noise while capturing major trend changes
- 820 periods approximately represents 3.2 years of trading days
- **Medium-term EMA (320 periods)**: Serves as trend confirmation
- Approximately 1.25 years of trading data
- Provides earlier entry signals while maintaining trend reliability
- Helps identify potential trend reversals before the major trend shift
### 2. Volume Analysis Component
The script employs a dynamic volume analysis system:
- Calculates 20-period moving average of volume as baseline
- Requires 1.5x surge above baseline for signal confirmation
- Volume surge requirement helps filter out weak moves and potential false breakouts
- Different from standard volume indicators as it uses adaptive thresholds
### 3. RSI Momentum Filter
Implements a specialized RSI configuration:
- 14-period RSI with dynamic overbought/oversold levels
- Oversold threshold: 30 (customizable)
- Overbought threshold: 70 (customizable)
- Used as a confirmation tool rather than primary signal generator
## Signal Generation Logic
### Buy Signal Requirements
1. Price must cross above 820 EMA (PRIMARY CONDITION)
2. Current price must be above 320 EMA (CONFIRMATION)
3. RSI must be above 30 but below 70 (MOMENTUM CHECK)
4. Volume must be 1.5x above 20-period average (STRENGTH VALIDATION)
### Sell Signal Requirements
1. Price must cross below 820 EMA (PRIMARY CONDITION)
2. Current price must be below 320 EMA (CONFIRMATION)
3. RSI must be above 30 but below 70 (MOMENTUM CHECK)
4. Volume must be 1.5x above 20-period average (STRENGTH VALIDATION)
## Risk Management Integration
The script automatically calculates key risk levels based on volatility:
1. **Stop Loss Calculation**:
- Default: 2% below entry for buys
- Dynamically adjusted based on price point
- Can be modified through input parameters
2. **Take Profit Targets**:
- Primary target: 6% above entry (3:1 reward-risk ratio)
- Based on historical tech stock movement patterns
- Adjustable through input parameters
## Multi-Symbol Implementation
The scanner monitors 6 symbols simultaneously using:
- Separate security calls for each data point
- Optimized data requests to prevent overload
- Individual signal processing for each symbol
- Synchronized alert generation system
## Technical Implementation Details
1. **Data Processing**:
```
- Security data requests on 10-minute timeframe
- Individual EMA calculations per symbol
- Separate volume analysis threads
- RSI calculations with standard deviation normalization
```
2. **Signal Processing**:
```
- Cross-verification of all conditions
- Time-based signal validation
- Volume surge confirmation
- Trend alignment check
```
3. **Alert System**:
```
- Bar-close confirmation required
- Multi-condition validation
- Detailed price level inclusion
- Risk parameter integration
```
## Optimization Features
1. **Memory Usage**:
- Optimized security calls
- Efficient data structure
- Reduced redundant calculations
2. **Processing Efficiency**:
- Single-pass data analysis
- Combined indicator calculations
- Streamlined alert generation
## Practical Application
The system is designed for:
1. Swing Trading (primary use)
2. Position Trading (secondary use)
3. Technical Breakout Trading
Optimal timeframes:
- Primary: 4H charts
- Secondary: Daily charts
- Verification: 1H charts
## Default Configuration
The scanner is preset to monitor key tech stocks:
- TSLA: High-volatility tech leader
- NVDA: Semiconductor sector benchmark
- AVGO: Stable tech infrastructure
- TSM: Global chip manufacturer
- META: Social media sector leader
- AMZN: E-commerce/Cloud computing leader
Each symbol can be modified through input parameters.
## Version Information
- Current Version: 1.3
- Last Updated: November 2024
- Compatibility: TradingView Pro/Pro+/Premium
## Limitations & Considerations
- Limited to 6 symbols due to TradingView security request limits
- Requires consistent market volume for optimal performance
- Best suited for liquid stocks with significant daily volume
- May need parameter adjustments during extreme market conditions
5-Minute Buy/Sell SignalThe 5-Minute Buy/Sell Signal Indicator is designed to help short-term traders identify potential buy and sell opportunities on a 5-minute chart using a combination of multiple technical indicators. This indicator integrates the following key components to generate buy and sell signals:
MACD (Moving Average Convergence Divergence):
The MACD helps identify the strength and direction of the market trend by comparing the difference between short-term and long-term moving averages. A positive MACD histogram indicates bullish momentum, while a negative histogram indicates bearish momentum.
RSI (Relative Strength Index):
The RSI is a momentum oscillator that measures the speed and change of price movements. The indicator is used to determine overbought or oversold conditions:
Oversold (below 30): Potential buy signal.
Overbought (above 70): Potential sell signal.
EMA (Exponential Moving Average):
The 50-period EMA is used to determine the prevailing trend. When the price is above the EMA, it indicates a bullish trend; when it is below the EMA, it indicates a bearish trend.
Volume:
The indicator incorporates volume analysis to confirm the strength of signals. Signals are only considered valid when the current volume exceeds the average volume over the last 20 periods, ensuring that there is sufficient market participation to support the move.
Signal Generation:
Buy Signal:
The signal is generated when:
MACD histogram is positive (bullish momentum).
RSI is below the oversold level (indicating a potential reversal).
The price is above the 50-period EMA (indicating an uptrend).
Current volume is higher than the 20-period volume moving average (confirming the strength of the buy signal).
Sell Signal:
The signal is generated when:
MACD histogram is negative (bearish momentum).
RSI is above the overbought level (indicating a potential reversal).
The price is below the 50-period EMA (indicating a downtrend).
Current volume is higher than the 20-period volume moving average (confirming the strength of the sell signal).
Signal Display:
Buy Signal: A green "BUY" label appears below the bar when all buy conditions are met.
Sell Signal: A red "SELL" label appears above the bar when all sell conditions are met.
Usage:
This indicator is specifically designed for 5-minute charts, making it ideal for scalpers and day traders who need quick, reliable signals to trade in short timeframes. By combining multiple indicators—MACD, RSI, EMA, and Volume—the system ensures that the buy or sell signals are well-confirmed, reducing the likelihood of false signals and increasing the probability of successful trades.
Alert Conditions:
Alerts can be set up for both buy and sell signals, enabling traders to be notified when the conditions for a potential trade are met, ensuring they never miss a trading opportunity.
In summary, this indicator provides a comprehensive, multi-faceted approach to identifying buy and sell opportunities, helping traders make more informed decisions based on a detailed technical analysis.
Jackson Volume breaker Indication# Jackson Volume Breaker Beta
### Advanced Volume Analysis Indicator
## Description
The Jackson Volume Breaker Beta is a sophisticated volume analysis tool that helps traders identify buying and selling pressure by analyzing price action and volume distribution. This indicator separates and visualizes buying and selling volume based on where the price closes within each candle's range, providing clear insights into market participation and potential trend strength.
## Key Features
1. **Smart Volume Distribution**
- Automatically separates buying and selling volume
- Color-coded volume bars (Green for buying, Red for selling)
- Winning volume always displayed on top for quick visual reference
2. **Real-time Volume Analysis**
- Shows current candle's buy/sell ratio
- Displays total volume with smart number formatting (K, M, B)
- Percentage-based volume distribution
3. **Technical Overlays**
- 20-period Volume Moving Average
- Dynamic scaling relative to price action
- Clean, uncluttered visual design
## How to Use
### Installation
1. Add the indicator to your chart
2. Adjust the Volume Scale input based on your preference (default: 0.08)
3. Toggle the Moving Average display if desired
### Reading the Indicator
#### Volume Bars
- **Green Bars**: Represent buying volume
- **Red Bars**: Represent selling volume
- **Stacking**: The larger volume (winning side) is always displayed on top
- **Height**: Relative to the actual volume, scaled for chart visibility
#### Information Table
The top-right table shows three key pieces of information:
1. **Left Percentage**: Winning side's volume percentage
2. **Middle Percentage**: Losing side's volume percentage
3. **Right Number**: Total volume (abbreviated)
### Trading Applications
1. **Trend Confirmation**
- Strong buying volume in uptrends confirms bullish pressure
- High selling volume in downtrends confirms bearish pressure
- Volume divergence from price can signal potential reversals
2. **Support/Resistance Breaks**
- High volume on breakouts suggests stronger moves
- Low volume on breaks might indicate false breakouts
- Monitor volume distribution for break direction confirmation
3. **Reversal Identification**
- Volume shift from selling to buying can signal potential bottoms
- Shift from buying to selling can indicate potential tops
- Use with price action for better entry/exit points
## Input Parameters
1. **Volume Scale (0.01 to 1.0)**
- Controls the height of volume bars
- Default: 0.08
- Adjust based on your chart size and preference
2. **Show MA (True/False)**
- Toggles 20-period volume moving average
- Useful for identifying volume trends
- Default: True
3. **MA Length (1+)**
- Changes the moving average period
- Default: 20
- Higher values for longer-term volume trends
## Best Practices
1. **Multiple Timeframe Analysis**
- Compare volume patterns across different timeframes
- Look for volume convergence/divergence
- Use higher timeframes for major trend confirmation
2. **Combine with Other Indicators**
- Price action patterns
- Support/resistance levels
- Momentum indicators
- Trend indicators
3. **Volume Pattern Recognition**
- Monitor for unusual volume spikes
- Watch for volume climax patterns
- Identify volume dry-ups
## Tips for Optimization
1. Adjust the Volume Scale based on your chart size
2. Use smaller timeframes for detailed volume analysis
3. Compare current volume bars to historical patterns
4. Watch for volume/price divergences
5. Monitor volume distribution changes near key price levels
## Note
This indicator works best when combined with proper price action analysis and risk management strategies. It should not be used as a standalone trading system but rather as part of a comprehensive trading approach.
## Version History
- Beta Release: Initial public version
- Features buy/sell volume separation, moving average, and real-time analysis
- Optimized for both intraday and swing trading timeframes
## Credits
Developed by Jackson based on other script creators
Special thanks to the trading community for feedback and suggestions
Futures Globex Session(s)This indicator draws a box around the Globex Session for the various Futures markets. The box height defines the highs and lows of that session, and the width defines the timeframe of that session. The boxes are outlined green if price rose during that period, and red if price fell during that period. The default Globex Session is set for the Equity Index Futures and is set in the UTC-4 time zone (Eastern Time). In the settings you can adjust the session time and time zone of your Globex Session to reflect the trading times of that market. Below are the session times for various Futures markets set in time zone UTC-4.
Equity Indexes: 18:00 - 9:30
(ES, NQ, YM, RTY)
Treasuries: 18:00 - 8:20
(ZN, ZB)
Metals: 18:00 - 8:20
(GC)
Energies: 18:00 - 9:00
(CL, NG)
Agricultures: 20:00 - 9:30
(ZS, ZW)
Universal Ratio Trend Matrix [InvestorUnknown]The Universal Ratio Trend Matrix is designed for trend analysis on asset/asset ratios, supporting up to 40 different assets. Its primary purpose is to help identify which assets are outperforming others within a selection, providing a broad overview of market trends through a matrix of ratios. The indicator automatically expands the matrix based on the number of assets chosen, simplifying the process of comparing multiple assets in terms of performance.
Key features include the ability to choose from a narrow selection of indicators to perform the ratio trend analysis, allowing users to apply well-defined metrics to their comparison.
Drawback: Due to the computational intensity involved in calculating ratios across many assets, the indicator has a limitation related to loading speed. TradingView has time limits for calculations, and for users on the basic (free) plan, this could result in frequent errors due to exceeded time limits. To use the indicator effectively, users with any paid plans should run it on timeframes higher than 8h (the lowest timeframe on which it managed to load with 40 assets), as lower timeframes may not reliably load.
Indicators:
RSI_raw: Simple function to calculate the Relative Strength Index (RSI) of a source (asset price).
RSI_sma: Calculates RSI followed by a Simple Moving Average (SMA).
RSI_ema: Calculates RSI followed by an Exponential Moving Average (EMA).
CCI: Calculates the Commodity Channel Index (CCI).
Fisher: Implements the Fisher Transform to normalize prices.
Utility Functions:
f_remove_exchange_name: Strips the exchange name from asset tickers (e.g., "INDEX:BTCUSD" to "BTCUSD").
f_remove_exchange_name(simple string name) =>
string parts = str.split(name, ":")
string result = array.size(parts) > 1 ? array.get(parts, 1) : name
result
f_get_price: Retrieves the closing price of a given asset ticker using request.security().
f_constant_src: Checks if the source data is constant by comparing multiple consecutive values.
Inputs:
General settings allow users to select the number of tickers for analysis (used_assets) and choose the trend indicator (RSI, CCI, Fisher, etc.).
Table settings customize how trend scores are displayed in terms of text size, header visibility, highlighting options, and top-performing asset identification.
The script includes inputs for up to 40 assets, allowing the user to select various cryptocurrencies (e.g., BTCUSD, ETHUSD, SOLUSD) or other assets for trend analysis.
Price Arrays:
Price values for each asset are stored in variables (price_a1 to price_a40) initialized as na. These prices are updated only for the number of assets specified by the user (used_assets).
Trend scores for each asset are stored in separate arrays
// declare price variables as "na"
var float price_a1 = na, var float price_a2 = na, var float price_a3 = na, var float price_a4 = na, var float price_a5 = na
var float price_a6 = na, var float price_a7 = na, var float price_a8 = na, var float price_a9 = na, var float price_a10 = na
var float price_a11 = na, var float price_a12 = na, var float price_a13 = na, var float price_a14 = na, var float price_a15 = na
var float price_a16 = na, var float price_a17 = na, var float price_a18 = na, var float price_a19 = na, var float price_a20 = na
var float price_a21 = na, var float price_a22 = na, var float price_a23 = na, var float price_a24 = na, var float price_a25 = na
var float price_a26 = na, var float price_a27 = na, var float price_a28 = na, var float price_a29 = na, var float price_a30 = na
var float price_a31 = na, var float price_a32 = na, var float price_a33 = na, var float price_a34 = na, var float price_a35 = na
var float price_a36 = na, var float price_a37 = na, var float price_a38 = na, var float price_a39 = na, var float price_a40 = na
// create "empty" arrays to store trend scores
var a1_array = array.new_int(40, 0), var a2_array = array.new_int(40, 0), var a3_array = array.new_int(40, 0), var a4_array = array.new_int(40, 0)
var a5_array = array.new_int(40, 0), var a6_array = array.new_int(40, 0), var a7_array = array.new_int(40, 0), var a8_array = array.new_int(40, 0)
var a9_array = array.new_int(40, 0), var a10_array = array.new_int(40, 0), var a11_array = array.new_int(40, 0), var a12_array = array.new_int(40, 0)
var a13_array = array.new_int(40, 0), var a14_array = array.new_int(40, 0), var a15_array = array.new_int(40, 0), var a16_array = array.new_int(40, 0)
var a17_array = array.new_int(40, 0), var a18_array = array.new_int(40, 0), var a19_array = array.new_int(40, 0), var a20_array = array.new_int(40, 0)
var a21_array = array.new_int(40, 0), var a22_array = array.new_int(40, 0), var a23_array = array.new_int(40, 0), var a24_array = array.new_int(40, 0)
var a25_array = array.new_int(40, 0), var a26_array = array.new_int(40, 0), var a27_array = array.new_int(40, 0), var a28_array = array.new_int(40, 0)
var a29_array = array.new_int(40, 0), var a30_array = array.new_int(40, 0), var a31_array = array.new_int(40, 0), var a32_array = array.new_int(40, 0)
var a33_array = array.new_int(40, 0), var a34_array = array.new_int(40, 0), var a35_array = array.new_int(40, 0), var a36_array = array.new_int(40, 0)
var a37_array = array.new_int(40, 0), var a38_array = array.new_int(40, 0), var a39_array = array.new_int(40, 0), var a40_array = array.new_int(40, 0)
f_get_price(simple string ticker) =>
request.security(ticker, "", close)
// Prices for each USED asset
f_get_asset_price(asset_number, ticker) =>
if (used_assets >= asset_number)
f_get_price(ticker)
else
na
// overwrite empty variables with the prices if "used_assets" is greater or equal to the asset number
if barstate.isconfirmed // use barstate.isconfirmed to avoid "na prices" and calculation errors that result in empty cells in the table
price_a1 := f_get_asset_price(1, asset1), price_a2 := f_get_asset_price(2, asset2), price_a3 := f_get_asset_price(3, asset3), price_a4 := f_get_asset_price(4, asset4)
price_a5 := f_get_asset_price(5, asset5), price_a6 := f_get_asset_price(6, asset6), price_a7 := f_get_asset_price(7, asset7), price_a8 := f_get_asset_price(8, asset8)
price_a9 := f_get_asset_price(9, asset9), price_a10 := f_get_asset_price(10, asset10), price_a11 := f_get_asset_price(11, asset11), price_a12 := f_get_asset_price(12, asset12)
price_a13 := f_get_asset_price(13, asset13), price_a14 := f_get_asset_price(14, asset14), price_a15 := f_get_asset_price(15, asset15), price_a16 := f_get_asset_price(16, asset16)
price_a17 := f_get_asset_price(17, asset17), price_a18 := f_get_asset_price(18, asset18), price_a19 := f_get_asset_price(19, asset19), price_a20 := f_get_asset_price(20, asset20)
price_a21 := f_get_asset_price(21, asset21), price_a22 := f_get_asset_price(22, asset22), price_a23 := f_get_asset_price(23, asset23), price_a24 := f_get_asset_price(24, asset24)
price_a25 := f_get_asset_price(25, asset25), price_a26 := f_get_asset_price(26, asset26), price_a27 := f_get_asset_price(27, asset27), price_a28 := f_get_asset_price(28, asset28)
price_a29 := f_get_asset_price(29, asset29), price_a30 := f_get_asset_price(30, asset30), price_a31 := f_get_asset_price(31, asset31), price_a32 := f_get_asset_price(32, asset32)
price_a33 := f_get_asset_price(33, asset33), price_a34 := f_get_asset_price(34, asset34), price_a35 := f_get_asset_price(35, asset35), price_a36 := f_get_asset_price(36, asset36)
price_a37 := f_get_asset_price(37, asset37), price_a38 := f_get_asset_price(38, asset38), price_a39 := f_get_asset_price(39, asset39), price_a40 := f_get_asset_price(40, asset40)
Universal Indicator Calculation (f_calc_score):
This function allows switching between different trend indicators (RSI, CCI, Fisher) for flexibility.
It uses a switch-case structure to calculate the indicator score, where a positive trend is denoted by 1 and a negative trend by 0. Each indicator has its own logic to determine whether the asset is trending up or down.
// use switch to allow "universality" in indicator selection
f_calc_score(source, trend_indicator, int_1, int_2) =>
int score = na
if (not f_constant_src(source)) and source > 0.0 // Skip if you are using the same assets for ratio (for example BTC/BTC)
x = switch trend_indicator
"RSI (Raw)" => RSI_raw(source, int_1)
"RSI (SMA)" => RSI_sma(source, int_1, int_2)
"RSI (EMA)" => RSI_ema(source, int_1, int_2)
"CCI" => CCI(source, int_1)
"Fisher" => Fisher(source, int_1)
y = switch trend_indicator
"RSI (Raw)" => x > 50 ? 1 : 0
"RSI (SMA)" => x > 50 ? 1 : 0
"RSI (EMA)" => x > 50 ? 1 : 0
"CCI" => x > 0 ? 1 : 0
"Fisher" => x > x ? 1 : 0
score := y
else
score := 0
score
Array Setting Function (f_array_set):
This function populates an array with scores calculated for each asset based on a base price (p_base) divided by the prices of the individual assets.
It processes multiple assets (up to 40), calling the f_calc_score function for each.
// function to set values into the arrays
f_array_set(a_array, p_base) =>
array.set(a_array, 0, f_calc_score(p_base / price_a1, trend_indicator, int_1, int_2))
array.set(a_array, 1, f_calc_score(p_base / price_a2, trend_indicator, int_1, int_2))
array.set(a_array, 2, f_calc_score(p_base / price_a3, trend_indicator, int_1, int_2))
array.set(a_array, 3, f_calc_score(p_base / price_a4, trend_indicator, int_1, int_2))
array.set(a_array, 4, f_calc_score(p_base / price_a5, trend_indicator, int_1, int_2))
array.set(a_array, 5, f_calc_score(p_base / price_a6, trend_indicator, int_1, int_2))
array.set(a_array, 6, f_calc_score(p_base / price_a7, trend_indicator, int_1, int_2))
array.set(a_array, 7, f_calc_score(p_base / price_a8, trend_indicator, int_1, int_2))
array.set(a_array, 8, f_calc_score(p_base / price_a9, trend_indicator, int_1, int_2))
array.set(a_array, 9, f_calc_score(p_base / price_a10, trend_indicator, int_1, int_2))
array.set(a_array, 10, f_calc_score(p_base / price_a11, trend_indicator, int_1, int_2))
array.set(a_array, 11, f_calc_score(p_base / price_a12, trend_indicator, int_1, int_2))
array.set(a_array, 12, f_calc_score(p_base / price_a13, trend_indicator, int_1, int_2))
array.set(a_array, 13, f_calc_score(p_base / price_a14, trend_indicator, int_1, int_2))
array.set(a_array, 14, f_calc_score(p_base / price_a15, trend_indicator, int_1, int_2))
array.set(a_array, 15, f_calc_score(p_base / price_a16, trend_indicator, int_1, int_2))
array.set(a_array, 16, f_calc_score(p_base / price_a17, trend_indicator, int_1, int_2))
array.set(a_array, 17, f_calc_score(p_base / price_a18, trend_indicator, int_1, int_2))
array.set(a_array, 18, f_calc_score(p_base / price_a19, trend_indicator, int_1, int_2))
array.set(a_array, 19, f_calc_score(p_base / price_a20, trend_indicator, int_1, int_2))
array.set(a_array, 20, f_calc_score(p_base / price_a21, trend_indicator, int_1, int_2))
array.set(a_array, 21, f_calc_score(p_base / price_a22, trend_indicator, int_1, int_2))
array.set(a_array, 22, f_calc_score(p_base / price_a23, trend_indicator, int_1, int_2))
array.set(a_array, 23, f_calc_score(p_base / price_a24, trend_indicator, int_1, int_2))
array.set(a_array, 24, f_calc_score(p_base / price_a25, trend_indicator, int_1, int_2))
array.set(a_array, 25, f_calc_score(p_base / price_a26, trend_indicator, int_1, int_2))
array.set(a_array, 26, f_calc_score(p_base / price_a27, trend_indicator, int_1, int_2))
array.set(a_array, 27, f_calc_score(p_base / price_a28, trend_indicator, int_1, int_2))
array.set(a_array, 28, f_calc_score(p_base / price_a29, trend_indicator, int_1, int_2))
array.set(a_array, 29, f_calc_score(p_base / price_a30, trend_indicator, int_1, int_2))
array.set(a_array, 30, f_calc_score(p_base / price_a31, trend_indicator, int_1, int_2))
array.set(a_array, 31, f_calc_score(p_base / price_a32, trend_indicator, int_1, int_2))
array.set(a_array, 32, f_calc_score(p_base / price_a33, trend_indicator, int_1, int_2))
array.set(a_array, 33, f_calc_score(p_base / price_a34, trend_indicator, int_1, int_2))
array.set(a_array, 34, f_calc_score(p_base / price_a35, trend_indicator, int_1, int_2))
array.set(a_array, 35, f_calc_score(p_base / price_a36, trend_indicator, int_1, int_2))
array.set(a_array, 36, f_calc_score(p_base / price_a37, trend_indicator, int_1, int_2))
array.set(a_array, 37, f_calc_score(p_base / price_a38, trend_indicator, int_1, int_2))
array.set(a_array, 38, f_calc_score(p_base / price_a39, trend_indicator, int_1, int_2))
array.set(a_array, 39, f_calc_score(p_base / price_a40, trend_indicator, int_1, int_2))
a_array
Conditional Array Setting (f_arrayset):
This function checks if the number of used assets is greater than or equal to a specified number before populating the arrays.
// only set values into arrays for USED assets
f_arrayset(asset_number, a_array, p_base) =>
if (used_assets >= asset_number)
f_array_set(a_array, p_base)
else
na
Main Logic
The main logic initializes arrays to store scores for each asset. Each array corresponds to one asset's performance score.
Setting Trend Values: The code calls f_arrayset for each asset, populating the respective arrays with calculated scores based on the asset prices.
Combining Arrays: A combined_array is created to hold all the scores from individual asset arrays. This array facilitates further analysis, allowing for an overview of the performance scores of all assets at once.
// create a combined array (work-around since pinescript doesn't support having array of arrays)
var combined_array = array.new_int(40 * 40, 0)
if barstate.islast
for i = 0 to 39
array.set(combined_array, i, array.get(a1_array, i))
array.set(combined_array, i + (40 * 1), array.get(a2_array, i))
array.set(combined_array, i + (40 * 2), array.get(a3_array, i))
array.set(combined_array, i + (40 * 3), array.get(a4_array, i))
array.set(combined_array, i + (40 * 4), array.get(a5_array, i))
array.set(combined_array, i + (40 * 5), array.get(a6_array, i))
array.set(combined_array, i + (40 * 6), array.get(a7_array, i))
array.set(combined_array, i + (40 * 7), array.get(a8_array, i))
array.set(combined_array, i + (40 * 8), array.get(a9_array, i))
array.set(combined_array, i + (40 * 9), array.get(a10_array, i))
array.set(combined_array, i + (40 * 10), array.get(a11_array, i))
array.set(combined_array, i + (40 * 11), array.get(a12_array, i))
array.set(combined_array, i + (40 * 12), array.get(a13_array, i))
array.set(combined_array, i + (40 * 13), array.get(a14_array, i))
array.set(combined_array, i + (40 * 14), array.get(a15_array, i))
array.set(combined_array, i + (40 * 15), array.get(a16_array, i))
array.set(combined_array, i + (40 * 16), array.get(a17_array, i))
array.set(combined_array, i + (40 * 17), array.get(a18_array, i))
array.set(combined_array, i + (40 * 18), array.get(a19_array, i))
array.set(combined_array, i + (40 * 19), array.get(a20_array, i))
array.set(combined_array, i + (40 * 20), array.get(a21_array, i))
array.set(combined_array, i + (40 * 21), array.get(a22_array, i))
array.set(combined_array, i + (40 * 22), array.get(a23_array, i))
array.set(combined_array, i + (40 * 23), array.get(a24_array, i))
array.set(combined_array, i + (40 * 24), array.get(a25_array, i))
array.set(combined_array, i + (40 * 25), array.get(a26_array, i))
array.set(combined_array, i + (40 * 26), array.get(a27_array, i))
array.set(combined_array, i + (40 * 27), array.get(a28_array, i))
array.set(combined_array, i + (40 * 28), array.get(a29_array, i))
array.set(combined_array, i + (40 * 29), array.get(a30_array, i))
array.set(combined_array, i + (40 * 30), array.get(a31_array, i))
array.set(combined_array, i + (40 * 31), array.get(a32_array, i))
array.set(combined_array, i + (40 * 32), array.get(a33_array, i))
array.set(combined_array, i + (40 * 33), array.get(a34_array, i))
array.set(combined_array, i + (40 * 34), array.get(a35_array, i))
array.set(combined_array, i + (40 * 35), array.get(a36_array, i))
array.set(combined_array, i + (40 * 36), array.get(a37_array, i))
array.set(combined_array, i + (40 * 37), array.get(a38_array, i))
array.set(combined_array, i + (40 * 38), array.get(a39_array, i))
array.set(combined_array, i + (40 * 39), array.get(a40_array, i))
Calculating Sums: A separate array_sums is created to store the total score for each asset by summing the values of their respective score arrays. This allows for easy comparison of overall performance.
Ranking Assets: The final part of the code ranks the assets based on their total scores stored in array_sums. It assigns a rank to each asset, where the asset with the highest score receives the highest rank.
// create array for asset RANK based on array.sum
var ranks = array.new_int(used_assets, 0)
// for loop that calculates the rank of each asset
if barstate.islast
for i = 0 to (used_assets - 1)
int rank = 1
for x = 0 to (used_assets - 1)
if i != x
if array.get(array_sums, i) < array.get(array_sums, x)
rank := rank + 1
array.set(ranks, i, rank)
Dynamic Table Creation
Initialization: The table is initialized with a base structure that includes headers for asset names, scores, and ranks. The headers are set to remain constant, ensuring clarity for users as they interpret the displayed data.
Data Population: As scores are calculated for each asset, the corresponding values are dynamically inserted into the table. This is achieved through a loop that iterates over the scores and ranks stored in the combined_array and array_sums, respectively.
Automatic Extending Mechanism
Variable Asset Count: The code checks the number of assets defined by the user. Instead of hardcoding the number of rows in the table, it uses a variable to determine the extent of the data that needs to be displayed. This allows the table to expand or contract based on the number of assets being analyzed.
Dynamic Row Generation: Within the loop that populates the table, the code appends new rows for each asset based on the current asset count. The structure of each row includes the asset name, its score, and its rank, ensuring that the table remains consistent regardless of how many assets are involved.
// Automatically extending table based on the number of used assets
var table table = table.new(position.bottom_center, 50, 50, color.new(color.black, 100), color.white, 3, color.white, 1)
if barstate.islast
if not hide_head
table.cell(table, 0, 0, "Universal Ratio Trend Matrix", text_color = color.white, bgcolor = #010c3b, text_size = fontSize)
table.merge_cells(table, 0, 0, used_assets + 3, 0)
if not hide_inps
table.cell(table, 0, 1,
text = "Inputs: You are using " + str.tostring(trend_indicator) + ", which takes: " + str.tostring(f_get_input(trend_indicator)),
text_color = color.white, text_size = fontSize), table.merge_cells(table, 0, 1, used_assets + 3, 1)
table.cell(table, 0, 2, "Assets", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, x + 1, 2, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = #010c3b, text_size = fontSize)
table.cell(table, 0, x + 3, text = str.tostring(array.get(assets, x)), text_color = color.white, bgcolor = f_asset_col(array.get(ranks, x)), text_size = fontSize)
for r = 0 to (used_assets - 1)
for c = 0 to (used_assets - 1)
table.cell(table, c + 1, r + 3, text = str.tostring(array.get(combined_array, c + (r * 40))),
text_color = hl_type == "Text" ? f_get_col(array.get(combined_array, c + (r * 40))) : color.white, text_size = fontSize,
bgcolor = hl_type == "Background" ? f_get_col(array.get(combined_array, c + (r * 40))) : na)
for x = 0 to (used_assets - 1)
table.cell(table, x + 1, x + 3, "", bgcolor = #010c3b)
table.cell(table, used_assets + 1, 2, "", bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, used_assets + 1, x + 3, "==>", text_color = color.white)
table.cell(table, used_assets + 2, 2, "SUM", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
table.cell(table, used_assets + 3, 2, "RANK", text_color = color.white, text_size = fontSize, bgcolor = #010c3b)
for x = 0 to (used_assets - 1)
table.cell(table, used_assets + 2, x + 3,
text = str.tostring(array.get(array_sums, x)),
text_color = color.white, text_size = fontSize,
bgcolor = f_highlight_sum(array.get(array_sums, x), array.get(ranks, x)))
table.cell(table, used_assets + 3, x + 3,
text = str.tostring(array.get(ranks, x)),
text_color = color.white, text_size = fontSize,
bgcolor = f_highlight_rank(array.get(ranks, x)))
SMA, VWAP with Buy/Sell Signals - First Signal OnlyIndicator: SMA, VWAP with First Buy/Sell Signals
Overview:
This indicator plots two Simple Moving Averages (SMA 20 and SMA 200) and the Volume-Weighted Average Price (VWAP) on the chart, with fully customizable colors and line thickness. Additionally, it provides buy and sell signals based on the price action relative to these indicators.
Buy Signal:
A buy signal is generated when a green candle (bullish candle) closes above the SMA 20, SMA 200, and VWAP without touching them (i.e., the low of the candle is above all three). This signal will only be plotted for the first such candle of the day to avoid signal clutter.
Sell Signal:
A sell signal is generated when a candle closes below the SMA 20, SMA 200, and VWAP without touching them (i.e., the high of the candle is below all three). Similar to the buy signal, it will only be plotted for the first qualifying candle of the day.
Customization:
SMAs and VWAP: Users can adjust the lengths, colors, and line thickness of the SMAs and VWAP to suit their preferences.
Signal Shape: You can choose from different shapes (arrow, circle, or cross) to represent the buy and sell signals on the chart.
Key Features:
First Candle Only: Both buy and sell signals are generated only for the first candle that satisfies the conditions, ensuring clean and actionable signals.
Visual Customization: Full control over the appearance of the indicator, including signal shapes and line properties.
Works Across Assets: This indicator is applicable to any asset (stocks, forex, crypto) where price action relative to moving averages and VWAP is important.
Sessions Full Markets [TradingFinder] Forex Stocks Index 7 Time🔵 Introduction
In global financial markets, particularly in FOREX and stocks, precise timing of trading sessions plays a crucial role in the success of traders. Each trading session—Asian, European, and American—has its own unique characteristics in terms of volatility and trading volume.
The Asian session (Tokyo), Sydney session, Shanghai session, European session (London and Frankfurt), and American session (New York AM and New York PM) are examples of these trading sessions, each of which opens and closes at specific times.
This session indicator also includes a Time Convertor, enabling users to view FOREX market hours based on GMT, UTC, EST, and local time. Another valuable feature of this indicator is the automatic detection of Daylight Saving Time (DST), which automatically applies time changes for the New York, London, and Sydney sessions.
🔵 How to Use
The indicator also displays session times based on the exact opening and closing times for each geographic region. Users can utilize this indicator to view trading hours either locally or in UTC time, and if needed, set their own custom trading times.
Additionally, the session information table includes the start and end times of each session and whether they are open or closed. This functionality helps traders make better trading decisions by using accurate and precise time data.
Key Features of the Session Indicator
The session indicator is a versatile and advanced tool that provides several unique features for traders.
Some of these features are :
• Automatic Daylight Saving Time (DST) Detection : This indicator dynamically detects Daylight Saving Time (DST) changes for various trading sessions, including New York, London, and Sydney, without requiring manual adjustments. This feature allows traders to manage their trades without worrying about time changes.
Below are the start and end dates for DST in the New York, London, and Sydney trading sessions :
1. New York :
Start of DST: Second Sunday of March, at 2:00 AM.
End of DST: First Sunday of November, at 2:00 AM
2. London :
Start of DST: Last Sunday of March, at 1:00 AM.
End of DST: Last Sunday of October, at 2:00 AM.
3. Sydney :
Start of DST: First Sunday of October, at 2:00 AM.
End of DST: First Sunday of April, at 3:00 AM.
• Session Display Based on Different Time Zones : The session indicator allows users to view trading times based on different time zones, such as UTC, the local time of each market, or the user’s local time. This feature is especially useful for traders operating in diverse geographic regions.
• Custom Trading Time Setup : Another notable feature of this indicator is the ability to set custom trading times. Traders can adjust their own trading times according to their personal strategies and benefit from this flexibility.
• Session Information Table : The session indicator provides a complete information table that includes the exact start and end times of each trading session and whether they are open or closed. This table helps users simultaneously and accurately monitor the status of all trading sessions and make better trading decisions.
🟣 Session Trading Hours Based on Market Mode and Time Zones
The session indicator provides precise information on the start and end times of trading sessions.
These times are adjusted based on different market modes (FOREX, stocks, and TFlab suggestions) and time zones (UTC and local time) :
🟣 (FOREX Session Time) Forex Market Mode
• Sessions in UTC (DST inactive) :
Sydney: 22:00 - 06:00
Tokyo: 23:00 - 07:00
Shanghai: 01:00 - 09:00
Asia: 22:00 - 07:00
Europe: 07:00 - 16:00
London: 08:00 - 16:00
New York: 13:00 - 21:00
• Sessions in UTC (DST active) :
Sydney: 21:00 - 05:00
Tokyo: 23:00 - 07:00
Shanghai: 01:00 - 09:00
Asia: 21:00 - 07:00
Europe: 06:00 - 15:00
London: 07:00 - 15:00
New York: 12:00 - 20:00
• Sessions in Local Time :
Sydney: 08:00 - 16:00
Tokyo: 08:00 - 16:00
Shanghai: 09:00 - 17:00
Asia: 22:00 - 07:00
Europe: 07:00 - 16:00
London: 08:00 - 16:00
New York: 08:00 - 16:00
🟣 Stock Market Trading Hours (Stock Market Mode)
• Sessions in UTC (DST inactive) :
Sydney: 00:00 - 06:00
Asia: 00:00 - 06:00
Europe: 07:00 - 16:30
London: 08:00 - 16:30
New York: 14:30 - 21:00
Tokyo: 00:00 - 06:00
Shanghai: 01:30 - 07:00
• Sessions in UTC (DST active) :
Sydney: 23:00 - 05:00
Asia: 23:00 - 06:00
Europe: 06:00 - 15:30
London: 07:00 - 15:30
New York: 13:30 - 20:00
Tokyo: 00:00 - 06:00
Shanghai: 01:30 - 07:00
• Sessions in Local Time:
Sydney: 10:00 - 16:00
Tokyo: 09:00 - 15:00
Shanghai: 09:30 - 15:00
Asia: 00:00 - 06:00
Europe: 07:00 - 16:30
London: 08:00 - 16:30
New York: 09:30 - 16:00
🟣 TFlab Suggestion Mode
• Sessions in UTC (DST inactive) :
Sydney: 23:00 - 05:00
Tokyo: 00:00 - 06:00
Shanghai: 01:00 - 09:00
Asia: 23:00 - 06:00
Europe: 07:00 - 16:00
London: 08:00 - 16:00
New York: 13:00 - 21:00
• Sessions in UTC (DST active) :
Sydney: 22:00 - 04:00
Tokyo: 00:00 - 06:00
Shanghai: 01:00 - 09:00
Asia: 22:00 - 06:00
Europe: 06:00 - 15:00
London: 07:00 - 15:00
New York: 12:00 - 20:00
• Sessions in Local Time :
Sydney: 09:00 - 16:00
Tokyo: 09:00 - 15:00
Shanghai: 09:00 - 17:00
Asia: 23:00 - 06:00
Europe: 07:00 - 16:00
London: 08:00 - 16:00
New York: 08:00 - 16:00
🔵 Setting
Using the session indicator is straightforward and practical. Users can add this indicator to their trading chart and take advantage of its features.
The usage steps are as follows :
Selecting Market Mode : The user can choose one of the three main modes.
Forex Market Mode: Displays the forex market trading hours.
oStock Market Mode: Displays the trading hours of stock exchanges.
Custom Mode: Allows the user to set trading hours based on their needs.
TFlab Suggestion Mode: Displays the higher volume hours of the forex market in Asia.
Setting the Time Zone : 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
Displaying Comprehensive Session Information : The session information table includes the opening and closing times of each session and whether they are open or closed. This table helps users monitor all sessions at a glance and precisely set the best time for entering and exiting trades.
🔵Conclusion
The session indicator is a highly efficient and essential tool for active traders in the FOREX and stock markets. With its unique features, such as automatic DST detection and the ability to display sessions based on different time zones, the session indicator helps traders to precisely and efficiently adjust their trading activities.
This indicator not only shows users the exact opening and closing times of sessions, but by providing a session status table, it helps traders identify the best times to enter and exit trades. Moreover, the ability to set custom trading times allows traders to easily personalize their trading schedules according to their strategies.
In conclusion, using the session indicator ensures that traders are continuously and accurately informed of time changes and the opening and closing hours of markets, eliminating the need for manual updates to align with DST changes. These features enable traders to optimize their trading strategies with greater confidence and up-to-date information, allowing them to capitalize on opportunities in the market.
XAU/USD Strategy with Correct ADX and Bollinger Bands Fill1. *Indicators Used*:
- *Exponential Moving Averages (EMAs)*: Two EMAs (20-period and 50-period) are used to identify the trend direction and potential entry points based on crossovers.
- *Relative Strength Index (RSI)*: A momentum oscillator that measures the speed and change of price movements. It identifies overbought and oversold conditions.
- *Bollinger Bands*: These consist of a middle line (simple moving average) and two outer bands (standard deviations away from the middle). They help to identify price volatility and potential reversal points.
- *Average Directional Index (ADX)*: This indicator quantifies trend strength. It's derived from the Directional Movement Index (DMI) and helps confirm the presence of a strong trend.
- *Average True Range (ATR)*: Used to calculate position size based on volatility, ensuring that trades align with the trader's risk tolerance.
2. *Entry Conditions*:
- *Long Entry*:
- The 20 EMA crosses above the 50 EMA (indicating a potential bullish trend).
- The RSI is below the oversold level (30), suggesting the asset may be undervalued.
- The price is below the lower Bollinger Band, indicating potential price reversal.
- The ADX is above a specified threshold (25), confirming that there is sufficient trend strength.
- *Short Entry*:
- The 20 EMA crosses below the 50 EMA (indicating a potential bearish trend).
- The RSI is above the overbought level (70), suggesting the asset may be overvalued.
- The price is above the upper Bollinger Band, indicating potential price reversal.
- The ADX is above the specified threshold (25), confirming trend strength.
3. *Position Sizing*:
- The script calculates the position size dynamically based on the trader's risk per trade (expressed as a percentage of the total capital) and the ATR. This ensures that the trader does not risk more than the specified percentage on any single trade, adjusting the position size according to market volatility.
4. *Exit Conditions*:
- The strategy uses a trailing stop-loss mechanism to secure profits as the price moves in the trader's favor. The trailing stop is set at a percentage (1.5% by default) below the highest price reached since entry for long positions and above the lowest price for short positions.
- Additionally, if the RSI crosses back above the overbought level while in a long position or below the oversold level while in a short position, the position is closed to prevent losses.
5. *Alerts*:
- Alerts are set to notify the trader when a buy or sell condition is met based on the strategy's rules. This allows for timely execution of trades.
### Summary
This strategy aims to capture significant price movements in the XAU/USD market by combining trend-following (EMAs, ADX) and momentum indicators (RSI, Bollinger Bands). The dynamic position sizing based on ATR helps manage risk effectively. By implementing trailing stops and alert mechanisms, the strategy enhances the trader's ability to act quickly on opportunities while mitigating potential losses.
Prometheus StochasticThe Stochastic indicator is a popular indicator developed in the 1950s. It is designed to identify overbought and oversold scenarios on different assets. A value above 80 is considered overbought and a value below 20 is considered oversold.
The formula is as follows:
%k = ((Close - Low_i) / (High_i / Low_i)) * 100
Low_i and High_i represent the lowest low and highest high of the selected period.
The Prometheus version takes a slightly different approach:
%k = ((High - Lowest_Close_i) / (High_i / Low_i)) * 100
Using the Current High minus the Lowest Close provides us with a more robust range that can be slightly more sensitive to moves and provide a different perspective.
Code:
stoch_func(src_close, src_high, src_low, length) =>
100 * (src_high - ta.lowest(src_close, length)) / (ta.highest(src_high, length) - ta.lowest(src_low, length))
This is the function that returns our Stochastic indicator.
What period do we use for the calculation? Let Prometheus handle that, we utilize a Sum of Squared Error calculation to find what lookback values can be most useful for a trader. How we do it is we calculate a Simple Moving Average or SMA and the indicator using a lot of different bars back values. Then if there is an event, characterized by the indicator crossing above 80 or below 20, we subtract the close by the SMA and square it. If there is no event we return a big value, we want the error to be as small as possible. Because we loop over every value for bars back, we get the value with the smallest error. We also do this for the smoothing values.
// Function to calculate SSE for a given combination of N, K, and D
sse_calc(_N, _K, _D) =>
SMA = ta.sma(close, _N)
sf = stoch_func(close, high, low, _N)
k = ta.sma(sf, _K)
d = ta.sma(k, _D)
var float error = na
if ta.crossover(d, 80) or ta.crossunder(d, 20)
error := math.pow(close - SMA, 2)
else
error := 999999999999999999999999999999999999999
error
var int best_N = na
var int best_K = na
var int best_D = na
var float min_SSE = na
// Loop through all combinations of N, K, and D
for N in N_range
for K in K_range
for D in D_range
sse = sse_calc(N, K, D)
if (na(min_SSE) or sse < min_SSE)
min_SSE := sse
best_N := N
best_K := K
best_D := D
int N_opt = na
int K_opt = na
int D_opt = na
if c_lkb_bool == false
N_opt := best_N
K_opt := best_K
D_opt := best_D
This is the section where the best lookback values are calculated.
We provide the option to use this self optimizer or to use your own lookback values.
Here is an example on the daily AMEX:SPY chart. The top Stochastic is the value with the SSE calculation, the bottom is with a fixed 14, 1, 3 input values. We see in the candles with boxes where some potential differences and trades may be.
This is another comparison of the SSE functionality and the fixed lookbacks on the NYSE:PLTR 1 day chart.
Differences may be more apparent on lower time frame charts.
We encourage traders to not follow indicators blindly, none are 100% accurate. SSE does not guarantee that the values generated will be the best for a given moment in time. Please comment on any desired updates, all criticism is welcome!
RSI Trend Following StrategyOverview
The RSI Trend Following Strategy utilizes Relative Strength Index (RSI) to enter the trade for the potential trend continuation. It uses Stochastic indicator to check is the price is not in overbought territory and the MACD to measure the current price momentum. Moreover, it uses the 200-period EMA to filter the counter trend trades with the higher probability. The strategy opens only long trades.
Unique Features
Dynamic stop-loss system: Instead of fixed stop-loss level strategy utilizes average true range (ATR) multiplied by user given number subtracted from the position entry price as a dynamic stop loss level.
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Two layers trade filtering system: Strategy utilizes MACD and Stochastic indicators measure the current momentum and overbought condition and use 200-period EMA to filter trades against major trend.
Trailing take profit level: After reaching the trailing profit activation level script activates the trailing of long trade using EMA. More information in methodology.
Wide opportunities for strategy optimization: Flexible strategy settings allows users to optimize the strategy entries and exits for chosen trading pair and time frame.
Methodology
The strategy opens long trade when the following price met the conditions:
RSI is above 50 level.
MACD line shall be above the signal line
Both lines of Stochastic shall be not higher than 80 (overbought territory)
Candle’s low shall be above the 200 period EMA
When long trade is executed, strategy set the stop-loss level at the price ATR multiplied by user-given value below the entry price. This level is recalculated on every next candle close, adjusting to the current market volatility.
At the same time strategy set up the trailing stop validation level. When the price crosses the level equals entry price plus ATR multiplied by user-given value script starts to trail the price with trailing EMA(by default = 20 period). If price closes below EMA long trade is closed. When the trailing starts, script prints the label “Trailing Activated”.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.75)
ATR Trailing Profit Activation Level (by default = 2.25)
MACD Fast Length (by default = 12, period of averaging fast MACD line)
MACD Fast Length (by default = 26, period of averaging slow MACD line)
MACD Signal Smoothing (by default = 9, period of smoothing MACD signal line)
Oscillator MA Type (by default = EMA, available options: SMA, EMA)
Signal Line MA Type (by default = EMA, available options: SMA, EMA)
RSI Length (by default = 14, period for RSI calculation)
Trailing EMA Length (by default = 20, period for EMA, which shall be broken close the trade after trailing profit activation)
Justification of Methodology
This trading strategy is designed to leverage a combination of technical indicators—Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Stochastic Oscillator, and the 200-period Exponential Moving Average (EMA)—to determine optimal entry points for long trades. Additionally, the strategy uses the Average True Range (ATR) for dynamic risk management to adapt to varying market conditions. Let's look in details for which purpose each indicator is used for and why it is used in this combination.
Relative Strength Index (RSI) is a momentum indicator used in technical analysis to measure the speed and change of price movements in a financial market. It helps traders identify whether an asset is potentially overbought (overvalued) or oversold (undervalued), which can indicate a potential reversal or continuation of the current trend.
How RSI Works? RSI tracks the strength of recent price changes. It compares the average gains and losses over a specific period (usually 14 periods) to assess the momentum of an asset. Average gain is the average of all positive price changes over the chosen period. It reflects how much the price has typically increased during upward movements. Average loss is the average of all negative price changes over the same period. It reflects how much the price has typically decreased during downward movements.
RSI calculates these average gains and losses and compares them to create a value between 0 and 100. If the RSI value is above 70, the asset is generally considered overbought, meaning it might be due for a price correction or reversal downward. Conversely, if the RSI value is below 30, the asset is considered oversold, suggesting it could be poised for an upward reversal or recovery. RSI is a useful tool for traders to determine market conditions and make informed decisions about entering or exiting trades based on the perceived strength or weakness of an asset's price movements.
This strategy uses RSI as a short-term trend approximation. If RSI crosses over 50 it means that there is a high probability of short-term trend change from downtrend to uptrend. Therefore RSI above 50 is our first trend filter to look for a long position.
The MACD (Moving Average Convergence Divergence) is a popular momentum and trend-following indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in an asset's price.
The MACD consists of three components:
MACD Line: This is the difference between a short-term Exponential Moving Average (EMA) and a long-term EMA, typically calculated as: MACD Line = 12 period EMA − 26 period EMA
Signal Line: This is a 9-period EMA of the MACD Line, which helps to identify buy or sell signals. When the MACD Line crosses above the Signal Line, it can be a bullish signal (suggesting a buy); when it crosses below, it can be a bearish signal (suggesting a sell).
Histogram: The histogram shows the difference between the MACD Line and the Signal Line, visually representing the momentum of the trend. Positive histogram values indicate increasing bullish momentum, while negative values indicate increasing bearish momentum.
This strategy uses MACD as a second short-term trend filter. When MACD line crossed over the signal line there is a high probability that uptrend has been started. Therefore MACD line above signal line is our additional short-term trend filter. In conjunction with RSI it decreases probability of following false trend change signals.
The Stochastic Indicator is a momentum oscillator that compares a security's closing price to its price range over a specific period. It's used to identify overbought and oversold conditions. The indicator ranges from 0 to 100, with readings above 80 indicating overbought conditions and readings below 20 indicating oversold conditions.
It consists of two lines:
%K: The main line, calculated using the formula (CurrentClose−LowestLow)/(HighestHigh−LowestLow)×100 . Highest and lowest price taken for 14 periods.
%D: A smoothed moving average of %K, often used as a signal line.
This strategy uses stochastic to define the overbought conditions. The logic here is the following: we want to avoid long trades in the overbought territory, because when indicator reaches it there is a high probability that the potential move is gonna be restricted.
The 200-period EMA is a widely recognized indicator for identifying the long-term trend direction. The strategy only trades in the direction of this primary trend to increase the probability of successful trades. For instance, when the price is above the 200 EMA, only long trades are considered, aligning with the overarching trend direction.
Therefore, strategy uses combination of RSI and MACD to increase the probability that price now is in short-term uptrend, Stochastic helps to avoid the trades in the overbought (>80) territory. To increase the probability of opening long trades in the direction of a main trend and avoid local bounces we use 200 period EMA.
ATR is used to adjust the strategy risk management to the current market volatility. If volatility is low, we don’t need the large stop loss to understand the there is a high probability that we made a mistake opening the trade. User can setup the settings ATR Stop Loss and ATR Trailing Profit Activation Level to realize his own risk to reward preferences, but the unique feature of a strategy is that after reaching trailing profit activation level strategy is trying to follow the trend until it is likely to be finished instead of using fixed risk management settings. It allows sometimes to be involved in the large movements.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.08.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 30%
Maximum Single Position Loss: -3.94%
Maximum Single Profit: +15.78%
Net Profit: +1359.21 USDT (+13.59%)
Total Trades: 111 (36.04% win rate)
Profit Factor: 1.413
Maximum Accumulated Loss: 625.02 USDT (-5.85%)
Average Profit per Trade: 12.25 USDT (+0.40%)
Average Trade Duration: 40 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 2h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Uptrick: SMA Pivot Marker### Uptrick: SMA Pivot Marker (SPM) — Extensive Guide
#### Introduction
The **Uptrick: SMA Pivot Marker (SPM)** is a sophisticated technical analysis tool crafted by Uptrick to help traders interpret market trends and identify key price levels where significant reversals might occur. By integrating the principles of the Simple Moving Average (SMA) with pivot point analysis, the SPM offers a comprehensive approach to understanding market dynamics. This extensive guide explores the purpose, functionality, and practical applications of the SPM, providing an in-depth analysis of its features, settings, and usage across various trading strategies.
#### Purpose of the SPM
The **SMA Pivot Marker (SPM)** aims to enhance trading strategies by offering a dual approach to market analysis:
1. **Trend Identification**:
- **Objective**: To discern the prevailing market direction and guide trading decisions based on the overall trend.
- **Method**: Utilizes the SMA to smooth out price fluctuations, providing a clearer picture of the trend. This helps traders align their trades with the market's direction, increasing the probability of successful trades.
2. **Pivot Point Detection**:
- **Objective**: To identify key levels where the price is likely to reverse, providing potential support and resistance zones.
- **Method**: Calculates and marks pivot highs and lows, which are significant price points where previous trends have reversed. These levels are used to predict future price movements and establish trading strategies.
3. **Trend Change Alerts**:
- **Objective**: To notify traders of potential shifts in market direction, enabling timely adjustments to trading positions.
- **Method**: Detects and highlights crossover and crossunder points of the smoothed line, indicating possible trend changes. This helps traders react promptly to changing market conditions.
#### Detailed Functionality
1. **Smoothing Line Calculation**:
- **Simple Moving Average (SMA)**:
- **Definition**: The SMA is a type of moving average that calculates the average of a security’s price over a specified number of periods. It smooths out price data to filter out short-term fluctuations and highlight the longer-term trend.
- **Calculation**: The SMA is computed by summing the closing prices of the chosen number of periods and then dividing by the number of periods. For example, a 20-period SMA adds the closing prices for the past 20 periods and divides by 20.
- **Purpose**: The SMA helps in identifying the direction of the trend. A rising SMA indicates an uptrend, while a falling SMA indicates a downtrend. This smoothing helps traders to avoid being misled by short-term price noise.
2. **Pivot Points Calculation**:
- **Pivot Highs and Lows**:
- **Definition**: Pivot points are significant price levels where a market trend is likely to reverse. A pivot high is the highest price over a certain period, surrounded by lower prices on both sides, while a pivot low is the lowest price surrounded by higher prices.
- **Calculation**: The SPM calculates pivot points based on a user-defined lookback period. For instance, if the lookback period is set to 3, the indicator will find the highest and lowest prices within the past 3 periods and mark these points.
- **Purpose**: Pivot points are used to identify potential support and resistance levels. Traders often use these levels to set entry and exit points, stop-loss orders, and to gauge market sentiment.
3. **Visualization**:
- **Smoothed Line Plot**:
- **Description**: The smoothed line, calculated using the SMA, is plotted on the chart to provide a visual representation of the trend. This line adjusts its color based on the trend direction, helping traders quickly assess the market condition.
- **Color Coding**: The smoothed line is colored green (upColor) when it is rising, indicating a bullish trend, and red (downColor) when it is falling, indicating a bearish trend. This color-coding helps traders visually differentiate between uptrends and downtrends.
- **Line Width**: The width of the line can be adjusted to improve visibility. A thicker line may be more noticeable, while a thinner line might provide a cleaner look on the chart.
- **Pivot Markers**:
- **Description**: Pivot highs and lows are marked on the chart with lines and labels. These markers help in visually identifying significant price levels.
- **Color and Labels**: Pivot highs are represented with green lines and labels ("H"), while pivot lows are marked with red lines and labels ("L"). This color scheme and labeling make it easy to distinguish between resistance (highs) and support (lows).
4. **Trend Change Detection**:
- **Trend Up**:
- **Detection**: The indicator identifies an upward trend change when the smoothed line crosses above its previous value. This crossover suggests a potential shift from a downtrend to an uptrend.
- **Usage**: Traders can interpret this signal as a potential buying opportunity or an indication to review and possibly adjust their trading positions to align with the new uptrend.
- **Trend Down**:
- **Detection**: A downward trend change is detected when the smoothed line crosses below its previous value. This crossunder indicates a potential shift from an uptrend to a downtrend.
- **Usage**: This signal can be used to consider selling opportunities or to reassess long positions in light of the emerging downtrend.
#### User Inputs
1. **Smoothing Period**:
- **Description**: This input determines the number of periods over which the SMA is calculated. It directly affects the smoothness of the line and the sensitivity of trend detection.
- **Range**: The smoothing period can be set to any integer value greater than or equal to 1. There is no specified upper limit, offering flexibility for various trading styles.
- **Default Value**: The default smoothing period is 20, which is a common choice for medium-term trend analysis.
- **Impact**: A longer smoothing period results in a smoother line, filtering out more noise and highlighting long-term trends. A shorter period makes the line more responsive to recent price changes, which can be useful for short-term trading strategies.
2. **Pivot Lookback**:
- **Description**: This input specifies the number of periods used to calculate the pivot highs and lows. It influences the sensitivity of pivot point detection and the relevance of the identified levels.
- **Range**: The pivot lookback period can be set to any integer value greater than or equal to 1, with no upper limit. Traders can adjust this parameter based on their trading timeframe and preferences.
- **Default Value**: The default lookback period is 3, which provides a balance between detecting significant pivots and avoiding excessive noise.
- **Impact**: A longer lookback period generates more stable pivot points, suitable for identifying long-term support and resistance levels. A shorter lookback period results in more frequent and recent pivot points, useful for intraday trading and quick responses to price changes.
#### Applications for Different Traders
1. **Trend Followers**:
- **Using the SMA**: Trend followers utilize the smoothed line to gauge the direction of the market. By aligning trades with the direction of the SMA, traders can capitalize on sustained trends and improve their chances of success.
- **Trend Change Alerts**: The trend change markers alert trend followers to potential shifts in market direction. These alerts help traders make timely decisions to enter or exit positions, ensuring they stay aligned with the prevailing trend.
2. **Reversal Traders**:
- **Pivot Points**: Reversal traders focus on pivot highs and lows to identify potential reversal points in the market. These points indicate where the market has previously reversed direction, providing potential entry and exit levels for trades.
- **Pivot Markers**: The visual markers for pivot highs and lows serve as clear signals for reversal traders. By monitoring these levels, traders can anticipate price reversals and plan their trades to exploit these opportunities.
3. **Swing Traders**:
- **Combining SMA and Pivot Points**: Swing traders can use the combination of the smoothed line and pivot points to identify medium-term trading opportunities. The smoothed line helps in understanding the broader trend, while pivot points provide specific levels for potential swings.
- **Trend Change Alerts**: Trend change markers help swing traders spot new swing opportunities as the market shifts direction. These markers provide potential entry points for swing trades and help traders adjust their strategies to capitalize on market movements.
4. **Scalpers**:
- **Short-Term Analysis**: Scalpers benefit from the short-term signals provided by the SPM. The smoothed line and pivot points offer insights into rapid price movements, while the trend change markers highlight quick trading opportunities.
- **Pivot Points**: For scalpers, pivot points are particularly useful in identifying key levels where price may reverse within a short time frame. By focusing on these levels, scalpers can plan trades with tight stop-loss orders and capitalize on quick price changes.
#### Implementation and Best Practices
1. **Setting Parameters**:
- **Smoothing Period**: Adjust the smoothing period according to your trading strategy and market conditions. For long-term analysis, use a longer period to filter out noise and highlight broader trends. For short-term trading, a shorter period provides more immediate insights into price movements.
- **Pivot Lookback**: Choose a lookback period that matches your trading timeframe. For intraday trading, a shorter lookback period offers quick identification of recent price levels. For swing trading or long-term strategies, a longer lookback period provides more stable pivot points.
2. **Combining with Other Indicators**:
- **Integration with Technical Tools**: The SPM can be used in conjunction with other technical indicators to enhance trading decisions. For instance, combining the
SPM with indicators like RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence) can provide additional confirmation for trend signals and pivot points.
- **Support and Resistance**: Integrate the SPM’s pivot points with other support and resistance levels to gain a comprehensive view of market conditions. This combined approach helps in identifying stronger levels of support and resistance, improving trade accuracy.
3. **Backtesting**:
- **Historical Performance**: Conduct backtesting with historical data to evaluate the effectiveness of the SPM. Analyze past performance to fine-tune the smoothing period and pivot lookback settings, ensuring they align with your trading style and market conditions.
- **Scenario Analysis**: Test the SPM under various market scenarios to understand its performance in different conditions. This analysis helps in assessing the reliability of the indicator and making necessary adjustments for diverse market environments.
4. **Customization**:
- **Visual Adjustments**: Customize the appearance of the smoothed line and pivot markers to enhance chart readability and match personal preferences. Clear visual representation of these elements improves the effectiveness of the indicator.
- **Alert Configuration**: Set up alerts for trend changes to receive timely notifications. Alerts help traders act quickly on potential market shifts without constant monitoring, allowing for more efficient trading decisions.
#### Conclusion
The **Uptrick: SMA Pivot Marker (SPM)** is a versatile and powerful technical analysis tool that combines the benefits of the Simple Moving Average with pivot point analysis. By providing insights into market trends, identifying key reversal points, and detecting trend changes, the SPM caters to a wide range of trading strategies, including trend following, reversal trading, swing trading, and scalping.
With its customizable inputs, visual markers, and trend change alerts, the SPM offers traders the flexibility to adapt the indicator to different market conditions and trading styles. Whether used independently or in conjunction with other technical tools, the SPM is designed to enhance trading decision-making and improve overall trading performance. By mastering the use of the SPM, traders can gain a valuable edge in navigating the complexities of financial markets and making more informed trading decisions.
KASPA Slope OscillatorKASPA Slope Oscillator for analyzing KASPA on the 1D (daily) chart.
The indicator is plotted in a separate pane below the price chart and uses a mathematical approach to calculate and visualize the momentum or "slope" of KASPA's price movements.
Input Parameters:
Slope Window (days):
Defines the period (66 days by default) over which the slope is calculated.
Normalization Window (days):
The window size (85 days) for normalizing the slope values between 0 and 100.
Smoothing Period:
The number of days (15 days) over which the slope values are smoothed to reduce noise.
Overbought and Oversold Levels:
Threshold levels set at 80 (overbought) and 20 (oversold), respectively.
Calculation of the Slope:
Logarithmic Price Calculation:
Converts the close price of KASPA into a logarithmic scale to account for exponential growth or decay.
Rolling Slope:
Computes the rate of change in logarithmic prices over the defined slope window.
Normalization:
The slope is normalized between 0 and 100, allowing easier identification of extreme values.
Smoothing and Visualization:
Smoothing the Slope:
A Simple Moving Average (SMA) is applied to the normalized slope for the specified smoothing period.
Plotting the Oscillator:
The smoothed slope is plotted on the oscillator chart. Horizontal lines indicate overbought (80), oversold (20), and the mid-level (50).
Background Color Indications:
Background colors (red or green) indicate when the slope crosses above the overbought or below the oversold levels, respectively, signaling potential buy or sell conditions.
Detection of Local Maxima and Minima:
The code identifies local peaks (maxima) above the overbought level and troughs (minima) below the oversold level.
Vertical background lines are highlighted in red or green at these points, signaling potential reversals.
Short Summary:
The oscillator line fluctuates between 0 and 100, representing the normalized momentum of the price.
Red background areas indicate periods when the oscillator is above the overbought level (80), suggesting a potential overbought condition or a sell signal.
Green background areas indicate periods when the oscillator is below the oversold level (20), suggesting a potential oversold condition or a buy signal.
The vertical lines on the background mark local maxima and minima where price reversals may occur.
(I also want to thank @ForgoWork for optimizing visuality and cleaning up the source code)
GC Strategy with Trend Filter and Sudden Move Profit TakingBYBIT:BTCUSDT.P 15M
Situation Assessment with Three Moving Averages
The strategy uses the crossover of the 5SMA and 25SMA as entry signals.
Additionally, the 75SMA is used as a filter. Long entries are only allowed when the price is above the 75SMA, and short entries are only allowed when the price is below the 75SMA.
ADX Filter
The Average Directional Index (ADX) is used to check the strength of the trend. Entry signals are only activated when the ADX is above 20. This ensures that trades are only executed when the trend is strong.
Sudden Move Detection
The strategy detects sudden price movements. If a sudden move occurs, the position is closed to lock in profits.
Entry
Long Entry: When the 5SMA crosses above the 25SMA, the price is above the 75SMA, and the ADX is above 20.
Short Entry: When the 5SMA crosses below the 25SMA, the price is below the 75SMA, and the ADX is above 20.
Exit
Positions are closed if a sudden move occurs. Positions are also closed if an opposing entry signal is generated.
This strategy aims to confirm the strength of the trend using moving average crossovers and ADX and to lock in profits based on sudden price movements.
３本の移動平均線による状況判断
5SMAと25SMA のクロスオーバーをエントリーシグナルとして使用します。
さらに、75SMAをフィルターとして使用し、価格が75SMAの上にある場合のみロングエントリーを許可し、75SMAの下にある場合のみショートエントリーを許可します。
ADXフィルター
ADX（平均方向性指数）を使ってトレンドの強さを確認します。
ADXが20より大きい場合のみ、エントリーシグナルを有効にします。これにより、トレンドが強い時にのみ取引を行うことができます。
急激な変動検知
価格の急激な変動を検出します。
急激な変動があった場合には、ポジションをクローズして利益を確定します。
エントリー
ロングエントリー
5SMAが25SMAを上にクロスし、価格が75SMAの上にあり、ADXが20を超えているとき。
ショートエントリー
5SMAが25SMAを下にクロスし、価格が75SMAの下にあり、ADXが20を超えているとき。
エグジット
急激な変動があった場合、ポジションをクローズします。
反対のエントリーシグナルが発生した場合にも、ポジションをクローズします。
このストラテジーは、移動平均のクロスオーバーとADXを使ってトレンドの強さを確認し、急激な変動に基づいて利益を確定することを目的としています。
Uptrick: Trend SMA Oscillator### In-Depth Analysis of the "Uptrick: Trend SMA Oscillator" Indicator
---
#### Introduction to the Indicator
The "Uptrick: Trend SMA Oscillator" is an advanced yet user-friendly technical analysis tool designed to help traders across all levels of experience identify and follow market trends with precision. This indicator builds upon the fundamental principles of the Simple Moving Average (SMA), a cornerstone of technical analysis, to deliver a clear, visually intuitive overlay on the price chart. Through its strategic use of color-coding and customizable parameters, the Uptrick: Trend SMA Oscillator provides traders with actionable insights into market dynamics, enhancing their ability to make informed trading decisions.
#### Core Concepts and Methodology
1. **Foundational Principle – Simple Moving Average (SMA):**
- The Simple Moving Average (SMA) is the heart of the Uptrick: Trend SMA Oscillator. The SMA is a widely-used technical indicator that calculates the average price of an asset over a specified number of periods. By smoothing out price data, the SMA helps to reduce the noise from short-term fluctuations, providing a clearer picture of the overall trend.
- In the Uptrick: Trend SMA Oscillator, two SMAs are employed:
- **Primary SMA (oscValue):** This is applied to the closing price of the asset over a user-defined period (default is 14 periods). This SMA tracks the price closely and is sensitive to changes in market direction.
- **Smoothing SMA (oscV):** This second SMA is applied to the primary SMA, further smoothing the data and helping to filter out minor price movements that might otherwise be mistaken for trend reversals. The default period for this smoothing is 50, but it can be adjusted to suit the trader's preference.
2. **Color-Coding for Trend Visualization:**
- One of the most distinctive features of this indicator is its use of color to represent market trends. The indicator’s line changes color based on the relationship between the primary SMA and the smoothing SMA:
- **Bullish (Green):** The line turns green when the primary SMA is equal to or greater than the smoothing SMA, indicating that the market is in an upward trend.
- **Bearish (Red):** Conversely, the line turns red when the primary SMA falls below the smoothing SMA, signaling a downward trend.
- This color-coded system provides traders with an immediate, easy-to-interpret visual cue about the market’s direction, allowing for quick decision-making.
#### Detailed Explanation of Inputs
1. **Bullish Color (Default: Green #00ff00):**
- This input allows traders to customize the color that represents bullish trends on the chart. The default setting is green, a color commonly associated with upward market movement. However, traders can adjust this to any color that suits their visual preferences or matches their overall chart theme.
2. **Bearish Color (Default: Red RGB: 245, 0, 0):**
- The bearish color input determines the color of the line when the market is trending downwards. The default setting is a vivid red, signaling caution or selling opportunities. Like the bullish color, this can be customized to fit the trader’s needs.
3. **Line Thickness (Default: 5):**
- This setting controls the thickness of the line plotted by the indicator. The default thickness of 5 makes the line prominent on the chart, ensuring that the trend is easily visible even in complex or crowded chart setups. Traders can adjust the thickness to make the line thinner or thicker, depending on their visual preferences.
4. **Primary SMA Period (Value 1 - Default: 14):**
- The primary SMA period defines how many periods (e.g., days, hours) are used to calculate the moving average based on the asset’s closing prices. The default period of 14 is a balanced setting that offers a good mix of responsiveness and stability, but traders can adjust this depending on their trading style:
- **Shorter Periods (e.g., 5-10):** These make the indicator more sensitive, capturing trends more quickly but also increasing the likelihood of reacting to short-term price fluctuations or "noise."
- **Longer Periods (e.g., 20-50):** These smooth the data more, providing a more stable trend line that is less prone to whipsaws but may be slower to respond to trend changes.
5. **Smoothing SMA Period (Value 2 - Default: 50):**
- The smoothing SMA period determines how much the primary SMA is smoothed. A longer smoothing period results in a more gradual, stable line that focuses on the broader trend. The default of 50 is designed to smooth out most of the short-term fluctuations while still being responsive enough to detect significant trend shifts.
- **Customization:**
- **Shorter Smoothing Periods (e.g., 20-30):** Make the indicator more responsive, better for fast-moving markets or for traders who want to capture quick trends.
- **Longer Smoothing Periods (e.g., 70-100):** Enhance stability, ideal for long-term traders looking to avoid reacting to minor price movements.
#### Unique Characteristics and Advantages
1. **Simplicity and Clarity:**
- The Uptrick: Trend SMA Oscillator’s design prioritizes simplicity without sacrificing effectiveness. By relying on the widely understood SMA, it avoids the complexity of more esoteric indicators while still providing reliable trend signals. This simplicity makes it accessible to traders of all levels, from novices who are just learning about technical analysis to experienced traders looking for a straightforward, dependable tool.
2. **Visual Feedback Mechanism:**
- The indicator’s use of color to signify market trends is a particularly powerful feature. This visual feedback mechanism allows traders to assess market conditions at a glance. The clarity of the green and red color scheme reduces the mental effort required to interpret the indicator, freeing the trader to focus on strategy execution.
3. **Adaptability Across Markets and Timeframes:**
- One of the strengths of the Uptrick: Trend SMA Oscillator is its versatility. The basic principles of moving averages apply equally well across different asset classes and timeframes. Whether trading stocks, forex, commodities, or cryptocurrencies, traders can use this indicator to gain insights into market trends.
- **Intraday Trading:** For day traders who operate on short timeframes (e.g., 1-minute, 5-minute charts), the oscillator can be adjusted to be more responsive, capturing quick shifts in momentum.
- **Swing Trading:** Swing traders, who typically hold positions for several days to weeks, will find the default settings or slightly adjusted periods ideal for identifying and riding medium-term trends.
- **Long-Term Trading:** Position traders and investors can adjust the indicator to focus on long-term trends by increasing the periods for both the primary and smoothing SMAs, filtering out minor fluctuations and highlighting sustained market movements.
4. **Minimal Lag:**
- One of the challenges with moving averages is lag—the delay between when the price changes and when the indicator reflects this change. The Uptrick: Trend SMA Oscillator addresses this by allowing traders to adjust the periods to find a balance between responsiveness and stability. While all SMAs inherently have some lag, the customizable nature of this indicator helps traders mitigate this effect to align with their specific trading goals.
5. **Customizable and Intuitive:**
- While many technical indicators come with a fixed set of parameters, the Uptrick: Trend SMA Oscillator is fully customizable, allowing traders to tailor it to their trading style, market conditions, and personal preferences. This makes it a highly flexible tool that can be adjusted as markets evolve or as a trader’s strategy changes over time.
#### Practical Applications for Different Trader Profiles
1. **Day Traders:**
- **Use Case:** Day traders can customize the SMA periods to create a faster, more responsive indicator. This allows them to capture short-term trends and make quick decisions. For example, reducing the primary SMA to 5 and the smoothing SMA to 20 can help day traders react promptly to intraday price movements.
- **Strategy Integration:** Day traders might use the Uptrick: Trend SMA Oscillator in conjunction with volume-based indicators to confirm the strength of a trend before entering or exiting trades.
2. **Swing Traders:**
- **Use Case:** Swing traders can use the default settings or slightly adjust them to smooth out minor price fluctuations while still capturing medium-term trends. This approach helps in identifying the optimal points to enter or exit trades based on the broader market direction.
- **Strategy Integration:** Swing traders can combine this indicator with oscillators like the Relative Strength Index (RSI) to confirm overbought or oversold conditions, thereby refining their entry and exit strategies.
3. **Position Traders:**
- **Use Case:** Position traders, who hold trades for extended periods, can extend the SMA periods to focus on long-term trends. By doing so, they minimize the impact of short-term market noise and focus on the underlying trend.
- **Strategy Integration:** Position traders might use the Uptrick: Trend SMA Oscillator in combination with fundamental analysis. The indicator can help confirm the timing of entries and exits based on broader economic or corporate developments.
4. **Algorithmic and Quantitative Traders:**
- **Use Case:** The simplicity and clear logic of the Uptrick: Trend SMA Oscillator make it an excellent candidate for algorithmic trading strategies. Its binary output—bullish or bearish—can be easily coded into automated trading systems.
- **Strategy Integration:** Quant traders might use the indicator as part of a larger trading system that incorporates multiple indicators and rules, optimizing the SMA periods based on historical backtesting to achieve the best results.
5. **Novice Traders:**
- **Use Case:** Beginners can use the Uptrick: Trend SMA Oscillator to learn the basics of trend-following strategies.
The visual simplicity of the color-coded line helps novice traders quickly understand market direction without the need to interpret complex data.
- **Educational Value:** The indicator serves as an excellent starting point for those new to technical analysis, providing a practical example of how moving averages work in a real-world trading environment.
#### Combining the Indicator with Other Tools
1. **Relative Strength Index (RSI):**
- The RSI is a momentum oscillator that measures the speed and change of price movements. When combined with the Uptrick: Trend SMA Oscillator, traders can look for instances where the RSI shows divergence from the price while the oscillator confirms the trend. This can be a powerful signal of an impending reversal or continuation.
2. **Moving Average Convergence Divergence (MACD):**
- The MACD is another popular trend-following momentum indicator. By using it alongside the Uptrick: Trend SMA Oscillator, traders can confirm the strength of a trend and identify potential entry and exit points with greater confidence. For example, a bullish crossover on the MACD that coincides with the Uptrick: Trend SMA Oscillator turning green can be a strong buy signal.
3. **Volume Indicators:**
- Volume is often considered the fuel behind price movements. Using volume indicators like the On-Balance Volume (OBV) or Volume Weighted Average Price (VWAP) in conjunction with the Uptrick: Trend SMA Oscillator can help traders confirm the validity of a trend. A trend identified by the oscillator that is supported by increasing volume is typically more reliable.
4. **Fibonacci Retracement:**
- Fibonacci retracement levels are used to identify potential reversal levels in a trending market. When the Uptrick: Trend SMA Oscillator indicates a trend, traders can use Fibonacci retracement levels to find potential entry points that align with the broader trend direction.
#### Implementation in Different Market Conditions
1. **Trending Markets:**
- The Uptrick: Trend SMA Oscillator excels in trending markets, where it provides clear signals on the direction of the trend. In a strong uptrend, the line will remain green, helping traders stay in the trade for longer periods. In a downtrend, the red line will signal the continuation of bearish conditions, prompting traders to stay short or avoid long positions.
2. **Sideways or Range-Bound Markets:**
- In range-bound markets, where price oscillates within a confined range without a clear trend, the Uptrick: Trend SMA Oscillator may produce more frequent changes in color. While this could indicate potential reversals at the range boundaries, traders should be cautious of false signals. It may be beneficial to pair the oscillator with a volatility indicator to better navigate such conditions.
3. **Volatile Markets:**
- In highly volatile markets, where prices can swing rapidly, the sensitivity of the Uptrick: Trend SMA Oscillator can be adjusted by modifying the SMA periods. A shorter SMA period might capture quick trends, but traders should be aware of the increased risk of whipsaws. Combining the oscillator with a volatility filter or using it in a higher time frame might help mitigate some of this risk.
#### Final Thoughts
The "Uptrick: Trend SMA Oscillator" is a versatile, easy-to-use indicator that stands out for its simplicity, visual clarity, and adaptability. It provides traders with a straightforward method to identify and follow market trends, using the well-established concept of moving averages. The indicator’s customizable nature makes it suitable for a wide range of trading styles, from day trading to long-term investing, and across various asset classes.
By offering immediate visual feedback through color-coded signals, the Uptrick: Trend SMA Oscillator simplifies the decision-making process, allowing traders to focus on execution rather than interpretation. Whether used on its own or as part of a broader technical analysis toolkit, this indicator has the potential to enhance trading strategies and improve overall performance.
Its accessibility and ease of use make it particularly appealing to novice traders, while its adaptability and reliability ensure that it remains a valuable tool for more experienced market participants. As markets continue to evolve, the Uptrick: Trend SMA Oscillator remains a timeless tool, rooted in the fundamental principles of technical analysis, yet flexible enough to meet the demands of modern trading.
CNN Fear and Greed Index JD modified from minusminusCNN Fear and Greed Index - www.cnn.com
Modified from minusminus -
See Documentation from CNN's website
CNN's Fear and Greed index is an attempt to quantitatively score the Fear and Greed in the SPX using 7 factors:
Market Momentum- S&P 500 (SPX) and its 125-day moving average
Stock Price Strength -Net new 52-week highs and lows on the NYSE
Stock Price Breadth - McClellan Volume Summation Index
Put and Call options - 5-day average put/call ratio
Market Volatility - VIX and its 50-day moving average
Safe Haven Demand - Difference in 20-day stock and bond returns
Junk Bond Demand - Yield spread: junk bonds vs. investment grade
Each Factor has a weight input for the final calculation initially set to a weight of 1. The final calculation of the index is a weighted average of each factor.
3 Factors have separate functions for calculation : See Code for Clarity
SPX Momentum : difference between the Daily CBOE:SPX index value and it's 125 Day Simple moving average.
Stock Price Strength : Net New 52-week highs and lows on the NYSE.
Function calculates a measure of Net New 52-week highs by:
NYSE 52-week highs (INDEX:MAHN) - all new NYSE Highs (INDEX:HIGH)
measure of Net New 52-week lows by:
NYSE 52-week lows (INDEX:MALN) - all new NYSE Lows (INDEX:LOWN)
Then calculate a ratio of Net New 52-week Highs and Lows over Total Highs and Lows then takes a 5-day moving average of that ratio-See Code
Stock Price Breadth is the McClellan Volume Summation Index :
First Calculate the McClellan Oscillator
Second Calculate the Summation Index
4 Factors are Straight data requests
5 Day Simple Moving Average of the Put-Call Ratio on SPY
50 Day Simple Moving Average of the SPX VIX
Difference between 20 Day Simple Moving Average of SPX Daily Close and 20 Day Simple Moving Average of 10Y Constant Maturity US Treasury Note
Yield Spread between ICE BofA US High Yield Index and ICE BofA US Investment Grade Corporate Yield Index
The Fear and Greed Index is a weighted average of these factors - which is then normalized to scale from 0 to 100 using the past 25 values - length parameter.
3 Zones are Shaded: Red for Extreme Fear, Grey for normal jitters, Green for Extreme Greed.
Disclaimer: This is not financial advice. These are just my ideas, and I am not an investment advisor or investment professional. This code is for informational purposes only and do your own analysis before making any investment decisions. This is an attempt to replicate in spirt an index CNN publishes on their website and in no way shape or form infringes on their content, calculations or proprietary information.
From CNN: www.cnn.com
FEAR & GREED INDEX FAQs
What is the CNN Business Fear & Greed Index?
The Fear & Greed Index is a way to gauge stock market movements and whether stocks are fairly priced. The theory is based on the logic that excessive fear tends to drive down share prices, and too much greed tends to have the opposite effect.
How is Fear & Greed Calculated?
The Fear & Greed Index is a compilation of seven different indicators that measure some aspect of stock market behavior. They are market momentum, stock price strength, stock price breadth, put and call options, junk bond demand, market volatility, and safe haven demand. The index tracks how much these individual indicators deviate from their averages compared to how much they normally diverge. The index gives each indicator equal weighting in calculating a score from 0 to 100, with 100 representing maximum greediness and 0 signaling maximum fear.
How often is the Fear & Greed Index calculated?
Every component and the Index are calculated as soon as new data becomes available.
How to use Fear & Greed Index?
The Fear & Greed Index is used to gauge the mood of the market. Many investors are emotional and reactionary, and fear and greed sentiment indicators can alert investors to their own emotions and biases that can influence their decisions. When combined with fundamentals and other analytical tools, the Index can be a helpful way to assess market sentiment.
Comprehensive Market Overview1. What is this indicator about?
The "Comprehensive Market Overview" indicator provides a holistic view of the market by incorporating several key metrics:
Close Price: Displays the current close price below each candle.
Percent from All-Time High: Calculates how far the current close price is from the highest high observed over a specified period.
RSI (Relative Strength Index): Measures the momentum of price movements to assess whether a stock is overbought or oversold.
Volume Gain: Computes the current volume relative to its 20-period simple moving average (SMA), indicating volume strength or weakness.
Volatility: Quantifies market volatility by calculating the ratio of the Bollinger Bands' width (difference between upper and lower bands) to the SMA.
2. How it works?
Close Price Label: This label is displayed below each bar, showing the current close price.
Percent from All-Time High: Calculates the percentage difference between the highest high observed (all-time high) and the current close price.
RSI Calculation: Computes the RSI using a 14-period setting, providing insight into whether a stock is potentially overbought or oversold.
Volume Strength: Computes the current volume divided by its 20-period SMA, indicating whether volume is above or below average.
Volatility Calculation: Calculates the width of the Bollinger Bands (based on a 20-period SMA and 2 standard deviations) and expresses it as a percentage of the SMA, providing a measure of market volatility
3.Correct Trend Identification with Indicators
All-Time High (ATH) Levels:
Low Value (Near ATH): When the percent from ATH is low (close to 0%), it indicates that the current price is near the all-time high zone. This suggests strong bullish momentum and potential resistance levels.
High Value (Below ATH): A high percentage from ATH indicates how much the current price is below the all-time high. This could signal potential support levels or opportunities for price recovery towards previous highs.
RSI (Relative Strength Index):
Overbought (High RSI): RSI values above 70 typically indicate that the asset is overbought, suggesting a potential reversal or correction in price.
Oversold (Low RSI): RSI values below 30 indicate oversold conditions, suggesting a potential rebound or price increase.
Swing Trading Strategies
Confirmation with Visual Analysis: Visualizing the chart to confirm ATH levels and RSI readings can provide strong indications of market sentiment and potential trading opportunities:
Bullish Signals: Look for prices near ATH with RSI confirming strength (not yet overbought), indicating potential continuation or breakout.
Bearish Signals: Prices significantly below ATH with RSI showing weakness (not yet oversold), indicating potential for a bounce or reversal.
Volume Confirmation: Comparing current volume to its SMA helps confirm the strength of price movements. Higher current volume relative to the SMA suggests strong price action.
Volatility Assessment: Monitoring volatility through the Bollinger Bands' width ratio helps assess potential price swings. Narrow bands suggest low volatility, while wide bands indicate higher volatility and potential trading opportunities.
4.Entry and Exit Points:
Entry: Consider entering long positions near support levels when prices are below ATH and RSI is oversold. Conversely, enter short positions near resistance levels when prices are near ATH and RSI is overbought.
Exit: Exit long positions near resistance or ATH levels when prices show signs of resistance or RSI becomes overbought. Exit short positions near support levels or when prices rebound from oversold conditions.
Risk Management: Always incorporate risk management techniques such as setting stop-loss orders based on support and resistance levels identified through ATH and RSI analysis.
Implementation Example
Coins Trend Tracker HTThe Coins Trend Tracker HT script provides a powerful tool for monitoring and comparing the trend signals of multiple cryptocurrencies based on their Exponential Moving Averages (EMAs). This script is particularly useful for traders who want to keep track of multiple coins across different timeframes and identify potential trading opportunities based on EMA crossovers.
Features:
Customizable Coin Selection: Users can select up to four different cryptocurrencies to monitor.
Flexible Timeframes: Users can choose two different timeframes for EMA calculations to suit their trading strategies.
Visual Trend Indicators: The script displays trend indicators (🚀 for bullish and 💀 for bearish) based on the EMA crossover status for each coin and timeframe.
Conditional Cell Coloring: Table cells are color-coded based on the EMA crossover conditions, helping users quickly identify bullish or bearish trends.
Opacity Control: Users can adjust the opacity of the table cell colors for better visualization on the chart.
How It Works:
Coin Selection: Users can select up to four different cryptocurrencies to monitor by entering their ticker symbols.
Timeframe Selection: Users can select two different timeframes for the EMA calculations. The script calculates the 5-period and 20-period EMAs for each coin and timeframe.
EMA Crossovers: The script checks for EMA crossovers (EMA 5 crossing above or below EMA 20) and updates the trend indicators and cell colors accordingly.
Table Display: The script displays a table with the selected coins, their current prices, and trend indicators for the chosen timeframes. The background color of the table cells changes based on the EMA crossover status.
Script Logic:
The get_price function retrieves the latest price of the selected coin for the specified timeframe.
The get_ema_cross function calculates the 5-period and 20-period EMAs and checks for crossover conditions.
The fill_row function populates the table with the coin data, trend indicators, and conditionally colored cells.
The table header and data rows are updated based on the user-selected coins, timeframes, and EMA crossover conditions.
Usage:
Add the script to your TradingView chart.
Customize the coin selection, timeframes, text color, default cell color, bullish and bearish cross colors, and cell opacity through the input settings.
The script will display a table with the selected coins, their current prices, and trend indicators based on the EMA crossovers for the chosen timeframes.
Hindsight TrendNon-realtime but highly accurate trend analyzer with only one fundamental parameter ( period aka "minimum trend length")
Basically Hindsight Trend is pivot points on steroids (handles many cases much better). Plus it shows the trend line.
Period
I usually like periods of 10, 20 or 30.
The indicator's delay is identical to the chosen period.
You can actually try a low period like 4 or 5 to get something resembling a realtime indicator.
Uptrends are based on candle lows, downtrends are based on candle highs. So it is possible to have an uptrend and a downtrend at the same time.
Triangles
At trend start, a triangle is drawn. (Trendline isn't always there if the trend didn't last that long.)
Triangle size shows how long the high or low that started the trend remained unbroken. E.g. with period 20: Small triangle = 20+ candles, medium triangle = 40+ candles, big triangle = 80+ candles. So a big triangle marks an important reversal point.
How Hindsight Trend works
Whenever a candle completes, its high and low are saved as potentially "notable" points. A high or low is the more notable the longer it stays unbroken (= not touched again by price).
Now we simply take the notable highs and lows (as in, staying unbroken at least for the user-selected period)... and connect them together - if they are close enough to each other (less than "period" candles away). And decorate the first point in each trend with a triangle.
We only know whether a point is notable after "period" more candles have printed, so that's where the indicator's delay comes from.
Finally we divide the period by 2 and look at highs and lows which are unbroken for that shorter time. While they are not fully "notable" as defined above, we'll call them "semi-notable". Those points are only considered at the end of a trend, and help us extend the trend line a bit further.
Uptrick:Intensity IndexPurpose:
The "Uptrick: Intensity Index" strategy is designed to provide traders with insights into the trend intensity of security by combining multiple moving averages and their relative positions. This versatile tool can be used effectively by both short-term and long-term traders to identify potential buy and sell signals based on specific conditions.
Explanation:
Input Parameters and Customization:
Moving Averages Lengths:
Adjust MA1, MA2, and MA3 lengths to change the calculation periods for the moving averages.
Trend Intensity Index SMA Length:
Adjust the length of the SMA applied to the TII.
Plot Colors:
Change the colors of the TII and TII MA plots for better visualization.
Background Colors and Transparency:
Set different colors for positive and negative TII MA values.
Control the transparency of the background color.
---------------------------------------------------------------------------
MA1 (Length 10): Short-term moving average, useful for capturing short-term market trends.
MA2 (Length 20): Medium-term moving average, providing a balanced view of market trends.
MA3 (Length 50): Long-term moving average, offering insights into long-term market trends.
The script calculates the relative positions of the closing price to each moving average (rel1, rel2, rel3) to determine how far the current price deviates from each average.
Trend Intensity Index (TII):
The TII is calculated as the average of the relative positions (rel1, rel2, rel3), multiplied by 100 to convert it into a percentage. This index reflects the overall intensity of the trend, considering short-term, medium-term, and long-term perspectives.
The TII is plotted in blue, providing a visual representation of trend intensity.
SMA of TII:
An additional SMA is applied to the TII (matii) to smooth out fluctuations and provide a clearer long-term trend signal.
The SMA of TII is plotted in orange, offering a reference for long-term trend analysis.
Determining Potential Price Movements:
For Short-Term Traders:
When the blue TII line crosses above the orange SMA of TII line, it indicates a potential buy signal.
When the blue TII line crosses below the orange SMA of TII line, it indicates a potential sell signal.
For Long-Term Traders:
When the orange SMA of TII line crosses above the highlighted 0 line, it indicates a potential buy signal.
When the orange SMA of TII line crosses below the highlighted 0 line, it indicates a potential sell signal.
Plotting and Visualization:
The TII and its SMA are plotted with distinct colors for easy identification.
A horizontal line at 0 is plotted in gray to serve as a reference point for long-term trend signals.
The background color changes based on the value of the SMA of TII (matii):
Green background for matii values above 0, indicating bullish conditions.
Red background for matii values below 0, indicating bearish conditions.
Utility and Potential Usage:
The "Uptrick: Intensity Index" indicator is a powerful tool for both short-term and long-term traders, offering clear buy and sell signals based on the crossover of the TII and its SMA, as well as the position of the SMA relative to the zero line.
By consolidating multiple moving averages and their relative positions into a single indicator, traders can gain comprehensive insights into market trends and intensity.
The ability to adjust all inputs and toggle visibility options enhances the flexibility and utility of the indicator, making it suitable for various trading styles and market conditions.
Through its versatile design and advanced features, the "Uptrick: Intensity Index" indicator equips traders with actionable insights into trend intensity and potential price movements. By integrating this robust tool into their trading strategies, traders can navigate the markets with greater precision and confidence, thereby enhancing their trading outcomes.
WHAT SETTINGS TO HAVE FOR THE MOVING AVERAGE:
Short-term traders (day traders) might prefer a shorter SMA length (e.g., 5-20 periods) as they are looking for quick signals and react to price changes more rapidly.
Medium-term traders (swing traders) might opt for a medium SMA length (e.g., 20-50 periods) which can filter out some noise and provide a clearer signal on the trend.
Long-term traders (position traders) might choose a longer SMA length (e.g., 50-200 periods) to get a broader view of the market trend and avoid reacting to short-term fluctuations.
